Systems Therapeutics Category Zero

Musings About Disease Origination

Reposted from Medium 2024

“These are my principles and if you don’t like them, well, I’ve got others.

Groucho Marx

Summary

Systems therapeutics has previously been described in detail, illustrating how pharmacologic processes interact with pathophysiologic processes to produce a clinical therapeutic response. At its center is a systems therapeutics diagram illustrating the four fundamental biologic levels of interaction between these processes, which then determine the four systems therapeutics categories, i.e., Category I (at the molecular level), Category II (at the cellular level), Category III (at the tissues/organ level) and Category IV (at the clinical level). Systems therapeutics Category Zero (0) refers to an interaction between pharmacologic and pathophysiologic processes at the front end of these processes — at the origin level — involving a pharmacologic agent and an initiator of disease origination. The objective of this paper is to consider a general hypothesis regarding disease origination, to outline the underlying rationale, and to discuss the two fundamental systems components involved, intrinsic operator and etiologic causative factor.

Introduction

Systems therapeutics defines how pharmacologic processes interact with pathophysiologic processes to produce a clinical therapeutic response. The systems therapeutics diagram shows two rows of four parallel systems components for pharmacologic processes and pathophysiologic processes, representing the four fundamental biologic levels of interaction between these two processes — at the molecular, cellular, tissue/organ, and clinical or whole body levels — which then define four systems therapeutics categories, i.e., Categories I, II, III and IV, respectively (Bjornsson 2023a).

During the construction of the systems therapeutics diagram two hypothetical systems components were introduced at the front end of pathophysiologic processes (Bjornsson 2023a). First, the systems component intrinsic operator was introduced as the initiator of the pathophysiologic processes, corresponding to the pharmacologic agent of the pharmacologic processes, in part to simplify and depict similarly the initial events of both pharmacologic and pathophysiologic processes, and in part to stimulate discussions on this front. These two front end systems components, an intrinsic operator and a pharmacologic agent — at the origin level — comprise the systems therapeutics Category Zero (0). The intrinsic operator represents an initiator or driver, acting on the second systems component, etiologic causative factor, which represents the seeds of the disease, and thus, determines the specific disease expression. In contrast, their counterparts on the pharmacologic processes side, the pharmacologic agent, i.e., a drug, and the pharmacologic response element, e.g., a receptor, are generally recognized and accepted.

As background for the present report, two recently published reports discussed where to place clinical disease modifiers (Bjornsson 2023b) and clinical disease categories (Bjornsson 2023c) within the systems therapeutics scheme, both of which may influence disease development and progression, while it is generally thought that these modifying factors are not directly involved in the disease origination processes.

Objective

The objective of this paper is to consider a general hypothesis regarding disease origination, to outline the underlying rationale, and to account for the two fundamental systems components initiating and determining specific disease expression. This involves the two systems components already mentioned, intrinsic operator and etiologic causative factor, and the systems processes disease preindication1 and disease initiation2, connecting the two components at the front end of the pathophysiologic processes. Refer to Chart 1, lower left hand corner. Together, these two processes and two systems components then constitute disease origination mechanisms.

Chart 1. The systems therapeutics diagram, with the addition of Category Zero/Origin Level, on the left hand side (modified from Bjornsson 2023a).

Any general hypothesis regarding disease origination thus developed, supported by experimental data and fully understood, could eventually suggest what kind of pharmacologic agents might counteract the disease origination mechanisms. It could also aid in the development of approaches to modeling and simulation of the pathophysiologic processes, and thus, coupled with pharmacologic processes, of the overall systems therapeutics processes.

Rationale

The present focus on Category Zero and its pathophysiologic processes extends logically from the systems therapeutics diagram, first posted in its current version in 2016 (Bjornsson 2023a). The impetus behind this report principally involves three general considerations:

a) Age of disease onset. While different diseases manifest clinically at different age ranges, one typically assumes the underlying etiologic causative mechanisms have been in place for some time, perhaps years or decades — even from the earliest signs of life. For example, the age of onset for schizophrenia is typically in early adulthood, in late teens to mid-30s, while the age of onset for Alzheimer’s disease is typically in late adulthood, in the 60s or later. On the other hand, inborn errors of metabolism, e.g., phenylketonuria, typically occur in very early childhood, often starting at a few months of age, while acute lymphocytic leukemia typically starts in early childhood, usually in the 2–5 years age range. A commonly stated explanation to account for the differently delayed onset of diseases involves the theory that varying durations of time are required for the pathophysiologic processes to progress before a disease becomes clinically manifest, from a few months to a few decades. Thus, only short durations of time are required for inborn enzymatic deficiencies to result in catastrophic accumulation of metabolites, while more subtle disease mechanisms might take years to decades for diseases to become clinically manifest. The first tenet of the present general hypothesis of disease origination is that the blueprints for the disease origination systems components and processes have been in place since the differentiation of the principal cell types of the different organs or organ systems, but only brought into existence at a later date.

b) Central role of principal cell types. Disease initiation events are generally assumed to take place in the principal cell types of the different organs/organ systems, i.e., the cells responsible for an organ’s biochemical and physiologic characteristics. Therefore, this further assumes that both the intrinsic operator and the etiologic causative factors originate and reside in these cells, and that the intrinsic operator initiates and maintains the disease origination process. Regarding the different cell types, it is of interest to note that there are currently ongoing extensive efforts to develop catalogues of the different human cell types (e.g., Human Cell Atlas and Human Cell Tree Map) as well as published articles relevant to their role on medicine (e.g., Rood et al. 2022). Two generic features are worth emphasizing, i) a typical organ/organ system based disease occurs only in one organ/organ system while the same genome exists in all organs/organ system, and ii) each organ/organ systems has only a limited number of disease expressions. These features suggest organ-specific mechanisms, and thus principal cell type specific mechanisms, as far as the intrinsic operator and the etiologic causative factor are concerned, and their interactions viathe disease preindication process. The second tenet of the present general disease origination hypothesis is that it applies to diseases in general, that its causative mechanisms reside in the principal cell types of the respective organ/organ system, and that it is independent of classic disease categories and disease modifiers, although these can influence disease development and progression.

c) Variability in clinical therapeutic drug response. Considering currently approved drugs, there are very few examples of drugs acting directly at the etiologic mechanistic cause of the disease (Category I), when one excludes treatments of infectious diseases and replacement therapies. As previously outlined with examples (Bjornsson 2023a), approved drugs work at different biologic levels, and can be categorized by the biologic levels of the pivotal interactions between pharmacologic processes and pathophysiologic processes, with most drugs interacting at the biochemical level (Category II) and the physiologic level (Category III), while others are at the clinical symptomatic level (Category IV). Thus, a meaningful clinical therapeutic response can be accomplished by interactions between the pharmacologic and pathophysiologic processes at different biologic levels. Yet there is considerable range in the average patient responder rate for different pharmacologic classes (Spear et al. 2001), as well as a significant interpatient response variability among patients within a given pharmacologic class. It is suggested that this overall variability in clinical therapeutic response can be attributed to variabilities in both pharmacologic processes and pathophysiologic processes, the former due to variabilities in pharmacokinetic and pharmacodynamic processes, the latter due to variabilities in disease originating and disease development and progression processes. The third tenet of the present general hypothesis of disease origination is the promise of being able to minimize the sources of key variabilities in both pharmacologic and pathophysiologic processes, thus achieving the highest possible clinical responder rate and the lowest interpatient response variability, with a promise of disease prevention or regression, through pharmacologic intervention at the origin level — at Category Zero.

General Hypothesis of Disease Origination

The disease origination hypothesis being considered involves an intrinsic operator and an etiologic causative factor, their interaction through a disease preindication process, and the subsequent connection of the etiologic causative factor to pathogenic pathways through a disease initiation process. Together, these two processes and the two systems components constitute disease origination. Refer to Chart 2, which shows the pathophysiologic processes divided into an early disease origination phase and a later disease development and progression phase. Below we will focus on the systems components intrinsic operator and etiologic causative factor.

Chart 2. Pathophysiologic processes showing disease origination, comprising intrinsic operator and etiologic causative factor, and disease preindication and disease initiation processes. Subsequent disease development and progression involves pathogenic pathway, pathophysiologic process and disease manifestation, and pathogenesis and progression processes.

Intrinsic Operator

The term intrinsic operator represents the front-end systems component of the pathophysiologic processes. It was introduced on the systems therapeutics diagram in 2016, in part to simplify and depict similarly the initial events of both pharmacologic and pathophysiologic processes, and in part to stimulate discussions on disease origination, as has been mentioned above.

The intrinsic operator is envisioned as an endogenous intracellular entity, not external or circulating, residing in the diseased organ’s principal cell type(s), although its production or activity could be modulated by an extracellular entity. It could be a macromolecular protein or a product derived from a larger intracellular compound. The prototypical candidate for an intrinsic operator involves a transcription factor or a transcription factor-like molecule. Transcription factors are proteins that control the rate of gene expression, they are involved in most cellular functions, and they are thus found in all living organisms. There is an extensive literature on transcription factors and related coactivators, coregulators and nuclear receptors, and how they bind to a given gene’s DNA sequence to elicit the formation of a normal or abnormal gene product (e.g., Boija et al. 2018; Lonard et al. 2012).

One of the attractive attributes of transcription(-like) factors (and attendant molecular machinery) as intrinsic operators is that it could help explain the age of disease onset differences. Their activity, post-differentiation, would be based in the principal cell type(s) of the organ/organ system to be affected by disease. This suggests that an intrinsic operator becomes active at a certain point in time, early or late, depending on the disease in question, initiating a disease preindication process.

Etiologic Causative Factor

The etiologic causative factor was initially envisioned as a singular biomolecular entity, representing the molecular abnormality or malfunction characterizing the disease under consideration, such as a specific genetic mutation or protein abnormality.

The analogous systems component for the etiologic causative factor on the pharmacologic side of the systems therapeutics diagram is the pharmacologic response element (e.g., a receptor); such a construct — a drug and a drug target — has been accepted for a century. In contrast, on the pathophysiologic side of the systems therapeutics diagram there is currently limited information about the identity of such causative entities and mechanisms, except examples of genes expressing abnormal proteins (e.g., enzymes). The concept of an etiologic causative factor can be broadened to potentially include a network or an assembly, including the primary etiologic causative factor, which then becomes an etiologic causative network. The prototypical candidate for a primary etiologic causative factor involves a disease-specific gene whose expression is stimulated by a specific disease associated intrinsic operator. Such a network is more in line with disease causation mechanisms discussed in the network medicine literature (e.g., Chan & Loscalzo 2012; Silverman et al. 2020), and does allow for a more general disease origination paradigm.

The etiologic causative factor/network contains the seeds of a disease, and after being interacted on by the intrinsic operator via a disease preindication process, leads to disease development and progression via a disease initiation process. Thus, the interaction of the intrinsic operator and the etiologic causative factor/network results in a directiveness3 towards a specific disease evolution, whose overall rate and variability is primarily determined by the initiating and driving factor, the intrinsic operator, and also influenced by the components of the etiologic causative factor/network.

One of the attractive attributes of an etiologic causative factor/network as leading to pathogenic pathways through a disease initiation process, is that its specific components need not always be identical, yet leading to the same disease expression and manifestation. This is reminiscent of the system theory concept of equifinality.

Conclusion

A general hypothesis has been considered for disease origination. Obviously, it’s a long road from musings involving an untested hypothesis to even a plausible hypothesis, necessitating extensive research over an untold number of decades. In addition to state-of-the-art cellular, biologic and bioinformatics research technologies, this effort is also likely to benefit from the study of the natural history of diseases.

In the systems therapeutics diagram the systems components responsible for disease origination have been referred to as intrinsic operator and etiologic causative factor. As has been mentioned above, the hypothetical intrinsic operator was initially introduced in part to simplify and depict similarly the initial events of both pharmacologic and pathophysiologic processes, and in part to stimulate discussions about disease origination. The etiologic causative factor/network has been envisioned as involving a primary abnormal biomolecular entity in a network, representing the molecular abnormality or malfunction characterizing the disease under consideration. Thus, the intrinsic operator represents the initiator or driver of the pathophysiological processes, and the etiologic causative factor/network contains the seeds of the disease, determining the specific disease expression.

We hope these systems components of the pathophysiologic processes of the systems therapeutics construct will eventually be as well understood as the interaction between a pharmacologic agent and a pharmacologic response element, and that such an understanding will help lead to the discovery and development of novel Category Zero pharmacologic agents.

References

Bjornsson TD. Systems Therapeutics: Framework, Diagram, Categories, Definitions, Examplestri-institute.org. January, 2023a.

Bjornsson TD. Systems Therapeutics and Disease ModifiersMedium, July 9, 2023b.

Bjornsson TD. Systems Therapeutics and Disease CategoriesMedium, July 22, 2023c.

Boija A, Klein IA, Sabari BR, Dall’Agnese A, Coffey EL, et al. Transcription Factors Activate Genes through the Phase-Separation Capacity of Their Activation Domains. Cell, 175: 1842–1855, 2018.

Chan SY, Loscalzo J. The emerging paradigm of network medicine in the study of human disease. Circ Res, 111(3): 359–374, 2012.

Human Cell Atlas, https://www.humancellatlas.org (last accessed in March 2024)

Human Cell Tree Map, https://humancelltreemap.mis.mpg.de (last accessed in March 2024)

Lonard DM, O’Malley BW. Nuclear receptor coregulators: modulators of pathology and therapeutic targets (2012). Nuclear receptor coregulators: modulators of pathology and therapeutic targets. Nat Rev Endocrinol., 8(10): 598–604, 2012.

Rood JE, Maartens A, Hupalowska A, Teichmann SA, Regev A. Impact of the Human Cell Atlas on Medicine, Nature Medicine, 28(12):2486–2496, 2022

Silverman E, Harald H, Schmidt HW, Anastasiadou E, Altucci L, et al. Molecular networks in Network Medicine: Development and applications. Wiley Interdisciplinary Reviews: Systems Biology and Medicine, vol. 12(6), 2020.

Spear BB, Heath-Chiozzi M, Huff J. Clinical applications of pharmacogenetics. TRENDS Mol Med, 7:201–204, 2001.

Footnotes

1 This term is based on preindication (noun), meaning an event that is experienced as indicating important things to come.

2 This term is based on initiation (noun), meaning the action of the beginning of something.

3 This term is based on directiveness (noun) or directivity (noun, synonym), meaning the character of being determined in direction of development.

Systems Therapeutics and Disease Modifiers

Reposted from Medium 2023

“Design’s purpose is always the same — inspire insight, evoke response, transform thought.”

Clement Mok in Designing Business

Summary

Systems therapeutics has previously been described in detail, illustrating how pharmacologic processes and pathophysiologic processes interact to produce clinical therapeutic response. Disease modifiers are factors that can potentially influence clinical disease development and progression, but are generally not thought to be involved in the disease initiation processes. The objective of this paper is to provide examples of disease modifiers and explore where to place these within the systems therapeutics diagram.

Systems Therapeutics

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. Systems therapeutics has previously been described in detail, including a systems therapeutics diagram (1). The organizing principle underlying the systems therapeutics diagram involves two rows of four parallel systems components for pharmacologic processes and pathophysiologic processes, representing the four fundamental biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ level, and the clinical level, in addition to the initiating drivers of these processes and the ultimate clinical therapeutic response. The four different biologic levels of interactions between these processes then determine the four systems therapeutic categories, i.e., Category I (at the molecular level), Category II (at the cellular level), Category III (at the tissue/organ level) and Category IV (at the clinical level).

While systems therapeutics has been described in detail, what has not been discussed includes how disease modifiers might fit into this scheme. Disease modifiers are factors which can potentially influence clinical disease development and progression. These include factors such as sex and age, and risk factors and aggravating factors. Another report discussed how different disease categories could be placed within the systems therapeutics scheme (2).

The objective of this paper is to review disease modifiers and explore where to place these within the pathophysiologic process part of the systems therapeutics diagram. Note that the biologic modifiers age and sex can also affect the pharmacologic processes, principally drug exposure, but this topic is beyond the scope of the present paper.

Disease Modifiers

There are different kinds of clinical disease modifiers, which are factors with the potential to influence different aspects of clinical disease development and progression. By themselves these are generally thought to be separate from disease initiation processes, but can be important determinants of the clinical disease expression. These modifiers are the biologic modifiers age and sex, aggravating factors and risk factors; these are briefly outlined below.

Biologic modifiers — age: This modifier, while not causative per se, influences at what age range a specific disease is most likely to manifest clinically. Specific ranges for age of disease onset are not provided in the examples below, instead only very general age ranges.

Examples of age of onset:

Acute lymphocytic leukemia (ALL): early childhood;

Schizophrenia: early adulthood;

Osteoarthritis: late adulthood;

Alzheimer’s disease: late adulthood.

Biologic modifiers — sex: Aside from specific male diseases and female diseases, this modifier, presumably acting via sex hormones, directly or indirectly, while not causative per se, influences the likelihood of getting a disease, and thus determines the relative sex prevalence. Specific values for sex preference ratios are not provided in the examples below, instead only very general sex preferences.

Examples of sex preference:

Rheumatoid arthritis: more common in females;

Systemic lupus erythematosus (SLE): more common in females;

Autoimmune diseases: more common in females;

Asthma: more common in females.

Aggravating factors: These are factors which can act as triggers of disease symptoms; the list for individual diseases is for illustration purposes, and not intended to be comprehensive.

Examples of aggravating factors for specific diseases:

Asthma: allergens, tobacco smoke, pets, air irritants;

Gastroeosopheal reflux syndrome (GERD): alcohol, fatty or fried foods, coffee, spicy food;

Migraine: stress, smells, lights and sounds, bright light;

Endometriosis: stress, caffeine, fatty meat, alcohol.

Risk factors: These are clinical factors which can increase the likelihood of getting a specific disease; the list for individual diseases is for illustration purposes, and not intended to be comprehensive.

Examples of risk factors for specific diseases:

Diabetes: weight, inactivity, family history, ethnicity;

Coronary heart disease: high LDL cholesterol, high blood pressure, family history, diabetes;

Osteoporosis: aging, inactivity, smoking, ethnicity;

Lung cancer: smoking, radon, family history, occupational chemicals;

Age-related macular degeneration: hypertension, smoking, diabetes, family history.

Disease Modifiers in Systems Therapeutics

As has already been mentioned while disease modifiers are factors that can potentially influence disease development and progression, they are generally not thought to be involved in disease initiation.

While not thought to play a direct etiologic causative role for individual diseases, risk factors and aggravating factors can be considered to influence the processes of disease development and progression. Risk factors can influence pathogenic pathways, while aggravating factors can influence symptomatic pathophysiologic processes. Examples of risk factors include the well known relationships between coronary heart disease, hypertension and hypercholesterolemia, presumably involving interconnected network pathways. Examples of aggravating factors include those that bring on clinical symptoms, such as in GERD and migraine.

Chart 1. Disease origination followed by disease development and progression; also shown are where the disease modifiers risk factors and aggravating factors, and the biologic modifiers sex and age, interact with disease development and progression.

The biologic modifiers age and sex can also be considered to be involved in the general processes of disease development and progression, but would not be considered to be generally involved in the disease initiation processes. The biologic modifier sex would be assumed to act, directly or indirectly, through the respective sex hormones, and thus acting during the early phases of disease development. The biologic modifier age, on the other hand, is of special interest as regards its role in determining the age range at which diseases start or manifest themselves. While different diseases start clinically at different age ranges, it is often assumed the underlying etiologic causative mechanisms have typically been in place for some time, perhaps years or decades. A commonly proposed explanation to account for the differently delayed onset of diseases involves the theory that varying durations of time are required for the pathophysiologic processes to progress before a disease becomes clinically manifest, from a few months to several decades.

Conclusions

The present paper has provided outlines of different clinical disease modifiers and explored where to place these within the systems therapeutics paradigm, as illustrated in Chart 1. It is generally thought that these modifying factors are not directly involved in disease initiation processes, although major research efforts are needed to elucidate how these interact with individual disease processes and networks, in both early and late disease development and progression.

In the systems therapeutics diagram the systems components presented in disease initiation have been referred to as intrinsic operator and etiologic causative factor. The hypothetical intrinsic operator was introduced, in part to simplify and depict similarly the initial events of both pharmacologic processes and pathophysiologic processes, and in part to stimulate discussions about disease origination. The etiologic causative factor has been envisioned as a singular abnormal biomolecular entity or an abnormal network, representing the molecular abnormality or malfunction characterizing the disease under consideration. Thus, the intrinsic operator represents the initiator or driver of the pathophysiological process, and the etiologic causative factor/network contains the seeds of the disease and determining the specific disease expression. We hope these pathophysiologic systems components will some time be as well understood as the interaction between a pharmacologic agent (drug) and a pharmacologic response element (receptor).

References

  1. Bjornsson TD. Systems therapeutics: Framework, Diagram, Categories, Definitions, Examples. tri-institute.org. January 2023
  2. Bjornsson TD. Systems Therapeutics and Disease Categories. Medium, July 22, 2023.

Systems Therapeutics and Disease Categories

Reposted from Medium 2023

“Without context and purpose, information is mere data.”

Clement Mok in Designing Business

Summary

Systems therapeutics has previously been described in detail, illustrating how pharmacologic processes and pathophysiologic processes interact to produce clinical therapeutic response. Various disease categories have classically been used to categorize or describe different diseases, but these have generally not provided comprehensive and systematic descriptions related to disease development and progression. The objective of this report is to provide examples of disease categories and explore where to place these within the systems therapeutics scheme.

Systems Therapeutics

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. A systems therapeutics diagram has been described to illustrate these interactions, consisting of parallel pharmacologic and pathophysiologic processes. While systems therapeutics has been described in detail (1), what has not been discussed includes how disease categories might be placed within this scheme. A related report has showed how disease modifiers could be placed within the systems therapeutics scheme (2); disease modifiers are factors which can potentially influence clinical disease development and progression, such as sex and age, and different risk factors and aggravating factors. The objective of this report is to review different disease categories and determine where these can be placed within the pathophysiologic process part of the systems therapeutics diagram.

Disease Categories

Diseases have classically been categorized or described in different ways. These range from being organ system based to how common vs. rare the diseases are. While these disease categories are high-level and descriptive in nature, they might serve as checklists when identifying examples to guide hypothetical and exploratory work on disease development and progression.

Examples of classical disease categories are as follows:

By organ or organ system: Cardiovascular, central nervous system, pulmonary, musculoskeletal, gastrointestinal, hematologic, genitourinary, endocrinologic, metabolic, renal, dermatologic. This disease category is often thought to be based on the defining cell types of the different organs or organ systems.

By etiology and pathophysiology: Inflammatory, dysfunctional, degenerative, neoplastic, infectious, toxicological. This disease category suggests different disease origination pathways or entry points. For example, infectious and toxicologic diseases have external origins, others have internal origins.

By duration: Acute vs. chronic. This category refers at the existence of short-term or continuous disease development and progression. For example, common infectious diseases are typically acute, whereas degenerative and dysfunctional diseases are typically chronic.

By general characteristics: Continuous (non-episodic) vs. non-continuous (episodic), and progressive vs. non-progressive. This category suggests different degrees of symptomatic manifestations or different rates of disease progression.

By prevalence: Rare vs. common. Most rare disease occur early in life and can be catastrophic, e.g., inborn metabolic errors, while most common diseases occur in adult life. Examples include phenylketonuria (rare) and osteoarthritis (common).

By severity: For example, as exemplified by assessments of unmet medical need (e.g., life expectancy, disease burden). This general category describes to what extent diseases impart serious limitations on physiologic functions and economic wherewithal.

Disease Categories in Systems Therapeutics

An initial review of these disease categories or descriptions suggests that they are not likely to be useful for our objective of better understanding disease initiation, disease development, and disease progression. This is because these categories are not comprehensive or systematic and they typically address only one aspect or dimension of a disease. Descriptions involving the basic biologic nature of etiologic causes are mostly absent, e.g., those based on types of genetic mutations or protein abnormalities.

Further examination of the disease categories mentioned above suggests that the those addressing duration (acute vs. chronic) and general characteristics (continuous vs. non-continuous and progressive vs. non-progressive) can be lumped together since both involve disease activity or changes in these over time. The categories based on etiology and pathophysiology, prevalence and severity represent different aspects of disease pathophysiology. Thus, we have three general disease categories, as shown in Chart 1, i.e., organ system, pathophysiology and activity/time. Note that the biologic modifiers sex and age, discussed in another report (2), are also included in Chart 1.

Chart 1. The general disease categories organ system, pathophysiology and activity/time are superimposed on the pathophysiologic part of the systems therapeutics diagram. The biologic modifiers sex and age are also shown.

Conclusions

The present report has provided outlines of different disease categories and explored where to place these within the systems therapeutics scheme, as illustrated in Chart 1. As has been mentioned these categories are not thought to be generally useful, although the characteristics of individual diseases are essential for better understanding of disease development and progression.

References

  1. Bjornsson TD. Systems Therapeutics: Framework, Diagram, Categories, Definitions, Examples. tri-institute.org, January 2023
  2. Bjornsson TD. Systems Therapeutics and Disease Modifiers. Medium, 9 July 2023

SYSTEMS THERAPEUTICS

Framework, Diagram, Categories, Definitions, Examples

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Thorir D. Bjornsson, MD, PhD

Therapeutics Research Institute

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Synopsis

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. A systems therapeutics diagram has been constructed to further describe such interactions, consisting of two rows of four parallel systems components for pharmacologic and pathophysiologic processes. These systems components represent the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ level, and the clinical level. Both processes have their own sets of initiators or drivers. These four different levels of pivotal interactions between these processes then determine four different systems therapeutics categories, i.e., Categories I, II, III and IV. Examples of pharmacologic classes are provided for each of these categories, and illustrative examples are provided for the interactions of each of these categories highlighting the pivotal interaction. Finally, a glossary of the systems components for pharmacologic and pathophysiologic processes is included. It is hoped that the systems therapeutics framework presented here will promote discussions regarding the need for better understanding of the determinants of therapeutic response characteristics of modern therapeutics. 

Table of Contents

Synopsis

Introduction

Systems Therapeutics Diagram

Systems Therapeutics Categories

Illustrative Examples

Discussion

References

Glossary

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Introduction

While hundreds of drugs have been approved by regulatory agencies over the past several decades, and we have witnessed significant scientific advances in molecular understanding of pharmacologic mechanisms and disease processes, there have only been sporadic efforts towards the construction of frameworks for understanding how pharmacologic and pathophysiologic processes interact to produce clinical therapeutic effects. One noteworthy effort was presented by Grahame-Smith and Aronson in the Oxford Textbook of Clinical Pharmacology and Drug Therapy, which describes the chain of events linking the pharmacologic actions of drugs to their clinical effects, including several examples (1). 

The purpose of the present work is to provide a systems therapeutics framework, depicting pharmacologic processes and pathophysiologic processes separately, thus enabling the presentation of the different biologic levels of pivotal interactions between these two processes, and thereby allowing the determination of different systems therapeutics categories.

Efforts on this project were initiated at the Therapeutics Research Institute in the mid 2010’s, although initially it was not clear how this work would evolve. The development of the systems therapeutics framework was an iterative process, most importantly in determining the number and naming of the systems components representing the different biological levels. Different iterations of this framework were produced and posted on the Therapeutics Research Institute’s website, TRI-institute.org, between 2015 and 2018, including an evolving construction of a systems therapeutics diagram, four biologic levels of interactions, four systems therapeutics categories, examples of approved drugs and pharmacologic classes for each category, relevant definitions, and illustrative examples of how the sequence of events proceeds for pharmacologic and pathophysiologic processes (2,3). The present version builds on the latest version from 2018, and includes an expanded description of the systems therapeutics diagram and an edited discussion.

Systems Therapeutics Diagram

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. A systems therapeutics diagram, shown in Figure 1, has been constructed to describe such interactions.

The organizing principle underlying the systems therapeutics diagram involves two rows of four parallel systems components for pharmacologic processes and pathophysiologic processes, representing the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ level, and the clinical level, in addition to the initiating entities or drivers of these processes and the ultimate therapeutic response.

Figure 1. Systems Therapeutics Diagram

The systems components for pharmacologic processes start with a pharmacologic response element, followed by a pharmacologic mechanism, a pharmacologic response, and a clinical (pharmacologic) effect, whereas the systems components for pathophysiologic processes start with an etiologic causative factor, followed by a pathogenic pathway, a pathophysiologic process, and a disease manifestation. The four different biologic levels of interactions between these two processes then determine the four systems therapeutics categories, i.e., Category I (at the molecular level), Category II (at the cellular level), Category III (at the tissue/organ level), and Category IV (at the clinical level). It is noted that these systems components represent generally recognized pharmacologic and pathophysiologic terms. Brief descriptions of the individual systems components are provided in the glossary below, including examples for each component.

Each of these two processes are initiated by their own sets of initiators or drivers, i.e., a pharmacologic agent and an intrinsic operator, for the pharmacologic and pathophysiologic processes, respectively. On the pharmacologic process side, a pharmacologic agent (i.e., a drug), through its concentration or exposure, interacting with a pharmacologic response element (e.g., a receptor, or so-called drug target), is the fundamental driver of pharmacologic processes. This initial interaction with the pharmacologic response element leads to initiation of a pharmacologic mechanism via signal transduction. On the pathophysiologic process side, a hypothetical intrinsic operator is proposed as an initiator or driver interacting with and influencing an etiologic causative factor, via disease preindication, and thus serving as a driver of pathophysiologic processes, while the etiologic causative factor determines the specific disease expression. The hypothetical intrinsic operator is envisioned as an endogenous entity, not external or circulating, originating in a diseased organ’s principal cell type(s). It is intended to comprise different unidentified biologic entities, to be characterized in the near future using advanced bioinformatics and network-based approaches.This initial interaction with the etiologic causative factor leads to the initiation of a pathogenic pathway via disease initiation. The etiologic causative factor represents a biomolecular entity or network determining the specific disease expression, e.g., a molecular abnormality or malfunction characterizing the disease under consideration, such as a specific genetic mutation or protein abnormality. 

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response

The next three systems components for pharmacologic processes, i.e., pharmacologic mechanism, pharmacologic response and clinical (pharmacologic) effect, first involve the sequence of effects from the cellular level to the tissue/organ level via pharmacodynamics, and then from the tissue/organ level to the clinical or whole-body level via translation. The corresponding three systems components for the pathophysiologic processes, i.e., pathogenic pathway, pathophysiologic process and disease manifestation, first involve the sequence of effects from the cellular level to the tissue/organ level via pathogenesis, and then from the tissue/organ level to the clinical or whole-body level via progression. The culminating result of the interaction between these two processes, independent of the biologic level of the pivotal interaction, involves a therapeutic response, determined by how the clinical (pharmacologic) effect moderates the disease manifestation.

It is noted that while it is well recognized that there is a wide variability in the clinical therapeutic response of individual patients to a given approved drug (4,5), it is less well recognized that both two processes, pharmacologic and pathophysiologic, have their inherent interpatient variabilities (6).

Systems Therapeutics Categories

The systems therapeutics diagram presented here lends itself to determine four systems therapeutics categories, corresponding to the four different biologic levels of pivotal interactions between pharmacologic processes and pathophysiologic processes, as follows:

Category I – at the Molecular Level: Elements/Factors

Category II – at the Cellular Level: Mechanisms/Pathways

Category III – at the Tissue/Organ Level: Responses/Processes

Category IV – at the Clinical level: Effects/Manifestations

A further description of each of these systems therapeutics categories is provided below, including definitions and examples of pharmacologic classes and approved drugs for each.

Category I – at the Molecular Level: Elements/Factors

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves the primary corresponding molecular entities, the pharmacologic response element and the etiologic causative factor, respectively.

Examples of Molecular-based Therapy – These can involve replacement therapies (hormones, enzymes, proteins) or interferences with altered gene products):

  • Enzyme replacement therapy, e.g., idursulfase (Elaprase) for Hunter Syndrome
  • Protein replacement therapy, e.g., recombinant Factor VIII (Recombinate) for Hemophilia A
  • Potentiation of defective protein, e.g., ivacaftor (Kalydeco) for Cystic Fibrosis
  • Inhibition of abnormal enzyme, e.g., imatinib (Gleevec) for Chronic Myelogenous Leukemia (CML)

Category II – at the Cellular Level: Mechanisms/Pathways

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a fundamental biochemical mechanism, related to the disease evolution, although not necessarily an etiologic pathway.

Examples of Metabolism-based Therapy – These can involve metabolism-based therapies (interference with a biochemical mechanism or a disease network-linked pathway):

  • HMG-CoA Reductase Inhibitors (statins), e.g., atorvastatin (Lipitor) for Hypercholesterolemia
  • TNF-a Inhibitors, e.g., adalimumab (Humira) for Rheumatoid Arthritis
  • Xanthine Oxidase Inhibitors, e.g., allopurinol (Zyloprim) for Hyperuricemia and Gout

Category III – at the Tissue/Organ Level: Responses/Processes

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a modulation of a (normal) physiologic function, linked to the disease evolution, although not necessarily an etiologic pathway.

Examples of Function-based Therapy – These can involve function-based therapies (modulation of a (normal) physiologic function or activity):

  • Angiotensin II Receptor Blockers, e.g., irbesartan (Avapro) for Hypertension
  • PDE-5 Inhibitors, e.g., tadalafil (Cialis) for Male Erectile Dysfunction
  • Factor Xa Inhibitors, e.g., apixaban (Eliquis) for Thrombosis

Category IV – at the Clinical Level: Effects/Manifestations

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves an effect directed at clinical symptom(s) of a disease, but not directly its cause or etiology.

Examples of Symptom-based Therapy – These can involve symptom-based therapies (various symptomatic or palliative treatments):

  • Antipyretics, e.g., acetaminophen (Tylenol) for lowering high body temperature
  • Analgesics, e.g., ibuprofen (Advil) for Osteoarthritis 
  • Antitussives, e.g., dextromethorphan (Delsym) for cough suppression

Illustrative Examples

Below are illustrative examples for each of the four systems therapeutics categories. The charts follow the design of the systems therapeutics diagram. The pivotal connection between pharmacologic and pathophysiologic processes represents the fundamental or primary interaction between these processes (represented by a fat arrow), thus determining the systems therapeutics category; these are followed by dependent or secondary connections to the right (represented by thin arrows). The descriptions for the individual systems components were generated from generally available textbooks of pharmacology, pathophysiology and medicine, and other sources, but with an emphasis on a separation of pharmacologic and pathophysiologic concepts and processes, culminating in a therapeutic response.

Illustrative Example for Systems Therapeutics Category I (Figure 2)

Pharmacologic Mechanism: Regulator of Cystic Fibrosis Transmembrane Conductance (CFTR)

Indication: Cystic Fibrosis

Figure 2. Illustrative Example for Category I

Illustrative Example for Systems Therapeutics Category II (Figure 3)

Pharmacologic Mechanism: Inhibition of HMG-CoA Reductase

Indication: Hypercholesterolemia

Figure 3. Illustrative Example for Category II

Illustrative Example for Systems Therapeutics Category III (Figure 4)

Pharmacologic Mechanism: Inhibition of Angiotensin-Converting Enzyme (ACE)

Indication: Hypertension (and other cardiovascular indications)

Figure 4. Illustrative Example for Category III

Illustrative Example for Systems Therapeutics Category IV (Figure 5)

Pharmacologic Mechanism: Inhibition of Cyclooxygenase (COX-1/COX-2)

Indication: Osteoarthritis (and other indications)

Figure 5. Illustrative Example for Category IV

Discussion

The systems therapeutics diagram was constructed to facilitate better understanding and discussion of the different types of successful therapies. Importantly, this framework shows the pharmacologic processes and the pathophysiologic processes separately, thus enabling illustrations at what biologic level these processes interact to produce a clinical therapeutic response. This contrasts with the commonly used single linear pharmacotherapeutics process, which is grounded in the clinical pharmacology and pharmacokinetics literature, starting with a drug dose, through concentration and pharmacologic effect, and ending in a clinical effect, thus not considering the pathophysiologic process (3). The illustrative examples presented above for the four different systems therapeutics categories provide descriptions of the two progressing processes in a storyboard-like fashion, highlighting at what biologic level the pivotal interaction occurs between these two processes.  

Systems Components of Pharmacologic and Pathophysiologic Processes – The systems components of the pharmacologic and pathophysiologic processes are the building blocks of the systems therapeutics diagram (see Figure 1 above). These were identified to allow description of the different biologic levels where interactions between the two processes occur, and thus enabling the determination of four different systems therapeutics categories. As outlined above, the systems components for both processes represent generally recognized pharmacologic and pathophysiologic terms (see definitions in Glossary below). The final systems component, the therapeutic response, is independent of the biologic level of the pivotal interaction and describes how the clinical (pharmacologic) effect moderates the disease manifestation. 

Pharmacologic processes and pathophysiologic processes can be co-determinants of the ultimate patient therapeutic response characteristics, and interpatient variability, to a specific therapeutic agent

Initiators or Drivers of Pharmacologic and Pathophysiologic Processes  In addition to the systems components for pharmacologic processes and pathophysiologic processes are the two initiators or drivers of these two processes, one actual (pharmacologic agent), the other hypothetical (intrinsic operator), respectively. The pharmacologic processes’ initiator or driver, a pharmacologic agent (a drug), is well recognized as determining the magnitude of the pharmacologic response, through its concentration and exposure, determined by biopharmaceutical and pharmacokinetic processes. On the other hand, the pathophysiologic processes’ initiator or driver, an intrinsic operator, is a hypothetical entity based in part on recent network-based approaches indicating that disease initiation can involve interactions between genetic and non-genetic components, although major research efforts are needed to elucidate the nature of these interactions (7,8). Also, an indirect rationale for proposing a hypothetical intrinsic operator derives from considerations of age of disease onset, where this entity acts on an etiologic causative factor, which determines the specific disease expression. While different diseases start clinically at different age ranges, one assumes the underlying etiologic causative mechanism has typically been in place for some time, perhaps years or decades. For example, the age of onset for schizophrenia is thought to be in early adulthood, while the age of onset for Alzheimer’s disease is thought to be in late adulthood. On the other end of the age spectrum, inborn errors of metabolism, e.g., phenylketonuria, typically occur in very early childhood, often starting at a few months of age, and acute lymphocytic leukemia typically starting in early childhood. A commonly proposed explanation to account for the differently delayed onsets of diseases involves the theory that varying durations of time are required for the pathophysiologic processes to progress before a disease becomes clinically manifest, from a few months to several decades. A hypothetical intrinsic operator, however, albeit with an unknown regulation, might prove a useful concept to better understand disease initiation and progression. In this regard one is reminded of the usefulness of hypothetical constructs in biology and disease models, e.g., the pharmacologic effect compartment in PK-PD modeling (9,10).

Interpatient Variability in Therapeutic Response – The systems therapeutics diagram by depicting pharmacologic and pathophysiologic processes separately acknowledges the potential for interpatient variability not only on the pharmacologic process side, e.g., due to drug exposure or pharmacologic response differences, but also on the pathophysiologic side, e.g., due to differences in pathogenic pathways or disease progression. Thus, pharmacologic processes and pathophysiologic processes can be co-determinants of the ultimate patient therapeutic response characteristics, and interpatient variability, to a specific therapeutic agent (2,3). This contrasts with the widely held clinical pharmacology dogma that interpatient variability in therapeutic response is principally due to variability in pharmacokinetic and pharmacologic processes. Presently, however, the relative contributions of each of these variabilities to the ultimate therapeutic response are typically unclear, most significantly due to limited availability of relevant data and methods and are likely to vary from one therapeutic class to another. Thus, the systems therapeutics framework suggests important future research needs in accounting for both processes and their independent variabilities. It is noted that some of the overall variability in conventional PK-PD modeling is likely to be due to variability in disease processes in addition to PK variability. 

Conclusions – It is our hope that the systems therapeutics framework will help stimulate research towards better understanding of the relationships between the biologic levels of interactions between pharmacologic and pathophysiologic processes on one hand and the therapeutic response characteristics on the other. Based on its two parallel processes and systems components, this framework has provided a more holistic view of the interfaces between pharmacology, pathophysiology and medicine than the commonly used single linear pharmacotherapeutics process. The inclusion of initiators or drivers for both processes provides potential new model-based approaches in clinical pharmacology and therapeutics. We further hope that this framework will stimulate research towards better qualitative and quantitative descriptions of the pharmacologic and pathophysiologic processes, including ways of defining the relative contributions of these two processes towards determining the overall therapeutic response characteristics and variability.

References

  1. Grahame-Smith DG, Aronson JK (1992). Oxford Textbook of Clinical Pharmacology and Drug Therapy, Oxford University Press, Oxford (Chapter 5. The Therapeutic Process, pp. 55-66).
  2. Therapeutics Research Institute. Systems Therapeutics: Diagram, Definitions and Illustrative Examples, TRI-institute.org, April 2018 (last edited August 2021).
  3. Therapeutics Research Institute. Systems Therapeutics Framework: Development and Structure, TRI-institute.org, August 2021. 
  4. Rowland M, Tozer TN (2011). Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications, Fourth edition, Lippincott Williams & Wilkins, Philadelphia (Chapter 12, Variability, pp. 333-356).
  5. Eichler HG, Abadie E, Breckenridge A, Flamion B, Gustafsson LL, Leufkens H, Rowland M, Schneider CK, Bloechl-Daum B (2011). Bridging the efficacy-effectiveness gap: a regulator’s perspective on addressing variability of drug response. Nat. Rev. Drug Disc., 10:495-506.
  6. Therapeutics Research Institute. Systems Therapeutics: Variabilities, TRI-institute.org, May 2016. 
  7. Barabasi AL, Gulbahce N, Loscalzo J (2011). Network medicine: a network-based approach to human disease. Nat. Rev. Genetics, 12:56-68.
  8. Silverman E, Harald H, Schmidt HW, Anastasiadou E, Altucci L, et al. Molecular networks in Network Medicine: Development and applications (2020). Wiley Interdisciplinary Reviews: Systems Biology and Medicine, vol. 12(6).
  9. Sheiner LB, Stanski DR, Vozeh S, Miller RD, Ham J (1979). Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin. Pharmacol. Ther., 25:358-371.
  10. Jusko WJ (1993). Conceptualization of drug distribution to a hypothetical pharmacodynamic effect compartment. Clin. Pharmacol. Ther., 54:112-113

Glossary

Below is a glossary of the individual systems components for the pharmacologic and pathophysiologic processes represented in the systems therapeutics diagram presented above. Examples for each systems component are from among approved treatments and diseases that have previously been addressed in individual posts on the Therapeutics Research Institute’s website, TRI-institute.org.  

Pharmacologic Processes

Pharmacologic Agent 

A compound, e.g., a small molecule or a large biopharmaceutical, that initiates the pharmacologic process by interacting with a pharmacologic response element. 

Examples:

  • esomeprazole (Nexium)
  • sildenafil (Viagra)

Pharmacologic Response Element

A native biologic element, could be a receptor or an enzyme, with which a pharmacologic agent interacts (via pharmacologic interaction). Commonly referred to as a pharmacologic target. 

Examples:

  • H+/K+ ATPase (proton pump)
  • cGMP-specific phosphodiesterase type 5 (PDE5)

Pharmacologic Mechanism

Molecular mechanism of action, typically involving a molecular pathway resulting in a biochemical reaction (via signal transduction). 

Examples:

  • Inhibition of proton pump (for Acid Reflux and Ulcer Disease)
  • Inhibition of PDE5 (for Male Erectile Dysfunction)

Pharmacologic Response

Pharmacologic effect at the tissue/organ level mediated through a pharmacologic mechanism (via pharmacodynamics). 

Examples:

  • Decreased gastric acid secretion resulting in decreased acidity (by proton pump inhibitor)
  • Smooth muscle relaxation in corpus cavernosum leading to increased blood flow (by PDE5 inhibitor)

Clinical Effect

A pharmacologic effect at the clinical level, which represents the pharmacologic basis for a therapeutic response (via translation). 

Examples:

  • Decreased symptoms from gastric acidity (by proton pump inhibitor)
  • Increased erection (by PDE5 inhibitor).

Pathophysiologic Processes

Intrinsic Operator

A hypothetical entity interacting with and influencing an etiologic causative factor, serving as a driver of a pathophysiologic process; could be genetic or non-genetic.

Examples:

  • Currently not known 

Etiologic Causative Factor

A genetic or non-genetic factor, upon interaction with an intrinsic operator (via disease preindication), determines a disease specific progression. 

Examples:

  • Dihydrotestosterone (DHT)-induced growth factors and their receptors (in Benign Prostatic Hyperplasia)
  • Post-menopausal and age-related osteoporosis is initiated by a developing imbalance between net bone formation and resorption (in Osteoporosis)

Pathogenic Pathway

Molecular pathogenic pathway mediating ongoing disease progression from etiologic causative factor (via disease initiation). 

Examples:

  • DHT-induced growth factors stimulate proliferation of stromal cells (in Benign Prostatic Hyperplasia)
  • The normally regulated bone remodeling process is modulated by numerous systemic factors (in Osteoporosis)

Pathophysiologic Process

Ongoing pathophysiologic process (via pathogenesis), possibly both structural and functional.

Examples:

  • Formation of discrete hyperplastic nodules in periurethral region (in Benign Prostatic Hyperplasia)
  • Gradual and continuing loss of bone mineral density, decreased bone quality, with increased risk of fracture (in Osteoporosis)

Disease Manifestation

Development of characteristic clinical signs and symptoms associated with a given disease (via progression), typically independent of a specific etiologic causative factor. 

Examples:

  • Lower urinary tract symptoms (in Benign Prostatic Hyperplasia)
  • Loss of bone mineral density and risk of bone fracture (in Osteoporosis)

Therapeutic Response

Therapeutic benefit of a drug on which approval is based, showing a beneficial change in specific objective and/or subjective measures of a disease.

Examples:

  • Symptom relief and mucosal healing (e.g., after proton pump inhibitors in Acid Reflux and Ulcer Disease)
  • Improved erection (e.g., after PDE5 inhibitors in Male Erectile Dysfunction)
  • Decreased urinary frequency (e.g., after 5-alpha reductase inhibitors in Benign Prostatic Hyperplasia)
  • Decreased bone fractures (e.g., after bisphosphonates in Osteoporosis)

Systems Therapeutics Framework: Development and Structure

While a large number of new drugs have been approved by regulatory agencies over the past several decades, and we have witnessed significant scientific advances in molecular understanding of pharmacologic mechanisms and disease processes, there have only been sporadic efforts towards the construction of frameworks for understanding how pharmacologic and pathophysiologic processes interact to produce therapeutic effects. One noteworthy effort was presented in the 1992 edition of Oxford Textbook of Clinical Pharmacology and Drug Therapy (1), which describes the chain of events linking the pharmacologic effects of drugs to their clinical therapeutic response, and includes several examples. For reference, a commonly used generic diagram is shown below illustrating the sequence of events (shown vertically) from a drug dose, through concentration and pharmacologic effect, to therapeutic response.  

Efforts on a systems therapeutics diagram were initiated in the mid 2010’s, although it was not initially clear how this work would evolve. The objective was to create a systems therapeutics framework, depicting the pharmacologic and pathophysiologic processes separately (shown horizontally), each with a set of systems components at different biologic levels, thus enabling the presentation of interactions between these two processes at the different biologic levels. 

Development of a Systems Therapeutics Framework

The development of the systems therapeutics framework was very much an iterative process, e.g., determining the number and naming of the systems components representing the different biological levels, and their connections and interactions. Five different iterations of a systems therapeutics diagram were subsequently developed and posted on the Therapeutics Research Institute’s website, tri-institute.org, between 2015 and 2018. This involved an evolving construction of a systems therapeutics diagram, four systems therapeutics categories, relevant definitions, and illustrative examples of the different categories, as well as a discussion of variabilities in the pharmacologic and pathophysiologic processes. 

During this development period there were important clarifications both at the front end of the diagram, i.e., the drivers of these two processes, pharmacologic agent and intrinsic operator, for the pharmacologic and pathophysiologic processes, respectively, and at the back end, i.e., net therapeutic response, which represents where the clinical (pharmacologic) effect and disease manifestation interact; thus, a symmetry between these processes was achieved. Importantly, this framework shows the pharmacologic processes and the pathophysiologic processes separately, rather than exhibiting a single linear diagram (see diagram above), and thus illustrating for a given pharmacologic agent at what biologic level the pharmacologic and pathophysiologic processes interact to result in a therapeutic response. There was also an ongoing effort on the nomenclature, definitions and examples; these are all provided in Systems Therapeutics: Diagram, Definition and Illustrative Examples, Therapeutics Research Institute’s website (2).

Systems Therapeutics Diagram

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response (see diagram below).

The organizing principle underlying the systems therapeutics diagram involves two rows of four parallel systems components for pharmacologic and pathophysiologic processes, representing the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ levels, and finally the clinical level, in addition to the initiating entities or drivers of these processes, and the ultimate therapeutic response. 

The systems components for pharmacologic processes involve a pharmacologic response element, followed by a pharmacologic mechanism, a pharmacologic response, and a clinical effect, whereas the systems components for pathophysiologic processes involve an etiologic causative factor, followed by a pathogenic pathway, a pathophysiologic process, and a disease manifestation. The four different biologic levels of interactions between these two processes then determine the four systems therapeutics categories, i.e., Category I (at the molecular level), Category II (at the cellular level), Category III (at the tissue/organ level), and Category IV (at the clinical level).Both of these two processes are initiated by their own sets of initiators or drivers, i.e., a pharmacologic agent and an intrinsic operator, for the pharmacologic and pathophysiologic processes, respectively. On the pharmacologic process side, a pharmacologic agent (a drug), interacting with a pharmacologic response element (a receptor or so-called drug target), and its concentration or exposure, is the fundamental driver of pharmacologic processes. On the pathophysiologic process side, a hypothetical intrinsic operator is proposed as an initiator interacting with and influencing an etiologic causative factor, and serving as a driver of pathophysiologic processes. This hypothetical intrinsic operator is intended to cover biologic entities identified using advanced network-based approaches in disease initiation.

The culminating result of the interaction between these two processes, independent of the biologic level of the pivotal interaction, involves a clinical therapeutic response, determined by the clinical (pharmacologic) effect and disease manifestation. While it is well recognized that there is a wide variability in the clinical therapeutic response of individual patients to a given approved drug, it is less well recognized that both of these two processes, pharmacologic and pathophysiologic, have their inherent variabilities. This systems therapeutics construct thus further suggests that interpatient variabilities in both of these active processes contribute to and thus are co-determinants of the ultimate patient therapeutic response characteristics, including range and extent of response, response variability, and responder rate. Presently, however, the relative contributions of each of these process variabilities to the ultimate therapeutic response are typically unclear, most significantly due to limited availability of data and methods, and are likely to vary from one therapeutic class to another. 

Systems Therapeutics Categories

The systems therapeutics diagram lends itself to determine four systems therapeutics categories, corresponding to the four different biologic levels of interactions between pharmacologic processes and pathophysiologic processes, as follows:

Category I – Molecular Level: Elements/Factors

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves the primary corresponding molecular entities, the pharmacologic response element and the etiologic causative factor, respectively.

Examples of Molecular-based Therapy – These can involve replacement therapies (hormones, enzymes, proteins, genes) or genome-based therapies (interference with altered gene products).

Category II – Cellular Level: Mechanisms/Pathways

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a fundamental biochemical mechanism, related to the disease evolution, although not necessarily an etiologic pathway.

Examples of Metabolism-based Therapy – These can involve metabolism-based therapies (interference with a biochemical mechanism or a disease network-linked pathway).

Category III – Tissue/Organ Level: Responses/Processes

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a modulation of a (normal) physiologic function, linked to the disease evolution, although not necessarily an etiologic pathway.

Examples of Function-based Therapy – These can involve function-based therapies (modulation of a (normal) physiologic function or activity).

Category IV – Clinical Level: Effects/Manifestations

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves an effect directed at clinical symptom(s) of a disease, but not directly its cause or etiology.

Examples of Symptom-based Therapy – These can involve symptom-based therapies (various symptomatic or palliative treatments).

Examples, Definitions, and Glossary

In addition to descriptions of the systems therapeutics framework and diagram, examples of approved drugs for each of the systems therapeutics categories were provided in Systems Therapeutics: Diagram, Definitions and Illustrative Examples, which was posted on the Therapeutics Research Institute’s website (2). Furthermore, this post also contains illustrative examples for the different systems therapeutics categories of how the pivotal interaction occurs between the two processes. Finally, this post also contains definitions and a glossary of the individual systems components for the pharmacologic and pathophysiologic processes represented in the systems therapeutics diagram.

Discussion

The systems therapeutics diagram and framework presented here represents the culmination of years long effort on the pharmacotherapeutics process. Of note are the two initiators or drivers of these two processes, one actual (pharmacologic agent), the other hypothetical (intrinsic operator); the four systems components for each of the pharmacologic and pathophysiologic processes and their interactions to create four different systems therapeutic categories; and the final common therapeutic response from the two end events of the pharmacologic and pathophysiologic processes, clinical effect and disease manifestation. 

It is worth highlighting a few aspects of the systems therapeutics framework and contrast these to the “classic” single linear diagram from a dose of a drug to pharmacologic effect or therapeutic response:

  • They differ in structure: The systems therapeutics framework involves two parallel processes, pharmacologic and pathophysiologic, each showing four biologic levels of potential interactions, at the molecular, cellular, tissue/organ and clinical levels, initiated by their respective drivers and culminating in a therapeutic response, in contrast to the single linear model from drug dose and exposure through pharmacologic actions, e.g., molecular, cellular, tissue/organ or clinical levels, resulting in pharmacologic effect or therapeutic response.
  • They differ in suggestive causes of variabilities in therapeutic response: The systems therapeutics framework recognizes the potential for interindividual variability not only on the pharmacologic process side, e.g., due to exposure or pharmacologic receptor differences, but also on the pathophysiologic side, e.g., due to differences in pathogenic pathways or disease manifestations, whereas the single linear sequence model views drug exposure as the key determinant of variability in pharmacologic effect or therapeutic response. Thus, the systems therapeutics framework views variabilities in both processes as contributors and co-determinants of variability in therapeutic response, although at the present time it may be difficult to determine pathophysiologic process variability and the respective contributions of both processes.
  • They differ in their abilities to illustrate how the pharmacologic and pathophysiologic process components interact: The systems therapeutics framework allows for a mechanistic explanation how the two processes interact, depending on the biologic level of the pivotal interaction. This has been illustrated by examples for each of the four levels of interactions, i.e., systems therapeutics categories, how the pharmacologic and pathophysiologic processes interact to produce a therapeutic response. There is not an equivalent manner to illustrate these interactions in the single linear sequence model.  
  • They differ in their focus on the initiators or drivers of their respective processes: The systems therapeutics framework allows for initiators or drivers of both processes. On the pharmacologic process side, the fundamental driver of the pharmacologic processes obviously is the pharmacologic agent in question and its exposure, whereas, on the pathophysiologic process side, a hypothetical intrinsic operator is proposed as an initiator interacting with and influencing an etiologic factor, and thus serving as a driver of the pathophysiologic processes. While currently there are no known examples of such initiators or drivers, current work in advanced network-based approaches in disease initiation suggests the existence of a driver mechanism. There is not an equivalent manner to suggest a disease process driver in the single linear sequence model.

Considering the above highlights, the systems therapeutics framework suggests future research needs, such as to address disease process measurements and variability, and to further define disease process initiators and drivers. It is noted that the some of the overall variability in conventional PK-PD modeling is likely to be due to variability in disease processes.

It is hoped that the systems therapeutics framework advanced here will help stimulate research towards qualitative and quantitative descriptions of the pharmacologic and pathophysiologic processes, including ways of defining the relative contributions of these two processes towards determining the overall therapeutic response characteristics.

References

  1. Grahame-Smith DG, Aronson JK: Oxford Textbook of Clinical Pharmacology and Drug Therapy, Oxford University Press, Oxford, 1992 (Chapter 5. The Therapeutic Process, pp. 55-66).
  2. Bjornsson, TD: Systems Therapeutics: Diagram, Definitions and Illustrative Examples. Therapeutics Research Institute’s website, tri-institute.org, April 2018, last edited August 5, 2021.

 

Pharmaceutical Predictivity

Pharmaceutical Attrition

Drug development is associated with a significant degree of attrition, which is generally thought to be in the 90 percent range, indicating that only about 10 percent of compounds entering development make it to regulatory submission, approval and market. During the past two decades numerous papers have been published on pharmaceutical attrition, attempting to arrive at an overall estimate of attrition, and the key reasons for attrition (e.g., Kola and Landis, 2004; Hay et al., 2014). Attrition rates have been reported to vary significantly depending on different attributes, such as therapeutic areas, phase of development and pharmacologic targets, and commonly cited causes of compound termination have included clinical safety, lack of efficacy, formulation, PK/bioavailability, commercial, toxicology, and cost of goods. 

A general comment concerning the published literature on attrition and its causes, as well as assessments within individual pharmaceutical companies, is that definitions and attributions have not been standardized, and common methodology has been lacking. It is also noted that even within individual companies, when reviewing their compound termination databases, it’s not always clear what was considered the primary reason for the termination of a specific compound by the project team. Furthermore, the literature focuses primarily on small molecules, but success rates of biopharmaceuticals and vaccines are thought to be considerably better than those for small molecules.

Considering the significant negative implications of candidate compound attrition for the pharmaceutical industry, principally in terms of R&D expenditure, opportunity cost and productivity, the question arises how the industry might be able to reduce attrition, and thus be able to bring more new therapies to market. As an example, an R&D organization might base how many candidate compounds to bring into development each year on the desired number of drug candidates to be submitted for regulatory submission at a future date following clinical development. Thus, assuming a goal of one regulatory submission per year, at least ten candidate compounds would need to be brought into development each year. Such an inefficient drug development process obviously makes it much harder to address the many unmet medical needs areas.

The purpose of this commentary is to present a framework to address attrition of small molecules from a different perspective. It is not intended in any way to provide an extensive literature review of this complex topic; references are representative.

From Attrition to Predictivity

While different high-level categories have been proposed as reasons for attrition, such as scientific reasons, technical reasons, commercial reasons and regulatory reasons, each with their specific underlying set of causes, fundamentally the key causes of terminations are scientific, i.e., based on lack of efficacy, safety issues, and undesirable compound properties (compound properties are defined as determinants and descriptors of drug exposure). These are also the causes of terminations that together are by far the most common, and that lend themselves to addressing attrition by better understanding of the underlying scientific causes. This involves focusing on predictivity, i.e., how predictive are the preclinical methods and models of clinical performance, as expressed below:

PT = pe x ps x pc                                                                                                                 

Where PT stands for total predictivity with respect to scientific causes of terminations, and pe, ps and pc stand for the individual predictivities of efficacy, safety and compound properties, respectively. This is shown graphically below, and in an enlarged format here.

Note that the predictivities of these three scientific components are considered to be multiplicative, which assumes these are independent of each other. Also note that this leaves aside terminations by attrition categories such as cost of goods, formulation issues, budget/resource constraints, portfolio rationalization, potential values, patent issues and regulatory hurdles, as these are fundamentally unrelated to the three scientific causes mentioned above, and are typically business-related rather than scientific.

Predictivity Rates of Discovery and Preclinical Data

As was mentioned above, the data and methodologies that have been used to address attrition and attrition categories, as reflected in the published literature, have generally not been uniform or standardized. Yet in order to identify opportunities to reduce attrition, what’s needed are well-defined studies with robust statistical analyses of how predictive current preclinical studies of efficacy, safety and compound properties are with respect to clinical performance. With an overall success rate of only about 10%, for small molecules at least, one has to conclude that our understanding of how to confidently progress candidate compounds from preclinical to clinical is limited. Indeed, to quote Sir Peter Medawar, Nobel Laureate in Physiology and Medicine 1960: “No branch of science can be called truly mature until it has developed some form of predictive capability.”

A table of examples of preclinical methods and models of efficacy, safety and compound properties and examples of clinical failures due to lack of efficacy failures, safety/toxicology issues or undesirable compound properties is shown below, and in an enlarged format.

At the present time, specific values for predictivities of efficacy, safety and compound properties are not readily available in the publishedliterature, but it is possible to arrive at a general range for these, at least for compound properties and safety. While there are obviously a variety of complicating factors, such as the chemical properties of the candidate compounds, which therapeutic areas, and which specific parameters are being addressed for these scientific causes of termination, such guesstimates can be useful for identifying where the weaknesses in the current preclinical-to-clinical paradigm lie. 

Compound Properties. A number of papers have been published on the predictivity of compound properties based on preclinical data and using a variety of computational models to predict PK parameters in humans and compared these with the observed parameters in man, typically from early Phase I studies (e.g., PISC/PhRMA group, 2011; Jones et al., 2013). The parameters addressed have included PK parameters, such as total clearance, AUC, maximum concentration, elimination half-life, bioavailability and food effect. The computational methods have included allometry, in vitro-in vivo extrapolation (IVIVE) and physiologically-based pharmacokinetics (PBPK). The published reports have included data from individual companies and from multi-company precompetitive collaborative efforts. In general, the predictivity for the individual compound properties parameters have broadly ranged from about 0.4 to 0.7 (predictions within a factor of two), although there has been considerable variability from report to report; PBPK appears to be the favored method. 

Safety. There have also been numerous published studies addressing predictivity of safety, typically based on the concordance between adverse effects in man (after Phase I or after clinical development) and the findings from preclinical safety studies (e.g., Olson et al., 2000; Monticello et al., 2017). In general, these studies have found good concordance between the findings in preclinical and clinical studies, although there has typically been considerable variability with respect to different organ systems. While methodologies based on concordance are not specifically addressing predictivities, these are generally thought to be of a similar magnitude as those for compound properties, in the broad range of 0.4 to 0.7. It is noteworthy that regulatory requirements for preclinical studies for safety and compound properties are well standardized and prescriptive, including ICH guidelines. 

Efficacy. In stark contrast to predictivity of safety and compound properties, the situation with respect to how predictive preclinical efficacy studies and methods are with respect to efficacy in humans is significantly more limited. Numerous challenges in this area have been suggested, such as non-uniform preclinical studies and methodologies associated with preclinical animal models, small sample sizes and translational challenges. However, for illustrative purposes in this commentary, one can grossly estimate these to be around 0.3, by solving for total predictivity of 0.10 and using 0.6 values for both predictivities of safety and compound properties; using values of 0.5 and 0.7 for safety and compound properties, efficacy predictivity values would be in the 0.4 and 0.2 range, respectively. Of the three scientific causes of attrition, clearly predictivity of efficacy represents the weakest link in successful progression of candidate compounds from the preclinical to the clinical stage of development. 

Conclusion

The present commentary focuses on scientific causes of attrition, and the predictivities of those: efficacy, safety and compound properties. Non-scientific causes of attrition, as reported in the published literature, have varied somewhat, in percentage of total attrition and being generally business-related. Since these are not included, it follows that the above predictivity estimates are likely to be somewhat undervalued. 

These considerations suggest that in order to meaningfully reduce attrition rate, much more work is needed to better define the predictivities of preclinical methods and models, particularly those with respect to efficacy. Work in this general area to date has clearly shown the value of precompetitive collaboration across the industry, as exemplified by recent work on compound properties (e.g., PISC/PhRMA group) and on safety (e.g., DruSafe group). It is important to note however that such collaborative work is both resource and time intensive and requires long-term commitment by all the concerned participants. Yet, it is hard to imagine how pharmaceutical productivity can be improved without it.

Predictivity => Productivity 

References

Hay M, Thomas DW, Craighead JL, et al. Clinical development success rates for investigational drugs. Nat. Biotechnol., 32: 40-51, 2014.

Jones HM, Mayawala K, Poulin P. Dose selection based on physiologically based pharmacokinetic (PBPK) approaches. The AAPS J. 15(2): 377-387, 2013

Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates? Nat. Rev. Drug Discov., 3:711-716, 2004.

Monticello TM, Jones TW, Dambach DM, et al. Current nonclinical testing paradigm enables safe entry to First-in-Human clinical trials: The IQ consortium nonclinical to clinical translational database. Toxicol. Appl. Pharmacol., 334: 100-109, 2017.

Olsen H, Betton G, Robinson D, et al. Concordance of the toxicity of pharmaceuticals in humans and in animals. Regul. Toxicol. Pharmacol., 32(1): 56-67, 2000.

PISC/PhRMA group. J. Pharmaceut. Sci, 100(10): 4045-4157, 2011. This issue has five papers from a PhRMA working group on predicting human pharmacokinetics, plus an editorial and a commentary by its two consultants.    

On Naming Categories

Personal Experience and Observations

Sometimes when you are writing a paper or a report, and you have gotten the main things down – the text and the figures – there is this one issue you need to finalize: the naming of categories included in the paper. Although this is an integral part of the paper, you just don’t consider it as a deciding factor for the acceptance of the work for publication, more like an embellishment. As an example, this could involve work on a categorization of a biomedical system, and you have already decided on the number of categories and their definitions. But what to name the categories?

Writing the Draft with Categories Named by Descriptive Terms

When I was writing the draft of a paper on a categorization of drug treatments based on the relationship between the therapeutic effect of a drug and the pathophysiologic process being treated or prevented (i.e., therapeutic specificity) – this was in 1995 and I was on the faculty at an academic medical center – and after I had completed the text and defined six therapeutic specificity categories, the question arose what their names should be. I recall spending quite some time on what to name the categories, and finally I came up with six descriptive names, using the adjectives preventing, inhibiting, intervening, altering, improving and facilitating. Feeling pretty good about the draft, I submitted the manuscript to Clinical Pharmacology & Therapeutics, but the manuscript was rejected and not considered for publication.

Finalizing the Paper with Categories Named by Roman Numerals

I told one of my senior medical school administrators about my experience, and he suggested I talk to a professor at the school who had been an editor of a journal in his discipline for a long time. So I sent him the manuscript for comments, and within a day or two he called me back and told me that in his opinion the paper read and looked fine, but I should not use descriptive names for categories of therapeutic specificity, because reviewers – and readers – will all get hung up on descriptive terms. So, that’s what I did, I just changed the names from descriptive names to numbered items, using Roman numerals (plus “0”), based on the relationship between the therapeutic effect of a drug and the pathophysiologic process(es) being treated or prevented, as follows:

  • Category 0: for disease prevention
  • Category I: directed at disease etiology
  • Category II: directed at specific disease processes
  • Category III: directed at specific disease manifestations
  • Category IV: for non-specific disease manifestations
  • Category V: for non-therapeutic drug use

An astute reader will note that if we don’t consider Categories 0 and V, which involve preventative treatments like vaccines and drugs like anesthetics, respectively, then the publication basically involves four categories of drug treatments for specific diseases. I the submitted the manuscript to the Journal of Clinical Pharmacology, which promptly accepted it, and that’s where was published: A Classification of Drug Action Based on Therapeutic Effects. J. Clin. Pharmacol., 36(8):669-673, 1996 (for therapeutic specificity scheme refer to Figure 2).

There are of course other non-descriptive approaches to naming categories that I could have used, such as numbers or letters, but I settled on Roman numerals as that felt less ordered than plain numbers, these categories being more categorical than hierarchical. In more complicated situations where there might be categories and subcategories, other approaches can be used, such as alphanumeric approaches, and those including lower-case and upper-case letters.

Subsequent Evolution of The Therapeutics Categorization Project

What happened next? More than two decades later – this was in 2018 and I had retired from the pharmaceutical industry – this general therapeutics categorization scheme had evolved into a much more comprehensive description of systems therapeutics, addressing how the pharmacologic and pathophysiologic processes interact, to culminate in a therapeutic response. This is based on a systems therapeutics diagram, which consists of two rows of parallel systems components for pharmacologic and pathophysiologic processes, representing four different biologic levels of interactions between these two processes, i.e., at the molecular, cellular, tissue/organ or the clinical levels, as follows:

  • Category I: at the molecular level, involving elements/factors
  • Category II: at the cellular level, involving mechanisms/pathways
  • Category III: at the tissue/organ level, involving responses/processes
  • Category IV: at the clinical level, involving effects/manifestations

This latter work, Systems Therapeutics: Diagram, Definitions and Illustrative Examples, was posted on the Therapeutics Research Institute’s website (tri-institute.org), in April, 2018 (for systems therapeutics diagram refer to diagram on page 2).

Takeaways

What are the takeaways from this experience? First, when naming categories avoid using descriptive terms, instead use numbers/numerals or letters. Second, regarding the number of categories, observe the parsimony principle, use only as many as are absolutely needed; three would typically be too few, and often four or five will work fine. Third, conceptual projects may often require many iterations and years to evolve as new experience and knowledge has accumulated to inform the work. Fourth, and not the least, seek help and advice from your colleagues and network; the systems therapeutics project might not have happened if the original therapeutic specificity project had not gotten published.

This post has also been published in Medium in August 2020, under the same title.

Systems Therapeutics: Diagram, Definitions and Illustrative Examples

Executive Summary

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. A systems therapeutics diagram has been constructed, consisting of two rows of four parallel systems components for pharmacologic and pathophysiologic processes, representing the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ levels, and finally the clinical level. Both of these processes have their own sets of initiators or drivers. These different levels of interactions then determine four different systems therapeutics categories. Illustrative examples of these four different systems therapeutics categories are provided, as well as a glossary of the systems components. The systems therapeutics diagram further suggests that the wide interpatient variability in therapeutic response characteristics to approved drugs is contributed to by variabilities in both of these two processes. It is hoped that the systems therapeutics framework advanced here will promote discussions regarding the need for better understanding of the determinants of therapeutic response characteristics of modern therapeutics. 

Contents:

  • Executive Summary
  • Introduction
  • Systems Therapeutics Diagram
  • Systems Therapeutics Categories
  • Systems Therapeutics Illustrative Examples
  • Discussion
  • References
  • Glossary

 

Introduction

While a large number of new drugs have been approved by regulatory agencies over the past several decades, and we have witnessed significant scientific advances in molecular understanding of pharmacologic mechanisms and disease processes, there have only been sporadic efforts towards the construction of frameworks for understanding how pharmacologic and pathophysiologic processes interact to produce therapeutic effects. One noteworthy effort was presented by Grahame-Smith & Aronson in the Oxford Textbook of Clinical Pharmacology and Drug Therapy, which describes the chain of events linking the pharmacologic effects of drugs to their clinical effects, including several examples (1). An earlier effort by this author on classification of drug action based on therapeutic effects  was published in 1996 (2). More recent efforts have included a comprehensive white paper on quantitative and systems pharmacology by Sorger et al. of the QSP Workshop Group, including recommendations (3).

The purpose of this paper is to provide an updated summary of a systems therapeutics framework, depicting pharmacologic and pathophysiologic processes separately, thus enabling the presentation of the different biologic levels of interactions between these two processes. This paper summarizes and updates five previous iterations on the systems therapeutics framework posted on the Therapeutics Research Institute’s website, TRI-institute.org, between April 2015 and February 2018. During this period, this has included an evolving construction of a systems therapeutics diagram, four systems therapeutics categories, relevant definitions, and illustrative examples of the different categories, as well as a discussion of variabilities in pharmacologic and pathophysiologic processes.

Systems Therapeutics Diagram

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response (see diagram below; click for a larger diagram).

The organizing principle underlying the systems therapeutics diagram presented above involves two rows of four parallel systems components for pharmacologic and pathophysiologic processes, representing the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ levels, and finally the clinical level, in addition to the initiating entities or drivers of these processes, and the ultimate therapeutic response.

The systems components for pharmacologic processes start with a pharmacologic response element, followed by a pharmacologic mechanism, a pharmacologic response, and a clinical effect, whereas the systems components for pathophysiologic processes start with an etiologic causative factor, followed by a pathogenic pathway, a pathophysiologic process, and a disease manifestation. The four different biologic levels of interactions between these two processes then determine the four systems therapeutics categories, i.e., Category I (at the molecular level), Category II (at the cellular level), Category III (at the tissue/organ level), and Category IV (at the clinical level). Brief descriptions of the individual systems therapeutics components are provided in the glossary below, including examples for each component.

Both of these two processes are initiated by their own sets of initiators or drivers, i.e., a pharmacologic agent and an intrinsic operator, for the pharmacologic and pathophysiologic processes, respectively. On the pharmacologic process side, a pharmacologic agent (a drug), interacting with a pharmacologic response element (e.g., a receptor or so-called drug target), and its concentration or exposure, is the fundamental driver of pharmacologic processes. On the pathophysiologic process side, a hypothetical intrinsic operator is proposed as an initiating entity or driver interacting with and influencing an etiologic causative factor, and serving as a driver of pathophysiologic processes. This hypothetical intrinsic operator is intended to cover different biologic entities identified using advanced bioinformatics and network-based approaches in disease initiation.

The culminating result of the interaction between these two processes, independent of the biologic level of the pivotal interaction, involves a clinical therapeutic response, determined by the clinical (pharmacologic) effect and the disease manifestation. While it is well recognized that there is a wide variability in the clinical therapeutic response of individual patients to a given approved drug (4,5), it is less well recognized that both of these two processes, pharmacologic and pathophysiologic, have their inherent variabilities. This systems therapeutics construct thus further suggests that interpatient variabilities in both of these active processes contribute to and thus are co-determinants of the ultimate patient therapeutic response characteristics, including range and extent of response, response variability, and responder rate. Presently, however, the relative contributions of each of these process variabilities to the ultimate therapeutic response are typically unclear, most significantly due to limited availability of relevant data and methods, and are likely to vary from one therapeutic class to another. A general commentary (6) discussed variabilities in pharmacologic processes (pharmacokinetics and pharmacodynamics) and pathophysiologic processes (disease initiation and disease progression).

Systems Therapeutics Categories

The systems therapeutics diagram presented here lends itself to determine four systems therapeutics categories, corresponding to the four different biologic levels of interactions between pharmacologic processes and pathophysiologic processes, as follows:

  • Category I – Molecular Level: Elements/Factors
  • Category II – Cellular Level: Mechanisms/Pathways
  • Category III – Tissue/Organ Level: Responses/Processes
  • Category IV – Clinical level: Effects/Manifestations

A further description of each of these systems therapeutics categories is provided below, including definitions and examples of pharmacologic classes and approved drugs for each.

Category I – Molecular Level: Elements/Factors

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves the primary corresponding molecular entities, the pharmacologic response element and the etiologic causative factor, respectively.

Examples of Molecular-based Therapy – These can involve replacement therapies (hormones, enzymes, proteins, genes) or genome-based therapies (interference with altered gene products):

  • Enzyme replacement therapy, e.g., Elaprase (idursulfase) for Hunter Syndrome
  • Protein replacement therapy, e.g., Recombinate (recombinant Factor VIII) for Hemophilia A
  • Potentiation of defective protein, e.g., Kalydeco (ivacaftor) for Cystic Fibrosis
  • Inhibition of abnormal enzyme, e.g., Gleevec (imatinib) for Chronic Myelogenous Leukemia (CML)

Category II – Cellular Level: Mechanisms/Pathways

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a fundamental biochemical mechanism, related to the disease evolution, although not necessarily an etiologic pathway.

Examples of Metabolism-based Therapy – These can involve metabolism-based therapies (interference with a biochemical mechanism or a disease network-linked pathway):

  • HMG-CoA Reductase Inhibitors (statins), e.g., Lipitor (atorvastatin) for Hypercholesterolemia
  • TNF-a Inhibitors, e.g., Humira (adalimumab) for Rheumatoid Arthritis
  • Proton Pump Inhibitors, e.g., Nexium (esomeprazole) for Gastric Reflux & Ulcer Disease

Category III – Tissue/Organ Level: Responses/Processes

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves a modulation of a (normal) physiologic function, linked to the disease evolution, although not necessarily an etiologic pathway.

Examples of Function-based Therapy – These can involve function-based therapies (modulation of a (normal) physiologic function or activity):

  • Angiotensin II Blockers, e.g., Avapro (irbesartan) for Hypertension
  • PDE-5 Inhibitors, e.g., Cialis (tadalafil) for Male Erectile Dysfunction
  • Factor Xa Inhibitors, e.g., Eliquis (apixaban) for Thrombosis

Category IV – Clinical Level: Effects/Manifestations

Definition – The pivotal interaction between pharmacologic processes and pathophysiologic processes involves an effect directed at clinical symptom(s) of a disease, but not directly its cause or etiology.

Examples of Symptom-based Therapy – These can involve symptom-based therapies (various symptomatic or palliative treatments):

  • Antipyretics, e.g., Tylenol (acetaminophen) for lowering high body temperature
  • Analgesics, e.g., Advil (ibuprofen) for Osteoarthritis 
  • Antitussives, e.g., Delsym (dextromethorphan) for cough suppression

Systems Therapeutics Illustrative Examples

Below are illustrative examples for each of the four systems therapeutics categories. The charts follows the design of the systems therapeutics diagram discussed above. The pivotal connection between pharmacologic and pathophysiologic processes represents the fundamental or primary interaction between these processes (represented by a fat arrow), thus determining the systems therapeutics category; these are followed by dependent or secondary connections to the right (represented by thin arrows). The descriptions for the individual systems components were generated from generally available textbooks of pharmacology, pathophysiology and medicine, and other sources, but with an emphasis on a separation of pharmacologic and pathophysiologic concepts and processes, culminating in a therapeutic response.

Illustrative Example for Category I:

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Modulator for Cystic Fibrosis.
See diagram below; click for a larger diagram.

Illustrative Example for Category II:

Proton Pump Inhibitors for Gastroesophageal Reflux Disease (GERD) and Peptic Ulcer Disease (PUD)
See diagram below; click for a larger diagram.

Illustrative Example for Category III:

Angiotensin-Converting Enzyme (ACE) Inhibitors for Hypertension
See diagram below; click for a larger diagram.

Illustrative Example for Category IV:

Non-Steroidal Anti-inflammatory Agents (NSAIDs) for Osteoarthritis
See diagram below; click for a larger diagram.

Discussion

The systems therapeutics diagram has been constructed with the goal of serving to facilitate better understanding and discussion of the different types of successful therapies involving approved drugs. Importantly, this framework shows the pharmacologic processes and the pathophysiologic processes separately, rather than exhibiting a singular pharmacotherapeutic process, and thus illustrating at what biologic level the pharmacologic and pathophysiologic processes interact to result in a therapeutic response. The illustrative examples presented for the four different systems therapeutics categories offer descriptions of the two progressing processes in a storyboard-like fashion, highlighting at what biology level the pivotal interaction occurs between these two processes. 

In addition to the systems components for pharmacologic processes and pathophysiologic processes are the two initiators or drivers of these two processes, one actual (pharmacologic agent), the other hypothetical (intrinsic operator). The former driver is well recognized, including its concentration or exposure, while the rationale for the latter is based on recent bioinformatics and network-based approaches indicating that disease initiation can involve interactions between genetic and non-genetic components, although major research efforts are needed to elucidate the nature of these interactions (6,7). Also, one can speculate that the wide range in the age of disease onset for different diseases, from first year of life to late in life, does suggest unrecognized driving factors acting on an etiologic causative factor. At the present time, however, we are not aware of any current pharmacologic agent/mechanism interacting with such a hypothetical intrinsic operator (which when identified could be represented as systems therapeutics Category Zero). 

It is our hope that the systems therapeutics framework advanced here will help stimulate research towards better understanding of the relationships between the biologic levels of interactions between pharmacologic and pathophysiologic processes on one hand and the therapeutic response characteristics of modern therapeutics on the other. It has previously been noted that although this systems-based framework does not explicitly address interpatient variability in therapeutic response, this framework clearly suggests that variabilities in pharmacologic processes and pathophysiologic processes both contribute to the overall variability in therapeutic response. We further hope that this framework will stimulate research towards better qualitative and quantitative descriptions of the pharmacologic and pathophysiologic processes, including ways of defining the relative contributions of these two processes towards determining the overall therapeutic response characteristics.

References

  1. Grahame-Smith DG, Aronson JK (1992). Oxford Textbook of Clinical Pharmacology and Drug Therapy, Oxford University Press, Oxford (Chapter 5. The Therapeutic Process, pp. 55-66).
  2. Bjornsson TD (1996). A classification of drug action based on therapeutic effects. J. Clin. Pharmacol., 36:669-673.
  3. Sorger PK, Allerheiligen SRB, Abernethy DR, et al. (2011). Quantitative and systems pharmacology in the post-genomic era: New approaches to discovering drugs and understanding therapeutic mechanisms. An NIH white paper by the QSP workshop group. Bethesda: NIH (pp. 1-47).
  4. Rowland M, Tozer TN (2011). Clinical Pharmacokinetics and Pharmacodynamics: Concepts and Applications, Fourth edition, Lippincott Williams & Wilkins, Philadelphia (Chapter 12, Variability, pp. 333-356).
  5. Eichler HG, Abadie E, Breckenridge A, Flamion B, Gustafsson LL, Leufkens H, Rowland M, Schneider CK, Bloechl-Daum B (2011). Bridging the efficacy-effectiveness gap: a regulator’s perspective on addressing variability of drug response. Nat. Rev. Drug Disc., 10:495-506.
  6. Therapeutics Research Institute. Systems Therapeutics: Variabilities, May 2016. https://tri-institute.org/TyQij
  7. Barabasi AL, Gulbahce N, Loscalzo J (2011). Network medicine: a network-based approach to human disease. Nat. Rev. Genetics, 12:56-68

Glossary

Below is a glossary of the individual systems components for the pharmacologic and pathophysiologic processes represented in the systems therapeutics diagram presented above. Examples for each systems component are from among approved treatments and diseases that have previously been addressed in individual posts on the Therapeutics Research Institute’s website, TRI-institute.org.  

Pharmacologic Processes

Pharmacologic Agent 
A compound, could be a small molecule or a large bio-pharmaceutical, that initiates the pharmacologic process by interacting with a pharmacologic response element.

Examples:
   Nexium (esomeprazole), and
   Viagra (sildenafil)

Pharmacologic Response Element
A native biologic element, could be a receptor or an enzyme, with which a pharmacologic agent interacts (pharmacologic interaction). Commonly referred to as a pharmacologic target.

Examples:
   H+/K+ ATPase (proton pump); and
   cGMP-specific phosphodiesterase type 5 (PDE5).

Pharmacologic Mechanism
Molecular mechanism of action, typically involving a molecular pathway resulting in a biochemical reaction (signal transduction).

Examples:
   Inhibition of proton pump (for Acid Reflux and Ulcer Disease); and
   Inhibition of PDE5 (for Male Erectile Dysfunction).

Pharmacologic Response
Pharmacologic effect at the tissue/organ level mediated through a pharmacologic mechanism (pharmacodynamics).

Examples:
   Decreased gastric acid secretion resulting in decreased acidity (by proton pump inhibitor); and
   Smooth muscle relaxation in corpus cavernosum leading to increased blood flow (by PDE5 inhibitor).

Clinical Effect
A pharmacologic effect at the clinical level, which represents the pharmacologic basis for a therapeutic response (translation).

Examples:
   Decreased symptoms from gastric acidity (by proton pump inhibitor); and
   Increased erection (by PDE5 inhibitor).

Pathophysiologic Processes

Intrinsic Operator
A hypothetical entity interacting with and influencing an etiologic causative factor, serving as a driver of a pathophysiologic process. Could be genetic or non-genetic.

Examples:
   Currently typically not known 

Etiologic Causative Factor
A genetic or non-genetic factor, upon interaction with an intrinsic operator (disease preindication), determines a disease specific progression.

Examples:
   Dihydrotestosterone (DHT)-induced growth factors and their receptors (in Benign Prostatic Hyperplasia); and
   Post-menopausal and age-related osteoporosis is initiated by a developing imbalance between net bone formation and resorption (in Osteoporosis).

Pathogenic Pathway
Molecular pathogenic pathway mediating ongoing disease progression (disease initiation).

Examples:
   DHT-induced growth factors stimulate proliferation of stromal cells (in Benign Prostatic Hyperplasia); and
   The normally regulated bone remodeling process is modulated by numerous systemic factors (in Osteoporosis)

Pathophysiologic Process
Ongoing pathophysiologic process (pathogenesis).

Examples:
   Formation of  discrete hyperplastic nodules in periurethral region (in Benign Prostatic Hyperplasia); and
   Gradual and continuing loss of bone mineral density, decreased bone quality, with increased risk of fracture (in Osteoporosis)

Disease Manifestation
Development of characteristic clinical signs and symptoms associated with a given disease (progression), typically independent of a specific etiologic causative factor.

Examples:
   Lower urinary tract symptoms (in Benign Prostatic Hyperplasia); and
   Loss of bone mineral density and risk of bone fracture (in Osteoporosis).

Therapeutic Response
Therapeutic benefit of a drug on which approval is based, showing a beneficial change in specific objective and/or subjective measures of a disease.

Examples:
   Symptom relief and mucosal healing (e.g., after proton pump nhibitors in Acid Reflux and Ulcer Disease)
   Improved erection (e.g., after PDE5 inhibitors in Male Erectile Dysfunction)
   Decreased urinary frequency (e.g., after 5-alpha reductase inhibitors in Benign Prostatic Hyperplasia)
   Decreased bone fractures (e.g., after bisphosphonates in Osteoporosis)

Systems Therapeutics: Representative Illustrative Example for Category II

Introduction

Systems therapeutics defines where pharmacologic processes and pathophysiologic processes interact to produce a clinical therapeutic response. A systems therapeutics diagram has been constructed (1), consisting of two rows of four parallel systems components for pharmacologic and pathophysiologic processes, representing the four different biologic levels of interactions between these two processes, i.e., at the molecular level, the cellular level, the tissue/organ levels, and the clinical level, culminating in a therapeutic response. The interactions at these different biologic levels then determine the four different systems therapeutics categories, Categories I – IV. The above referenced summary only named therapeutic class examples for each of the four systems therapeutics categories, but did not include representative illustrative examples for each of these categories.

The purpose of this post is to provide an illustrative example for one of the systems therapeutics categories, Category II, where the pivotal interaction between the pharmacologic and pathophysiologic processes involves a fundamental biochemical mechanism at the cellular level, related to the disease evolution, although not necessarily an etiologic pathway. The illustrative example chosen for Category II involves Proton Pump Inhibitors for Gastroesophageal Reflux Disease (GERD) and Peptic Ulcer Disease (PUD). Future communications will provide illustrative examples for the other systems therapeutics categories.

Illustrative Example for Category II

The chart below (click for a larger view) illustrates the individual systems components for pharmacologic and pathophysiologic processes for Proton Pump Inhibitors for Gastroesophageal Reflux Disease (GERD) and Peptic Ulcer Disease (PUD), culminating in a therapeutic response.

This chart follows the design of the systems therapeutics diagram previously referenced (1), which includes definitions of the individual systems therapeutics categories and a glossary of the individual systems components. The chart was developed using OmniGraffle (The Omni Group, Seattle, WA). The bold connection between pharmacologic and pathophysiologic processes represents the pivotal interaction between these processes, which here is at the cellular level (Category II). The descriptions for the individual systems components were generated from generally available textbooks of pharmacology, pathophysiology and medicine, and other sources, but with an emphasis on a separation of pharmacologic and pathophysiologic concepts and processes, culminating in a therapeutic response.

Comments

The systems therapeutics framework referenced above (1), including a diagram, four categories, definitions and a glossary, was constructed with the goal of serving to facilitate discussion and understanding of the different types of FDA approved drugs. Importantly, this framework attempts to illustrate the pharmacologic processes and the pathophysiologic processes separately, rather than exhibiting a singular pharmacotherapeutic process, in contrast to previously published attempts, thus enabling highlighting at what level the pharmacologic process engages with the pathophysiologic process. It has previously been noted that this systems-based framework does not explicitly address interpatient variability in therapeutic response, although this framework clearly suggests that variabilities in pharmacologic processes and pathophysiologic processes both contribute to the overall variability in therapeutic response. A general commentary on variabilities in pharmacologic processes (pharmacokinetics and pharmacodynamics) and pathophysiologic processes (disease initiation and disease progression) has been previously published (2).

The chart presented in this publication has provided a representative illustrative example for one of the four systems therapeutics categories (Category II). It is hoped that this illustration will serve as a useful example of how the systems therapeutics framework can provide a framework for facilitating discussions concerning various aspects of different therapeutics, as well as suggesting areas in need of future research and better understanding.

References

  1. Systems Therapeutics: Where Pharmacologic and Pathophysiologic Processes Interact. Therapeutics Research Institute, February 2017.
    This post summarizes the systems therapeutics framework, including the systems therapeutics diagram, its four categories, related definitions, as well as a glossary. Note the example presented above for Category II was initially named as Category III.
  2. Systems Therapeutics: Variabilities. Therapeutics Research Institute, May 2016. 
    This post discusses variability in pharmacologic processes (pharmacokinetics and pharmacodynamics) and pathophysiologic processes (disease initiation and disease progression). Note the systems therapeutics diagram in this post represents an earlier version of the diagram. 

 

 

 

 

Infographics of Modern Therapeutics

Introduction

The purpose of this report is to provide highlights from two posts involving infographics of modern therapeutics, since these posts were originally only listed under their months of posting, but not indicating their titles. These were as follows:

The graphs in these two posts are in addition to extensive infographics on the progression of 40 therapeutic classes, across 14 therapeutic categories, included in Progression of Modern Therapeutics, issued January 2016, and in a more extended reporting on 16 therapeutic classes, summarized in List of 16 Posts on Individual Therapeutic Classesissued January 2018.

Methodology

The data used in both of these two above referenced posts are originally from Progression of Modern Therapeutics, which covers 40 therapeutic classes from 14 therapeutic categories, and which includes a detailed description of the methodology and definitions used in this project. Note the following definitions used throughout:

  • Modern therapeutics – refers to those new drug approvals belonging to a given pharmacologic class that were first approved in the 1970’s to 1980’s timeframe and going forward, as further defined in Progression of Modern Therapeutics.
  • Pharmacologic class – refers typically to a biologic target-based or mechanism of action-related classification, but in some instances involves a chemical classification, or a mix of the two.
  • Therapeutic class – refers to new drug approvals for a given disease or indication, independent of pharmacologic class.
  • Therapeutic category – refers to approved therapeutics in a given anatomical organ or system.
  • Length of registration interest – refers to the time interval between the dates of the first and the latest new drug approval within a given pharmacologic class.

Number of Pharmacologic Classes per Therapeutic Classes

The number of pharmacologic classes per individual therapeutic classes for new drug approvals is shown in the graph below, in a descending order, for 38 of the 40 therapeutic classes covered in Progression of Modern Therapeutics. 

Click here for a larger graph. Note the wide range in the number of pharmacologic classes per therapeutic classes, ranging from 11 and 9 for Type-2 Diabetes and Multiple Sclerosis, respectively, and 8 each for Rheumatoid Arthritis and Melanoma, to 1 each for Idiopathic Thrombocytopenic Purpura and Systemic Lupus Erythematosus, and several therapeutic classes with 2 each, including Alzheimer’s Disease and Schizophrenia. Note that the mean and median for the number of pharmacologic classes per individual therapeutic classes (N=38) are 4.3 and 4.0, respectively.

New Drug Approvals per Therapeutic Classes

The number of new drug approvals for 38 of the 40 therapeutic classes covered in Progression of Modern Therapeutics is shown in the graph below, in descending order. 

Click here for a larger graph. Note the wide variability in the number of new drug approvals for the different therapeutic classes, ranging from 44 for Hypertension, 28 for HIV-1/AIDS, 27 for Type-2 Diabetes and 23 for Schizophrenia, to 1 for Systemic Lupus Erythematosus, 2 each for Idiopathic Thrombocytopenic Purpura and Idiopathic Pulmonary Fibrosis (both orphan indications) and 3 for Fibromyalgia. Note that the mean and median for the number of new drug approvals per individual therapeutic classes (N=38) are 11.5 and 9.5, respectively.

Selected Snapshots from Noteworthy Patterns in Registration Avivities

Below are two selected snapshots based on data in Progression of Modern Therapeutics, each illustrating a specific pattern in registration activities of modern therapeutics:

Snapshot #1: Two therapeutic classes showing two key pharmacologic classes with no overlaps in registration activities, i.e., H2 Receptor Antagonists and Proton Pump Inhibitors for Acid Reflux and Ulcer Disease, and Benzodiazepines and Non-benzodiazepines for Insomnia. Both examples show an abrupt switch in new drug introductions from older pharmacologic classes to newer pharmacologic classes. For a larger graph click here.

no overlap

Snapshot #2: Two therapeutic classes showing two key pharmacologic classes with overlaps in registration activities, i.e., Corticosteroids and Beta-2 Adrenergic Agonists for Asthma, and SSRI’s and SNRI’s for Depression. Both examples show concurrent new drug introductions for two dominant or somewhat similar pharmacologic classes or mechanisms of action. For a larger graph click here.

overlap

Length of Registration Interest

Perusal of the graphs for 40 therapeutic classes in Progression of Modern Therapeutics also illustrates a wide variability in the length of registration interest, i.e., the time interval between the dates of the first and the latest new drug approval within a given pharmacologic class (shown on the right hand side of the graphs). Of the more than 180 pharmacologic classes covered, it is if interest to note that 16 classes have lengths of registration interest longer than 25 years, e.g., Beta-Blockers for Hypertension (40.1 decimal years) and Typical and Atypical Antipsychotics for Schizophrenia (26.9 and 25.9 decimal years, respectively), and that lengths between 10 and 20 years are quite common for established pharmacologic classes, e.g., TNF Inhibitors for Rheumatoid Arthritis (10.5 decimal years) and PDE-5 Inhibitors for Erectile Dysfunction (14.1 decimal years).

Comments

The infographics of modern therapeutics presented in this report involve examples from two previous posts, but are highlighted here, since the original posts were only listed under their months of posting (February 2016 and June 2016), but not indicating their titles. 

The graphs and texts illustrate wide variability in new drug approvals among the different pharmacologic classes and therapeutic classes. This involves both the number of pharmacologic classes per individual therapeutic classes, and the number of new drug approvals per individual therapeutic classes. For example, the number of pharmacologic classes per individual therapeutic classes ranged from 11 (Type-2 Diabetes) to 1 (Systemic Lupus Erythematosus), and the number of new drug approvals per individual therapeutic classes ranged from 44 (Hypertension) to 1 (Systemic Lupus Erythematosus). Also noteworthy is that 16 pharmacologic classes of the more than 180 covered have lengths of registration interest longer than a quarter of a century; also note the most common interval of lengths of registration interest is 10-20 years (31 pharmacologic classes), for lengths longer than 5 years.

Note these graphs only involve new drug approvals, and do not include generics, new formulations, or new trademarks of previously approved chemical entities. Also note these graphs and texts are based on data available in early 2016; there may have been a few new drug approvals in some of the covered therapeutic classes since then, but not so much as to alter the key conclusions presented.

It is tempting to speculate what might be the reasons underlying such wide variabilities in the number of pharmacologic classes per therapeutic classes, in the total number of new drug approvals per therapeutic classes, and in the relatively long periods of registration interest for numerous pharmacologic classes, but that will be left to another time. Public discussion on these important topics, however, is very important, since at a high level, these are likely to relate to how society in general – including the academic research community, the regulatory agencies, the pharmaceutical R&D community, and patient and disease organizations – attempt to address varying degrees of scientific knowledge about disease etiology and pathophysiology, levels of research funding, commercial assessment, and different levels of unmet medical need.