Responder Rates and Therapeutic Response Variabilities

Background

While it’s generally recognized that individual patients respond differently to approved drugs, this topic has received limited public comments by developers and regulators. A single publication from 2001 lists approved drugs across thirteen therapeutic classes, reporting that the patient responder rate ranged from 25 to 80%, averaging about 50% across these therapies (1). The therapeutic classes examined involved drugs for Alzheimer’s disease, analgesics (Cox-2 inhibitors), asthma, cardiac arrhythmias, depression (SSRIs), type-2 diabetes, hepatitis C virus, urinary incontinence, migraine, oncology, osteoporosis, rheumatoid arthritis, and schizophrenia (click on Table 1). Only the percentage of the trial populations characterized as responders was reported for each therapeutic class, but neither the inter-patient variability in therapeutic response nor which or how many drugs were evaluated for each class. The responder qualifications were based on regulatory requirements for approval for each class, and the responder rates were based on information provided in the approved product labels (2); thus, a responder rate as used here is a regulatory construct. There doesn’t appear to have been any update or followup on this topic since that publication. It is noteworthy in this regard that since the time of the above-mentioned publication, a total of 386 new drugs or NMEs (between years 2001 and 2014, inclusive) have been approved by the FDA (3), including those with novel mechanisms of action, new platforms, new indications, suggesting that some of the reported therapeutic class-based responder rates may have changed and new ones added. It is also worth noting that the above-mentioned publication has often been quoted to promote personalized medicine (4,5), based in part on the unmet medical need of the non-responders.

Publicly Available Database on Therapeutic Response Characteristics

Considering the significance of therapeutic response characteristics, including responder rates, of approved drugs or therapeutic classes, it’s all the more surprising how limited data is readily available on this topic, i.e., information that’s presented in a uniform and easily understood format. Given the current situation and the desire for a comprehensive, publicly available database on therapeutic response characteristics of approved drugs, before there can be meaningful progress on this front, there are a few significant methodological and procedural issues that need to be considered and resolved.

First, clinical trials data – The most comprehensive clinical trials data for approved drugs, including clinical study reports with complete data tables, listings and figures, involve the registration submission dossiers from individual pharmaceutical sponsors. Considering that these documents are proprietary, the most obvious sources of patient response and efficacy information would be the regulatory authorities that review and approve new drug applications or marketing authorizations, as well as the respective product labels. For US approvals, this involves the review summaries by the FDA medical and other reviewers (formerly called Summary Basis for Approval), containing the different regulatory reviews supporting approval and the product label (6). Similar information is available for European approvals, in a slightly different format (7). While both of these public sources contain huge amounts of data, the information of interest does not appear to be specifically highlighted, or at least not developed into a readily digestible uniform format. Also, when using such clinical trials data for the task at hand, there are different aspects that may need to be considered for a given therapeutic class, e.g., changes in regulatory requirements, changes in clinical practice, data from post-approval clinical trials, dose-response relationships, number of approved doses, and risk-benefit considerations. These considerations require the development of a review protocol, with details commensurate with the intended level of assessment granularity.

Second, definitions and methodology – Patients with varying degrees of a desired pharmacologic or therapeutic response have been referred to clinically by different terms, which have often been poorly and inconsistently defined. This refers typically to patients on both ends of the response distribution curve, e.g., non-responders, poor responders and treatment resistant patients on one end, and good responders, super-responders and treatment sensitive patients on the other end. This calls for unambiguous definitions of the different terms used for therapeutic response characteristics. Also, for greater utility, should other definitions than those based on regulatory approval requirements for responders be considered? It would seem desirable that a consistent format be developed and adopted for presenting therapeutic response characteristics of approved drugs, somewhat analogous to the development of data standards for clinical trials data, including the actual response or efficacy endpoint values, and the outlier response groups, both the top and bottom values. Then there are the issues of how to address drugs within the same pharmacologic class, individually or as a group, and whether the approved NME involved is a single drug or a combination product or therapy, e.g., on top of standard of care? It is suggested that to arrive at innovative and informative designs for characterizing therapeutic response data will require inputs from the relevant academic, industry and regulatory communities.

Third, implementation approach – As has been addressed above, preliminary work is needed on what clinical trials data to use, although the FDA medical and statistical reviewers summaries sound like a good starting place, and on definitions and methodology, including infographics designs, and what therapeutic classes to start with. It is noted that our organization’s project on “Progression of Modern Therapeutics” was initiated in part to help guide this project on “Therapeutic Response Characteristics”, including what pharmacologic and therapeutic classes first to consider for this project. Clearly, considering the many issues and complexities involved in both the needed preliminary work and the subsequent work on the therapeutic response characteristics database, this is a long-term project that will require well coordinated partnerships among the relevant academic, industry and regulatory communities.

Benefits of a Publicly Available Database

There are many benefits and opportunities to the medical and scientific communities associated with having a comprehensive, publicly available database on key therapeutic performance measures of approved drugs within their therapeutic classes, including actual responses, responder rates, and response outliers, in an easily understood and consistent manner. These include the following:

  • Raising widespread awareness, among patients, prescribers, payors, researchers, developers large and small, regulators, and disease organizations regarding differing therapeutic response characteristics among approved drugs by indications and therapeutic areas;
  • Highlighting unmet medical need due to therapeutic inadequacy for a disease or indication based on high rates of poor responders to approved drugs and related healthcare implications;
  • Providing an evidence-based foundation for future knowledge-base explorations, e.g., combining such a database with biologic, pharmacologic, disease and genomic databases;
  • Catalyzing interest in the development of companion diagnostics and clinically applicable tests to monitor treatment effects to avoid continuing treatment in those not responding (but still at risk of experiencing adverse effects);
  • Allowing explorations across different therapeutic classes, e.g., comparing response characteristics of small molecules vs. biological drugs, and comparing response characteristics based on surrogate vs. clinical endpoints; and finally,
  • Addressing various questions and hypotheses relating to systems therapeutics, e.g., how similar are response characteristics for different pharmacologic classes for given therapeutic classes?

Conclusions

The case has been presented for the development of a publicly available database on therapeutic response characteristics of approved drugs, presented in a consistent and easily understood format. We believe that this important topic has not been given the attention it deserves. We further believe there are numerous benefits and opportunities deriving from such a database, not the least of which is catalyzing activities on precision medicine and regulatory science. Obviously, an undertaking of this magnitude will require a significant effort involving the participation and partnerships with the relevant academic, industry and regulatory communities.

References

  1. Spear, B.B., Heath-Chiozzi, M., Huff, J. Clinical applications of pharmacogenetics. TRENDS Mol. Med., 7, 201-204 (2001).
  2. Physicians Desk Reference (printed version, 54th edition, 2000), now available online at http://www.pdr.net.
  3. FDA’s New Molecular Entity (NME) Drug and New Biologic Approvals, http://www.fda.gov/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/DrugandBiologicApprovalReports/NDAandBLAApprovalReports/ucm373420.htm
  4. Personalized Medicine Coalition. The Case for Personalized Medicine, 4th Edition, 2014, accessible at http://www.PersonalizedMedicineCoalition.org
  5. Aspinall, M.G., Hamermesh, R.G. Realizing the promise of personalized medicine. Harvard Business Review, 85(10), 108-117 (2007).
  6. Food and Drug Administration’s Drugs@FDA, http://www.accessdata.fda.gov/scripts/cder/drugsatfda
  7. European Medicines Agency’s European Public Assessment Reports (EPAR), http://www.ema.europa.eu/ema/index.jsp?curl=pages/medicines/landing/epar_search.jsp&mid=WC0b01ac058001d125