Applying New Science to Drug Safety Janet Woodcock, M.D. Acting Deputy Commissioner for Operations April 15, 2005

Current Drug Safety System n n Extensive premarket testing with rigorous FDA review, including evaluating of remaining uncertainties n n (Proposed) user-friendly communication via drug label, compatible with e-prescribing & electronic decision support n n Proactive risk management strategies prior to and post approval n n Voluntary adverse event reporting system with additional population-based information

Capacities of Current System: n n Generate profile of common adverse events in tested populations during drug development n n Understand drug metabolism and common metabolism-based drug-drug interactions n n Develop plans for managing/evaluating certain anticipated risks after marketing n n Identify rare serious adverse events after marketing

What Current System May Not Elucidate: n n Increases in frequency of events that occur commonly-to-uncommonly in the population without the drug n n Time dependent events n n Events occurring more frequently in populations not tested in trials: the very sick, those on polypharmacy, multiple medical problems, etc. n n Events that occur much more frequently with off- label use – –Tendency toward medical errors or abuse

Approaches to Resolution of the Knowledge Gaps n n Utilization of emerging electronic medical record systems for surveillance n n Randomized trials or registries conducted in practice settings after marketing n n More surveillance systems in specialized settings: e.g., ER, nursing homes, etc.

These Approaches Should Be Implemented But They are Not Sufficient n n Traditional focus on detection, communications, (warnings, precautions), management n n Need to add where possible: prediction; prevention; monitoring; mitigation n n Avoid treatment of individuals at high risk for event: serious side effects occur in only a small fraction of patients n n Develop new ways of monitoring for emerging toxicity before it becomes severe

Imperatives for Change n n Drug development (e.g., animal & human testing) is largely empirical in nature n n This tradition focuses on population means & observations of outliers n n Directly translated into “trial and error” approach in clinical medicine n n Major loss of information

Imperatives for Change n n There are significant limitations on the number of questions that can be answered via empirical testing (imposed by # of patients, changing practice patterns, cost, etc) n n Despite hundreds of millions of dollars invested in a development program – we often lack key information at approval. We know that the drug is effective in a defined population, and can describe the common side effects n n Many of the patients subsequently exposed will not benefit from the Rx

Imperatives for Change n n Success rate for Phase I entries below 15% n n No other major part of the technological infrastructure (e.g. civil engineering, aeronautics, electrical engineering, electronics, etc) operates on nearly this level of risk n n The same evaluative tools that will improve predictability will also support markedly improved decision making in clinical medicine n n Much of this information can be developed now

Example: Drug Metabolism n n Drugs that are CYP450 2D6 substitutes may have up to 10 fold higher blood levels from “normal” dosing in “poor metabolizers” n n Distribution of alleles varies with ethnicity n n These drugs frequently implicated in “unavoidable” side effects n n Role of variable exposure not well elucidated n n FDA recently approved a commercial test to determine an individual’s 2D6 status

Drug Metabolism in Drug Development n n Development of in vitro human cell models and animal models over last 15 years have enabled manufacturers to predict human metabolism n n Avoid candidates with problematic metabolism/drug- drug interactions n n These have dropped in same timeframe from leading cause of late clinical failures to minor cause n n Critical path focused on development of additional tools

Example: New Technologies n n Genomic, proteomic, metabolomic markers n n Status in patients with serious side effects vs those without? n n Study in prospective trials and from MedWatch reports n n Develop ability to avoid high risk patients or monitor for development before overt toxicity occurs

Development of Targeted Therapeutics n n Identify subgroups of patients with high response rates n n Avoid treatment of people with low probability of benefit n n Can remarkably decrease required power of trials in drug development n n Can significantly improve benefit/risk assessment

Future of Drug Safety n n Continue to improve current system but also– n n Deliver right dose to right patient and – n n Monitor for emergence of side effects n n Prevent serious side effects

Issues n n How to get this applied science done? n n No entity charged with task n n Public-private partnerships may be ideal n n Need venues to pool anonymized proprietary data n n Need ability to conduct studies or add-on modules to existing trials