The Role of Model Based Drug Development – Is it time to repaint the canvas?
Vikram Sinha (Director, Division of Pharmacometrics, Office of Clinical Pharmacology, CDER, USFDA)
FDA
Drug development and regulatory decisions are driven by information that is compiled primarily from clinical trials and other supportive experiments, but also through clinical experience in the post-market period. The wisdom of these decisions determines the efficiency of drug development, the decision to approve the drug, and the resultant guidance on how to use the product, in the label.
While the decisions are usually simple in nature (e.g., trial design and project progression at the company, product and labeling approval at FDA), the data informing the decision are complex and diverse. The used of models in informing decisions (MBDD) with an intent to build a mathematical model of the pertinent physiology includes a pharmacokinetic/pharmacodynamic drug model that tells us how the compound works. It is used to simulate clinical trials in which the following elements can be tested: 1) Develop and test hypotheses for optimizing dosing, 2) simulate alternative dosing strategies, 3) simulate alternative patient populations and, 3) simulate alternative combination treatments.
In addition to ensuring quality standards, regulators are looking for evidence regarding appropriate dosing, consistency among multiple end points and evidence that benefits exceed harms. Many of these elements can be ascertained before a phase 3 trial is conducted. Indeed, what constitutes confirmatory evidence in support of confirmatory trials has been a subject of much debate. Since the first days of the science of pharmacology, evidence of “dose-response” has always constituted the strongest possible positive evidence of a pharmacologic mechanism of action. As our understanding of pharmacologic and pathophysiologic mechanisms increases and more drugs are designed to interact with specific receptors whose links to pathophysiologic mechanisms are well understood, drugs whose pharmacologic mechanism of benefit remains uncertain will constitute a smaller fraction of candidates for development and approval. Thus, MBDD offer an important learning tool not only into mech anistic insights but require clear expression of assumptions and expectations. The single-most important strength of such analyses is its ability to integrate knowledge across the development program, compounds, and biology.
This presentation will address the role and scope of model based drug development throughout the drug development process with a focus on the role its role in regulatory decision making. Challenges faced regarding modeling and simulation in drug development and strategies to foster and advance appropriate use of modeling and simulation across disciplines will be discussed. Specific use of MBDD in the following areas will be discussed 1) Role of M&S for a trial/program design (e.g. pediatrics) 2) Characterization of dose (exposure) response and dose justification 3) Characterization of multiple endpoints and 4) Subgroup analysis.
