CDER Conversation: Model Informed Drug Development
Talking with Raj Madabushi, Ph.D., Team Leader, Guidance and Policy Team, Office of Translational Sciences, Office of Clinical Pharmacology, CDER.
Model-informed drug development (MIDD) is an approach that involves developing and applying exposure-based, biological and statistical models derived from preclinical and clinical data sources to inform drug development and decision-making. It aims to integrate information from diverse data sources to help decrease uncertainty and lower failure rates, and to develop information that cannot or would not be generated experimentally1. Integrating MIDD into more drug applications and advancing its use are some of FDA’s goals under the Prescription Drug User Fee Amendments of 2017 (PDUFA VI).
Raj Madabushi, Ph.D., Team Leader, Guidance and Policy Team, Office of Translational Sciences, Office of Clinical Pharmacology, CDER, discusses the current status and promise of this approach.
What are the key elements of Model Informed Drug Development (MIDD)?
MIDD is based on three elements:
- Leveraging a thorough understanding of the drug, a disease, and how a drug affects the human body, as well as how the body responds to the drug.
- Quantifying information by developing mathematical models based on full use of all available data, from sources such as in vitro (e.g., outside the body), preclinical and clinical studies.
- Applying this knowledge to address issues pertaining to drug development or clinical use. MIDD has been applied to predict clinical outcomes, inform clinical trial designs, support evidence of effectiveness, optimize dosing, predict product safety, and evaluate potential adverse events. MIDD approaches routinely provide a starting point for pediatric drug development, based on solid understanding of developmental physiology and disease pathology. In some disease areas, dosing in children is based on MIDD approaches.
What activities are planned to support the PDUFA VI goal of advancing the use of MIDD?
FDA is planning multiple activities to advance the use of MIDD under PDUFA VI. These include four workshops focusing on best practices and methodological limitations, a pilot program, updated guidance, and new standard operating procedures for conducting specific analyses.
The workshops will offer a forum for discussions among experts, with the goal of achieving consensus and providing clarity on areas that are already well advanced, and areas needing more effort. These discussions can also ensure that MIDD is fully understood by everyone, including decision-makers. Workshop topics include (1) physiologically-based pharmacokinetic modeling; (2) design analysis and inferences from dose-exposure-response studies; (3) disease progression model development, including natural history and trial simulation; and (4) immunogenicity and correlates of protection for evaluating biological products, including vaccines and blood products.2
Under the pilot program, an internal FDA group will review programs with limited clinical data, and where non-traditional sources of evidentiary support may be helpful. The pilot program aims to advance the use of MIDD as part of the regulatory pathway for drugs, helping both FDA and sponsors to work through issues around developing models, establishing their credibility, and determining how they can be used to address regulatory or drug development issues.
FDA plans to publish a draft guidance on MIDD or revise relevant existing guidances. In addition, the agency will develop or revise relevant policies and procedures, review templates, and conduct training that will help sponsors and reviewers understand how to use MIDD consistently as part of the regulatory process.
How can MIDD potentially streamline and accelerate drug development?
MIDD can streamline and accelerate the development of new medical products by helping to design better future trials. In some instances, MIDD can reduce the need for additional clinical trials, require fewer patients for studies, or increase the probability of success by aiding in the selection of the right dosing, duration, and patient population. These advantages enable more informed decision-making, and reduce uncertainty when moving between phases of development, giving sponsors confidence to move more quickly to the next phase.
MIDD has been applied in many areas. The approach has helped sponsors identify target concentrations and therapeutic windows; examine drug-drug interactions; optimize doses, particularly in children; ensure the safety of specific populations; and design better trials. As a result, some companies have been able to perform smaller or shorter clinical studies, and carry out fewer postmarketing studies.3
How do MIDD approaches bring value to regulatory decision-making and therapeutic use?
MIDD is unique in that it can provide insights about the benefits and risks of new therapies beyond the primary intent of clinical trials.
Clinical trials are carried out in a sample of patients with a disease, and are aimed mainly at answering one or several questions, such as whether the primary outcome measure differs significantly between or among treatment groups. But other questions may arise during regulatory review and once a new treatment is approved. For example:
- Can the dosing be optimized for the general population or high-risk subpopulations?
- Can we provide dosing for some unstudied subpopulations of interest?
- Are there risks when other medications are co-administered, and if so, how can these be mitigated?
MIDD can answer these and other questions by providing information to bridge efficacy and safety for certain unstudied patient subpopulations or use scenarios. This rational approach makes the most efficient use of available information to inform next steps or, in some cases, reduce or eliminate the need for additional trials.
What are the challenges in applying MIDD approaches to drug development and regulatory decision-making?
The limitations of MIDD are the same as those for any prediction approach – models are only as good as the data on which they are built. Models cannot always substitute for a basic level of required information. Also, the need for acceptance of MIDD is a major challenge. At present, MIDD is widely accepted in some therapeutic areas but not in others. Another challenge is that it is not yet applied consistently to critical drug development decisions and in regulatory decisions. These challenges underscore the need for best practices for determining when a model is deemed acceptable for application. MIDD best practices would also help clarify regulatory expectations. Today, extensive information is available to help make decisions. However, our infrastructure for warehousing the data and knowledge lags behind, which limits our ability to translate MIDD approaches to address drug development issues.
What is the future landscape of MIDD?
Industry has been proactively using MIDD approaches to supplement internal decisions as part of drug development. Moreover, the activities outlined under PDUFA VI goals will determine how MIDD approaches are applied to regulatory decision-making. There have been exciting advances in new approaches and methods of analysis, allowing for greater use of the totality of evidence than in the past. We are seeing advances in understanding the physiological basis of disease and in systems pharmacology. These advances are helping us anticipate who might be at risk for certain diseases or drug safety events. Ongoing innovation will offer more chances to enhance the value offered by MIDD in drug development.
Global initiatives are also underway. The European Medicines Agency is actively developing best practices, and similar efforts are ongoing at the Japan Pharmaceuticals and Medical Devices Agency. There is also interest in a consolidated approach by the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use.
These and other future efforts bode well for MIDD approaches to deliver on their promise.
For more information:
Read about the Model-Informed Drug Development Pilot Program.