Transforming Evidence Generation for Drug Label Changes: A Case Study

Annals of biomedical engineering(2022)

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Abstract
Computer Modeling and Simulation (CM&S) provides the opportunity to drastically reduce clinical trial patient burden and advance regulatory decision making. At the suggestion of the US Food and Drug Administration (FDA), MannKind Corporation and Nudge BG submitted an application to the FDA Model-Informed Drug Development (MIDD) pilot program to support a label change for the initial dose of Afrezza® (insulin human), a novel inhalable insulin with a rapid pharmacokinetic and pharmacodynamic profile. The MIDD pilot program demonstrates the FDA’s commitment to advancing regulatory science through the adoption of evidence generated by CM&S. A simulation framework was developed based on empirical data. It was used to generate evidence to support the label change. Briefing packages and presentations were prepared for two meetings with the FDA, over a period of four months. The model was thoroughly characterized, determined to be low risk for the question of interest, and submitted along with additional clinical evidence for validation. The FDA found the simulation framework to be helpful in providing insights into the question of interest and provides reasonable glycemic outcome predictions. At the conclusion of the MIDD paired meetings, FDA personnel from the Center for Drug Evaluation and Research review team accepted the simulation and requested additional, traditional clinical evidence to support the proposed label change. In the post-meeting comments, the FDA invited MannKind to submit a proposal for a data package including the CM&S evidence in a Type C meeting for further discussion on the label change. This MIDD pilot experience suggests that CM&S is a credible method for evidence generation. Collaboration between sponsor organizations as well as all stakeholders in the FDA, including proponents of CM&S, can further support regulatory decision-making. The learnings from early participants will allow the program to reach its full potential and thereby ultimately benefit patients, sponsors, and FDA.
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Key words
Afrezza,Computer modeling and simulation,Diabetes,FDA,Inhaled insulin,Insulin,Model-informed drug development
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