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PBPK Is Ready for NDA- and IND-related Submissions! But Are YOU Ready for PBPK?

Recently, the US Food and Drug Administration held a workshop on “Application of Physiologically-based Pharmacokinetic (PBPK) Modeling to Support Dose Selection.” With the FDA’s intention to maintain an efficient review process for human drug and biological products, PBPK models may be useful for assessing risk during drug development. Indeed, PBPK models have increasingly been applied to complex drug development issues that cannot be evaluated in a clinical trial or to issues that can be reliably assessed in silico, thereby minimizing the need for costly clinical trials. Regulatory agencies around the world are also looking to adopt a rigorous approach to the review of PBPK submissions and the conduct of de novo PBPK analysis to support regulatory review. However, there are challenges ahead. For example:

(1) The system parameters are not static and change with time, necessitating regular updates based on published reports by experts in each field.
(2) The lack of agreed procedures and sub-model sets when comparing models offered by different groups makes comparing these applications an immense task.
(3) Since many of the tasks are too big for any single organization to conduct, obtaining the system parameters and assessing model performance requires large collaborations.

Dr. Rostami discussed these issues during the webinar.

With the FDA’s intention to maintain an efficient review process for human drug and biological products, PBPK models may be useful for assessing risk during drug development. Indeed, PBPK models have increasingly been applied to complex drug development issues that cannot be evaluated in a clinical trial or to issues that can be reliably assessed in silico, thereby minimizing the need for costly clinical trials. Regulatory agencies around the world are also looking to adopt a rigorous approach to the review of PBPK submissions and the conduct of de novo PBPK analysis to support regulatory review. However, there are challenges ahead. For example:

(1) The system parameters are not static and change with time, necessitating regular updates based on published reports by experts in each field.
(2) The lack of agreed procedures and sub-model sets when comparing models offered by different groups makes comparing these applications an immense task.
(3) Since many of the tasks are too big for any single organization to conduct, obtaining the system parameters and assessing model performance requires collaboration.

Dr. Rostami discussed these issues during the webinar.