Physiologically-based pharmacokinetic models: approaches for enabling personalized medicine

Area of Science:

• Pharmacology and Drug Development
• Computational Biology
• Personalized Medicine

Background:

• Inter-person variability is a key challenge in achieving effective drug therapy, leading to therapeutic failures in specialized patient populations.
• Physiologically-based pharmacokinetic (PBPK) modeling offers a powerful computational approach to understand and predict drug disposition by integrating physiological and physicochemical data.
• PBPK models are increasingly crucial for regulatory submissions, reducing the need for complex ethical and technical experiments in special populations.

Purpose of the Study:

• To review the application of PBPK modeling in personalized medicine, focusing on its role in drug product formulation development.
• To highlight the methodology for subpopulation modeling using an iterative and integrative approach.
• To discuss the integration of PBPK modeling within the Quality by Design framework for formulation development.

Main Methods:

• Utilizing an iterative and integrative methodology (adopt, adapt, develop, assess, amend, deliver) for subpopulation modeling.
• Simulating various physiological states using physiological and physicochemical data to predict pharmacokinetic responses.
• Focusing on physiological differences related to sex, age, disease state, and biological rhythms.

Main Results:

• PBPK modeling enables the identification of critical subpopulations and the determination of formulation design space for targeted drug plasma concentration profiles.
• The approach allows for the evaluation of complex clinical scenarios and inter-person variability in drug pharmacokinetics.
• Model development considers physiological variations across different demographic and health statuses.

Conclusions:

• PBPK modeling is a valuable tool for advancing personalized medicine and optimizing drug formulation development.
• Further acceptance and integration of PBPK modeling by pharmacologists, clinicians, and industry are needed.
• The methodology supports the Quality by Design framework for robust drug product development.