Advanced In Vivo Prediction by Introducing Biphasic Dissolution Data into PBPK Models

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Formulation Development
• In Silico Modeling

Background:

• Integrating biorelevant in vitro dissolution with in silico physiological-based pharmacokinetic (PBPK) tools offers a powerful approach for predicting drug performance in vivo.
• This method is crucial for formulation development, encompassing complex processes like non-passive transport, prodrug activation, and first-pass metabolism.

Purpose of the Study:

• To evaluate the predictive capability of human pharmacokinetics using biphasic dissolution data from the BiPHa+ assay and PBPK tools.
• To assess the accuracy of in vitro to in vivo extrapolation (IVIVE) for commercial drug products formulated with various enabling technologies.

Main Methods:

• Utilized biphasic dissolution profiles from the BiPHa+ assay for six commercial drug products.
• Employed two PBPK in silico modeling tools, PK-Sim and GastroPlus®, to process dissolution data, treating them similarly to extended-release profiles.
• Developed elimination/distribution models to simulate and compare predicted pharmacokinetics with available human data, without requiring mechanistic dissolution/precipitation models.

Main Results:

• Successfully developed an in vitro to in vivo extrapolation (IVIVE) method.
• Organic partitioning profiles from BiPHa+ dissolution analysis enabled highly accurate predictions of drug product pharmacokinetic behavior.
• PBPK models improved prediction accuracy for drugs with significant first-pass metabolism by adjusting passive diffusion predictions.

Conclusions:

• The combination of BiPHa+ dissolution analysis and PBPK modeling provides a robust platform for predicting in vivo drug performance.
• This approach streamlines formulation development by offering reliable in vitro to in vivo extrapolation (IVIVE).
• The methodology is particularly effective for drugs exhibiting complex pharmacokinetic profiles, including those with substantial first-pass metabolism.