Physiologically based pharmacokinetic model outputs depend on dissolution data and their input: Case examples...

Area of Science:

• Pharmacokinetics
• Drug Delivery
• Computational Modeling

Background:

• Numerous dissolution tests for oral dosage forms exist, varying in media, hydrodynamics, and equipment.
• Predicting in vivo drug performance from dissolution data requires careful consideration of test parameters and modeling approaches.

Purpose of the Study:

• To determine how media composition, dissolution test type, and PBPK model data input influence in vivo plasma profile simulation.
• To evaluate the impact of different biorelevant media and testing designs on predicting oral drug absorption.

Main Methods:

• Dissolution tests were conducted on glibenclamide and dipyridamole immediate-release formulations using USP Apparatus II.
• Biorelevant media (FaSSGF, FaSSIF V1-V3) and single-stage/two-stage test designs were employed.
• Data were integrated into PBPK models (Simcyp®) using Dissolution Rate Model (DRM) and Diffusion Layer Model (DLM) approaches.

Main Results:

• Glibenclamide dissolution was sensitive to pH differences in FaSSIF media, while dipyridamole was not.
• Single-stage vs. two-stage testing yielded equivalent simulations for glibenclamide.
• Accurate dipyridamole pharmacokinetic simulation depended on the specific test design (single-stage FaSSGF with DRM) or data input method (two-stage with DLM and dynamic pH).

Conclusions:

• The choice of biorelevant media and dissolution test design can significantly affect drug dissolution profiles.
• Data input methods into PBPK models critically influence the accuracy of in vivo pharmacokinetic predictions.
• Optimizing dissolution testing and PBPK modeling strategies is essential for reliable drug formulation development.