Automated In Vitro Sample Preparation for PBBM to Predict Food Effect on Oral Drugs
The solubility of orally administered drugs is highly influenced by the composition of the intestinal fluids, the presence of fatty acids and cholesterol, and the pH. All these factors can be affected by the individual’s diet (food effect). Typical biorelevant studies, however, fail to capture food effects as the experiments are commonly performed on fixed simulated intestinal fluid (SIF) compositions. Consequently, accurate prediction of the food effect observed in clinical studies is hindered due to lack of reliable data for the model.
Here, we propose a high-throughput automated workflow for the study of API solubility in complex, ad hoc biorelevant media, and the implementation of the data obtained in vitro into a Physiologically Based Biopharmaceutic Model (PBBM) used to predict the food effect on a BCS IV zwitterionic drug. The automated workflow led to considerable time and material savings, while the model accurately predicted the results of the food effect.
Key Learning Objectives:
- Determination of food effect, through use of complex biorelevant media, to describe and predict clinical data
- Automated preparation of ad hoc complex biorelevant media
- Automated in vitro biorelevant solubility screen of an API
- Integration of in vitro solubility and permeability into a Physiologically
- Based Biopharmaceutic Model (PBBM)
Who Should Attend:
- Scientist, Sr. Scientist, Development Chemist, Formulation Chemist, Process Chemist, (Directors of preceding), Research Fellow, Professor
- Product Development Scientists, Biochemist
Presenter: Paola Ferrini (Investigator, High-Throughput Automation Team, GSK)
Presenter: Konstantinos Stamatopoulos (Biopharmaceutics Investigator, GSK)
Presenter: Catherine Dold (Health & Environment Writer, C&EN Media Group)
