Current methods for predicting human food effect

Area of Science:

• Pharmacokinetics and Drug Development
• Drug Metabolism and Interactions
• Biopharmaceutics

Background:

• Food intake significantly influences drug pharmacokinetics through various mechanisms like altered solubility and gastrointestinal (GI) physiology.
• Predicting human food effects on drug products is a complex challenge in drug development.
• Managing food intake during clinical trials adds complexity to drug development timelines and protocols.

Purpose of the Study:

• To review and discuss various models for predicting and assessing drug food effects during drug development.
• To highlight the challenges associated with predicting human food effects for new drug products.
• To evaluate the utility of in vitro and in vivo models in understanding drug-food interactions.

Main Methods:

• In vitro models utilizing physical-chemical properties for early screening of food effect potential.
• Biorelevant dissolution testing to predict in vivo drug performance under fed and fasted conditions.
• In vivo pharmacokinetic studies, focusing on the dog model and critical parameters for predictability (gastric pH, meal composition).

Main Results:

• In vitro models can classify the potential for food effects (positive, negative, or none) during early drug discovery.
• Dissolution tests in biorelevant media can predict human drug performance in fed versus fasted states.
• The dog model shows promise for predicting human food effects, but requires precise control over feeding parameters for improved accuracy.

Conclusions:

• No single universal model accurately predicts drug food effects across all development stages.
• A combination of in vitro and in vivo models may be necessary depending on the specific development goal.
• Optimizing models, particularly the dog model, is crucial for reliable prediction of pharmacokinetic changes due to food.