Integrating a Microphysiological System and Physiologically Based Pharmacokinetic Modeling to Predict Human Responses to Diclofenac

Conventional two-dimensional in vitro cell cultures and animal models often inadequately predict human pharmacokinetics (PKs) and pharmacodynamics owing to the complexity of human physiology and interspecies diversity. This study introduces an innovative approach integrating a microphysiological systems (MPS) with physiologically based pharmacokinetic (PBPK) modeling and transcriptomic analysis to address these challenges. Our multiorgan MPS, incorporating gut, liver, and kidney chips, employs advanced microfluidic technology with cocultures of relevant human cell types to more accurately replicate the human physiological environment. Employing diclofenac, a widely used nonsteroidal anti-inflammatory drug, as a case study, we validated our model, demonstrating its accuracy in simulating human PK parameters. Integration of PBPK modeling with MPS results enhanced predictive precision. Furthermore, we incorporated transcriptomic analysis to investigate diclofenac’s mechanistic effects, revealing pathways potentially associated with its gastrointestinal toxicity and identifying differentially expressed genes linked to drug exposure and adverse effects. The integrated MPS with PBPK and transcriptomic approach holds substantial promise for improving drug development processes, offering a more predictive, ethical, and comprehensive method for drug behavior and toxicity assessments in humans. Our findings suggest that this methodology could advance early-stage drug development, potentially reducing reliance on animal testing and enabling more personalized therapeutic strategies.