Microphysiological systems (MPS) consisting of multiple linked organ-on-a-chip (OoC) components are highly promising tools with potential to provide more relevant in vitro to in vivo translation of drug disposition, efficacy and toxicity. A gut–liver OoC system was employed with Caco2 cells in co-culture with HT29 cells in the intestinal compartment and single donor primary hepatocytes in the hepatic compartment for the investigation of intestinal permeability, metabolism (intestinal and hepatic) and potential interplay of those processes. The prodrug mycophenolate mofetil was tested for quantitative evaluation of the gut–liver OoC due to the contribution of both gut and liver in its metabolism. Conversion of mycophenolate mofetil to active drug mycophenolic acid and further metabolism to a glucuronide metabolite was assessed over time in the gut apical, gut basolateral and liver compartments. Mechanistic modelling of experimental data was performed to estimate clearance and permeability parameters for the prodrug, active drug and glucuronide metabolite. Integration of gut–liver OoC data with in silico modelling allowed investigation of the complex combination of intestinal and hepatic processes, which is not possible with standard single tissue in vitro systems. A comprehensive evaluation of the mechanistic model, including structural model and parameter identifiability and global sensitivity analysis, enabled a robust experimental design and estimation of in vitro pharmacokinetic parameters. We propose that similar methodologies may be applied to other multi-organ microphysiological systems used for drug metabolism studies or wherever quantitative knowledge of changing drug concentration with time enables better understanding of biological effect.

Microphysiological systems (MPS) are complex and more physiologically realistic cellular in vitro tools that aim to provide more relevant human in vitro data for quantitative prediction of clinical pharmacokinetics while also reducing the need for animal testing.

Organ‐on‐a‐chip (OoC) systems are a promising new class of in vitro devices that can combine various tissues, cultured in different compartments, linked by media flow. The properties of these novel in vitro systems linked to increased physiological relevance of culture conditions may lead to more in vivo‐relevant cell phenotypes, enabling better in vitro pharmacology and toxicology assessment. Improved cell activities combined with longer lasting cultures offer opportunities to improve the characterization of absorption, distribution, metabolism, and excretion (ADME) processes, potentially leading to more accurate prediction of human pharmacokinetics (PKs). The inclusion of barrier tissue elements and metabolically competent tissue types results in complex concentration‐time profiles (in vitro PK) for test drugs and their metabolites that require appropriate mathematical modeling of in vitro data for parameter estimation. In particular, modeling is critical to estimate in vitro ADME parameters when multiple different tissues are combined in a single device. Therefore, sophisticated in silico data analysis and a priori experimental design are highly recommended for OoC experiments in a manner not needed with standard ADME screening. The design of the experiment should be optimized based on an investigation of the structural characteristics of the in vitro system, the ADME features of the test compound and any available knowledge of cell phenotypes. This tutorial aims to provide such a modeling framework to inform experimental design and refine parameter estimation in a Gut‐Liver OoC (the most studied multi‐organ systems to predict the oral drug PKs) to improve translatability of data generated in such complex cellular systems.

Gill, Muenchau et al. demonstrated the presence of key drug transporters and metabolic enzymes in an engineered intestinal barrier model, and combined the system with in silico modeling to simultaneously capture drug permeability and metabolism.