Potential integration of multiple organs-on-a-chip for comprehensive drug–drug interaction prediction
MOC systems are currently poised to complement, not replace, established <i>in</i> <i>vitro</i> and modeling approaches for DDI predictions. Near-term value lies in fit-for-purpose contexts of use, supplying physiologically grounded parameters and mechanistic insight to physiologically based pharmacokinetic (PBPK) modeling. With continued progress in addressing key challenges (e.g. physiological scaling, sorptive materials, microscale analytics, variability, throughput, and standardization), MOCs should mature into reliable tools to assist in DDI prediction, and potentially even qualified assays as part of regulatory DDI risk assessment frameworks.
Authors
- Catherine K. Yeung (ORCID: https://orcid.org/0000-0002-6556-6641)
- Yik Pui Tsang (ORCID: https://orcid.org/0009-0007-9541-3199)
- Jonathan Himmelfarb (ORCID: https://orcid.org/0000-0002-3319-1224)
- Edward J. Kelly (ORCID: https://orcid.org/0000-0002-6534-9313)
- Kai Wang (ORCID: https://orcid.org/0000-0002-1373-579X)
- Eric W. Hsu
Institutions
- University of Washington (US)
Publication Details
- Journal
- Expert Opinion on Drug Metabolism & Toxicology
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1080/17425255.2026.2633283
- Primary Topic
- 3D Printing in Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00