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Physiologically Based Pharmacokinetic and Pharmacodynamic Analysis Enabled by Microfluidically Linked
Rachelle Prantil-Baun1, Richard Novak1, Debarun Das2
1Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115, USA;
Annual Review of Pharmacology and Toxicology
|January 9, 2018
Summary
Physiologically based pharmacokinetic (PBPK) modeling advances drug development by predicting drug behavior from lab data. Organ-on-a-Chip technology overcomes PBPK limitations, improving drug response prediction and regulatory review.
Area of Science:
- Pharmacology
- Biotechnology
- Drug Development
Background:
- Physiologically based pharmacokinetic (PBPK) modeling predicts drug behavior from in vitro data.
- Current PBPK models struggle with organ-specific drug processing and lack pharmacodynamic (PD) insights.
- Limitations hinder accurate prediction of human drug responses and in vitro to in vivo extrapolation (IVIVE).
Purpose of the Study:
- To explore the potential of Organ-on-a-Chip (Organ Chip) technology to overcome PBPK modeling limitations.
- To discuss the application of linked Organ Chips for PBPK and PD modeling.
- To evaluate the advancement of drug development and regulatory review through these integrated approaches.
Main Methods:
- Utilizing microfluidic Organ Chip devices that mimic organ interfaces and vascular perfusion.
- Linking multiple Organ Chips through vascular channels to create integrated systems.
- Applying these models for PBPK and PD analysis of human drug responses and IVIVE.
Main Results:
- Organ Chip systems recapitulate organ-level functionality and tissue-tissue interfaces.
- Linked Organ Chips enable the incorporation of organ-specific drug processing.
- These models show promise for improved prediction of drug disposition and effects.
Conclusions:
- Organ Chip technology offers a powerful tool to enhance PBPK and PD modeling capabilities.
- Addressing current challenges will further integrate these models into drug development pipelines.
- This approach has the potential to significantly advance drug discovery and regulatory science.
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