Scholarlink

<p>(Background) Organ-on-a-Chip (OoC) technology has emerged as a microphysiological platform that addresses key limitations of conventional two-dimensional (2D) cell cultures and animal models in pharmacokinetics research. Reliable prediction of drug absorption, distribution, metabolism, and excretion (ADME) remains a major bottleneck in drug development, contributing to high clinical attrition rates driven by unanticipated toxicity and poor translational relevance. (Scope) OoC systems integrate human cells within dynamically perfused, three-dimensional microenvironments that recapitulate key structural, biochemical, and mechanical features of native organs. This review examines the mechanistic principles and pharmacokinetic applications of OoC platforms across major ADME-relevant organs—including the liver, kidney, gut, lung, and blood–brain barrier—and discusses their integration with physiologically based pharmacokinetic (PBPK) modeling. (Key Insights) Microfluidic flow, tissue–tissue interfaces, and mechanical cues sustain organ-specific functions and enable quantitative assessment of drug metabolism, transport, clearance, and tissue-specific toxicity. Representative studies demonstrate that OoC models capture human-specific drug responses overlooked by animal studies and generate pharmacokinetic parameters with close concordance to clinical observations. Multi-organ OoC configurations serve as physical analogues of systemic pharmacokinetic models, enabling interrogation of inter-organ crosstalk and whole-body drug disposition in vitro. (Concluding Perspective) Despite these advances, significant challenges related to biological fidelity, standardization, scalability, workflow integration, and regulatory qualification persist. Continued progress in automation, patient-derived models, artificial intelligence integration, and computational modeling is expected to further position OoC technologies as indispensable tools for predictive, human-relevant pharmacokinetics research and translational drug development.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Advancing Pharmacokinetics Research with Organ-on-Chips: A Microphysiological Approach to ADME Studies

  • 期刊论文

  • 发表日期：

    2026年6月29日

查看全文
  • Yu Chul Kim,
  • Sehoon Jeong

摘要

(Background) Organ-on-a-Chip (OoC) technology has emerged as a microphysiological platform that addresses key limitations of conventional two-dimensional (2D) cell cultures and animal models in pharmacokinetics research. Reliable prediction of drug absorption, distribution, metabolism, and excretion (ADME) remains a major bottleneck in drug development, contributing to high clinical attrition rates driven by unanticipated toxicity and poor translational relevance. (Scope) OoC systems integrate human cells within dynamically perfused, three-dimensional microenvironments that recapitulate key structural, biochemical, and mechanical features of native organs. This review examines the mechanistic principles and pharmacokinetic applications of OoC platforms across major ADME-relevant organs—including the liver, kidney, gut, lung, and blood–brain barrier—and discusses their integration with physiologically based pharmacokinetic (PBPK) modeling. (Key Insights) Microfluidic flow, tissue–tissue interfaces, and mechanical cues sustain organ-specific functions and enable quantitative assessment of drug metabolism, transport, clearance, and tissue-specific toxicity. Representative studies demonstrate that OoC models capture human-specific drug responses overlooked by animal studies and generate pharmacokinetic parameters with close concordance to clinical observations. Multi-organ OoC configurations serve as physical analogues of systemic pharmacokinetic models, enabling interrogation of inter-organ crosstalk and whole-body drug disposition in vitro. (Concluding Perspective) Despite these advances, significant challenges related to biological fidelity, standardization, scalability, workflow integration, and regulatory qualification persist. Continued progress in automation, patient-derived models, artificial intelligence integration, and computational modeling is expected to further position OoC technologies as indispensable tools for predictive, human-relevant pharmacokinetics research and translational drug development.