Organs-on-Chips in Drug Development: Engineering Foundations, Artificial Intelligence, and Clinical Translation
Органы-на-чипе в разработке лекарственных средств: инженерные основы, искусственный интеллект и клиническая трансляция
2026-03-11
SCID: 54.1/4qtxcjs9
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artificial intelligencebiosensor-enabled drug developmentmicrofluidicsmicrophysiological systemsorgan-on-a-chip
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Abstract (AI)
Organ-on-a-chip (OoC) technologies, also termed microphysiological systems (MPSs), integrate microfluidics, engineered biomaterials, human-derived cells, and on-chip biosensing to model human physiology in microscale devices that deliver quantitative, time-resolved readouts. This review surveys the 2010-2025 literature, emphasizing how sensing, standardized sampling, and analytics enable clinical concordance and fit-for-purpose regulatory use. We synthesize advances in (i) materials, fabrication, and microfluidic design; (ii) organ- and disease-focused case studies; and (iii) translational benchmarks that align chip outputs with clinical pharmacokinetics, toxicology, and biomarker datasets. Across organ systems, platforms increasingly incorporate vascularization, immune components, and organoid hybrids, paired with real-time measurements of barrier integrity, metabolism, electrophysiology, and secreted biomarkers using impedance (TEER), electrochemical, and optical modalities. Representative benchmarking studies report cardiac OoCs achieving AUROC ≥ 0.85 for torsadogenic risk classification, and renal chips improving prediction of transporter-mediated clearance relative to conventional in vitro assays. We summarize validation approaches and regulatory developments relevant to new approach methodologies, including the FDA Modernization Act 2.0, and discuss how AI and multi-omics can automate signal and image analysis, harmonize cross-platform datasets, and support digital-twin workflows that couple OoC measurements to in silico models. Overall, biosensor-enabled OoCs are progressing toward quantitatively benchmarked platforms for safety pharmacology, ADME/PK-PD, and precision medicine.
Key Findings
1
Artificial intelligence and multi-omics can automate signal and image analysis, harmonize datasets, and connect OoC measurements with in silico digital-twin workflows.
2
Benchmarking studies report cardiac OoCs achieving AUROC ≥ 0.85 for torsadogenic risk classification and renal chips improving prediction of transporter-mediated clearance over conventional assays.
3
Biosensor-enabled OoCs are progressing toward quantitatively validated applications in safety pharmacology, ADME/PK-PD, precision medicine, and regulatory new approach methodologies.
4
Integration of vascularization, immune components, and organoid hybrids increasingly improves organ- and disease-specific physiological modeling across OoC systems.
5
Organ-on-a-chip platforms combine microfluidics, biomaterials, human-derived cells, and biosensors to generate quantitative, time-resolved models of human physiology.
6
Real-time impedance, electrochemical, and optical measurements enable monitoring of barrier integrity, metabolism, electrophysiology, and secreted biomarkers.
Research Object
biosensor-enabled organ-on-a-chip (OoC) platforms, including microphysiological systems modeling human physiology
Research Subject
their quantitative, time-resolved physiological and pharmacological readouts, validation against clinical data, and regulatory and AI-enabled translation for drug development
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2026-03-11
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