Revolutionizing drug development: harnessing the potential of organ-on-chip technology for disease modeling and drug discovery

“

TL;DR

This review summarizes how organ-on-chip (OOC) platforms, which are microfluidic devices containing living human tissues, can model human diseases and test drugs more accurately than traditional animal or 2D cell models. The paper catalogs specific parameters (cell types, flow rates, shear stress, biomarkers) used across dozens of OOC studies for diseases of the lung, liver, kidney, gut, brain, heart, and other organs. The clinical significance is that OOC technology has the potential to replace animal testing, accelerate drug discovery, and enable personalized medicine by using patient-derived cells.

Full summary

3,494 CHARS

**Background:** Traditional animal models and 2D cell cultures have significant limitations in drug development, including poor prediction of human drug responses, lack of human pathophysiological relevance, and ethical concerns. The US FDA Modernization Act (2022) now permits evaluation of experimental drugs using non-animal alternatives. Organ-on-chip (OOC) platforms are bioengineered microdevices that mimic human organ functions by culturing living human cells in microfluidic channels under controlled dynamic conditions, including shear stress, mechanical cues, and tissue-tissue interactions. This review aims to comprehensively summarize the parameters, disease models, drug toxicity studies, and PK-PD applications of OOC technology.

**Methods:** The authors conducted a narrative review of the OOC literature, focusing on studies that modeled specific disease phenotypes (genetic diseases, cancers, infectious diseases, etc.) on chip platforms. They extracted and tabulated key parameters for each study: cell types, platform materials (primarily PDMS and plastic), shear stress values, flow rates, disease inducers, biomarkers measured, and biochemical assays used. The review covers single-organ and multi-organ chips, including lung, blood-brain barrier (BBB), kidney, liver, gut, heart, eye, pancreas, cartilage, mammary gland, nerve, and lymphatic vessel models.

**Key Results:** The review catalogs extensive parameter data across dozens of studies. For lung disease modeling, flow rates ranged from 1 to 70 μL/h with shear stresses of 0.2–1 dyn/cm². Key lung biomarkers included IL-6, IL-8, IP-10, RANTES, ACE2, and TMPRSS2. For kidney models, flow rates ranged from 3 to 45 μL/min with shear stresses of 0.06–0.3 dyn/cm²; biomarkers included KIM-1, HSP70, IL-6, ET-1, ZO-1, and SGLT2. Liver models used flow rates of 1–2 μL/min and identified biomarkers such as albumin, urea, α-SMA, COL1A1, TIMP-1, IL-6, and TNF-α. BBB models applied shear stresses of 0.01–2.4 dyn/cm² and assessed GFAP, α-SMA, and PDGFRb. Drug toxicity studies evaluated 27 drugs on 870 Liver-Chips, demonstrating that OOC platforms can predict drug-induced liver injury (DILI) more accurately than animal models. PK-PD modeling using interconnected liver-kidney-intestine chips successfully predicted human clinical pharmacokinetics for nicotine and cisplatin. Multi-organ chips have modeled type 2 diabetes (pancreas-liver), cancer metastasis, and systemic drug ADME (absorption, distribution, metabolism, excretion).

**Clinical Implications:** OOC technology offers a human-relevant alternative to animal testing that can accelerate drug discovery, reduce costs, and improve prediction of drug efficacy and toxicity. The combination of OOC with patient-specific induced pluripotent stem cells (iPSCs) enables personalized medicine by modeling individual drug responses and genetic variations. However, challenges remain: PDMS (the most common chip material) absorbs 50–60% of drugs, there is a lack of standardized platforms for specific diseases, and most current OOC models are proof-of-concept rather than validated for regulatory use. The authors call for standardized platforms, online real-time monitoring, mandatory ADME evaluation in all drug testing models, and integration of omics data (genomics, transcriptomics, proteomics) for biomarker validation. Despite these limitations, OOC technology is positioned to become an indispensable tool in drug development and personalized medicine.