Introduction
Modern challenges in drug development
From petri dish to microphysiological systems
Biological basis: Mimicking human physiology
Case studies
Translational outlook
Regulatory interest: The FDA Modernization Act
References
Further Reading
Organoid-on-chip technology merges patient-derived organoids with microfluidic engineering to recreate human physiology and predict drug responses with high precision. This innovation is reshaping preclinical testing by bridging the gap between laboratory models and real-world clinical outcomes.
Image Credit: Adisak Riwkratok / Shutterstock.com
Introduction
Over 90% of therapeutics that enter clinical trials ultimately fail, largely because traditional preclinical models do not accurately predict human efficacy or toxicity. Organoid-on-a-chip (OoC) systems combine self-organizing 3D biology with microengineered perfusion and mechanical cues, allowing for the real-time study of tissue-level function under physiologically relevant conditions.3
Modern challenges in drug development
The development of novel therapeutics is a high-cost and high-failure process. The drug discovery process, from preclinical research to market approval, is notoriously inefficient, with over 90% of drug candidates that enter clinical trials ultimately failing.1
These systemic failures are primarily attributed to a lack of clinical efficacy in humans and unmanageable toxicity, which lead to 50 % and 30 % of failures, respectively. Importantly, these side effects were inaccurately predicted by previous preclinical models.1
Although two-dimensional (2D) cell cultures are scalable and easy to use, they oversimplify biological systems by lacking three-dimensional (3D) tissue structure, essential cell–cell and cell–matrix interactions, and the complexity of tumor microenvironments (TMEs), which limits their clinical relevance.2 Despite the importance of studying drugs in preclinical animal models, fundamental interspecies differences in metabolism, genetics, and immune function frequently lead to incorrect predictions of a drug's pharmacokinetics (PK), pharmacodynamics (PD), and safety in humans.2
Recent reviews emphasize that these limitations have led to the integration of organoid and microfluidic chip technologies to improve preclinical predictivity by mimicking in vivo-like perfusion, oxygen gradients, and mechanical stimulation.3
Image Credit: Vink Fan / Shutterstock.com
From petri dish to microphysiological systems
OoC is a relatively new concept that describes the merging of two distinct but complementary technologies: organoids and microfluidic chips. Each technology was developed to address the limitations of 2D culture, yet they also have their own particular challenges.1,3
Organoids are three-dimensional, self-organizing structures derived from pluripotent or adult stem cells. These technologies replicate the structural and functional characteristics of human organs while preserving the genetic heterogeneity and cellular composition of a patient's original tissue.3
When cultured under static conditions or in suspension or Matrigel, organoids often show limited maturation and only short-term functional activity.3 These limitations have been attributed to organoids lacking a perfusable vascular system, which leads to necrotic cores due to the inadequate diffusion of nutrients and oxygen.3
An OOC is a microfluidic device, often made from polymers like polydimethylsiloxane (PDMS), that uses microchannels to construct models of human organs. Microfluidics enables the precise management of nutrient gradients, hydrodynamic parameters such as fluid shear stress, and mechanical signals, including stretching, observed in lung-on-a-chip models.3
Historically, OOCs have used 2D cell monolayers or simpler cell architectures, which lack the sophisticated 3D cellular intricacy of an organoid.3 To address these limitations, scientists have developed OoC, a hybrid platform that combines the strengths of both organoids and OOCs while addressing their respective limitations.2
By seeding a biologically complex 3D organoid into a dynamically controlled microfluidic chip, the OoC platform achieves a superior level of physiological relevance. Intrinsic microfluidic perfusion provides the continuous nutrient supply and waste removal that organoids need for long-term viability, while simultaneously providing the physical and chemical signals necessary for their functional maturation.3
Recent work has demonstrated quantitative in vitro–in vivo translation (IVIVT) of human pharmacokinetics using multi-organ chips that link gut, liver, kidney, and bone marrow modules under vascular perfusion, thereby achieving human-like predictions for absorption, distribution, metabolism, and toxicity.6
Biological basis: Mimicking human physiology
OoCs enable the use of tissue-specific matrix compositions, thereby supporting tissue-specific organization and function.1,3 Furthermore, OoC platforms use microfluidic channels to mimic systemic circulation to provide continuous perfusion for vascular and epithelial cell maturation.
OoCs can also integrate multiple cell types to model tissue crosstalk, particularly in the TME. For example, OoC platforms can co-culture epithelial tumor cells with key components of the microenvironment, including stromal and immune cells.4
These capabilities make OoC platforms uniquely suited for testing immunotherapies, such as programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) checkpoint inhibitors, which rely on the interaction between a patient's tumor and immune cells.2
Incorporating immune–tumor co-cultures within tumor-on-chip systems allows direct evaluation of immune checkpoint blockade responses under perfused, gradient-controlled microenvironments.4
Organoids-on-a-chip technologies | CEA-Leti
Video credit: CEA/Youtube.com
Case studies
A leading application of OoC is patient-derived tumor organoids (PDOs), which originate from the patient’s tumor biopsy. PDOs are living 3D models that retain key histopathological, genetic, and phenotypic features of the parent tumor, accurately reflecting its unique cellular heterogeneity.2
When cultured on-chip, PDOs serve as high-fidelity platforms for in vitro testing of drug sensitivity. In studies of colorectal cancer, PDOs are associated with a drug-response accuracy of over 87 % as compared to the patient's original clinical outcome.2,5
These OoC properties enable guided precision medicine, where a panel of therapeutics can be screened against the patient's specific tumor in vitro to identify the most effective, individualized treatment strategy.5
Multi-organ chips are widely used for toxicity and PK/PD modeling. These platforms fluidically link multiple organ-on-a-chip models with a common medium to simulate human absorption, distribution, metabolism, excretion, and toxicity (ADMET).6
The quantitative power of this approach has been confirmed by using an MOC platform that combined gut, liver, and kidney chips for oral drug administration of nicotine, as well as bone marrow, liver, and kidney chips for intravenous administration of cisplatin.
Study findings validated the ability of quantitative in vitro-to-in vivo translation (IVIVT) to successfully predict human PK parameters that were quantitatively similar to real-world human observations.6
Translational outlook
OoC systems generate extensive datasets from high-content (3D) microscopy and multi-omics, both of which are associated with inefficient manual analysis protocols that are prone to errors and unscalable. To overcome this challenge, AI vision algorithms have been used to automate organoid image segmentation, cell tracking, and morphological classification.7 ML models are being used to analyze multi-omic data, thereby identifying novel biomarkers of drug response and resistance.2,7
AI–organoid integration now extends to label-free recognition, quality control of fabrication, and three-dimensional reconstruction of organoid structures, improving predictive accuracy and reproducibility in precision drug testing.7
Regulatory interest: The FDA Modernization Act
In 2022, the U.S. Congress passed the Food and Drug Administration (FDA) Modernization Act 2.0, which removed the mandatory animal testing requirement for Investigational New Drug (IND) applications.8
This act explicitly authorized the use of non-animal alternatives like OoCs to support drug applications, which encourages the pharmaceutical industry to adopt these platforms for their drug discovery projects.4,8
The legislation specifically recognizes cell-based assays, microphysiological systems, and computer models as acceptable alternatives for safety and efficacy testing, marking a turning point in federal regulatory policy.8
References
- Sokolowska, P., Zuchowska, A., & Brzozka, Z. (2022). Why Can Organoids Improve Current Organ-on-Chip Platforms? Organoids 1(1); 69–84. DOI:10.3390/organoids1010007, https://www.mdpi.com/2674-1172/1/1/7.
- Xiao, Y., Li, Y., Jing, X., et al. (2025). Organoid models in oncology: advancing precision cancer therapy and vaccine development. Cancer Biology & Medicine 1–25. DOI:10.20892/j.issn.2095-3941.2025.0127, https://www.cancerbiomed.org/article/doi/10.20892/j.issn.2095-3941.2025.0127.
- Wang, H., Ning, X., Zhao, F., et al. (2024). Human organoids-on-chips for biomedical research and applications. Theranostics 14(2); 788–818. DOI:10.7150/thno.90492, https://www.thno.org/v14p0788.htm.
- Ahn, J., Sei, Y., Jeon, N., & Kim, Y. (2017). Tumor Microenvironment on a Chip: The Progress and Future Perspective. Bioengineering 4(3); 64. DOI:10.3390/bioengineering4030064, https://www.mdpi.com/2306-5354/4/3/64.
- Di Paola, F. J., Calafato, G., Piccaluga, P. P., et al. (2025). Patient-Derived Organoid Biobanks for Translational Research and Precision Medicine: Challenges and Future Perspectives. Journal of Personalized Medicine 15(8); 394. DOI:10.3390/jpm15080394, https://www.mdpi.com/2075-4426/15/8/394.
- Herland, A., Maoz, B. M., Das, D., et al. (2020). Quantitative prediction of human pharmacokinetic responses to drugs via fluidically coupled vascularized organ chips. Nature Biomedical Engineering 4(4); 421–436. DOI:10.1038/s41551-019-0498-9, https://www.nature.com/articles/s41551-019-0498-9.
- Maramraju, S., Kowalczewski, A., Kaza, A., et al. (2024). AI‐organoid integrated systems for biomedical studies and applications. Bioengineering & Translational Medicine 9(2). DOI:10.1002/btm2.10641, https://aiche.onlinelibrary.wiley.com/doi/10.1002/btm2.10641.
- Congress.gov. (2022). S.5002 - 117th Congress (2021–2022): FDA Modernization Act 2.0. https://www.congress.gov/bill/117th-congress/senate-bill/5002. Accessed on 09 November 2025.
Further Reading
Last Updated: Nov 21, 2025