The search for better models in drug discovery has always followed the same goal: bringing experimental systems closer to human biology.
For decades, two-dimensional (2D) cell cultures have been the standard tool for studying cellular responses to drugs. Over the past decade, patient and iPSC-derived organoids have emerged as a new generation of in vitro models. Derived from stem cells, these three-dimensional (3D) multicellular structures self-organize to replicate key architectural and functional features of human organs. Their ability to capture tissue complexity and cellular heterogeneity has opened new possibilities for studying disease mechanisms and testing therapeutic compounds.
Today, the adoption of organoids in drug discovery pipelines is increasing, and so is the number of studies published. Yet one challenge remains: translating their biological promise into scalable and reproducible screening workflows.
What Makes Organoids a Valuable Model for Drug Screening in Preclinical Research
Preclinical drug discovery relies on experimental models to evaluate how cells and tissues respond to pharmacological compounds. Traditionally, this work has been carried out using 2D cell cultures and animal models. While both approaches remain widely used in the drug screening pipeline, each presents limitations when it comes to reproducing human biology.
Conventional 2D cell cultures are easy to manage and compatible with high-throughput workflows. These models include primary cells and immortalized cell lines, each with their own limitations. Primary cells are difficult to obtain, grow, and expand. Cell lines solve these issues, but lack some real cell functions. Most of them have undergone malignant transformation due to their oncogenic origin or their adaptation to 2D growth on plastic surfaces.
Besides, these models are reductionist, especially monoculture, which only includes one cell type, failing to replicate tissue complexity. Because these cells grow on flat plastic surfaces, they do not reproduce the structural organization, lacking cell-cell interaction. As a result, they often fail to capture important physiological processes that influence how drugs behave in the body.
Animal models provide a more complex biological context, allowing for the study of drug responses within a whole organism. Yet interspecies differences can limit how accurately these models predict human drug efficacy and safety; in fact, only 4% of compounds that pass preclinical testing ultimately succeed in clinical trials. In addition, animal studies are typically time-consuming and resource-intensive, and their use is increasingly subject to ethical and regulatory considerations. In fact, regulatory agencies are opening the door to phase out animal testing in preclinical drug development, by replacing them, when possible, with New Approach Methodologies (NAMs) such as organoids.
Human iPSC-derived organoids offer an alternative approach that bridges the gap between these systems.
Organoids preserve aspects of tissue organization and cellular heterogeneity closely reflecting more human physiology than traditional 2D cell cultures. This structural complexity improves the ability of organoid models to capture disease phenotypes and biological responses to drugs.
Another major advantage is their potential for patient-specific applications. Organoids can be generated from patient biopsy samples, creating patient-derived organoids that retain the genetic background and biological characteristics of the individual. This makes it possible to test how specific patients respond to different therapeutic compounds, enabling personalized approaches to treatment evaluation.
Compared to animal models, organoid culture used in drug screening enables high-throughput, allowing for testing hundreds of compounds and concentrations in parallel to prioritize the ones with the highest potential. Organoids provide a human-relevant in vitro system that improves the predictive value of preclinical drug screening workflows. Unlike animal models, which require sequential testing and are limited by interspecies biological differences, organoid-based platforms can run hundreds of compound-dose combinations simultaneously, reducing the time and cost associated with early-stage compound prioritization.
This human relevance translates directly into higher predictive accuracy. Because organoids recapitulate the three-dimensional architecture, cell-cell interactions, and tissue-specific gene expression found in vivo, they are better positioned to reflect how a drug will behave in humans, both in terms of efficacy and toxicity. This can help de-risk compounds earlier in the pipeline, ultimately contributing to more informed decisions before entering costly clinical phases.
Types of Organoids and Their Applications in Drug Discovery
A wide range of organoid types has been developed to model different diseases, enabling the study of diverse biological processes and evaluating therapeutic interventions. Some examples include:
- Brain organoids allow to investigate neurodevelopmental and neurodegenerative diseases. These models have been used to study conditions such as Parkinson’s disease, Alzheimer’s disease, and frontotemporal dementia by replicating key pathological features observed in patients.
- Kidney organoids provide models for studying renal diseases, including polycystic kidney disease. These systems reproduce disease-specific features such as cyst formation and allow researchers to identify compounds that influence disease progression.
- Liver organoids are used to study metabolic diseases and evaluate drug metabolism and toxicity. Because they reproduce essential liver functions such as protein synthesis, bile production, and metabolic activity, they provide a valuable platform for investigating therapeutic responses.
- Intestinal organoids are used to model diseases such as cystic fibrosis, inflammatory bowel disease, or celiac disease. They are also increasingly recognized as valuable in vitro models for studying drug absorption, distribution, metabolism, and excretion (ADME) as well as intestinal toxicity.
- Lung also play important roles in modeling infectious diseases and epithelial disorders, such as SARS-CoV-2, but also cystic fibrosis. These systems can replicate tissue-specific cell types and physiological processes, enabling researchers to study pathogen interactions and drug responses under controlled experimental conditions.
Besides healthy organoids, tumor organoids can be generated by expanding the oncogenic tissue. They capture the cellular heterogeneity and genetic diversity of human tumors, making them useful for studying tumor biology, identifying biomarkers, and predicting responses to anticancer drugs.
How Automated Platforms Are Scaling Organoid Drug Screening Workflows
The high-throughput promise of organoids for large-scale drug screening is limited by manual handling. Conventional organoid culture methods often rely on manual handling and low-throughput platforms, which can introduce variability and limit scalability. Automation remains essential to exploit their full potential.
Organoid development is highly sensitive to culture conditions, including matrix composition, spatial organization, and environmental parameters. Small variations in these factors can lead to differences in organoid size, morphology, and function, complicating the reproducibility of experimental results.
Automation technologies address these challenges and enable more standardized organoid workflows. Early automated systems focused primarily on fluid-handling tasks, such as supplying and removing cell culture media. By eliminating manual pipetting, these systems made it possible to maintain many culture units in parallel and represented an important first step toward scalable organoid culture operations.
Robotic liquid-handling platforms further expanded automation capabilities. These systems can automate processes such as cell seeding, exposure to experimental conditions, and downstream processing steps, including fixation, permeabilization, staining, and washing during assay preparation. However, many conventional liquid-handling systems require lengthy implementation timelines, from months to years. Not to mention the lack of flexibility. It is difficult to work with several types of organoids in parallel, since each of them grows in different conditions (plate formats, suspension, ECMs…. Last, but not least, liquid-handling systems are optimized for speed rather than precision. In organoid workflows, accuracy is critical because improper aspiration or dispensing can damage or remove organoids during culture.
The MO:BOT was designed to solve these problems. Our automated platform combines robotics, imaging, and validated biological protocols to support automated organoid workflows. Its modular architecture allows different functional modules, such as imaging, heating, cooling, tilting, or shaking, to be arranged flexibly on the system with no cables or screws. Flexibility goes beyond ease of use: the platform is compatible with diverse cell culture systems and growth conditions, automating cell seeding, media exchange, imaging, compound exposure, and data acquisition across any 3D cell culture model.
Besides its modular design, the platform includes validated protocols and user-friendly software to adapt one of them to your experiment, with no need to code. You just need to place your reagents, consumables, and cell culture material on the system. It reduces the technical complexity of implementing automated organoid culture. Within the same day, you can seamlessly switch between entirely different workflows: starting with a medium exchange for iPSC-derived cardiac organoids growing in suspension, moving on to cell seeding of a liver cell line across five 96-well plates, and finishing with a drug screening assay in patient-derived synovial cells, all without interruption or reprogramming.
By improving reproducibility, scalability, and workflow integration, the MO:BOT is already helping researchers to transform organoid technologies from experimental tools into practical systems for high-throughput drug screening and preclinical research.
Sources
Kim D, Youn J, Kim J, Lee J, Yoon J, Kim DS. From organoid culture to manufacturing: technologies for reproducible and scalable organoid production. npj Biomedical Innovations. 2026;3:12. doi:10.1038/s44385-025-00054-6.
Wang D, Villenave R, Stokar-Regenscheit N, Clevers H. Human organoids as 3D in vitro platforms for drug discovery: opportunities and challenges. Nat Rev Drug Discov. 2026 Mar;25(3):204-226. doi: 10.1038/s41573-025-01317-y.
