From Animal Testing to Organoids: The New Era of Human-Based Drug Development

The rules of drug development are being rewritten.

In Spring 2025, the FDA announced plans to phase out the requirement for animal testing in the development of monoclonal antibodies (mAbs) and other drugs.

This announcement marks a turning point in drug development, shifting the focus toward models that better reflect human biology.

With new policies reducing reliance on animals, the field is now free to pivot toward human-based models: organoids and organ-on-a-chip systems. These approaches offer a more accurate, patient-relevant bridge from discovery to the clinic.

Interrogating human-based models with the right high-resolution tools fast-tracks such achievement.

As the industry transitions away from animal testing, early adopters of human-based systems will set new standards for safety, efficacy, and precision, while those who delay risk falling behind in a rapidly modernizing landscape.

Organoids are self-organizing structures that can recapitulate the architecture and the biological functions of an organ. They can derive from induced pluripotent stem cells (iPSCs), embryonic stem cells (hESC), or from tissue-derived cells (TDCs) originating from tissues, including tissue-resident stem cells, differentiated cells, or tumor cells.

To create organoids, dissociated cells are embedded in a 3D extracellular matrix (ECM) of proteins like collagen and growth factors, which recreates the stem cell niche. The specific combination of ECM components and growth factors influences cell behavior, leading to either differentiation or maintenance of stemness.

More advanced systems like bioreactors enable control of the culture environment like temperature, pH, oxygen levels, nutrients, and growth factors, while scaffolds give structural support and guide the three-dimensional organization of developing tissues.

Organ-on-a-chip systems combine microchip technology and tissue and organ engineering in creating a 3D structure that simulates the physiological conditions of human organ development. Multiple organoids can be connected through the microchips, enabling the analysis of multi-organ interactions.

Organoids recapitulate human organ architecture and represent the cellular heterogeneity within the tissues. Human-derived organoids don’t have inter-species variability, making them more representative of humans’ disease and response to treatment. They are cultured in closed environments that control chemical, physical, and genetic variability, making them more reproducible.

Patients-derived organoids (PDOs) mimic the biology of a patient’s health or diseased tissue, including the genetic and tissue makeup. PDOs can derive from both patient’s tissues (biopsies, surgical specimens) or can be generated from the donor stem cells.

Take for example the “cancer-on-a-chip” (CoCs): these 3D organoids on a microchip can recreate the tumor microenvironment, including tumor cells, extracellular matrix, blood cells, and immune cells. Multiorgan CoCs simulate inter-organ interactions, facilitating the study of tumor cell circulation and metastasis, and allowing simultaneous testing of drug efficacy and toxicity across multiple tissues.

Brain organoids provide unprecedented access to parts of the living human brain. In spite of their limitations in replicating the multilayered and functional architecture of the human brain, these organoids still enable researchers to observe the early stages of neurogenesis, analyze disease onset and progression, test gene editing outcomes, new treatments, and response.

Organoids are a living, scalable source of samples and cells: thousands can be developed simultaneously.

As they self-organize and differentiate, organoids give rise to different cell types at various degrees of differentiation, with regulatory networks and genetic characteristics. ScRNA-seq provides an unbiased gene expression profiling without any a-priori assumptions, a critical feature to explore the full breadth of tissue cell heterogeneity and individual cell states.

All scRNA-seq methods rely on labeling each cell’s mRNAs with unique tags, ensuring every transcript can be traced back to its cell of origin. Unique Molecular Identifiers (UMIs) enable precise transcript counting. The analysis pipeline then demultiplexes the data: cell-specific tags assign cell identity, while UMIs quantify gene expression.

The differentiating factor across scRNA-seq technologies is the ability to scale up while maintaining ease of sample management, outstanding data quality, and true whole transcriptome coverage, free from the a-priori assumptions of pre-defined targets.

Combinatorial barcoding does that. Each cell and its transcripts are identified using a plate-based system that ligates a unique combination of four barcodes. Because the number of possible barcode combinations is extremely large, the chance of two cells receiving the same combination is very low. As the capacity of cells and samples increases, the pool of possible combinations grows even larger, further reducing the probability of doublets.

Such scalability is crucial for organoids studies. Organoids require multi-condition, multi-lineage comparisons, and are inherently evolving systems with transient states requiring a technology that enables a controlled, consistent, clean data collection, with reduced batch effects, ambient RNA, and other sources of technical noise.

This approach allows massive multiplexing, processing numerous samples in a single experiment. Since it does not rely on a-priori probe design or target selection, it offers a truly unbiased view of the samples transcriptional landscape. Indeed, with the combinatorial barcoding method samples are fixed and permeabilized, turning each cell into its own reaction chamber while preserving the organoids biology as it exists at collection. Fixation also provides workflow flexibility: samples can be collected, stabilized, and stored long-term before processing. This decouples sample collection from sequencing, while retaining high-quality single-cell data integrity.

ScRNA-seq has multiple uses at every stage of the organoid development. From the organoid development protocol itself, to quality control and benchmarking, to lineage mapping and differentiation trajectories, to cell identification, stem cells characterization, and drug screening.

Organoids Differentiation Protocols

Organoids need to closely resemble the real tissue or organ structure.

Different differentiation protocols produce organoids under varying conditions, resulting in outcomes that do not always accurately reflect the characteristics of the real organ.

Comparing the transcriptional profile of organoids generated under varying conditions, researchers discovered that organoids with more elaborate structures showed gene expression patterns closely matching the human organ, whereas those with simplified morphology displayed disrupted cell-type composition. ScRNA-seq links morphology to molecular identity and establishes transcriptional fidelity as a key indicator of organoid quality.

Synergy of Organoids and ScRNA-seq in Drug Discovery and Screening

Organoids can be collected, seeded in 96 or 384 well plates, and used to conduct high throughput testing. Such scalability accelerates drug discovery: going beyond the yes/no readout enables a comprehensive understanding of how compounds affect every cell within the model.

Think about disease mapping: scRNA-seq reveals specific cell subtypes involved in disease. In a medulloblastoma organoid model, scRNA-seq was able to distinguish between individual cell populations sensitive to the tested drug and determine its toxicity only in the tumor cells and not in the myelinating cells.

Massively Parallel Organoid Profiling with Scalable scRNA-seq

Thousands of perturbations across countless organoids, analyzed through scalable scRNA-seq, generate the massive datasets required by Artificial Intelligence (AI) models to decode and ultimately defeat cancer.

It is already happening. The Wellcome Sanger Institute, the Computational Health Center at Helmholtz Munich, and the GigaLab at Parse Biosciences have joined forces to explore cancer plasticity through innovative organoid perturbation and AI-driven single cell mapping. This collaboration aims to lay the foundation for a large-scale cancer plasticity atlas capturing data from hundreds of millions of cells.

CRISPR-Edited Organoids: Precision Models for Understanding and Treating Disease

Applying CRISPR editing to these 3D organ-like structures enables researchers to fix genetic defects or introduce mutations to study disease progression. In patients-derived organoids it corrects mutations, restoring tissue health and enabling evaluation of new therapies.

ScRNA-seq can verify and map gene editing effects, as it identifies cellular changes caused by genetic edits, from the target edited gene to the downstream cascading effects on the connected pathways.

Maintaining the fidelity of the genetic background in a patient’s derived organoid is critical: when an edit is introduced, any downstream effects observed should be attributable to that specific edit and not to unrelated genetic differences. ScRNA-seq links the genetic alteration to its functional consequences, confirming that the edit has produced the intended effect.

Moreover, it can distinguish between intended and off-target effects. Indeed, a seminal paper using combinatorial barcoding to track Cas9 edit outcomes found a high frequency of off-target effects disrupting the expression of hundreds of downstream genes.

Drug Testing for Personalized Medicine: Organoid as Physiologically Relevant Models
Organoids are powerful tools for advancing personalized medicine. By comparing treated and untreated organoids, scientists can identify cell type–specific gene expression changes that act as biomarkers of drug efficacy or reveal the molecular pathways targeted by a compound, shedding light on its mechanism of action. Such insights can even uncover new or off-label uses for existing drugs.

Building on this approach, a recent study used a breast cancer TME derived organ-on-chip (TMEC) combined with scRNA-seq to dissect the complex interactions within the tumor microenvironment (TME). Specifically, the study examined the synergistic interaction between CAFs, macrophages, and triple-negative breast cancer cells (TNBC). The analysis revealed that stromal-immune crosstalk drives cancer invasion, proliferation, and immune evasion through molecular mechanisms like the Kynurenine pathway. Importantly, the pathway’s pharmacological inhibition suppressed tumor cells migration without affecting CAFs and macrophages viability, highlighting a promising new therapeutic avenue for TNBC.

In the next article, we will interview a scientist and animal activist who used Parse Evercode™  in human-derived models. She shares how her work is helping shift the paradigm, from using dogs as research subjects to treating them as patients.