When Multi-Omics Studies Require Functional Ex Vivo Assays?
How functional ex vivo assays transform biomarker discovery
Multi-omics technologies have become indispensable in preclinical drug development, progressing from traditional genomics and transcriptomics to the great recent developments in access to patient samples, epigenomics, proteomics and AI analysis. Yet, most analyses are still performed on baseline samples, where cells remain at rest. For some types of drugs, this static picture can miss the most relevant signals for drug activity. For example, changes in key targets and signaling pathways responsible for activity and resistance for drugs whose mechanism of action require cell proliferation, may not be detected in the original resting sample. Volcano plot below shows the tremendous differences in RNAseq between original vs proliferating cells. Similar profound differences are observed with other multi-omics.
Functional ex vivo assays change the paradigm by exposing patient-derived samples in the minimally correct biological context to therapeutic candidates enabling multi-omic studies closer to what actually happens in patients.
Applications across therapeutic classes
The approach is relevant for multiple drug modalities and disease areas:
- Cytotoxic drugs that require cell proliferation (e.g. DNA intercalating drugs, kinase inhibitors for cell cycling targets, etc…)
- ADC drugs whose payload requires tumor cell proliferation
- Epigenetic drugs that require opening up the chromatin upon cell division
- Immunotherapies require an immune-oncological reaction where T/NK cells are activated and proliferating, killing tumor cells.
- Immune checkpoints (PD1, TIM3, LAG3, etc…)
- Bispecific & Trispecific antibodies, including TCEs & NKEs
- o Immunomodulators (A2A, IDO1, etc…)
Applications by study type
- Mechanism of action studies
- Biomarker discovery
From static to dynamic data on drug responses
Functional assays also enables the multi-omic study of drugs acting on the tumor cells, e.g. identifying sensitive vs resistant cells within a sample and across different samples. Baseline profiling captures genetic alterations and expression levels but cannot predict how cells will react to therapy. Once a sample is exposed to a compound ex vivo, the biology changes: cytokines are released, receptors are upregulated, and resistance pathways are activated. These induced signals provide mechanistic information that static analysis alone cannot deliver.
Why ex vivo makes the difference
By working with authentic patient samples in their native context, ex vivo assays capture critical interactions between tumor, immune, and stromal cells. This setting provides a unique opportunity to conduct what is effectively a “mini clinical trial” in the laboratory, generating highly translational data that inform biomarker strategy and patient selection.
Conclusion
Integrating functional ex vivo assays with omics technologies opens the door to a deeper understanding of drug response and resistance. It is a powerful way to de-risk development and accelerate translation to the clinic.
Next steps
Would you like to see how this approach can be tailored to your compound or therapeutic program? Contact our scientific team to explore how we can support your MoA studies, biomarker discovery and translational research.