Why Functional Assays Alone Can Miss Drug Mechanisms
In the preclinical phase of drug development, assessing how a compound affects diseased cells is fundamental. Traditionally, this has relied on functional assays that measure outcomes such as viability, proliferation, or cell death. These readouts provide a first indication of drug efficacy, particularly in systems that attempt to reproduce the biological context of the disease.
However, as drug modalities become more complex—targeting specific signaling pathways, immune checkpoints, or transcriptional programs—functional phenotypes alone often fail to explain the full mechanism of action. A drug may induce cell death in some samples and not in others, or display partial effects with unknown molecular underpinnings. Moreover, some surviving subpopulations may escape through adaptive responses or inherent resistance mechanisms that functional data alone cannot elucidate.
This limitation becomes more pronounced in diseases characterized by genetic heterogeneity—such as acute leukemias, lymphomas, or solid tumors—where two patients may exhibit similar functional profiles but carry distinct molecular drivers. Conversely, identical mutations may lead to divergent drug responses due to differences in cellular context or epigenetic state.
The Need for Integrated Functional–Molecular Profiling
To address these challenges, there is growing recognition of the need to combine functional assays with molecular characterization. This dual-layer approach enables a more mechanistic understanding of drug response by linking observed cellular phenotypes with the genomic, transcriptomic, or epigenetic features that drive them.
Key advantages of this integration include:
- Dissecting mechanisms of action beyond cytotoxicity.
- Profiling resistant cell fractions: Characterizing the molecular features of cells that survive treatment, enabling early identification of resistance pathways.
- Linking response to biomarkers: Correlating sensitivity or resistance with defined mutations, gene expression signatures, or pathway activation states.
- Rational design of combinations: Revealing synergistic or antagonistic interactions based on complementary functional and molecular data.
Such integration supports not only compound prioritization but also patient stratification strategies in later clinical stages by defining predictive biomarkers grounded in both molecular biology and phenotypic response.
A Functional–Molecular Strategy in Practice
To operationalize this approach, platforms must be able to:
- Perform high-resolution functional assays in primary patient-derived samples under physiologically relevant conditions.
- Preserve viable material post-treatment for molecular profiling, such as targeted sequencing or transcriptome analysis.
- Analyze both responsive and non-responsive compartments in parallel.
Several groups are beginning to adopt such models across indications, particularly in oncology and immunology, where dynamic interactions between tumor, immune, and stromal compartments play a critical role in treatment outcomes.
A Functional–Molecular Strategy in Practice
At Vivia Biotech, we have developed a platform that combines native-condition functional assays with downstream molecular profiling in primary patient samples. Our methodology allows us to evaluate drug response phenotypes (e.g., cell death, proliferation, immune activation) while retaining treated and surviving cells for genomic or transcriptomic characterization.
This integrated strategy has been applied across hematologic malignancies, solid tumors, and immune-mediated diseases, enabling the identification of:
- Mechanisms of action linked to specific pathways or cell types
- Resistance signatures in clinically defined patient cohorts
- Biomarker-response correlations to support stratified medicine
By bringing functional and molecular data into a single experimental workflow, we provide a mechanistic framework that enhances drug candidate evaluation and informs strategic decisions during preclinical development.