Biocom LifeLines Magazine Feature: “How multi-omics can unleash the full potential of cell and gene therapy”

While cell- and gene-based treatments hold immense potential, their development is not without challenges. What makes these drug modalities most promising is their ability to specifically target genes or cells associated with a disease, providing delivery precision to maximize therapeutic efficacy while minimizing off-target effects. Yet, there is still much variation in target engagement and drug response across patients, as well as in adverse events experienced from drug exposure. Such variability can stem from the therapy itself, in terms of the viral vectors or cells used, and/or from patient-specific factors including tumor/disease biology or immune status. Deciphering and addressing this heterogeneity is essential to advance more gene and cell therapies to market that can deliver patients a predictable clinical response.

Biomarkers have an important role to play in improving our understanding of the multifactorial phenotypes and processes contributing to gene or cell therapy efficacy or toxicity. Many development programs already employ biomarkers to varying extent, such as using genetic markers to stratify patient populations with a disease-associated gene mutation or profiling biomarkers of immune response to assess the therapeutic mechanisms of chimeric antigen receptor T-cell (CAR-T) therapies.

The field is finding, however, that with the compounding complexity in drug, disease, and patient population composition, single biomarkers can have limited utility, particularly when it comes to predicting therapeutic response. There is a need to evolve to multi-omics biomarker strategies that can more fully elucidate the intricate interactions of host, disease, and drug effects on cellular pathways, the immune system, and tissue microenvironments. Multiomics for gene therapy and cell therapy can capture information that may provide greater predictive value of patients likely to be responsive to a particular therapy, as well as enable earlier detection of drug-induced toxicity or drug resistance over time.

Armed with integrated layers of insight, we can optimize the reproducibility of gene and cell therapy benefits within distinct and across diverse patient populations.