Omics-driven Drug Discovery and Development
Surendra Sarsaiya, Archana Jain, Qihai Gong, Qihai Gong · CABI eBooks · 2026
Modern drug discovery from medicinal plants is being revolutionized by the integration of multi-omics data and computational tools, which together enable several advanced strategies. High-throughput screening is now significantly enhanced by multi-omics data, allowing for the rapid PRIORITIZATION and identification of therapeutic candidates such as novel anti-cancer agents. Concurrently, network pharmacology provides a framework for precision target identification by elucidating the polypharmacological mechanisms of complex botanicals like Sauropus androgynus, mapping their compounds onto biological networks to reveal synergistic targets and pathways. For refining promising candidates, lead optimization employs computational strategies—including quantitative structure–activity relationship (QSAR) modeling and molecular docking—informed by omics data to improve critical absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. Finally, translational omics bridges preclinical and clinical development through the identification of toxicity biomarkers and the application of physiologically based pharmacokinetic (PBPK) modeling, aiming to predict human outcomes and accelerate the development pipeline. Case studies (e.g. curcuminoids from turmeric) validate omics-driven efficacy but highlight persistent challenges: poor bioavailability requiring nano-formulations, regulatory fragmentation in phytopharmaceutical standardization, and intellectual property complexities. Future directions emphasize AI-driven predictive modeling, sustainable bioproduction via synthetic biology, and regulatory harmonization. Despite hurdles in data integration and clinical translation, omics-powered approaches promise accelerated development of plant-derived drugs, merging traditional knowledge with precision science to address global health needs.