A COMPREHENSIVE REVIEW ON DISCOVERY OF NEW DRUGS

Drug discovery is a complex, multidisciplinary, and time-intensive process aimed at transforming an initial scientific concept into a safe, effective, and marketable therapeutic agent. The process encompasses several interconnected stages, including target identification and validation, hit and lead compound screening, optimization of molecular structures, and extensive preclinical and clinical evaluation to ensure efficacy and safety. In recent years, technological innovations have significantly revolutionized the landscape of drug discovery. The integration of Artificial Intelligence (AI), machine learning, and computational modeling has enabled rapid data processing, virtual screening, and predictive analysis of pharmacological and toxicological properties, thereby accelerating the identification of promising drug candidates. Furthermore, diverse molecular sources—such as synthetic libraries, combinatorial chemistry, and natural products—continue to provide invaluable chemical diversity for the development of novel therapeutics. Collectively, these advancements are reshaping modern pharmaceutical research, enhancing efficiency, reducing costs, and expanding opportunities for the discovery of innovative medicines that address unmet clinical needs.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-16
DOI
https://doi.org/10.5281/zenodo.21356115
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

A COMPREHENSIVE REVIEW ON DISCOVERY OF NEW DRUGS

*1Gurude Sneha Uttam, 2Mr. Shivraj Suryawanshi, 3Dr. Ganesh Tolsarwad
Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

A COMPREHENSIVE REVIEW ON DISCOVERY OF NEW DRUGS

*1Gurude Sneha Uttam, 2Mr. Shivraj Suryawanshi, 3Dr. Ganesh Tolsarwad
article en

Abstract

Drug discovery is a complex, multidisciplinary, and time-intensive process aimed at transforming an initial scientific concept into a safe, effective, and marketable therapeutic agent. The process encompasses several interconnected stages, including target identification and validation, hit and lead compound screening, optimization of molecular structures, and extensive preclinical and clinical evaluation to ensure efficacy and safety. In recent years, technological innovations have significantly revolutionized the landscape of drug discovery. The integration of Artificial Intelligence (AI), machine learning, and computational modeling has enabled rapid data processing, virtual screening, and predictive analysis of pharmacological and toxicological properties, thereby accelerating the identification of promising drug candidates. Furthermore, diverse molecular sources—such as synthetic libraries, combinatorial chemistry, and natural products—continue to provide invaluable chemical diversity for the development of novel therapeutics. Collectively, these advancements are reshaping modern pharmaceutical research, enhancing efficiency, reducing costs, and expanding opportunities for the discovery of innovative medicines that address unmet clinical needs.

Zenodo (CERN European Organization for Nuclear Research)
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Computational Drug Discovery Methods
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