COMPREHENSIVE REVIEW ON AI IN THE PHARMACEUTICAL INDUSTRY: NEW IDEAS, USES, AND WHAT THE FUTURE HOLDS

AI is changing the pharmaceutical industry by making drug discovery, development, manufacturing, and patient care more efficient, accurate, and cost-effective. Conventional pharmaceutical processes frequently entail significant time consumption, elevated costs, and substantial failure rates. AI-driven technologies like machine learning (ML) and deep learning (DL) have made drug discovery faster, improved formulation development, and made clinical trial results better. AI is also critical for pharmacovigilance, precision medicine, and managing the supply chain. Even though it has the potential to change things, there are still problems like data privacy, ethical issues, regulatory uncertainty, and a lack of interpretability. This review examines the applications, benefits, constraints, and future potential of AI in the pharmaceutical sector, offering a thorough overview for researchers and professionals.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-01
DOI
https://doi.org/10.5281/zenodo.19884160
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

COMPREHENSIVE REVIEW ON AI IN THE PHARMACEUTICAL INDUSTRY: NEW IDEAS, USES, AND WHAT THE FUTURE HOLDS

Sruthi E. J.1 Aby Augustine*1
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

COMPREHENSIVE REVIEW ON AI IN THE PHARMACEUTICAL INDUSTRY: NEW IDEAS, USES, AND WHAT THE FUTURE HOLDS

Sruthi E. J.1 Aby Augustine*1
article en

Abstract

AI is changing the pharmaceutical industry by making drug discovery, development, manufacturing, and patient care more efficient, accurate, and cost-effective. Conventional pharmaceutical processes frequently entail significant time consumption, elevated costs, and substantial failure rates. AI-driven technologies like machine learning (ML) and deep learning (DL) have made drug discovery faster, improved formulation development, and made clinical trial results better. AI is also critical for pharmacovigilance, precision medicine, and managing the supply chain. Even though it has the potential to change things, there are still problems like data privacy, ethical issues, regulatory uncertainty, and a lack of interpretability. This review examines the applications, benefits, constraints, and future potential of AI in the pharmaceutical sector, offering a thorough overview for researchers and professionals.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Artificial Intelligence in Healthcare and Education
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