Future Prospects of AI in Pharmaceutical Industry and its Limitation

Year : 2025 | Volume : 15 | Issue : 02 | Page : 6 13
    By

    Mohd. Wasiullah,

  • Piyush Yadav,

  • Anjali Maurya,

  • Saurabh Shukla,

  1. Principal, Dept. of Pharmacy, Prasad Institute Technology, Jaunpur, Uttar Pradesh, India
  2. Academic Head, Dept. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  3. Lecturer, Dept. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  4. Scholar, Dept. of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India

Abstract

The pharmaceutical industry is facing significant challenges, including prolonged drug development timelines, high costs, and low success rates in clinical trials. Traditional methods often result in inefficiencies, with new drug development taking over a decade and billions of dollars, yet most candidates fail in clinical trials due to issues like inefficacy or safety concerns. Artificial Intelligence (AI) has become a groundbreaking technology with the potential to tackle these issues effectively. Through advanced techniques, like machine learning (ML), natural language processing (NLP), and deep learning, AI optimizes various stages of the pharmaceutical value chain – from accelerating drug discovery and streamlining clinical trials to enhancing manufacturing processes and optimizing supply chain logistics. AI offers potential in advancing personalized healthcare by customizing therapies to align with each person’s unique genetic makeup and environmental influences. Despite its potential, the integration of AI faces obstacles, such as data quality and accessibility, ethical concerns (including algorithmic bias and data privacy), regulatory challenges, and cybersecurity risks. Overcoming these limitations is essential for realizing AI’s full potential in the pharmaceutical industry. This review explores the current applications of AI, its future prospects, and the challenges that must be addressed to facilitate its widespread adoption, ultimately leading to more efficient, cost-effective, and personalized healthcare solutions.

Keywords: Artificial Intelligence, pharmaceutical industries, AI limitation, machine learning (ML), natural language processing (NLP).

[This article belongs to Research and Reviews: A Journal of Pharmacology ]

How to cite this article:
Mohd. Wasiullah, Piyush Yadav, Anjali Maurya, Saurabh Shukla. Future Prospects of AI in Pharmaceutical Industry and its Limitation. Research and Reviews: A Journal of Pharmacology. 2025; 15(02):6-13.
How to cite this URL:
Mohd. Wasiullah, Piyush Yadav, Anjali Maurya, Saurabh Shukla. Future Prospects of AI in Pharmaceutical Industry and its Limitation. Research and Reviews: A Journal of Pharmacology. 2025; 15(02):6-13. Available from: https://journals.stmjournals.com/rrjop/article=2025/view=203744


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Regular Issue Subscription Original Research
Volume 15
Issue 02
Received 14/12/2024
Accepted 03/03/2025
Published 18/03/2025
Publication Time 94 Days
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