Pharma Tech: Leveraging Software for Drug Development & Clinical Research

Year : 2025 | Volume : 03 | Issue : 01 | Page : 11-19
    By

    Vikash Yadav,

  • Mohd. Wasiullah,

  • Piyush Yadav,

  • Rahul Nishad,

  1. Assistant Professor, Department of Pharmacy, Prasad Institute of Technology, Jaunpur,, Uttar Pradesh, India
  2. Principal, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  3. Academic Head, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  4. Scholar, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India

Abstract

The pharmaceutical sector is progressively adopting software solutions to enhance the drug development process and optimize clinical research results. Drug development is a time-consuming, expensive, and intricate process that traditionally requires extensive laboratory research, preclinical testing, and several stages of clinical trials. Software tools are revolutionizing these stages by improving efficiency, minimizing errors, and speeding up timelines. During preclinical testing, predictive software tools are used to model toxicological effects and assess the safety profiles of drug candidates, reducing the risk of adverse outcomes in human trials. These tools contribute to making early stage testing more efficient and focused on viable candidates. In clinical research, software solutions play a critical role in trial design, patient recruitment, data collection, and monitoring. Clinical trial management systems (CTMS), electronic data capture (EDC) platforms, and data analytics tools facilitate real-time data collection and integration, simplifying the tracking of progress, identification of trends, and ensuring adherence to regulatory standards. The use of artificial intelligence (AI) and machine learning (ML) is becoming increasingly prevalent in clinical research, as these technologies allow for advanced data analysis and predictive modelling. AI and ML can uncover patterns in patient responses, predict drug outcomes, and optimize treatment plans, thus improving the precision of clinical trials. Software tools also support regulatory compliance, ensuring that clinical data is accurate, traceable, and consistent with health authority guidelines

Keywords: CTMS, artificial intelligence, electronic data capture, machine learning, electronic health records

[This article belongs to International Journal of Bioinformatics and Computational Biology ]

How to cite this article:
Vikash Yadav, Mohd. Wasiullah, Piyush Yadav, Rahul Nishad. Pharma Tech: Leveraging Software for Drug Development & Clinical Research. International Journal of Bioinformatics and Computational Biology. 2025; 03(01):11-19.
How to cite this URL:
Vikash Yadav, Mohd. Wasiullah, Piyush Yadav, Rahul Nishad. Pharma Tech: Leveraging Software for Drug Development & Clinical Research. International Journal of Bioinformatics and Computational Biology. 2025; 03(01):11-19. Available from: https://journals.stmjournals.com/ijbcb/article=2025/view=197412


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Regular Issue Subscription Review Article
Volume 03
Issue 01
Received 14/12/2024
Accepted 07/01/2025
Published 07/02/2025
Publication Time 55 Days
Total Visits: 81


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