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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | A Review on Artificial Intelligence (AI) in Pharmaceutical Sector |
| Authors Name: | Disha Agarwal , Ajay Annadate , Chetan Bakliwal , Leena Bhajankar , Sanjay Walode |
| Unique Id: | IJSDR2403056 |
| Published In: | Volume 9 Issue 3, March-2024 |
| Abstract: | Artificial Intelligence (AI) has been transforming the practice of drug discovery in the past decade. Various AI techniques have been used in many drug discovery applications, such as virtual screening and drug design. In this survey, we first give an overview on drug discovery and discuss related applications, which can be reduced to two major tasks, i.e., molecular property prediction and molecule generation. We then present common data resources, molecule representations and benchmark platforms. As a major part of the survey, AI techniques are dissected into model architectures and learning paradigms. To reflect the technical development of AI in drug discovery over the years, the surveyed works are organized chronologically. We expect that this survey provides a comprehensive review on AI in drug discovery. We also provide a GitHub repository with a collection of papers (and codes, if applicable) as a learning resource, which is regularly updated. Artificial intelligence has the potential to revolutionize the drug discovery process, offering improved efficiency, accuracy, and speed. However, the successful application of AI isdependent on the availability of high-quality data, the addressing of ethical concerns, and therecognition of the limitations of AI-based approaches. In this article, the benefits, challenges anddrawbacks of AI in this field are reviewed, and possible strategies and approaches for overcoming the present obstacles are proposed. The use of data augmentation, explainable AI, and the integration of AI with traditional experimental methods, as well as the potential advantages of AI in pharmaceutical research are also discussed. Overall, this review highlights the potential of AI in drug discovery and provides insights into the challenges and opportunities for realizing its potential in this field. |
| Keywords: | Artificial Intelligence, drug discovery, clinical trial, QA and QC |
| Cite Article: | "A Review on Artificial Intelligence (AI) in Pharmaceutical Sector", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.9, Issue 3, page no.370 - 381, March-2024, Available :http://www.ijsdr.org/papers/IJSDR2403056.pdf |
| Downloads: | 000337365 |
| Publication Details: | Published Paper ID: IJSDR2403056 Registration ID:210382 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: 370 - 381 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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