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Revolutionizing Pharmaceuticals: the Transformative Role of AI in Expedited Drug Discovery

EasyChair Preprint no. 11956

12 pagesDate: February 5, 2024


The pharmaceutical industry is experiencing a groundbreaking transformation with the integration of artificial intelligence (AI) into drug discovery processes. This paper explores the unprecedented advancements and the transformative role that AI plays in accelerating drug discovery, revolutionizing the way new therapeutic solutions are identified and developed. AI, particularly machine learning and deep learning algorithms, has emerged as a powerful tool in processing vast amounts of biological data, deciphering complex patterns, and predicting potential drug candidates. By analyzing genomics, proteomics, and other omics data, AI algorithms can uncover hidden correlations, identify potential drug targets, and predict the efficacy of drug candidates with remarkable speed and precision. This paper delves into specific AI-driven methodologies, such as virtual screening, de novo drug design, and predictive modeling, shedding light on how these techniques are reshaping the pharmaceutical landscape. Additionally, it examines case studies where AI has successfully expedited the drug discovery process, leading to the identification of novel compounds and significantly reducing time and costs traditionally associated with drug development.

Keyphrases: Artificial Intelligence, De Novo Drug, deep learning, Design, drug discovery, machine learning, omics data, personalized medicine, Pharmaceutical Industry, predictive modeling, virtual screening

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {William Jack and Sani Doel},
  title = {Revolutionizing Pharmaceuticals: the Transformative Role of AI in Expedited Drug Discovery},
  howpublished = {EasyChair Preprint no. 11956},

  year = {EasyChair, 2024}}
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