AI in Drug Discovery: the Impact of AI on Accelerating the Drug Development Process and Discovering New Therapies.

EasyChair Preprint 15055

Abstract

Artificial intelligence (AI) is revolutionizing the field of drug discovery by significantly accelerating the drug development process and facilitating the discovery of new therapies. This transformation is driven by AI's capabilities in data analysis, predictive modeling, and high-throughput screening, which streamline traditionally lengthy and costly phases of drug development. By integrating diverse datasets and employing machine learning algorithms, researchers can identify promising drug candidates more efficiently, ultimately reducing timelines and costs. Additionally, AI enables the repurposing of existing medications, tailoring therapies to individual patients through personalized medicine, and addressing unmet medical needs in rare diseases. As the landscape of healthcare continues to evolve, the collaboration between academia, industry, and regulatory bodies will be essential to overcome challenges related to data quality, regulatory compliance, and algorithmic bias. This abstract underscores the critical role of AI in not only expediting drug development but also enhancing therapeutic innovation, signaling a future where AI is integral to the healthcare ecosystem.

Keyphrases: Artificial Intelligence (AI), High-throughput screening, data analysis, drug development process, drug discovery, drug repurposing, personalized medicine, predictive modeling

@booklet{EasyChair:15055,
  author    = {Adeyeye Barnabas},
  title     = {AI in Drug Discovery: the Impact of AI on Accelerating the Drug Development Process and Discovering New Therapies.},
  howpublished = {EasyChair Preprint 15055},
  year      = {EasyChair, 2024}}