AI Finds New Medicines: How Machines Can Help Discover New Medicines and Make Clinical Trials More Efficient

EasyChair Preprint 14838

Abstract

The traditional drug discovery and development process is notoriously time-consuming and expensive, often spanning over a decade and costing billions of dollars. Despite these investments, the majority of drug candidates fail during clinical trials. Artificial intelligence (AI) presents a promising solution to these challenges by revolutionizing both drug discovery and the clinical trial process. AI can analyze vast datasets, identify potential drug candidates, and predict the efficacy and toxicity of compounds, dramatically reducing the time and cost associated with early-stage research. Furthermore, AI enhances clinical trials by optimizing patient selection, personalizing treatments, and streamlining data collection and analysis. This paper explores the applications of AI in drug discovery, its role in improving clinical trials, and the ethical challenges associated with these technologies. Through real-world case studies, such as AI’s contributions during the COVID-19 pandemic, we highlight the tangible benefits and transformative potential of AI in pharmaceutical research. While there are challenges, including data privacy concerns and regulatory hurdles, the future of AI in medicine holds immense promise for accelerating medical breakthroughs and delivering personalized therapies more efficiently than ever before.

Keyphrases: COVID-19 pandemic, Technologies, The traditional drug, data privacy

@booklet{EasyChair:14838,
  author    = {Docas Akinyele},
  title     = {AI Finds New Medicines: How Machines Can Help Discover New Medicines and Make Clinical Trials More Efficient},
  howpublished = {EasyChair Preprint 14838},
  year      = {EasyChair, 2024}}