AI APPLICATIONS IN DRUG DISCOVERY

The integration of Artificial Intelligence (AI) in medicine, particularly throughMachine
Learning (ML), has significantly advanced drug discovery. AI acts as catalyst, narrowing the
gap between understanding diseases and identifying potential therapeutic agents. This review
provides an overview of AI's role in various stages of drug discovery, including disease
identification, target identification, screening, and lead discovery.AI's capability to analyze
extensive datasets and discern patterns is crucial in these stages, enhancing predictions and
efficiencies in disease identification, drug discovery,and clinical trial management. By
leveraging AI, researchers can expedite drug development, reducing time and costs
associated with introducing new drugs to the market.However, AI's effectiveness depends on
data quality, algorithm training, and ethical considerations, particularly in handling patient
data during clinical trials. Addressing these factors is essential to harness AI's potential in
transforming drugdevelopment.By doing so, AI can offer significant benefits to patients and
society, revolutionizing the field of medicine. The future of AI in drug discovery holds
immense promise, and its continued development is likely to have a profound impact on
healthcare.The review highlights AI's transformative role in drug discovery, emphasizing its
potential to analyze vast data volumes, reduce costs, and improve patient outcomes. AsAI
technology advances, its applications in medicine are expected to expand, leading to
breakthroughs in disease treatment and management.
Keywords:Artificial intelligence, Drug discovery,Machine learning, Healthcare,
Medicine