A Review on Artificial Intellegence in Drug Discovery & Pharmaceutical Industry

Abstract

Introduction: The use of artificial intelligence (AI) in drug discovery and the pharma industry has been rapidly expanding in recent years. AI algorithms can analyze vast amounts of data, identify patterns, and make predictions that can accelerate drug discovery and improve patient outcomes. Methods: AI is being used in various stages of the drug discovery process, from target identification and lead optimization to clinical trials and post-market surveillance. Machine learning algorithms, neural networks, and natural language processing are among the AI techniques used in drug discovery. Results: AI-based drug discovery has already shown promising results, with several drugs in clinical trials or approved for use that were discovered using AI. AI is also being used to improve clinical trial design and patient selection, as well as to monitor adverse drug events and optimize drug dosing. Conclusion: AI has the potential to transform the drug discovery and pharma industry, making drug development faster, more efficient, and more effective. However, there are still challenges that need to be addressed, such as the need for high-quality data and the potential for bias in AI algorithms. Overall, the use of AI in drug discovery and the pharma industry is an exciting and rapidly evolving field that has the potential to improve patient outcomes and revolutionize healthcare.