Abstract
The convergence of Artificial Intelligence (AI) and drug discovery represents a pivotal turning point in the pharmaceutical industry. Traditional drug development has long been fraught with challenges, from lengthy timelines to high failure rates. However, the integration of AI-driven technologies has ushered in a new era of efficiency, precision, and innovation in the quest for novel therapeutic solutions.
This abstract provides a comprehensive overview of AI's transformative role in drug discovery. It highlights key applications, including target identification, compound screening, rational drug design, clinical trial optimization, drug repurposing, and pharmacovigilance. AI's data-driven approach unlocks invaluable insights from extensive biological, chemical, and clinical datasets, accelerating the identification and development of potential drug candidates.
Furthermore, ethical considerations and regulatory implications are examined in the context of AI-driven drug discovery, emphasizing the importance of transparency, bias mitigation, and data privacy.
In summary, AI in drug discovery has not only redefined the research landscape but also holds the promise of delivering safer, more effective, and personalized medicines at an unprecedented pace. This abstract underscores the transformative impact of AI, setting the stage for a future where drug development is propelled by data-driven insights and computational precision.
