Artificial intelligence (AI) and machine learning (ML) are transforming healthcare, particularly in drug delivery, development, and therapeutics. These technologies offer unprecedented potential to address complex diseases and improve patient outcomes. AI-powered drug delivery systems optimize drug release, target specific tissues, and enhance treatment efficacy, thereby minimizing side effects and maximizing therapeutic effectiveness. ML algorithms accelerate drug development by identifying promising candidates and streamlining clinical trials, which reduces both development time and costs. Another significant application is personalized therapeutics, which are tailored to individual patient profiles. AI analyzes genomic and medical history data to predict drug responses and generate optimized treatment plans. This personalized approach increases treatment effectiveness and reduces adverse reactions. AI and ML are also being applied to the management of neurodegenerative disorders, antimicrobial resistance, and ocular diseases, providing tools for early diagnosis and disease management. Ethical considerations such as data privacy, algorithmic transparency, and robust pharmacovigilance are essential for responsible advancement. The integration of AI and ML in drug delivery and therapeutics is poised to significantly improve patient outcomes.
Parashar et al. (Wed,) studied this question.