Exploring Advanced Applications of Artificial Intelligence in Neuropharmacology: A Comprehensive Overview

Artificial Intelligence (AI) is revolutionizing neuropharmacology by transforming the understanding and treatment of neurological disorders. This review highlights AI's advanced applications in drug discovery, disease modeling, and personalized medicine. Technologies like machine learning, deep learning, and natural language processing drive these advancements by improving research efficiency, accuracy, and cost-effectiveness. AI plays a key role in predicting drug-target interactions, optimizing virtual screening, and modeling pharmacokinetics, accelerating the development of therapies for conditions such as Alzheimer’s and Parkinson’s. By integrating diverse datasets, AI facilitates the discovery of biomarkers and enhances clinical trial design, advancing precision medicine. These developments enable the customization of treatments to individual patient needs. Additionally, AI bridges gaps in understanding complex neural systems by combining genetic, proteomic, and neuroimaging data, making research more reproducible and scalable. AI also transforms personalized medicine by predicting drug responses, minimizing adverse effects, and optimizing treatment efficacy. Real-time applications, including wearable devices and brain-computer interfaces, provide continuous monitoring and dynamic treatment adjustments. These innovations are particularly effective in managing chronic conditions like epilepsy, Parkinson’s, and multiple sclerosis. However, integrating AI into neuropharmacology presents challenges such as ethical concerns, data privacy, and model interpretability. Overcoming these obstacles requires collaboration among researchers, clinicians, policymakers, and technologists to establish transparency, accountability, and robust regulatory frameworks. Trust in AI solutions depends on ensuring fairness, safeguarding patient rights, and developing explainable and reliable models. Looking ahead, AI has the potential to refine neural pathway simulations, enhance personalized treatments, and improve neurological condition management. Innovations such as real-time analytics for stroke and wearable devices for Parkinson’s disease exemplify its transformative impact on patient care. By addressing challenges and fostering collaboration, AI is poised to reshape neuropharmacology, revolutionize treatments, and improve patient outcomes.