Integrating Artificial Intelligence into Neurotherapeutics: A New Frontierin Drug Design and Precision Healthcare

Introduction: Neurodegenerative disorders such as Alzheimer’s disease, Parkinson’s disease, epilepsy, and multiple sclerosis are particularly challenging due to their complex pathophysiology and the relative lack of effective treatments Methods: Traditional drug discovery tools are costly and time-consuming, which necessitates the adoption of newer approaches. Artificial intelligence (AI) has emerged as a transformative technology in neurotherapeutics, accelerating drug discovery, drug repurposing, and personalized medicine Results: AI-driven strategies leverage extensive genomic, proteomic, and clinical trial data to identify novel drug targets, rationalize molecular design, and predict drug efficacy and toxicity. Deep learning algorithms uncover intricate biological interactions and support the identification and validation of drug candidates. AI-driven natural language processing enables automated extraction of data from the literature, thereby accelerating research. AI also facilitates drug repurposing through comprehensive analysis of large drug target networks, significantly reducing development timelines. AI driven clinical trial optimization improves patient recruitment, protocol design, and real time monitoring through predictive analytics. Discussion: Challenges such as data standardization, regulatory compliance, and model interpretability must be addressed to ensure effective integration of AI into drug development. Continued advances in AI, automation, robotics, and quantum computing are expected to further refine neurological drug discovery and personalized therapeutic approaches. Autonomous laboratories integrating AI with high throughput screening are likely to transform neurodrug development and personalized therapy design. Conclusion: By accelerating treatment development, AI represents a paradigm shift in the fight against neurological diseases through the integration of precision medicine and real time approaches.