Artificial Intelligence for Drug Discovery Accelerating the Development of New Pharmaceuticals

Abstract

AI’s emergence in drug discovery will transform diagnostics, allow accelerated drug development, and realize personalized medicine. However, despite its potential, current AI can cause several challenges, including small-scale validation, AI bias, data privacy, regulatory compliance, as well as scalability and integration into clinical practice. These challenges can be addressed through large-scale real-world validations, fairness-aware algorithms and privacy-preserving techniques building a next-gen AI framework enabling our research. We literally build them in systems to provide transparency with the XAI, scale them up for various healthcare ecosystems, and also work compliant globally with policies like HIPAA, and GDPR. Through the efforts of, you know, we want to try and use various datasets, and embed AI into existing healthcare infrastructures, and apply AI drug discovery to real world patients. Thus, this approach will shorten drug development timelines, reduce healthcare costs, and improve quality of life for patients through more effective personalized treatment options. Basically, our research ties our ethical, transparent and scalable AI-controlled healthcare system to the realization of new digital medicines and universal access to healthcare worldwide.

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