21. ỨNG DỤNG TRÍ TUỆ NHÂN TẠO TRONG NGHIÊN CỨU VÀ PHÁT TRIỂN DƯỢC PHẨM

Abstract

Objective: This study explores the transformative impact of artificial intelligence (AI) across the pharmaceutical industry, focusing on key areas like R&D, manufacturing, business operations, and clinical applications. The objective is to provide an overview of AI applications, identifying trends and assessing their potential.

Method: The research synthesizes literature from scientific articles, industry reports, and case studies, using keywords such as “artificial Intelligence”, “pharmaceuticals”, “drug discovery”, and “process optimization”. Both qualitative and quantitative analyses were conducted, examining metrics such as cost-effectiveness and drug development timelines. The study also includes specific applications of AI such as “drug target identification”, “de novo drug design”, “toxicity prediction” and “clinical trial optimization”.

Results: AI is revolutionizing drug target identification, drug design, and toxicity prediction, accelerating preclinical phases. AI optimizes manufacturing through quality control and predictive maintenance and enhances decision-making in procurement and supply chain management. AI also helps optimize clinical trials through patient recruitment and real time data monitoring, and facilitates drug repurposing. Data mining and predictive modeling contribute to AI-driven market forecasting, sales optimization, and customer engagement. Companies like Pfizer and Novartis have deployed AI for drug discovery and predicting trial outcomes.

Conclusions: The study highlights AI’s potential for reducing costs, shortening development timelines, and improving treatment outcomes. Strategic AI integration is crucial for pharmaceutical competitiveness