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Artificial intelligence (AI) is transforming clinical trials by enhancing efficiency, accuracy, and cost-effectiveness. Harsha Vardhan Reddy Yeddula's research highlights the role of AI in patient recruitment, supply chain management, data security, and regulatory compliance. The integration of machine learning, predictive analytics, and natural language processing is accelerating drug development while ensuring high-quality standards.
AI-driven solutions are addressing significant challenges in clinical trials, such as low patient enrollment and high dropout rates. By utilizing electronic health records and advanced data processing, AI models can identify eligible candidates with remarkable precision. Furthermore, AI's impact on supply chain optimization and data security is reducing costs and improving overall trial outcomes.
• AI improves patient recruitment efficiency in clinical trials.
• Machine learning optimizes supply chain management, reducing material wastage.
AI is utilized to enhance the efficiency and accuracy of clinical trials.
Machine learning algorithms analyze trial data to improve patient recruitment and logistics.
Predictive analytics models forecast trial needs and optimize resource allocation.
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