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Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and machine learning in the entire spectrum of drug R&D
Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval
Offers a balanced approach to data science organization build
Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development
Affords sufficient context for each problem and provides detailed description of solutions suitable for practitioners with limited data science expertise
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Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and machine learning in the entire spectrum of drug R&D
Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval
Offers a balanced approach to data science organization build
Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development
Affords sufficient context for each problem and provides detailed description of solutions suitable for practitioners with limited data science expertise