医薬品開発とデータサイエンス・ＡＩ・機械学習 Data Science, AI, and Machine Learning in Drug Development (Chapman & Hall/crc Biostatistics Series)

医薬品開発とデータサイエンス・ＡＩ・機械学習<br>Data Science, AI, and Machine Learning in Drug Development (Chapman & Hall/crc Biostatistics Series)

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医薬品開発とデータサイエンス・ＡＩ・機械学習
Data Science, AI, and Machine Learning in Drug Development (Chapman & Hall/crc Biostatistics Series)

Yang, Harry (EDT)

ウェブストア価格 ¥31,468（本体¥28,608）
Chapman & Hall/CRC（2022/10発売）
外貨定価 US$ 150.00
ポイント 286pt

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製本 Hardcover:ハードカバー版／ページ数 320 p.
言語 ENG
商品コード 9780367708078
DDC分類 615.1900285

Full Description

The confluence of big data, artificial intelligence (AI), and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change.

Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R & D, emerging applications of big data, AI and ML in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations.

Features

Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and ML 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 a detailed description of solutions suitable for practitioners with limited data science expertise

1 Transforming Pharma with Data Science, AI and Machine Learning 2 Regulatory Perspective on Big Data, AI, and Machining Learning 3 Building an Agile and Scalable Data Science Organization 4 AI and Machine Learning in Drug Discovery 5 Predicting Anti-Cancer Synergistic Activity Through Machine Learning and Natural Language Processing 6 AI-Enabled Clinical Trials 7 Machine Learning for Precision Medicine 8 Reinforcement Learning in Personalized Medicine 9 Leveraging Machine Learning, Natural Language Processing, and Deep Learning in Drug Safety and Pharmacovigilance 10 Intelligent Manufacturing and Supply of Biopharmaceuticals 11 Reinventing Medical Affairs in the Era of Big Data and Analytics 12 Deep Learning with Electronic Health Record 13 Real-World Evidence for Treatment Access and Payment Decisions