Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development

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Description

Artificial intelligence and machine learning (AI/ML) is a set of technologies that includes automated systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, and decision-making. AI/ML has promising applications in health care, including drug development. For example, it may have the potential to help identify new treatments, reduce failure rates in clinical trials, and generally result in a more efficient and effective drug development process. However, applying AI/ML technologies within the health care system also raises ethical, legal, economic, and social questions. GAO was asked to conduct a technology assessment on the use … continued below

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viii, 74 pages : color illustrations

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United States. Government Accountability Office. December 2019.

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This report is part of the collection entitled: Artificial Intelligence (AI) Policy Collection and was provided by the UNT Libraries Government Documents Department to the UNT Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

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  • Persons, Timothy M. Timothy M. Persons, PhD, Chief Scientist and Managing Director, Science, Technology Assessment, and Analytics, U.S. Government Accountability Office
  • McGinnis, J. Michael Executive Officer and Executive Director, NAM Leadership Consortium

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  • Main Title: Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development
  • Added Title: Artificial Intelligence in Health Care
  • Added Title: Benefits and Challenges of Machine Learning in Drug Development
  • Added Title: Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development: With Field Background Content From the National Academy of Medicine
  • Added Title: GAO Technology Assessment
  • Added Title: Technology Assessment
  • Series Title: Report to Congressional Requesters

Description

Artificial intelligence and machine learning (AI/ML) is a set of technologies that includes automated systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, and decision-making. AI/ML has promising applications in health care, including drug development. For example, it may have the potential to help identify new treatments, reduce failure rates in clinical trials, and generally result in a more efficient and effective drug development process. However, applying AI/ML technologies within the health care system also raises ethical, legal, economic, and social questions. GAO was asked to conduct a technology assessment on the use of AI technologies in drug development with an emphasis on foresight and policy implications. This report discusses (1) current and emerging AI technologies available for drug development and their potential benefits; (2) challenges to the development and adoption of these technologies; and (3) policy options to address challenges to the use of machine learning in drug development. -- from Foreword

Physical Description

viii, 74 pages : color illustrations

Notes

"This report is being jointly published by the Government Accountability Office (GAO) and the National Academy of Medicine (NAM). Part One of this joint publication presents material excerpted and adapted by NAM from its 2020 NAM Special Publication Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. Part Two is the full presentation of GAO's Technology Assessment Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development. Although GAO and NAM staff consulted with and assisted each other throughout this work, reviews were conducted by NAM and GAO separately and independently, and authorship of the text of Part One and Part Two of the report lies solely with NAM and GAO, respectively" (p. 2).

Contents: Part one -- Artificial intelligence in health care: field background (National Academy of Medicine). -- Introduction. -- 1. Definitions of key AI terms. -- 2. A historical perspective and overview of current AI. -- 3. How artificial intelligence is changing health and health care. -- 4. Potential tradeoffs and unintended consequences of AI. -- 5. Best practices for machine-learning model development and validation. -- 6. Deploying AI in clinical settings. -- 7. Conclusion. -- Bibliography. -- Authors of NAM special publication. -- Part two -- Artificial intelligence in health care: benefits and challenges of machine learning in drug development (U.S. Government Accountability Office). -- Introduction. --!. Background. -- 2. Status and potential benefits of machine learning in drug development. -- 3. Challenges hindering the use of machine learning in drug development. -- 4. Policy options to address challenges to the use of machine learning in drug development. -- 5. Agency and expert comments. -- Appendices.

"With field background content from the National Academy of Medicine" - Cover.

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Artificial Intelligence (AI) Policy Collection

The Artificial Intelligence (AI) Policy Collection contains open access resources that provide policy overviews, implementation plans, guiding frameworks, and resources for implementing artificial intelligence and machine learning in a wide range of environments. This collection includes documents published by Federal agencies, non-governmental organizations, international, state, and local governments.

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Government Accountability Office Reports

The U.S. Government Accountability Office (GAO) is an independent, nonpartisan agency that works for the U.S. Congress investigating how the federal government spends taxpayers' money. Its goal is to increase accountability and improve the performance of the federal government. The Government Accountability Office Reports Collection consists of over 13,000 documents on a variety of topics ranging from fiscal issues to international affairs.

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  • December 2019

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  • Feb. 25, 2024, 5:10 p.m.

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  • March 26, 2024, 12:35 p.m.

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United States. Government Accountability Office. Artificial Intelligence in Health Care: Benefits and Challenges of Machine Learning in Drug Development, report, December 2019; Washington, D.C.. (https://digital.library.unt.edu/ark:/67531/metadc2288714/: accessed May 24, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.

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