The volume and complexity of information about individual patients is greatly increasing with use of electronic records and personal devices. Potential effects on medical product development in the context of this wealth of real-world data could be numerous and varied, ranging from the ability to determine both large-scale and patient-specific effects of treatments to the ability to assess how therapeutics affect patients' lives through measurement of lifestyle changes. In October 2016, the National Academies of Sciences, Engineering, and Medicine held a workshop to facilitate dialogue among stakeholders about the opportunities and challenges for incorporating real-world evidence into all stages in the process for the generation and evaluation of therapeutics. Participants explored unmet stakeholder needs and opportunities to generate new kinds of evidence that meet those needs. This publication summarizes the presentations and discussions from the workshop. Table of Contents Front Matter 1 Introduction 2 Improving Evidence Generation for Decision Making on Approval and Use of New Treatments: Some Stakeholder Priorities 3 Opportunities for Real-World Data 4 Generating and Incorporating Real-World Evidence into Medical Product Development and Evaluation: Building from Successful Case Studies 5 Potential Strategies for a Way Forward Appendix A: Bibliography Appendix B: Workshop Agenda Appendix C: Participant Biographies Appendix D: Discussion Paper: Real-World Evidence to Guide theApproval and Use of New Treatments

Sharing knowledge is what drives scientific progress - each new advance or innovation in biomedical research builds on previous observations. However, for experimental findings to be broadly accepted as credible by the scientific community, they must be verified by other researchers. An essential step is for researchers to report their findings in a manner that is understandable to others in the scientific community and provide sufficient information for others to validate the original results and build on them. In recent years, concern has been growing over a number of studies that have failed to replicate previous results and evidence from larger meta-analyses, which have pointed to the lack of reproducibility in biomedical research. On September 25 and 26, 2019, the National Academies of Science, Engineering, and Medicine hosted a public workshop in Washington, DC, to discuss the current state of transparency in the reporting of preclinical biomedical research and to explore opportunities for harmonizing reporting guidelines across journals and funding agencies. Convened jointly by the Forum on Drug Discovery, Development, and Translation; the Forum on Neuroscience and Nervous System Disorders; the National Cancer Policy Forum; and the Roundtable on Genomics and Precision Health, the workshop primarily focused on transparent reporting in preclinical research, but also considered lessons learned and best practices from clinical research reporting. This publication summarizes the presentation and discussion of the workshop. Table of Contents Front Matter 1 Introduction 2 Transparency and Trust 3 Approaches to Cultivate Transparent Reporting in Biomedical Research 4 Lessons Learned and Best Practices 5 Checklists and Guidelines 6 Toward Minimal Reporting Standards for Preclinical Biomedical Research 7 Stakeholder Opportunities for Promoting Transparent Reporting Appendix A: References Appendix B: Background Discussion Document: Selected Guidelines for Transparent Reporting Appendix C: Workshop Agenda

The cloud model of data sharing has led to a vast increase in the quantity and complexity of data and expanded access to these data, which has attracted many more researchers, enabled multi-national neuroscience collaborations, and facilitated the development of many new tools. Yet, the cloud model has also produced new challenges related to data storage, organization, and protection. Merely switching the technical infrastructure from local repositories to cloud repositories is not enough to optimize data use. To explore the burgeoning use of cloud computing in neuroscience, the National Academies Forum on Neuroscience and Nervous System Disorders hosted a workshop on September 24, 2019. A broad range of stakeholders involved in cloud-based neuroscience initiatives and research explored the use of cloud technology to advance neuroscience research and shared approaches to address current barriers. This publication summarizes the presentation and discussion of the workshop. Table of Contents Front Matter 1 Introduction and Background 2 Harnessing Cloud-Based Technologies to Advance Neuroscience Research: Select Current Initiatives Part 1: Cloud-Based Technologies for Neuroscience Research: Challenges and Potential Solutions 3 Protecting Privacy in the Cloud 4 Managing Data and Promoting Interoperability in the Cloud 5 Assigning Credit, Determining Ownership, and Licensing Data in the Cloud 6 Governing, Funding, and Sustaining Cloud-Based Platforms Part 2: Different Types of Neuroscience Data: Challenges and Potential Opportunities 7 Clinical Trial and Research Data 8 Genetic Data 9 Neuroimaging Data 10 Real-World Data 11 Future Directions Appendix A: References Appendix B: Workshop Agenda Appendix C: Registered In-Person Attendees

Those involved in the drug development process face challenges of efficiency and overall sustainability due in part to high research costs, lengthy development timelines, and late-stage drug failures. Novel clinical trial designs that enroll participants based on their genetics represent a potentially disruptive change that could improve patient outcomes, reduce costs associated with drug development, and further realize the goals of precision medicine. On March 8, 2017, the Forum on Drug Discovery, Development, and Translation and the Roundtable on Genomics and Precision Health of the National Academies of Sciences, Engineering, and Medicine hosted the workshop Enabling Precision Medicine: The Role of Genetics in Clinical Drug Development. Participants examined successes, challenges, and possible best practices for effectively using genetic information in the design and implementation of clinical trials to support the development of precision medicines, including exploring the potential advantages and disadvantages of such trials across a variety of disease areas. This publication summarizes the presentations and discussions from the workshop. Table of Contents Front Matter 1 Introduction 2 Overarching Considerations for Implementing Successful Genetics-Enabled Drug Development 3 Case Studies in Precision Drug Development 4 Integrating Genetics into the Drug Development Pathway for Complex Diseases 5 Finding Innovative Ways to Integrate Genetic Research into the Drug Development Process 6 Reflecting Back and Looking Forward: Key Themes and Potential Next Steps in Genetics-Enabled Drug Development Appendix A: References Appendix B: Statement of Task and Workshop Agenda Appendix C: Speaker Biographical Sketches Appendix D: Registered Attendees

The evolution of health care is expanding the possibilities for integration of clinical research into the continuum of clinical care; new approaches are enabling the collection of data in real-world settings; and new modalities, such as digital health technologies and artificial intelligence applications, are being leveraged to overcome challenges and advance clinical research. At the same time, the clinical research enterprise is strained by rising costs, varying global regulatory and economic landscapes, increasing complexity of clinical trials, barriers to recruitment and retention of research participants, and a clinical research workforce that is under tremendous demands. Looking ahead to 2030, the Forum on Drug Discovery, Development, and Translation of the National Academies of Sciences, Engineering, and Medicine convened a public workshop for stakeholders from across the drug research and development life cycle to reflect on the lessons learned over the past 10 years and consider opportunities for the future. The workshop was designed to consider goals and priority action items that could advance the vision of a 2030 clinical trials enterprise that is more efficient, effective, person-centered, inclusive, and integrated into the health care delivery system so that outcomes and experiences for all stakeholders are improved. This Proceedings of a Workshop summarizes the presentations and discussions that took place during the four-part virtual public workshop held on January 26, February 9, March 24, and May 11, 2021. Table of Contents Front Matter 1 Introduction 2 Defining the Vision 3 Enhancing Outcomes in a More Person-Centered and Inclusive Clinical Trials Enterprise 4 Practical Applications for Technology to Enhance the Clinical Trials Enterprise 5 Building a More Resilient, Sustainable, and Transparent Clinical Trials Enterprise 6 Opportunities for Transformation References Appendix A: Health Affairs Blog Posts Appendix B: Speaker and Moderator Biographies Appendix C: Workshop Agendas

Investment and innovation in drug research and development (R&D) for highly prevalent chronic diseases has stalled in recent decades, despite half of all Americans living with at least one chronic disease. As a result, prevalent chronic diseases are producing immense health care costs as well as preventable suffering and death. On February 22, March 2, and March 8, 2021, the National Academies of Sciences, Engineering, and Medicine, convened a workshop to discuss barriers to innovation in this space and examine strategies and incentives to support equitable, person-centered drug R&D for prevalent chronic diseases. Table of Contents Front Matter 1 Introduction 2 Person-Centered Drug Research and Development 3 New Technologies to Enable Research in Prevalent Chronic Disease 4 Investment and Incentives 5 Learning from Success 6 Lessons Learned for the Future 7 Reflections and Final Thoughts Appendix A: Workshop Agenda Appendix B: Biographical Sketches of Workshop Speakers

Advances in cancer research have led to an improved understanding of the molecular mechanisms underpinning the development of cancer and how the immune system responds to cancer. This influx of research has led to an increasing number and variety of therapies in the drug development pipeline, including targeted therapies and associated biomarker tests that can select which patients are most likely to respond, and immunotherapies that harness the body's immune system to destroy cancer cells. Compared with standard chemotherapies, these new cancer therapies may demonstrate evidence of benefit and clearer distinctions between efficacy and toxicity at an earlier stage of development. However, there is a concern that the traditional processes for cancer drug development, evaluation, and regulatory approval could impede or delay the use of these promising cancer treatments in clinical practice. This has led to a number of efforts?by patient advocates, the pharmaceutical industry, and the Food and Drug Administration (FDA)?to accelerate the review of promising new cancer therapies, especially for cancers that currently lack effective treatments. However, generating the necessary data to confirm safety and efficacy during expedited drug development programs can present a unique set of challenges and opportunities. To explore this new landscape in cancer drug development, the National Academies of Sciences, Engineering, and Medicine developed a workshop held in December 2016. This workshop convened cancer researchers, patient advocates, and representatives from industry, academia, and government to discuss challenges with traditional approaches to drug development, opportunities to improve the efficiency of drug development, and strategies to enhance the information available about a cancer therapy throughout its life cycle in order to improve its use in clinical practice. This publication summarizes the presentations and discussions from the workshop. Table of Contents Front Matter Proceedings of a Workshop Appendix A: Statement of Task Appendix B: Workshop Agenda

The process of discovering and developing a new drug or therapy is extremely costly and time consuming, and recently, it has been estimated that the creation of a new medicine costs on average more than $2 billion and takes 10 years to reach patients. The challenges associated with bringing new medicines to market have led many pharmaceutical companies to seek out innovative methods for streamlining their drug discovery research. One way to increase the odds of success for compounds in the drug development pipeline is to adopt genetically guided strategies for drug discovery, and recognizing the potential benefits of collecting genetic and phenotypic information across specific populations, pharmaceutical companies have started collaborating with healthcare systems and private companies that have curated genetic bioresources, or large databases of genomic information. Large-scale cohort studies offer an effective way to collect and store information that can be used to assess gene?environment interactions, identify new potential drug targets, understand the role of certain genetic variants in the drug response, and further elucidate the underlying mechanisms of disease onset and progression. To examine how genetic bioresources could be used to improve drug discovery and target validation, the National Academies of Sciences, Engineering, and Medicine hosted a workshop in March 2016. Participants at the workshop explored the current landscape of genomics-enabled drug discovery activities in industry, academia, and government; examined enabling partnerships and business models; and considered gaps and best practices for collecting population data for the purpose of improving the drug discovery process. This publication summarizes the presentations and discussions from the workshop. Table of Contents Front Matter 1 Introduction and Themes of the Workshop 2 Maximizing Discovery Capabilities Through Cohort Design 3 Discovery Activities Related to Genetic Bioresources 4 Business Models That Support Bioresource Discovery and Collaboration 5 Potential Next Steps in Using Genomics to Advance Drug Discovery References Appendix A: Workshop Agenda Appendix B: Speaker Biographical Sketches Appendix C: Statement of Task Appendix D: Registered Attendees

The field of endeavors known as "regulatory science" has grown out of the need to link and integrate knowledge within and among basic science research, clinical research, clinical medicine, and other specific scientific disciplines whose focus, aggregation, and ultimate implementation could inform biomedical product development and regulatory decision making. Substantial efforts have been devoted to defining regulatory science and communicating its value and role across the scientific and regulatory ecosystems. Investments are also being made in technology infrastructure, regulatory systems, and workforce development to support and advance this burgeoning discipline. In October 2015, the National Academies of Sciences, Engineering, and Medicine held a public workshop to facilitate dialogue among stakeholders about the current state and scope of regulatory science, opportunities to address barriers to the discipline's success, and avenues for fostering collaboration across sectors. Participants explored key needs for strengthening the discipline of regulatory science, including considering what are the core components of regulatory science infrastructure to foster innovation in medical product development. This report summarizes the presentations and discussions from the workshop. Table of Contents Front Matter 1 Introduction 2 Characterizing the Regulatory Science Landscape 3 Regulatory Science Applications: Using Case Studies to Focus on Approaches to Advance the Discipline 4 Regulatory Science Infrastructure and Workforce 5 Challenges and Opportunities in Regulatory Science Appendix A: Bibliography Appendix B: Workshop Agenda Appendix C: Participant Biographies

Randomized controlled trials (RCTs) have traditionally served as the gold standard for generating evidence about medical interventions. However, RCTs have inherent limitations and may not reflect the use of medical products in the real world. Additionally, RCTs are expensive, time consuming, and cannot answer all questions about a product or intervention. Evidence generated from real-world use, such as real-world evidence (RWE) may provide valuable information, alongside RCTs, to inform medical product decision making. To explore the potential for using RWE in medical product decision making, the National Academies of Sciences, Engineering, and Medicine planned a three-part workshop series. The series was designed to examine the current system of evidence generation and its limitations, to identify when and why RWE may be an appropriate type of evidence on which to base decisions, to learn from successful initiatives that have incorporated RWE, and to describe barriers that prevent RWE from being used to its full potential. This publication summarizes the discussions from the entire workshop series. Table of Contents Front Matter 1 Introduction 2 Perspectives on Real-World Evidence 3 Learning from Success 4 Barriers and Disincentives to the Use of Real-World Evidence and Real-World Data 5 Getting Unstuck: Mythbusting the Current System 6 When Is a Real-World Data Element Fit for Assessment of Eligibility, Treatment Exposure, or Outcomes? 7 How Tightly Should Investigators Attempt to Control or Restrict Treatment Quality in a Pragmatic or Real-World Trial? 8 Obscuring Intervention Allocation in Trials to Generate Real-World Evidence: Why, Who, and How? 9 Gaining Confidence in Observational Comparisons 10 Looking Ahead References Appendix A: Related Resources Appendix B: Workshop One Agenda Appendix C: Workshop Two Agenda Appendix D: Workshop Three Agenda