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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
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