Title of proposed idea: Regulatory Science Initiative  

Nominator: NIH Institutes/Centers

 Major obstacle/challenge to overcome: The rapid pace of scientific discovery coupled with development of new technologies presents a challenge to researchers, clinical investigators, and regulators as they work to translate basic scientific advances into approved medical products.  Basic and preclinical research has been performed in large part independent of regulatory issues. In addition, it is clear that novel technologies and approaches to medical research are outpacing the ability of our regulatory system to incorporate them into current review practices and guidelines. To overcome these obstacles, NIH should support strategic initiatives that are essential to the translation of NIH funded discoveries into diagnostic and therapeutics.

Emerging scientific opportunity ripe for Common Fund investment:   An investment in Regulatory Science will benefit all stakeholders by helping to advance and incorporate cutting-edge science into regulatory decision making and helping to develop improved tools, standards and approaches for assessing the safety, efficacy, quality and performance of medical products. Major advances in genomics and genomics-based medicine are also creating potential scenarios in the clinical setting that are relatively new to the FDA regulatory process. Moreover, the unprecedented partnership between the NIH and FDA through the Joint Leadership Council provides an extraordinary opportunity to coordinate therapy development efforts, including regulatory decision-making guidelines, between the two agencies. 

Common Fund investment that could accelerate scientific progress in this field: A number of scientific opportunities are ripe for investment in the area of Regulatory science and across the therapeutics development pipeline. For instance:

• Advances stemming from next generation sequencing technologies to help set the stage for personalized medicine, and other novel, genomics-based approaches to drug development, and treatments, such gene-editing, regulatory RNAs, gene –silencing or transcriptional activation
• Nanotechnology, microfluidics, and stem cell technologies to alter the way experimental agents are tested for safety and efficacy, and ultimately delivered to patients as therapies
• New approaches to predictive toxicology including high-throughput screening strategies/models, new in-silico approaches and computer-simulation models
• Development of bioinformatics tools and approaches for data mining and meta-analyses on safety and efficacy that capitalizes on the increasing volumes of clinical and medical product-related information in data repositories,
• Novel approaches of conducting clinical trials for rare and neglected diseases

Potential impact of Common Fund investment: Pre-clinical and clinical investigators, and other researchers who are engaged in the diagnostics and therapeutics development industries will benefit from having a more rapid integration of evidence-based knowledge into a regulatory framework, thereby quickening the pace at which basic science advances can move into the therapy development realm. For instance, in the area of stem-cell technologies, the NIH and FDA are working together to identify and define markers and characteristics of “stemness”, thus providing standards that the entire field can use for purposes of comparing studies and preparing for regulatory considerations.  The possibility of individualized, autologous utility of stem cell-derived therapeutics, organs, tissues, and other biomedical products are fast becoming a reality. Other emerging areas in regulatory science will advance, such as nanomedicine, personalized medicine, efficient and expeditious clinical trial designs, predictive toxicology, and biomimetic models that are able to simulate human conditions and better predict safety and efficacy.  The NIH-FDA joint efforts in these areas would help to pave a clearer and more transparent scientific and regulatory path for the scientific community that will impact therapeutics product development and clinical practice.

Title of proposed idea: Meeting the Challenge of Big Data in Biomedical and Translational Science (see “Cross-Cutting Issues in Computation and Informatics” in Innovation Brainstorm ideas)     

Nominator: NIH Institutes/Centers

 Major obstacle/challenge to overcome: The complexity of human biology in health and illness is increasingly being taken into account by research design, with individual studies collecting genomic, image, biosensor, and clinical data, along with information about sociocultural and environmental factors.  And, these large amounts of diverse data are almost always collected in digital form.  Thus, modern biomedicine is confronted at once by great opportunity and great challenge.  The opportunity presented by collecting multiple measures is to understand disease and gain insight to its prevention, treatment and cure, from a broad, encompassing perspective more likely to bear fruit than from studies limited to a small number of measures.  The opportunity presented by collecting digital data is the ability to share, compare, reaggregate, reuse, and integrate data, as well as to use these data for models and simulations in ways that have been heretofore impossible.  The challenge, however, is to be able to organize, present, analyze and manage these data to fully realize such opportunities.  The challenge is one of “big data,” where handling and working with complex data at large scale is both quantitatively and qualitatively different than at a smaller scale. 

Emerging scientific opportunity ripe for Common Fund investment: As the translation of biomedical research results into improved human health accelerates, and as the diversity of clinically-relevant measures grows to include those of basic biology, new approaches to big data, drawing from information science, informatics, computer science, and computational biology, must be developed and used to maximize the return on the research investment.  Advancing the science of big data and developing associated tools requires test-beds to stimulate and shape conceptual progress and its reduction to practice.  While this has happened in other fields, such as astronomy (which has benefited greatly as a consequence), a concerted effort to move these ideas and tools forward has not yet been made in translational biomedicine.  The number, size, and scope of biomedical and translational research projects collecting large amounts of different types of data is now sufficient to offer numerous test-beds that would be demanding enough to move forward the science of big data and developing a big data research environment.  The time is right for seizing the opportunity these test beds offer to drive the development of big data approaches in the context and service of translational science.

Common Fund investment that could accelerate scientific progress in this field: This initiative would support the research and development of a big data research environment for each of several sites hosting translational science projects, collectively spanning analyses that might include genomic, image, sensor, clinical, sociocultural, environmental, and electronic medical record data.  Some examples of elements likely to be developed under a given award include, but are not limited to:

• Scientific foundation – e.g., meaningful analysis of multiple diverse data sets, scalable algorithms
• Informational foundation  - e.g., identification/development of vocabularies, ontologies, metadata
• Technology and technical infrastructure - e.g., to move personal biosensor data to the environment
• Approaches for management of the data – e.g., semi-automated annotation, data compression and decompression, crawlers to associate particular data points
• Approaches for the use of the data – e.g., a synthesis platform that could be used to conduct “preliminary clinical trials” in silico to be used with adaptive trial methods, methods to evaluate the contribution of multidimensional measures to particular clinical and health outcomes
• Approaches, technical and cultural, to share and compare data across research groups
• Training in the science, development, and use of big data and its technology

Awards would be made to support such integrated efforts to advance the science of big data and build a big data research environment associated with sites at which large clinical research projects and clinical trials are typically ongoing.   While this initiative could be implemented in any of a number of ways, one possible implementation would be the use of cooperative agreements.  The methods, results, progress, setbacks, and lessons learned would be shared among all of these cooperative agreements in an ongoing way so as to allow for an adaptive project process. 

Potential impact of Common Fund investment: Informatics approaches currently used have largely been developed in the context of more limited data types and amounts than large translational science projects are now producing.  A big data research environment built around, and assuming, such large, multidimensional studies producing gargantuan amounts of complex data would represent not only a quantitatively different understanding, but a qualitatively different understanding of the basic biology of health and disease.  This new understanding, based on an integrative perspective from omics to the environment,  would, in turn, provide new insights to improve human health, as well as clinical and public health decision-making.

Title of proposed idea: Innovative Mobile and Wireless Technologies (mHealth) to Improve Health Research and Health Outcomes

Nominator: NIH Institutes/Centers

 Major obstacle/challenge to overcome:

 Mobile and wireless health (mHealth) technologies have developed at an exponential pace in recent years; however, the integration and translation of these cutting-edge technologies into rigorously evaluated health research and healthcare tools have lagged behind.  For example, low-cost, real-time devices to assess disease, movement, images, behavior, social interactions, environmental toxins, hormones, and other physiological variables, have made remarkable advances in the last decade because of increased computational sophistication, as well as reductions in size and power requirements. The basic engineering and computer science knowledge exists to develop technologies that will alter the collection of health-related data for basic and translational research, clinical practice, healthcare delivery, and public health in ways that were not imaginable a decade ago. Scientific investments are needed to translate this basic science into quality mobile and wireless health technologies that also leverage other rapidly advancing biomedical technologies. 

In fact, development of the mobile and wireless health technologies is currently progressing at a much faster pace than the science to evaluate their validity and efficacy.  Unnecessary devices will be created with little medical impact because they were developed without an empirical foundation and input from the health research community. Private sector technology companies, along with a limited amount of public funding from NSF and NIBIB, support the basic development of novel wireless and mobile technologies, but NIH provides limited support toward the translation of these basic technologies into quality wireless and mobile solutions to facilitate research and improve health. Once a technology is fully developed, various NIH institutes support rigorous evaluation, but there is insufficient funding for the period between basic technology development and evaluation; that is, the development, integration and validation of software and hardware required to develop these cutting-edge technologies into evaluable tools.

Moreover, these technologies, which promise to sense and assess physiology, disease, behavior, and environmental changes continuously and in real-time, will generate an avalanche of multi-faceted, longitudinal data.  The rich longitudinal datasets generated by these multiple inputs also require advanced analytics, akin to a high throughput approach to a continuous stream of data. These analytic tools and sophisticated visualization techniques will provide interpretable data for researchers and/or actionable data for healthcare providers and public health practitioners, as well as new approaches to efficient management of chronic disease.

Emerging scientific opportunity ripe for Common Fund investment:

 Mobile and wireless health (mHealth) is a nascent and rapidly growing field.  These technologies provide the potential to advance research, prevent disease, enhance diagnostics, improve treatment, reduce disparities, increase access to health services and lower healthcare costs in ways previously unimaginable.  Real-time, continuous biological, behavioral and environmental data collected by wireless and mobile technologies will improve our understanding of the etiology of health and disease, particularly when integrated with data from areas such as genomics, biomarkers, and electronic medical records.  These data are also essential for answering the difficult questions of gene-environment interplay in health and disease, adherence, and the developmental origins of adult disease, as well as informing the development of treatments and prevention programs that are preemptive, personalized and adaptive over time.  Further, these tools have the potential to transform clinical trials.  Remote monitoring and sensing can allow researchers to recruit and follow patients without the need or cost to transport them to a research or healthcare setting. This will increase participant access and decrease burden, while increasing sample representativeness and the quantity and quality of follow-up data, all at decreased cost. 

A major opportunity also arises from the potential of mobile and wireless health technologies  to continuously monitor chronic medical conditions around the world, as well as to implement disease management plans that capitalize on this expanded information. Chronic disease conditions have been recognized in the developed world as a major source of morbidity and mortality. Similarly, in the low- and middle-income countries (LMICs), chronic disease is increasingly being cited as an emerging problem and a major component of disease burden. A prospective in the NEJM (2007;356:209-211) cites that cardiovascular disease accounts for nearly 30% of all deaths worldwide and this percentage is similar in LMICs to the global average. A fundamental characteristic of most chronic disease is that the medical profession manages the disease rather than ‘cures‘  it. The hypothesis that better monitoring will lead to better management, better outcomes and reduced disease burden has yet to be tested.

The need for rigorous research that examines the potential, as well as the challenges, of harnessing mobile technologies to improve health outcomes is critical to global health.  Given the high penetration of cell phones and related technologies in LMICs, as well as the lack of bandwidth in many parts of these countries, research investments could illuminate the potential of these technologies to serve as the underlying infrastructure for transmission of health information and data in low-resource settings.  For example, given the capacity for adaptive learning facilitated by these technologies and the potentially heightened level of empowerment experienced by users, research investments can inform how best to use mobile technologies to help educate and train the next generation of providers and patients in low-resource settings, as well as serve as a vehicle for behavior change across diseases and conditions.  Equally exciting is the potential for these technologies to provide low-cost alternatives to traditional imaging modalities for screening of chronic, non-communicable diseases, such as cancer and heart disease.   Therefore, in addition to the ways in which mobile and wireless technologies support research and health in the United States, numerous specific areas of global health research could benefit from increased and targeted NIH investment in this field. 

To ensure long-term impact of investments in mobile and wireless technologies and to improve health globally as well as domestically, NIH funding should be designed to ensure that both the technology developers and the researchers start with problems that demand solving, so that the field is needs-driven, rather than product-driven.  In addition, mobile and wireless technologies are part of an information and healthcare ecosystem in which systems must be able to communicate with each other; therefore, NIH can provide leadership to encourage and support the development of novel, interoperable solutions.  Furthermore, significant support for building research capacity in this field will help to ensure a pipeline of investigators both in the U.S. and abroad who have the skills and experience to advance the field forward as technologies and public health needs evolve.  

Computer scientists, engineers, and biomedical/behavioral researchers are beginning to collaborate, and transdisciplinary groups are forming, making this area ripe for Common Fund investment now.  In addition, the wide interest in this area provides an opportunity for potential federal (National Science Foundation, World Bank) and non-federal collaborations (e.g., Robert Wood Johnson Foundation, private technology and communication companies) that could augment Common Fund resources and increase the value of the initiative. In addition, NIH has an mHealth Scientific Interest Group that will ensure programmatic expertise across the Institutes and Centers. 

Common Fund investment that could accelerate scientific progress in this field:

With its potential for providing low-cost, high quality data to enhance health research and improve health outcomes around the world, mobile/wireless health is of growing interest to the NIH ICs, but no individual IC is able to foster the integrated development needed to move basic wireless/mobile technological development to evaluable solutions, especially since most of these technologies apply to multiple diseases and conditions.  This initiative provides the funding to develop and translate novel technologies from prototype components to integrated and validated tools to advance health research, diagnose and treat disease and promote health. 

Common Fund investment in this area would stimulate the required interdisciplinary efforts among computer scientists, engineers, and biomedical, behavioral, and social scientists to fill this translation, development, integration and validation gap. Funding would target four essential aims:

1.     Translation, development,  integration of interoperable and affordable mobile and wireless technology into novel scientifically-validated tools for use in research, healthcare or public health;

2.     Validation and implementation of existing wireless and mobile devices into ongoing clinical trials, especially those addressing treatment of chronic disease; and,

3.     Development of “high throughput” analytic techniques for complex, comprehensive, and multi-streamed data, as well as models of and data visualization to enhance the value of these data.

4.     Development of mobile health technologies that can address infectious and noncommunicable disease problems (obesity, cancer, diabetes, cardiac disease, etc.) around the world by facilitating disease prevention and behavior change.

Potential applicants would include technology developers, industry partners, health researchers and others in an iterative development process for which there is currently no model of public funding. Currently, mobile and wireless health research requires multiple grants targeting each step of development, causing delays and preventing research from keeping pace with technological change.  Partnerships with industry and other stakeholders will facilitate commercialization and sustained development. Further, to address global health challenges and to facilitate the exchange of information, collaborations between U.S. investigators and partners in low-resource settings (both globally and in the U.S.) would be encouraged.  This initiative would also develop a cadre of reviewers with experience evaluating grant applications that involve a combination of technical development aims and health outcome aims.  By providing models for how to move these basic technologies through integrated development and rigorous outcome evaluation, this effort could eventually be subsumed by technology companies and basic technology funders extending their reach into integrative development and by having NIH and other clinical research funders expand their interests into the integrated development required to prepare mobile and wireless applications for clinical evaluation.  

Potential impact of Common Fund investment:

One impact of Common Fund investment of mobile and wireless technologies would be to move this field from developing devices to developing solutions for chronic disease management or other conditions. One recent example of the potential (Lancet, 2011; 377:658-666) demonstrated that wireless pulmonary artery monitoring of individuals with chronic heart failure resulted in a 40% reduction in heart-failure related hospitalization over the six month follow-up period. The infrastructure developed could also have a significant impact on research on disease monitoring, treatment , and management.

Further, if this Common Fund program achieves its objectives, scientific and business models will be created for moving cutting-edge technologies much more quickly through integrated development to research evaluation.  Currently, many of the wireless and mobile technologies being evaluated with NIH support are considered old, if not obsolete, by the technology community.   As a result, the wireless and mobile technologies evaluated with NIH funding will be much more innovative and novel and the pipeline from basic technological development to health research evaluation will be accelerated and streamlined.  In addition, this initiative will support the development of the methods needed to analyze and present these complex data sets to enhance both health research, but also healthcare delivery and public health as these large, complex data streams are summarized into actionable health information.