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Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision medicine have recently paved the way for the development of digital pathology-based approaches for quantitative pathologic assessments, namely whole slide imaging and artificial intelligence (AI)–based solutions, allowing us to explore and extract information beyond human visual perception. Within the field of immuno-oncology, the application of such methodologies in drug development and translational research have created invaluable opportunities for deciphering complex pathophysiology and the discovery of novel biomarkers and drug targets. With an increasing number of treatment options available for any given disease, practitioners face the growing challenge of selecting the most appropriate treatment for each patient. The ever-increasing utilization of AI-based approaches substantially expands our understanding of the tumor microenvironment, with digital approaches to patient stratification and selection for diagnostic assays supporting the identification of the optimal treatment regimen based on patient profiles. This review provides an overview of the opportunities and limitations around implementing AI-based methods in biomarker discovery and patient selection and discusses how advances in digital pathology and AI should be considered in the current landscape of translational medicine, touching on challenges this technology may face if adopted in clinical settings. The traditional role of pathologists in delivering accurate diagnoses or assessing biomarkers for companion diagnostics may be enhanced in precision, reproducibility, and scale by AI-powered analysis tools.

The mission of translational science is to bring predictivity and efficiency to the development and dissemination of interventions that improve human health. Ten years ago this year, the National Center for Advancing Translational Sciences was founded to embody, conduct, and support this new discipline. The Center’s first decade has brought substantial progress across a broad range of translational areas, from diagnostic and drug development to clinical trials to implementation science to education. The origins of the translational science and advances to this point are reviewed here and allow the establishment of an ambitious future research agenda for the field.

Translating Expertise: The Librarian's Role in Translational Research provides background and context on the CTSA program. Case studies detail routes to librarian involvement in translational research, including collection development, relationships with researchers and administrators, instruction and training, data management, and team science.

A broad interest in finding purpose is understandable, as having purpose is situated in notions of “the good life” and is linked in studies to greater health and wellbeing. Yet, the empirical basis for whether purpose is truly findable is inadequate, lacking guidance from theories predicting behavioral capacities that drive its acquisition. If feeling purposeful is as favorable as studies suggest, then more transparent and precise explanations of how it is derived are needed; otherwise, the field risks illuminating this resource while leaving the pathways to it unlit. Here, I call for a translational science of purpose acquisition directed at gathering and disseminating evidence of the processes by which this sense can be cultivated. I introduce a minimal viable framework for integrating basic and applied investigations into purpose by bridging laboratory research, intervention and implementation efforts, community-engaged practices, and policies to accelerate testing and strategies for enhancing this salubrious sense in people’s lives.

Integrates the various disciplines of the science of health disparities in one comprehensive volume The Science of Health Disparities Research is an indispensable source of up-to-date information on clinical and translational health disparities science. Building upon the advances in health disparities research over the past decade, this authoritative volume informs policies and practices addressing the diseases, disorders, and gaps in health outcomes that are more prevalent in minority populations and socially disadvantaged communities. Contributions by recognized scholars and leaders in the field—featuring contemporary research, conceptual models, and a broad range of scientific perspectives—provide an interdisciplinary approach to reducing inequalities in population health, encouraging community engagement in the research process, and promoting social justice. In-depth chapters help readers better understand the specifics of minority health and health disparities while demonstrating the importance of advancing theory, refining measurement, improving investigative methods, and diversifying scientific research. In 26 chapters, the book examines topics including the etiology of health disparities research, the determinants of population health, research ethics, and research in African American, Asians, Latino, American Indian, and other vulnerable populations. Providing a unified framework on the principles and applications of the science of health disparities research, this important volume: * Defines the field of health disparities science and suggests new directions in scholarship and research * Explains basic definitions, principles, and concepts for identifying, understanding and addressing health disparities * Provides guidance on both conducting health disparities research and translating the results * Examines how social, historical and contemporary injustices may influence the health of racial and ethnic minorities * Illustrates the increasing national and global importance of addressing health disparities * Discusses population health training, capacity-building, and the transdisciplinary tools needed to advance health equity A significant contribution to the field, The Science of Health Disparities Research is an essential resource for students and basic and clinical researchers in genetics, population genetics, and public health, health care policymakers, and epidemiologists, medical students, and clinicians, particularly those working with minority, vulnerable, or underserved populations.

Drug repurposing is a strategy for identifying new uses of approved or investigational drugs that are outside the scope of the original medical indication. Even though many repurposed drugs have been found serendipitously in the past, the increasing availability of large volumes of biomedical data has enabled more systemic, data-driven approaches for drug candidate identification. At National Center of Advancing Translational Sciences (NCATS), we invent new methods to generate new data and information publicly available to spur innovation and scientific discovery. In this study, we aimed to explore and demonstrate biomedical data generated and collected via two NCATS research programs, the Toxicology in the 21st Century program (Tox21) and the Biomedical Data Translator (Translator) for the application of drug repurposing. These two programs provide complementary types of biomedical data from uncovering underlying biological mechanisms with bioassay screening data from Tox21 for chemical clustering, to enrich clustered chemicals with scientific evidence mined from the Translator towards drug repurposing. 129 chemical clusters have been generated and three of them have been further investigated for drug repurposing candidate identification, which is detailed as case studies.

Clinical and translational science needs to address roadblocks to the translational processes. We conducted a survey at two institutions, a private medical school and a large public university, to understand the frequency and distribution of barriers and roadblocks to research. We reviewed the literature to compile a pool of barriers and roadblocks and convened a panel of relevant stakeholders to develop a 20‐item questionnaire. Survey respondents were asked to select and prioritize the five leading clinical and translational roadblocks, provide information regarding their academic degrees and rank/position, complete open‐ended items regarding their areas of research, and optionally add additional remarks in a comment box. The survey was disseminated in August 2022 to faculty and staff with active research protocols at Baylor College of Medicine and the University of Houston. In total, 227 respondents completed the survey. Their disciplines were basic science (29.5%), translational research (52.9%), clinical research (55.5%), community‐engaged research (9.7%), and educational research (9.7%). Respondents identified (1) lack of access to trained research coordinators, (2) lack of understanding about different resources that facilitate research, (3) complex regulatory environment and delays, (4) fragmented infrastructure for administrative and fiscal processes, and (5) inadequate funding for pilot projects to foster new research. Other roadblocks included lack of established community stakeholder partnerships, inadequate access to medical record data, and limited biostatistical support. We identified leading roadblocks to research from the perspectives of scientists and staff conducting clinical and translational research. Operational innovations addressing these roadblocks can accelerate the pace of translation.

The main histopathology of Alzheimer’s disease (AD) is featured by the extracellular accumulation of amyloid-β (Aβ) plaques and intracellular tau neurofibrillary tangles (NFT) in the brain, which is likely to result from co-pathogenic interactions among multiple factors, e.g., aging or genes. The link between defective autophagy/mitophagy and AD pathologies is still under investigation and not fully established. In this review, we consider how AD is associated with impaired autophagy and mitophagy, and how these impact pathological hallmarks as well as the potential mechanisms. This complicated interplay between autophagy or mitophagy and histopathology in AD suggests that targeting autophagy or mitophagy probably is a promising anti-AD drug candidate. Finally, we review the implications of some new insights for induction of autophagy or mitophagy as the new therapeutic way that targets processes upstream of both NFT and Aβ plaques, and hence stops the neurodegenerative course in AD.