Health technology assessment (HTA) can occur at different stages of a technology’s lifecycle. In the accompanying paper, Grutters and colleagues present a consensus definition of “early HTA” as a health technology assessment conducted to inform decisions about subsequent development, research, and/or investment by explicitly evaluating the potential value of a conceptual or actual health technology. Early HTA is particularly relevant to non-medicine technologies, which are often developed more iteratively than medicines. This article explores some of the ways in which early HTA is already being conducted on non-medicine technologies in the United Kingdom, as well as future perspectives and possible challenges in using early HTA.

The interaction of helminth infections with type 2 diabetes (T2D) has been a major area of research in the past few years. This paper, therefore, focuses on the systematic review of the effects of helminthic infections on metabolism and immune regulation related to T2D, with mechanisms through which both direct and indirect effects are mediated. Specifically, the possible therapeutic role of helminths in T2D management, probably mediated through the modulation of host metabolic pathways and immune responses, is of special interest. This paper discusses the current possibilities for translating helminth therapy from basic laboratory research to clinical application, as well as existing and future challenges. Although preliminary studies suggest the potential for helminth therapy for T2D patients, their safety and efficacy still need to be confirmed by larger-scale clinical studies.

Current evidence underscores a need to transform how we do clinical research, shifting from academic-driven priorities to co-led community partnership focused programs, accessible and relevant career pathway programs that expand opportunities for career development, and design of trainings and practices to develop cultural competence among research teams. Failures of equitable research translation contribute to health disparities. Drivers of this failed translation include lack of diversity in both researchers and participants, lack of alignment between research institutions and the communities they serve, and lack of attention to structural sources of inequity and drivers of mistrust for science and research. The Duke University Research Equity and Diversity Initiative (READI) is a program designed to better align clinical research programs with community health priorities through community engagement. Organized around three specific aims, READI-supported programs targeting increased workforce diversity, workforce training in community engagement and cultural competence, inclusive research engagement principles, and development of trustworthy partnerships.

Recent years have seen increasing focus, including by the National Institutes for Health (NIH), on developing the field of translational science (TS). TS focuses on improving the process of translational research (TR), including generating knowledge that can facilitate TR across specific diseases or translational stages. With TS as an emerging field, research organizations have an increasing need to understand how to develop capacity for and support the advancement of TS. To support such institutional and infrastructural change, this paper outlines a Translational Science Promotion and Research Capacity (T-SPARC) Framework. The T-SPARC Framework provides a foundation to 1) inform the development of TS-creating and science-supporting interventions and programs, and 2) examine the effectiveness of said interventions and programs. The framework outlines organizational levels that T-SPARC programs can target; mechanisms, or intervention activities, that can foster change; and outcomes, including specific attitudinal or behavioral changes, institutional changes, and domains on which TS changes can focus. T-SPARC’s capacity-building focus builds upon earlier efforts focused on conceptualizing and defining TS. T-SPARC supports movement towards TS goals of reducing longstanding challenges in the TR process, thus accelerating the health impact of TR, and ultimately improving health outcomes.

Actively engaging community health centers (CHCs) in research is necessary to ensure evidence-based practices are relevant to all communities and get us closer to closing the health equity gap. We report here on the Boston HealthNet Research Collaborative, a partnership between health centers, Boston HealthNet and the Boston University Clinical, and Translational Science Institute with the explicit goal of supporting research partnerships early in the planning phase of the study lifecycle. We used the principles of community engagement guided by a collective impact framework to codesign, pilot, and evaluate a process for facilitating research partnerships. Accomplishments in the first 2 years include a web-based Toolkit with a step-by-step guide and an active learning collaborative with health center representatives to support research capacity building. The process resulted in 81 new research project partnerships across 50 individual research projects. Most research partnership requests were made later in the research lifecycle, after the planning phase. Partnership acceptance was largely driven by the Collaborative’s pre-defined Guiding Principles and Rules of Engagement. These lessons drive an iterative process to improve the longitudinal relationship between our translational research program and our CHC partners.

Although early health technology assessment (HTA) is increasingly being used to guide and inform decisions on product development, a consensus definition is currently lacking. A working group under the HTA International Society was established to develop a consensus-based definition of early HTA. The working group developed a definition using an iterative process that comprised five stages of work and included a two-round Delphi survey with 133 respondents in the first and 99 respondents in the second round of the survey, with various backgrounds and levels of expertise. Following this process, the working group reached the first consensus-based definition of early HTA, which is an HTA conducted to inform decisions about subsequent development, research, and/or investment by explicitly evaluating the potential value of a conceptual or actual health technology. In total, 86 (87 percent) of the 99 panelists who participated in the second round of the Delphi survey either strongly agreed or agreed with this definition. This consensus definition represents an important milestone in early HTA. It will enhance the uniformity of terminology, increasing the visibility of research and policy in this field. We also hope that it will act as a catalyst sparkling further research and developments in this discipline.

To facilitate and sustain community-engaged research (CEnR) conducted by academic-community partnerships (ACPs), a Clinical Translational Science Award (CTSA)-funded Community Engagement Core (CEC) and Community Partner Council (CPC) co-created two innovative microgrant programs. The Community Health Grant (CHG) and the Partnership Development Grant (PDG) programs are designed to specifically fund ACPs conducting pilot programs aimed at improving health outcomes. Collectively, these programs have engaged 94 community partner organizations while impacting over 55,000 individuals and leveraging $1.2 million to fund over $10 million through other grants and awards. A cross-sectional survey of 57 CHG awardees demonstrated high overall satisfaction with the programs and indicated that participation addressed barriers to CEnR, such as building trust in research and improving partnership and program sustainability. The goal of this paper is to (1) describe the rationale and development of the CHG and PDG programs; (2) their feasibility, impact, and sustainability; and (3) lessons learned and best practices. Institutions seeking to implement similar programs should focus on integrating community partners throughout the design and review processes and prioritizing projects that align with specific, measurable goals.

Adrenal vein sampling (AVS) is a complicated procedure requiring clinical expertise, collaboration, and patient involvement to ensure it occurs successfully. Implementation science offers unique insights into the barriers and enablers of service delivery of AVS. The primary aim of this review was to identify implementation components as described within clinical studies, that contribute to a successful AVS procedure. The secondary aim was to inform practice considerations to support the scale-up of AVS. A scoping review of clinical papers that discussed factors contributing to effective AVS implementation was included. A phased approach was employed to extract implementation science data from clinical studies. Implementation strategies were named and defined, allowing for implementation learnings to be synthesized, in the absence of dedicated research examining implementation process and findings only. Ten implementation components reported as contributing to a successful AVS procedure were identified. These components were categorized according to actions required pre-AVS, during AVS, and post-AVS. Using an implementation science approach, the findings of this review and analysis provide practical considerations to facilitate AVS service delivery design. Extracting implementation science information from clinical research has provided a mechanism that accelerates the translation of evidence into practice where implementation research is not yet available.

This paper explores the development of the Dissemination and Implementation Science Collaborative (DISC) at the Medical University of South Carolina, established through the Clinical and Translational Science Award program. DISC aims to accelerate clinical and translational science by providing training, mentorship, and collaboration opportunities in dissemination and implementation (D&I) science. Through DISC, investigators, trainees, and community partners are equipped with the knowledge and skills to conduct D&I research and translate findings into practice, particularly in South Carolina’s public health and healthcare landscape. We describe efforts to achieve the major overarching aims of DISC, which include conducting scientific workforce training, providing mentorship and consultation, and advancing methods and processes for D&I research. By sharing DISC experiences, successes, and challenges, this paper aims to support the growth of D&I research and capacity-building programs, fostering collaboration and shared resources in the field.

Organizations supporting translational research and translational science, including Clinical and Translational Science Award (CTSA) hubs, provide a diverse and often changing array of resources, support, and services to a myriad of researchers and research efforts. While a wide-ranging scope of programs is essential to the advancement of translational research and science, it also complicates a systematic and unified process for tracking activities, studying research processes, and examining impact. To overcome these challenges, the Duke University School of Medicine’s CTSA hub created a data platform, Translational Research Accomplishment Cataloguer (TRACER), that provides capacity to enhance strategic decision-making, impact assessment, and equitable resource distribution. This article reviews TRACER development processes, provides an overview of the TRACER platform, addresses challenges in the development process, and describes avenues for addressing or overcoming these challenges. TRACER development allowed our hub to conceptually identify key processes and goals within programs and linkages between programs, and it sets the stage for advancing evidence-based improvement across our hub. This platform development provides key insight into facilitators that can inform other initiatives seeking to collect and align organizational data for strategic decision-making and impact assessment. TRACER or similar platforms are additionally well positioned to advance the study of translational science.

The Stanford Population Health Sciences Data Ecosystem was created to facilitate the use of large datasets containing health records from hundreds of millions of individuals. This necessitated technical solutions optimized for an academic medical center to manage and share high-risk data at scale. Through collaboration with internal and external partners, we have built a Data Ecosystem to host, curate, and share data with hundreds of users in a secure and compliant manner. This platform has enabled us to host unique data assets and serve the needs of researchers across Stanford University, and the technology and approach were designed to be replicable and portable to other institutions. We have found, however, that though these technological advances are necessary, they are not sufficient. Challenges around making data Findable, Accessible, Interoperable, and Reusable remain. Our experience has demonstrated that there is a high demand for access to real-world data, and that if the appropriate tools and structures are in place, translational research can be advanced considerably. Together, technological solutions, management structures, and education to support researcher, data science, and community collaborations offer more impactful processes over the long-term for supporting translational research with real-world data.

The survey investigates COVID-19 information source trust levels and Vietnamese Americans’ willingness to participate in clinical trials. An analysis of 212 completed surveys revealed that trust in coronavirus disease 2019 (COVID-19) clinical trial information from university hospitals and drug companies was associated with willingness to participate in clinical trials. Trust in COVID-19 information from federal governments and state governments was also associated with willingness to participate in clinical trials. However, trust in local health facilities was linked to trial participation reluctance. The results suggest that Vietnamese Americans’ participation in clinical trials can be increased by identifying and using trusted sources of information.