A Bibliometric Measure of Translational Science

Translation in action: Influence, collaboration, and evolution of COVID-19 research with Clinical and Translational Science Awards consortium support

The National Institutes of Health (NIH)'s Clinical and Translational Science Awards (CTSA) consortium aims to accelerate translational processes that move discoveries from bench to bedside. The coronavirus disease 2019 (COVID-19) pandemic presented unmatched challenges and applications for CTSA hubs nationwide. Our study used bibliometrics to assess features of COVID-19 publications supported by the national CTSA program to characterize the consortium's response to the pandemic. Our goal was to understand relative scientific influence, collaboration across hubs, and trends in research emphasis over time. We identified publications from NIH's curated iSearch COVID-19 Publication Portfolio from February 2020 to February 2023; 3234 peer-reviewed articles relevant to COVID-19 cited a CTSA grant. All 66 CTSA hubs were represented, with large-size and longstanding hubs contributing more publications. Most publications cited UL1 grants, 457 cited KL2/TL1 training grants, and 164 cited multiple hub grants. Compared to a random sample of non-CTSA-supported COVID-19 publications, the CTSA portfolio exhibited greater clinical relevance, more human research, and higher altmetric and citation influence. Results were similar for multi-hub publications involving networked initiatives like multi-site clinical trials or the National COVID-19 Cohort Collaborative. Shifts from molecular/cellular-oriented research toward human-oriented research over time were evident, demonstrating translation in action. Results illuminate how the CTSA consortium confronted the pandemic through high-quality projects oriented toward human research, working across hubs on high-value collaborations, advancing along the translational spectrum over time. Findings validate CTSA hubs as critical support structures during health emergencies.

Distinguishing between translational science and translational research in CTSA pilot studies: A collaborative project across 12 CTSA hubs

Introduction

The institutions (i.e., hubs) making up the National Institutes of Health (NIH)-funded network of Clinical and Translational Science Awards (CTSAs) share a mission to turn observations into interventions to improve public health. Recently, the focus of the CTSAs has turned increasingly from translational research (TR) to translational science (TS). The current NIH Funding Opportunity Announcement (PAR-21-293) for CTSAs stipulates that pilot studies funded through the CTSAs must be "focused on understanding a scientific or operational principle underlying a step of the translational process with the goal of developing generalizable solutions to accelerate translational research." This new directive places Pilot Program administrators in the position of arbiters with the task of distinguishing between TR and TS projects. The purpose of this study was to explore the utility of a set of TS principles set forth by NCATS for distinguishing between TR and TS.

Methods

Twelve CTSA hubs collaborated to generate a list of Translational Science Principles questions. Twenty-nine Pilot Program administrators used these questions to evaluate 26 CTSA-funded pilot studies.

Results

Factor analysis yielded three factors: Generalizability/Efficiency, Disruptive Innovation, and Team Science. The Generalizability/Efficiency factor explained the largest amount of variance in the questions and was significantly able to distinguish between projects that were verified as TS or TR (t = 6.92, p < .001) by an expert panel.

Conclusions

The seven questions in this factor may be useful for informing deliberations regarding whether a study addresses a question that aligns with NCATS' vision of TS.

Exploring the clinical translation intensity of papers published by the world's top scientists in basic medicine

The extent to which basic medical research is translated into clinical practice is a topic of interest to all stakeholders. In this study, we assessed the clinical translation intensity of papers published by scientists who have made outstanding contributions to the field of basic medicine (Lasker Prize winners for Basic Medical Research). Approximate Potential for Translation (APT), Translational science scores (TS), and Citations by clinical research (Cited by Clin.) were analyzed as dependent variables. A traditional citation indicator was used as a reference (relative citation ratio, RCR). In order to examine the correlation between these different indicators and the characteristics of the paper, the author, and the institution. we used nonparametric tests, Spearman correlations, ordinal least squares regressions (OLS), quantile regressions, and zero-inflated negative binomial regression methods. We found that among the basic medical research papers published by Lasker Basic Medicine Award winners, (1) 20% are cited by clinical research; 11.6% of the papers were more valuable for clinical research than basic research; 12.8% have a probability of more than 50% to be cited in future clinical studies; (2) Spearman correlations were conducted among APT, TS, Cited by Clin., RCR, and all of the other continuous variables. There is a significant, positive, low to moderate correlation between APT, TS, and Cited by Clin (APT and TS: r = 0.549, p < 0.01; APT and Cited by Clin: r = 0.530, p < 0.01; TS and Cited by Clin: r = 0.383, p < 0.01). However, the relationship between RCR and the three indicators of clinical translation intensity was not consistent. APT was positively correlated with RCR (r = 0.553, p < 0.01). Cited by Clin. is weakly positively correlated with RCR (r = 0.381, p < 0.01). There is almost no correlation between TS and RCR (r = 0.184, p < 0.01). (3) Publication age, primary research paper, multidisciplinary science, number of disciplines, authors, institutions, funded projects, references, length of the title, length of paper, physical age, gender, nationality, institutional type, Nobel Prize have a significant relationship with 1 to 3 types of clinical translation intensity measures. In a sample of basic medical research papers published by the world's top scientists in basic medicine, we came to the following conclusions: the three indicators, APT, TS and Cited by Clin., measured the clinical translation intensity of the papers from different perspectives. They are both related to each other and have their own characteristics. In a sample of basic medical research papers published by the world's top scientists in basic medicine, characteristics at the paper, winner, and institution level significantly correlated with the measures of clinical translation intensity. Gender effect on the clinical translation intensity of papers was confirmed. Traditional citation-based indicators and translational-focused indicators measure academic impact and clinical impact respectively. There is a certain degree of disconnect between them. Two types of indicators should be used in combination in future assessments of basic medical research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11192-023-04634-4.

The rocky road to translational science: An analysis of Clinical and Translational Science Awards

Studies point out that the productivity decline in biomedicine is in significant part due to difficulties in translating basic science into clinical application. To promote translational research, the US NIH launched the Clinical and Translational Science Awards (CTSA) program in 2006. Prior evaluations of the CTSA program often assumed that the key to translation is inter-organizational collaboration or multidisciplinarity; hence, changes in either of these were measured as evidence of translational science. However, using novel measures of translational science, this study examines the relationship between CTSAs and translational science per se. We define ‘translational science’ as basic science that has translational features, and we employ two distinct, complementary measures of translational science based on publication data. Using 115 Carnegie R1 universities and their translational science publications, we find that receiving a CTSA does not obviously cause receiving institutions to conduct more translational science. Furthermore, our Principal Investigator-level analysis shows that those who received direct support from the CTSA program had already generated more translational science than others and that their research behavior did not change significantly after receiving a CTSA. Future evaluation research can adopt our novel measures of translational science and evaluation research design in the assessment of translational research activities. Finally, we conclude with a discussion of the implications of our findings for science governance.

Tracking biomedical articles along the translational continuum: a measure based on biomedical knowledge representation

Keeping track of translational research is essential to evaluating the performance of programs on translational medicine. Despite several indicators in previous studies, a consensus measure is still needed to represent the translational features of biomedical research at the article level. In this study, we first trained semantic representations of biomedical entities and documents (i.e., bio-entity2vec and bio-doc2vec) based on over 30 million PubMed articles. With these vectors, we then developed a new measure called Translational Progression (TP) for tracking biomedical articles along the translational continuum. We validated the effectiveness of TP from two perspectives (Clinical trial phase identification and ACH classification), which showed excellent consistency between TP and other indicators. Meanwhile, TP has several advantages. First, it can track the degree of translation of biomedical research dynamically and in real-time. Second, it is straightforward to interpret and operationalize. Third, it doesn't require labor-intensive MeSH labeling and it is suitable for big scholarly data as well as papers that are not indexed in PubMed. In addition, we examined the translational progressions of biomedical research from three dimensions (including overall distribution, time, and research topic), which revealed three significant findings. The proposed measure in this study could be used by policymakers to monitor biomedical research with high translational potential in real-time and make better decisions. It can also be adopted and improved for other domains, such as physics or computer science, to assess the application value of scientific discoveries.

Translational Research in Audiology: Presence in the Literature

Translational research is a process that focuses on advancing basic research-based clinical solutions and is characterized by a structured process accelerating the implementation of scientific discoveries in healthcare. Translational research originated in oncology but has spread to other disciplines in recent decades. A translational project may refer to pharmacological research, the development of non-pharmacological therapies, or to disease monitoring processes. Its stages are divided into basic research focused on the clinical problem (T0), testing the developed means in humans (T1), conducting trials with patients (T2), implementation and dissemination of successful approaches (T3), and improving community health (T4). Many audiological studies are translational in nature. Accordingly, this scoping review aimed to evaluate the use of the terms "translational audiology" and "translational research in audiology" in the literature and examine the goals of the identified studies. PubMed and Web of Science search identified only two publications meeting the search criteria. We conclude that identifying translational audiological studies in the literature may be hampered by the lack of use of the terms "translational audiology" or "translational research". We suggest using these terms when describing translational work in audiology, with a view to facilitating the identification of this type of research and credit it appropriately.

Translational research: from basic research to regional biomedical entrepreneurship

This paper examines the effect of translational research on knowledge production and biomedical entrepreneurship across U.S. regions. Researchers have earlier investigated the outputs of translational research by focusing on academic publications. Little attention has been paid to linking translational research to biomedical entrepreneurship. We construct an analytical model based on the knowledge spillover theory of entrepreneurship and the entrepreneurial ecosystem approach to examine the relationship between translational research, biomedical patents, clinical trials, and biomedical entrepreneurship. We test the model across 381 U.S. metropolitan statistical areas using 10 years of panel data related to the NIH Clinical and Translational Science Awards (CTSA) program. CTSA appears to increase the number of biomedical patents and biomedical entrepreneurship as proxied by the NIH Small Business Innovation Research (SBIR) grants. However, the magnitudes of the effects are relatively small. Path analysis shows that the effect of translational research on regional biomedical entrepreneurship is not strongly conveyed through biomedical patents or clinical trials.

Methods for identifying biomedical translation: a systematic review

Translational medicine is an important area of biomedicine, and has significantly facilitated the development of biomedical research. Despite its relevance, there is no consensus on how to evaluate its progress and impact. A systematic review was carried out to identify all the methods to evaluate translational research. Seven methods were found according to the established criteria to analyze their characteristics, advantages, and limitations. They allow us to perform this type of evaluation in different ways. No relevant advantages were found between them; each one presented its specific limitations that need to be considered. Nevertheless, the Triangle of Biomedicine could be considered the most relevant method, concerning the time since its publication and usefulness. In conclusion, there is still a lack of a gold-standard method for evaluating biomedical translational research.

Research Characteristics on Cyanotoxins in Inland Water: Insights from Bibliometrics

Eutrophication is a long-standing ecological and environmental problem, and the severity of harmful algal blooms continues to increase, causing large economic losses globally. One of the most important hazards created by harmful algal blooms is the production of cyanotoxins. This study aimed to analyze the characteristics and development trends of cyanotoxin research through bibliometric analysis. A total of 3265 publications from 1990 to 2020 on cyanotoxins were retrieved from the Science Citation Index (SCI) Expanded database, Web of Science. Over the past 30 years, most research has been concentrated in China (21.4%) and the USA (21.3%). Throughout the study period, microcystin was the focus of the research, accounting for 86% of the total number of publications. A word frequency analysis revealed that as people became more aware of drinking water safety and the construction of large-scale water conservation facilities, “reservoirs” and “rivers” became hot words for researchers, while “lakes” have always been important research objects. Nonmetric multidimensional scaling (NMDS) analysis of studies from the five countries with the largest numbers of publications showed that Chinese researchers typically associate eutrophication with Microcystis, while research subjects in other countries are more extensive and balanced. The development of cyanotoxin research around the world is not even, and we need to push for more research on major lakes that are outside of North America, Europe and China.

A large National Institute for Health Research (NIHR) Biomedical Research Centre facilitates impactful cross-disciplinary and collaborative translational research publications and research collaboration networks: a bibliometric evaluation study

Background

The evaluation of translational health research is important for various reasons such as the research impact assessment, research funding allocation, accountability, and strategic research policy formulation. The purpose of this study was to evaluate the research productivity, strength and diversity of research collaboration networks and impact of research supported by a large biomedical research centre in the United Kingdom (UK).

Methods

Bibliometric analysis of research publications by translational researchers affiliated with the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) from April 2012 to March 2017.

Results

Analysis included 2377 translational research publications that were published during the second 5-year funding period of the NIHR Oxford BRC. Author details were available for 99.75% of the publications with DOIs (2359 of 2365 with DOIs), and the number of authors per publication was median 9 (mean  = 18.03, SD  = 3.63, maximum  = 2467 authors). Author lists also contained many consortia, groups, committees, and teams (n  = 165 in total), with 1238 additional contributors, where membership was reported. The BRC co-authorship i.e., research collaboration network for these publications involved 20,229 nodes (authors, of which 1606 nodes had Oxford affiliations), and approximately 4.3 million edges (authorship linkages). Articles with a valid DOIs (2365 of 2377, 99.5%) were collectively cited more than 155,000 times and the average Field Citation Ratio was median 6.75 (geometric mean  = 7.12) while the average Relative Citation Ratio was median 1.50 (geometric mean  = 1.83) for the analysed publications.

Conclusions

The NIHR Oxford BRC generated substantial translational research publications and facilitated a huge collaborative network of translational researchers working in complex structures and consortia, which shows success across the whole of this BRC funding period. Further research involving continued uptake of unique persistent identifiers and the tracking of other research outputs such as clinical innovations and patents would allow a more detailed understanding of large research enterprises such as NIHR BRCs in the UK.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03149-x.