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BackgroundThe issue of endocrine disrupting chemicals (EDCs) is receiving wide attention from both the scientific and regulatory communities. Recent analyses of the EDC literature have been criticized for failing to use transparent and objective approaches to draw conclusions about the strength of evidence linking EDC exposures to adverse health or environmental outcomes. Systematic review methodologies are ideal for addressing this issue as they provide transparent and consistent approaches to study selection and evaluation. Objective methods are needed for integrating the multiple streams of evidence (epidemiology, wildlife, laboratory animal, in vitro, and in silico data) that are relevant in assessing EDCs.MethodsWe have developed a framework for the systematic review and integrated assessment (SYRINA) of EDC studies. The framework was designed for use with the International Program on Chemical Safety (IPCS) and World Health Organization (WHO) definition of an EDC, which requires appraisal of evidence regarding 1) association between exposure and an adverse effect, 2) association between exposure and endocrine disrupting activity, and 3) a plausible link between the adverse effect and the endocrine disrupting activity.ResultsBuilding from existing methodologies for evaluating and synthesizing evidence, the SYRINA framework includes seven steps: 1) Formulate the problem; 2) Develop the review protocol; 3) Identify relevant evidence; 4) Evaluate evidence from individual studies; 5) Summarize and evaluate each stream of evidence; 6) Integrate evidence across all streams; 7) Draw conclusions, make recommendations, and evaluate uncertainties. The proposed method is tailored to the IPCS/WHO definition of an EDC but offers flexibility for use in the context of other definitions of EDCs.ConclusionsWhen using the SYRINA framework, the overall objective is to provide the evidence base needed to support decision making, including any action to avoid/minimise potential adverse effects of exposures. This framework allows for the evaluation and synthesis of evidence from multiple evidence streams. Finally, a decision regarding regulatory action is not only dependent on the strength of evidence, but also the consequences of action/inaction, e.g. limited or weak evidence may be sufficient to justify action if consequences are serious or irreversible.

The current report is the result of the recent EFSA‐EBTC initiative to advance the use of automation tools in systematic reviews. The working group members identified the need for data exchange standards to facilitate transferring data between SR automation tools without loss or changes in data as a first priority. Closely related objectives identified were the concurrent development of data guidance and data content standards, and a strategy for governance of the resulting data standards, including their maintenance and regular updates. These conversations led up to the organization of workshops to initiate the development of data standards, as described in the current report. The EFSA‐EBTC collaboration organized a four half‐day workshop for an extensive group of stakeholders actively involved in the development or use of SR automation tools. The main objectives were 1) to generate a common understanding of the needs and hurdles for data standards in SR automation, 2) to collate viewpoints from all relevant stakeholders on how such standards may be developed, and 3) to kick‐off the development process. Three preparatory workshops preceding the final workshop were organized to clarify the scope and objectives of the main workshop. This external scientific report contains the summary of the preparatory and main workshops, as well as the proposed strategy for the process of how these data standards could be developed. The recommended next steps for development focus on further refining the aims, analysis of the landscape, interoperability with existing standards, setting up the infrastructure (e.g., establishing a governance structure and working groups containing all essential stakeholders), and the process of actual data standard development, launching and monitoring adoption of the standards. [ABSTRACT FROM AUTHOR]

There is an ongoing debate about the value of animal experiments to inform medical practice, yet there are limited data on how well therapies developed in animal studies translate to humans. We aimed to assess 2 measures of translation across various biomedical fields: (1) The proportion of therapies which transition from animal studies to human application, including involved timeframes; and (2) the consistency between animal and human study results. Thus, we conducted an umbrella review, including English systematic reviews that evaluated the translation of therapies from animals to humans. Medline, Embase, and Web of Science Core Collection were searched from inception until August 1, 2023. We assessed the proportion of therapeutic interventions advancing to any human study, a randomized controlled trial (RCT), and regulatory approval. We meta-analyzed the concordance between animal and human studies. The risk of bias was probed using a 10-item checklist for systematic reviews. We included 122 articles, describing 54 distinct human diseases and 367 therapeutic interventions. Neurological diseases were the focus of 32% of reviews. The overall proportion of therapies progressing from animal studies was 50% to human studies, 40% to RCTs, and 5% to regulatory approval. Notably, our meta-analysis showed an 86% concordance between positive results in animal and clinical studies. The median transition times from animal studies were 5, 7, and 10 years to reach any human study, an RCT, and regulatory approval, respectively. We conclude that, contrary to widespread assertions, the rate of successful animal-to-human translation may be higher than previously reported. Nonetheless, the low rate of final approval indicates potential deficiencies in the design of both animal studies and early clinical trials. To ameliorate the efficacy of translating therapies from bench to bedside, we advocate for enhanced study design robustness and the reinforcement of generalizability. Based on the analysis of 376 therapies in 54 human diseases, this study shows that, contrary to widespread assertions, the proportion of successful animal-to-human translation may be higher than anticipated; however, the low rate of final regulatory approval indicates potential design flaws of both animal studies and early clinical trials. [ABSTRACT FROM AUTHOR]

Correctable weaknesses in the design, conduct, and analysis of biomedical and public health research studies can produce misleading results and waste valuable resources. Small effects can be difficult to distinguish from bias introduced by study design and analyses. An absence of detailed written protocols and poor documentation of research is common. Information obtained might not be useful or important, and statistical precision or power is often too low or used in a misleading way. Insufficient consideration might be given to both previous and continuing studies. Arbitrary choice of analyses and an overemphasis on random extremes might affect the reported findings. Several problems relate to the research workforce, including failure to involve experienced statisticians and methodologists, failure to train clinical researchers and laboratory scientists in research methods and design, and the involvement of stakeholders with conflicts of interest. Inadequate emphasis is placed on recording of research decisions and on reproducibility of research. Finally, reward systems incentivise quantity more than quality, and novelty more than reliability. We propose potential solutions for these problems, including improvements in protocols and documentation, consideration of evidence from studies in progress, standardisation of research efforts, optimisation and training of an experienced and non-conflicted scientific workforce, and reconsideration of scientific reward systems.

The US National Institute of Neurological Disorders and Stroke convened major stakeholders in June 2012 to discuss how to improve the methodological reporting of animal studies in grant applications and publications. The main workshop recommendation is that at a minimum studies should report on sample-size estimation, whether and how animals were randomized, whether investigators were blind to the treatment, and the handling of data. We recognize that achieving a meaningful improvement in the quality of reporting will require a concerted effort by investigators, reviewers, funding agencies and journal editors. Requiring better reporting of animal studies will raise awareness of the importance of rigorous study design to accelerate scientific progress.

This research aimed to describe and evaluate research on the Postgraduate Taught (PGT) sector in the UK from January 2008 to October 2019. The focus on PGT allowed a detailed analysis of an often overlooked part of the HE sector. Methodologically, the research is original in its use of an innovative machine learning approach to a systematic scoping review. The review scrutinised subject areas, topics studied and methodological approaches taken. Initial searches found 9,814 potentially relevant studies which were reduced to 693 for analysis. The machine learning approach was successful in reducing time without compromising accuracy. We conclude that this methodological approach is appropriate for similar reviews within education. Findings show a dominance of research into professional education programmes; a majority of research with PGT as the context rather than focus; a small number of comparative and large-scale studies; and substantial research categorised as 'scholarship of teaching'. While further research is required to ascertain if the findings are transferable to other national contexts, this study provides a reproducible methodology and identifies areas for future research to examine. [ABSTRACT FROM AUTHOR]