BMJ Open Science
EISSN : 2398-8703
Published by: BMJ (10.1136)
Total articles ≅ 34
Latest articles in this journal
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2021-100203
Objective The roll-out of the Pfizer-BioNTech BNT162b2 COVID-19 vaccine has brought many logistical challenges, such as the absence of comprehensive stability data leading to strict handling instructions during dilution and administration. Accidental mishandling therefore presents challenging clinical dilemmas, which often led vaccine providers to err on the side of caution and discard mishandled vials rather than risk administering ineffective vaccine. This study aims to answer key questions about the vaccine’s stability to allow for a more informed decision-making process should a non-conformity occur. Methods Residual vaccine in freshly used, but appropriately stored vials collected from vaccination centres in Brighton, UK, were tested after exposure to various handling conditions and analysed by dynamic light scattering to determine the size of the lipid-mRNA nanoparticles, and gel electrophoresis to visualise the mRNA integrity and separation from the lipid formulation. Results Knocking or dropping vaccine samples from small heights resulted in lowest levels of instability, indicating low risk of compromising clinical efficacy. However, repeated drawing and injecting through 23 G needles at high speed and, more significantly, shaking and vortexing led to progressive increase in the size and polydispersity index of the lipid-mRNA nanoparticles, coupled with or caused by up to ~50% release of mRNA from the lipid formulation. This is thought to impact the vaccine’s efficacy due to lack of free mRNA protection and cellular internalisation. Conclusions These results reiterate the importance of adhering to the manufacturer’s instructions on handling, especially with regard to shaking and exposing the vaccine to excessive vibration.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2021-100241
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2021-100202
The emergence of SARS-CoV-2 in the end of 2019, an aetiologic agent responsible for the 1SARS plunged the world into an unprecedented sanitary crisis. Papers on COVID-19 have been fast-tracked since then.2–5 Accelerated time from submission to publication6–8 and qualitative changes in peer review,9 associated with empirical evidence that duplicate and implausible clinical trials have been carried out during the pandemic,10–12 could perhaps imply lower quality of peer review in COVID-19 research.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100131
Metaresearch is a scientific field involving the study of research itself. It has been applied to clinical trials since the 1980s,1 but has only become an emerging discipline over the last decade in the preclinical field. The primary tool of metaresearch is the systematic review, which uses predefined methods to provide a transparent and comprehensive summary of the evidence relating to a research question. A systematic review is defined as ‘a review that uses explicit, systematic methods to collate and synthesize findings of studies that address a clearly formulated question’.2 Systematic reviews allow for evaluation of methods and comprehensiveness of reporting, to assay likelihood of reproducibility and potential for translatability to subsequent domains of research and can investigate the impact of incentives on primary research. This, in turn, allows for a more rigorous understanding of what makes research reliable, and how research can be improved,3 while driving evidence-based decisions for future research.4 5
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100061
Introduction Cell therapy has been studied in many different research domains. Cellular replacement of damaged solid tissues is at an early stage of development, with much still to be understood. Systematic reviews and meta-analyses are widely used to aggregate data and find important patterns of results within research domains. We set out to find common biological denominators affecting efficacy in preclinical cell therapy studies for renal, neurological and cardiac disease. Methods We used datasets of five previously published meta-analyses investigating cell therapy in preclinical models of chronic kidney disease, spinal cord injury, stroke and ischaemic heart disease. We transformed primary outcomes to ratios of means to permit direct comparison across disease areas. Prespecified variables of interest were species, immunosuppression, cell type, cell origin, dose, delivery and timing of the cell therapy. Results The five datasets from 506 publications yielded data from 13 638 animals. Animal size affects therapeutic efficacy in an inverse manner. Cell type influenced efficacy in multiple datasets differently, with no clear trend for specific cell types being superior. Immunosuppression showed a negative effect in spinal cord injury and a positive effect in cardiac ischaemic models. There was a dose–dependent relationship across the different models. Pretreatment seems to be superior compared with administration after the onset of disease. Conclusions Preclinical cell therapy studies are affected by multiple variables, including species, immunosuppression, dose and treatment timing. These data are important when designing preclinical studies before commencing clinical trials.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100103
Preclinical research is a vital step in the drug discovery pipeline and more generally in helping to better understand human disease aetiology and its management. Systematic reviews (SRs) can be powerful in summarising and appraising this evidence concerning a specific research question, to highlight areas of improvements, areas for further research and areas where evidence may be sufficient to take forward to other research domains, for instance clinical trial. Guidance and tools for preclinical research synthesis remain limited despite their clear utility. We aimed to create an online end-to-end platform primarily for conducting SRs of preclinical studies, that was flexible enough to support a wide variety of experimental designs, was adaptable to different research questions, would allow users to adopt emerging automated tools and support them during their review process using best practice. In this article, we introduce the Systematic Review Facility (https://syrf.org.uk), which was launched in 2016 and designed to support primarily preclinical SRs from small independent projects to large, crowdsourced projects. We discuss the architecture of the app and its features, including the opportunity to collaborate easily, to efficiently manage projects, to screen and annotate studies for important features (metadata), to extract outcome data into a secure database, and tailor these steps to each project. We introduce how we are working to leverage the use of automation tools and allow the integration of these services to accelerate and automate steps in the systematic review workflow.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100126
Within preclinical research, attention has focused on experimental design and how current practices can lead to poor reproducibility. There are numerous decision points when designing experiments. Ethically, when working with animals we need to conduct a harm–benefit analysis to ensure the animal use is justified for the scientific gain. Experiments should be robust, not use more or fewer animals than necessary, and truly add to the knowledge base of science. Using case studies to explore these decision points, we consider how individual experiments can be designed in several different ways. We use the Experimental Design Assistant (EDA) graphical summary of each experiment to visualise the design differences and then consider the strengths and weaknesses of each design. Through this format, we explore key and topical experimental design issues such as pseudo-replication, blocking, covariates, sex bias, inference space, standardisation fallacy and factorial designs. There are numerous articles discussing these critical issues in the literature, but here we bring together these topics and explore them using real-world examples allowing the implications of the choice of design to be considered. Fundamentally, there is no perfect experiment; choices must be made which will have an impact on the conclusions that can be drawn. We need to understand the limitations of an experiment’s design and when we report the experiments, we need to share the caveats that inherently exist.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100077
Objective Studies in rodents associated the deficits of adult hippocampal neurogenesis with behavioural anomalies which may be reversed by antidepressant treatments. A previous systematic review (SR) and meta-analysis (MA) indicated a hierarchy within the proneurogenic effects of different antidepressants in naive rodents. The present review aims to evaluate a more comprehensive sample of studies investigating the links between the effects of different antidepressants and adult hippocampal neurogenesis. Search strategy, screening annotation, data management Protocols were planned following Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines. Searches in Embase, Medline, Scopus and Web of Science followed by screening with inclusion/exclusion criteria will provide relevant publications. First SR will summarise the effects of antidepressants on adult hippocampal neurogenesis on different laboratory rodents. Second SR will summarise the correlations between neurogenic and behavioural effects of antidepressants while the third will focus on cause–effect relationships between them. If feasible, data will be analysed by pairwise or network random-effect or multivariate MA to determine the direction, magnitude, significance and heterogeneity (I2) of the estimated effect sizes on global or subgroup levels. Funnel plotting, Egger regression, ‘trim and fill’ will be used to estimate the risk of publication bias. Quality assessment of the included publications will be performed by applying adapted CAMARADES, Syrcles’ risk of bias or CINeMA tools. Reporting Find a preliminary version of this protocol at the Open Science Framework (https://osf.io/gmsvd/). Data extraction has already started. Results shall be published in a peer-reviewed journal. Due to the continuous production in the field, the implementation of a ‘living SR’ is intended.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100074
Background Meta-analysis of preclinical data is used to evaluate the consistency of findings and to inform the design and conduct of future studies. Unlike clinical meta-analysis, preclinical data often involve many heterogeneous studies reporting outcomes from a small number of animals. Here, we review the methodological challenges in preclinical meta-analysis in estimating and explaining heterogeneity in treatment effects. Methods Assuming aggregate-level data, we focus on two topics: (1) estimation of heterogeneity using commonly used methods in preclinical meta-analysis: method of moments (DerSimonian and Laird; DL), maximum likelihood (restricted maximum likelihood; REML) and Bayesian approach; (2) comparison of univariate versus multivariable meta-regression for adjusting estimated treatment effects for heterogeneity. Using data from a systematic review on the efficacy of interleukin-1 receptor antagonist in animals with stroke, we compare these methods, and explore the impact of multiple covariates on the treatment effects. Results We observed that the three methods for estimating heterogeneity yielded similar estimates for the overall effect, but different estimates for between-study variability. The proportion of heterogeneity explained by a covariate is estimated larger using REML and the Bayesian method as compared with DL. Multivariable meta-regression explains more heterogeneity than univariate meta-regression. Conclusions Our findings highlight the importance of careful selection of the estimation method and the use of multivariable meta-regression to explain heterogeneity. There was no difference between REML and the Bayesian method and both methods are recommended over DL. Multiple meta-regression is worthwhile to explain heterogeneity by more than one variable, reducing more variability than any univariate models and increasing the explained proportion of heterogeneity.
BMJ Open Science, Volume 5; https://doi.org/10.1136/bmjos-2020-100135
ObjectiveThigmotaxis is an innate predator avoidance behaviour of rodents and is enhanced when animals are under stress. It is characterised by the preference of a rodent to seek shelter, rather than expose itself to the aversive open area. The behaviour has been proposed to be a measurable construct that can address the impact of pain on rodent behaviour. This systematic review will assess whether thigmotaxis can be influenced by experimental persistent pain and attenuated by pharmacological interventions in rodents.Search strategyWe will conduct search on three electronic databases to identify studies in which thigmotaxis was used as an outcome measure contextualised to a rodent model associated with persistent pain. All studies published until the date of the search will be considered.Screening and annotationTwo independent reviewers will screen studies based on the order of (1) titles and abstracts, and (2) full texts.Data management and reportingFor meta-analysis, we will extract thigmotactic behavioural data and calculate effect sizes. Effect sizes will be combined using a random-effects model. We will assess heterogeneity and identify sources of heterogeneity. A risk-of-bias assessment will be conducted to evaluate study quality. Publication bias will be assessed using funnel plots, Egger’s regression and trim-and-fill analysis. We will also extract stimulus-evoked limb withdrawal data to assess its correlation with thigmotaxis in the same animals. The evidence obtained will provide a comprehensive understanding of the strengths and limitations of using thigmotactic outcome measure in animal pain research so that future experimental designs can be optimised. We will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines and disseminate the review findings through publication and conference presentation.