Analysis of animal-to-human translation shows that only 5% of animal-tested therapeutic interventions obtain regulatory approval for human applications.

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.

Recommendations for measuring and standardizing light for laboratory mammals to improve welfare and reproducibility in animal research.

Light enables vision and exerts widespread effects on physiology and behavior, including regulating circadian rhythms, sleep, hormone synthesis, affective state, and cognitive processes. Appropriate lighting in animal facilities may support welfare and ensure that animals enter experiments in an appropriate physiological and behavioral state. Furthermore, proper consideration of light during experimentation is important both when it is explicitly employed as an independent variable and as a general feature of the environment. This Consensus View discusses metrics to use for the quantification of light appropriate for nonhuman mammals and their application to improve animal welfare and the quality of animal research. It provides methods for measuring these metrics, practical guidance for their implementation in husbandry and experimentation, and quantitative guidance on appropriate light exposure for laboratory mammals. The guidance provided has the potential to improve data quality and contribute to reduction and refinement, helping to ensure more ethical animal use.

Reproducibility of animal research in light of biological variation.

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms' responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.

Do multiple experimenters improve the reproducibility of animal studies?

The credibility of scientific research has been seriously questioned by the widely claimed "reproducibility crisis". In light of this crisis, there is a growing awareness that the rigorous standardisation of experimental conditions may contribute to poor reproducibility of animal studies. Instead, systematic heterogenisation has been proposed as a tool to enhance reproducibility, but a real-life test across multiple independent laboratories is still pending. The aim of this study was therefore to test whether heterogenisation of experimental conditions by using multiple experimenters improves the reproducibility of research findings compared to standardised conditions with only one experimenter. To this end, we replicated the same animal experiment in 3 independent laboratories, each employing both a heterogenised and a standardised design. Whereas in the standardised design, all animals were tested by a single experimenter; in the heterogenised design, 3 different experimenters were involved in testing the animals. In contrast to our expectation, the inclusion of multiple experimenters in the heterogenised design did not improve the reproducibility of the results across the 3 laboratories. Interestingly, however, a variance component analysis indicated that the variation introduced by the different experimenters was not as high as the variation introduced by the laboratories, probably explaining why this heterogenisation strategy did not bring the anticipated success. Even more interestingly, for the majority of outcome measures, the remaining residual variation was identified as an important source of variance accounting for 41% (CI95 [34%, 49%]) to 72% (CI95 [58%, 88%]) of the observed total variance. Despite some uncertainty surrounding the estimated numbers, these findings argue for systematically including biological variation rather than eliminating it in animal studies and call for future research on effective improvement strategies.

Systematic heterogenisation to improve reproducibility in animal studies.

A recent study published in PLOS Biology investigated whether the systematic use of multiple experimenters boosts the reproducibility of behavioural assays in mice. These findings open up prospects for solutions to reproducibility issues in animal research.

A qualitative study of the barriers to using blinding in in vivo experiments and suggestions for improvement.

In animal experiments, blinding (also known as masking) is a methodological strategy to reduce the risk that scientists, animal care staff, or other staff involved in the research may consciously or subconsciously influence the outcome. Lack of masking has been shown to correlate with an overestimation of treatment efficacy and false positive findings. We conducted exploratory interviews across academic and a commercial setting to discuss the implementation of masking at four stages of the experiment: during allocation and intervention, during the conduct of the experiment, during the outcome assessment, and during the data analysis. The objective was to explore the awareness, engagement, perceptions, and the barriers to implementing masking in animal experiments. We conducted multiple interviews, to explore 30 different experiments, and found examples of excellent practice but also areas where masking was rarely implemented. Significant barriers arose from the operational and informatic systems implemented. These systems have prioritised the management of welfare without considering how to allow researchers to use masking in their experiments. For some experiments, there was a conflict between the management of welfare for an individual animal versus delivering a robust experiment where all animals are treated in the same manner. We identified other challenges related to the level of knowledge on the purpose of masking or the implementation and the work culture. The exploration of these issues provides insight into how we, as a community, can identify the most significant barriers in a given research environment. Here, we offer practical solutions to enable researchers to implement masking as standard. To move forward, we need both the individual scientists to embrace the use of masking and the facility managers and institutes to engage and provide a framework that supports the scientists.

A guide to open science practices for animal research.

Translational biomedical research relies on animal experiments and provides the underlying proof of practice for clinical trials, which places an increased duty of care on translational researchers to derive the maximum possible output from every experiment performed. The implementation of open science practices has the potential to initiate a change in research culture that could improve the transparency and quality of translational research in general, as well as increasing the audience and scientific reach of published research. However, open science has become a buzzword in the scientific community that can often miss mark when it comes to practical implementation. In this Essay, we provide a guide to open science practices that can be applied throughout the research process, from study design, through data collection and analysis, to publication and dissemination, to help scientists improve the transparency and quality of their work. As open science practices continue to evolve, we also provide an online toolbox of resources that we will update continually.

Through an animal's eye: the implications of diverse sensory systems in scientific experimentation.

'Accounting for the sensory abilities of animals is critical in experimental design.' No researcher would disagree with this statement, yet it is often the case that we inadvertently fall for anthropocentric biases and use ourselves as the reference point. This paper discusses the risks of adopting an anthropocentric view when working with non-human animals, and the unintended consequences this has on our experimental designs and results. To this aim, we provide general examples of anthropocentric bias from different fields of animal research, with a particular focus on animal cognition and behaviour, and lay out the potential consequences of adopting a human-based perspective. Knowledge of the sensory abilities, both in terms of similarities to humans and peculiarities of the investigated species, is crucial to ensure solid conclusions. A more careful consideration of the diverse sensory systems of animals would improve many scientific fields and enhance animal welfare in the laboratory.

Fetal and post-natal outcomes in offspring after intrauterine metformin exposure: A systematic review and meta-analysis of animal experiments.

AIMS: The impact of maternal metformin use during pregnancy on fetal, infant, childhood and adolescent growth, development, and health remains unclear. Our objective was to systematically review the available evidence from animal experiments on the effects of intrauterine metformin exposure on offspring's anthropometric, cardiovascular and metabolic outcomes. METHODS: A systematic search was conducted in PUBMED and EMBASE from inception (searched on 12th April 2023). We extracted original, controlled animal studies that investigated the effects of maternal metformin use during pregnancy on offspring anthropometric, cardiovascular and metabolic measurements. Subsequently, risk of bias was assessed and meta-analyses using the standardized mean difference and a random effects model were conducted for all outcomes containing data from 3 or more studies. Subgroup analyses were planned for species, strain, sex and type of model in the case of 10 comparisons or more per subgroup. RESULTS: We included 37 articles (n = 3133 offspring from n = 716 litters, containing n = 51 comparisons) in this review, mostly (95%) on rodent models and 5% pig models. Follow-up of offspring ranged from birth to 2 years of age. Thirty four of the included articles could be included in the meta-analysis. No significant effects in the overall meta-analysis of metformin on any of the anthropometric, cardiovascular and metabolic offspring outcome measures were identified. Between-studies heterogeneity was high, and risk of bias was unclear in most studies as a consequence of poor reporting of essential methodological details. CONCLUSION: This systematic review was unable to establish effects of metformin treatment during pregnancy on anthropometric, cardiovascular and metabolic outcomes in non-human offspring. Heterogeneity between studies was high and reporting of methodological details often limited. This highlights a need for additional high-quality research both in humans and model systems to allow firm conclusions to be established. Future research should include focus on the effects of metformin in older offspring age groups, and on outcomes which have gone uninvestigated to date.

A 3-year evaluation of preclinicaltrials.eu reveals room for improvement in preregistration of animal studies.

In 2018, the first registry dedicated to preregistration of animal study protocols was launched. Despite international support, the overall number of (pre)registered protocols is still low, illustrating the need for pushing the preregistration agenda among researchers and policymakers.

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research.

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research.

Epidemiology and reporting characteristics of preclinical systematic reviews.

In an effort to better utilize published evidence obtained from animal experiments, systematic reviews of preclinical studies are increasingly more common-along with the methods and tools to appraise them (e.g., SYstematic Review Center for Laboratory animal Experimentation [SYRCLE's] risk of bias tool). We performed a cross-sectional study of a sample of recent preclinical systematic reviews (2015-2018) and examined a range of epidemiological characteristics and used a 46-item checklist to assess reporting details. We identified 442 reviews published across 43 countries in 23 different disease domains that used 26 animal species. Reporting of key details to ensure transparency and reproducibility was inconsistent across reviews and within article sections. Items were most completely reported in the title, introduction, and results sections of the reviews, while least reported in the methods and discussion sections. Less than half of reviews reported that a risk of bias assessment for internal and external validity was undertaken, and none reported methods for evaluating construct validity. Our results demonstrate that a considerable number of preclinical systematic reviews investigating diverse topics have been conducted; however, their quality of reporting is inconsistent. Our study provides the justification and evidence to inform the development of guidelines for conducting and reporting preclinical systematic reviews.

A computational approach to estimate postmortem interval using postmortem computed tomography of multiple tissues based on animal experiments.

The estimation of postmortem interval (PMI) is a complex and challenging problem in forensic medicine. In recent years, many studies have begun to use machine learning methods to estimate PMI. However, research combining postmortem computed tomography (PMCT) with machine learning models for PMI estimation is still in early stages. This study aims to establish a multi-tissue machine learning model for PMI estimation using PMCT data from various tissues. We collected PMCT data of seven tissues, including brain, eyeballs, myocardium, liver, kidneys, erector spinae, and quadriceps femoris from 10 rabbits after death. CT images were taken every 12 h until 192 h after death, and HU values were extracted from the CT images of each tissue as a dataset. Support vector machine, random forest, and K-nearest neighbors were performed to establish PMI estimation models, and after adjusting the parameters of each model, they were used as first-level classification to build a stacking model to further improve the PMI estimation accuracy. The accuracy and generalized area under the receiver operating characteristic curve of the multi-tissue stacking model were able to reach 93% and 0.96, respectively. Results indicated that PMCT detection could be used to obtain postmortem change of different tissue densities, and the stacking model demonstrated strong predictive and generalization abilities. This approach provides new research methods and ideas for the study of PMI estimation.

Associations of Bisphenols Exposure and Hyperuricemia Based on Human Investigation and Animal Experiments.

Hyperuricemia is characterized by elevated blood uric acid (UA) levels, which can lead to certain diseases. Epidemiological studies have explored the association between environmental contaminant exposure and hyperuricemia. However, few studies have investigated the role of chemical exposure in the development of hyperuricemia. Here, we sought to investigate the effects of bisphenol exposure on the occurrence of hyperuricemia. Fifteen bisphenol chemicals (BPs) were detected in human serum and urine samples collected from an area with a high incidence of hyperuricemia in China. Serum UA levels positively correlated with urinary bisphenol S (BPS), urinary bisphenol P (BPP), and serum bisphenol F (BPF). The effects of these three chemicals on UA levels in mice were explored at various exposure concentrations. An increase in serum UA levels was observed in BPS- and BPP-exposed mice. The results showed that BPS exposure increased serum UA levels by damaging the structure of the kidneys, whereas BPP exposure increased serum UA levels by disturbing purine metabolism in the liver. Moreover, BPF did not induce an increase in serum UA levels owing to the inhibition of guanine conversion to UA. In summary, we provide evidence of the mechanisms whereby exposure to three BPs disturbs UA homeostasis. These findings provide new insights into the risks of exposure to bisphenol chemicals.

Development of an adverse outcome pathway network for nephrotoxicity.

Adverse outcome pathways (AOPs) were introduced in modern toxicology to provide evidence-based representations of the events and processes involved in the progression of toxicological effects across varying levels of the biological organisation to better facilitate the safety assessment of chemicals. AOPs offer an opportunity to address knowledge gaps and help to identify novel therapeutic targets. They also aid in the selection and development of existing and new in vitro and in silico test methods for hazard identification and risk assessment of chemical compounds. However, many toxicological processes are too intricate to be captured in a single, linear AOP. As a result, AOP networks have been developed to aid in the comprehension and placement of associated events underlying the emergence of related forms of toxicity-where complex exposure scenarios and interactions may influence the ultimate adverse outcome. This study utilised established criteria to develop an AOP network that connects thirteen individual AOPs associated with nephrotoxicity (as sourced from the AOP-Wiki) to identify several key events (KEs) linked to various adverse outcomes, including kidney failure and chronic kidney disease. Analysis of the modelled AOP network and its topological features determined mitochondrial dysfunction, oxidative stress, and tubular necrosis to be the most connected and central KEs. These KEs can provide a logical foundation for guiding the selection and creation of in vitro assays and in silico tools to substitute for animal-based in vivo experiments in the prediction and assessment of chemical-induced nephrotoxicity in human health.

Effects of Saikosaponin-A on Insulin Resistance in Obesity: Computational and Animal Experimental Study.

Obesity is known to be associated with increased inflammation and dysregulated autophagy, both of which contribute to insulin resistance. Saikosaponin-A (SSA) has been reported to exhibit anti-inflammatory and lipid-lowering properties. In this research, we employed a combination of computational modeling and animal experiments to explore the effects of SSA. Male C57BL/6 mice were categorized into four groups: normal diet, high-fat diet (HFD), HFD + atorvastatin 10 mg/kg, and HFD + SSA 10 mg/kg. We conducted oral glucose and fat tolerance tests to assess metabolic parameters and histological changes. Furthermore, we evaluated the population of Kupffer cells (KCs) and examined gene expressions related to inflammation and autophagy. Computational analysis revealed that SSA displayed high binding affinity to tumor necrosis factor (TNF)-α, nuclear factor (NF)-κB, fibroblast growth factor 21 (FGF21), and autophagy-related 7 (ATG7). Animal study demonstrated that SSA administration improved fasting and postprandial glucose levels, homeostatic model assessment of insulin resistance (HOMA-IR) index, as well as triglyceride, free fatty acid, total cholesterol, low-density lipoprotein cholesterol (LDL-C)-cholesterol, and high-density lipoprotein cholesterol (HDL-C)-cholesterol levels in HFD-fed mice. Moreover, SSA significantly reduced liver weight and fat accumulation, while inhibiting the infiltration and M1 activation of KCs. At the mRNA level, SSA downregulated TNF-α and NF-κB expression, while upregulating FGF21 and ATG7 expression. In conclusion, our study suggests that SSA may serve as a therapeutic agent for addressing the metabolic complications associated with obesity. This potential therapeutic effect is attributed to the suppression of inflammatory cytokines and the upregulation of FGF21 and ATG7.

A Commentary on Fasting of Nonclinical Research Animals.

This commentary discusses the implementation of fasting in nonclinical animal experimental subjects. The short-term removal of food from cages of experimental animals is in all respects innocuous. The term "stress" is ill-defined and the statutes and regulations governing animal research laboratories that exert their authority in the performance of their operations do so without substantive grounds to base compliance. The legislative and administrative history of the implementation of the Animal Welfare Act (AWA) has evolved into the development of laboratory management strategies that focus on the reduction of the biological cost of stress to the animals and the determination of when subclinical stress (eustress) becomes distress. Animal welfare is based on the tenet that in laboratories conducting animal research in compliance with Good Laboratory Practices (Title 21 USC, Chapter 13,§58), it is the study protocol and the study director that establish procedures and processes that are approved by each Institutional Animal Care and Use Committee to ensure the humane care and use of animals in research, teaching, and testing and to ensure compliance with guidelines and regulations. This approval process establishes the justification of eustress in the environment that do not rise to the threshold of distress under the AWA.

Laboratory animal ethics education improves medical students' awareness of laboratory animal ethics.

OBJECTIVE: In this study, we added laboratory animal ethics education into both didactic sessions and practical sessions the general surgery laboratory course, with the didactic sessions focus on teaching the fundamental principles of laboratory animal ethics, while the practical sessions emphasize the application of these principles in laboratory classes and have assessed the changes in medical students' perception of laboratory animal ethics following medical students exposure to such education. METHODS: One hundred and eighty-nine third-year medical students from Wuhan University's Second Clinical College completed a laboratory animal ethics awareness questionnaire and a laboratory animal ethics written examination before and after laboratory animal ethics education. RESULTS: After receiving laboratory animal ethics education, the percentage of students who supported euthanasia for the execution of animals and humane treatment of laboratory animals were 95.2% and 98.8%, respectively, which did not differ from the 94.9% and 96.4% observed before the education. Moreover, there was a notable increase in the proportion of students who knew about regulations related to laboratory animals (from 39.9% to 57.1%), welfare issues (from 31.9% to 50.0%), and the 3R principle (from 30.4% to 58.9%) post-education, all statistically significant at P < 0.05. Test scores also showed improvement, with students scoring (93.02 ± 11.65) after education compared to (67.83 ± 8.08) before, a statistically significant difference. CONCLUSIONS: This research helps to provide information for the good practices of laboratory animal ethics education. After receiving laboratory animal ethics education, students are better able to treat laboratory animals in a correct animal ethical manner. Laboratory animal ethics education helps improve students' knowledge of laboratory animal ethics. Students' perception towards how the laboratory animal ethics course should be delivered may vary. Still, new courses or better organized courses on laboratory animal ethics education are required in order to provide students an in-depth understanding.

Development of a Smart Wireless Multisensor Platform for an Optogenetic Brain Implant.

Implantable cell replacement therapies promise to completely restore the function of neural structures, possibly changing how we currently perceive the onset of neurodegenerative diseases. One of the major clinical hurdles for the routine implementation of stem cell therapies is poor cell retention and survival, demanding the need to better understand these mechanisms while providing precise and scalable approaches to monitor these cell-based therapies in both pre-clinical and clinical scenarios. This poses significant multidisciplinary challenges regarding planning, defining the methodology and requirements, prototyping and different stages of testing. Aiming toward an optogenetic neural stem cell implant controlled by a smart wireless electronic frontend, we show how an iterative development methodology coupled with a modular design philosophy can mitigate some of these challenges. In this study, we present a miniaturized, wireless-controlled, modular multisensor platform with fully interfaced electronics featuring three different modules: an impedance analyzer, a potentiostat and an optical stimulator. We show the application of the platform for electrical impedance spectroscopy-based cell monitoring, optical stimulation to induce dopamine release from optogenetically modified neurons and a potentiostat for cyclic voltammetry and amperometric detection of dopamine release. The multisensor platform is designed to be used as an opto-electric headstage for future in vivo animal experiments.