The article "Can Animal Models of Disease Reliably Inform Human Studies?" by van der Worp et al. (2010) discusses the challenges and limitations of using animal models to predict the effectiveness of treatments in clinical trials. Despite the significant contributions of animal experiments to our understanding of disease mechanisms, their predictive value for clinical outcomes remains controversial. The authors highlight that only a small fraction of interventions tested in animal studies are subsequently approved for human use, and many promising interventions fail in clinical trials despite showing positive results in animal studies. The article identifies several factors contributing to the disparity between animal models and clinical trials, including methodological shortcomings in animal studies, inadequate animal data, overoptimistic conclusions from flawed studies, and lack of external validity. External validity issues arise from differences in disease pathophysiology, comorbidities, timing of treatment administration, and outcome measures between animal models and clinical trials. To improve the reliability of animal studies and their translation to clinical practice, the authors recommend adopting standards similar to those used in clinical trials. These include randomization, blinding, adequate sample size calculation, monitoring of physiological parameters, clear eligibility criteria, and statistical analysis. They also emphasize the importance of addressing publication bias, which can lead to overestimation of treatment effects and unreliable evidence for decision-making. The article provides a comprehensive review of the literature, including systematic reviews and meta-analyses, to support these recommendations. It concludes by suggesting that adopting rigorous standards in animal studies can help bridge the gap between preclinical and clinical research, ultimately improving the reliability of animal models in informing human studies.The article "Can Animal Models of Disease Reliably Inform Human Studies?" by van der Worp et al. (2010) discusses the challenges and limitations of using animal models to predict the effectiveness of treatments in clinical trials. Despite the significant contributions of animal experiments to our understanding of disease mechanisms, their predictive value for clinical outcomes remains controversial. The authors highlight that only a small fraction of interventions tested in animal studies are subsequently approved for human use, and many promising interventions fail in clinical trials despite showing positive results in animal studies. The article identifies several factors contributing to the disparity between animal models and clinical trials, including methodological shortcomings in animal studies, inadequate animal data, overoptimistic conclusions from flawed studies, and lack of external validity. External validity issues arise from differences in disease pathophysiology, comorbidities, timing of treatment administration, and outcome measures between animal models and clinical trials. To improve the reliability of animal studies and their translation to clinical practice, the authors recommend adopting standards similar to those used in clinical trials. These include randomization, blinding, adequate sample size calculation, monitoring of physiological parameters, clear eligibility criteria, and statistical analysis. They also emphasize the importance of addressing publication bias, which can lead to overestimation of treatment effects and unreliable evidence for decision-making. The article provides a comprehensive review of the literature, including systematic reviews and meta-analyses, to support these recommendations. It concludes by suggesting that adopting rigorous standards in animal studies can help bridge the gap between preclinical and clinical research, ultimately improving the reliability of animal models in informing human studies.