How to design preclinical studies in nanomedicine and cell therapy to maximize the prospects of clinical translation

被引:0
|
作者
John P. A. Ioannidis
Betty Y. S. Kim
Alan Trounson
机构
[1] Stanford University,Departments of Medicine, Health Research and Policy, and Biomedical Data Science, Stanford University School of Medicine, and Department of Statistics, Stanford University School of Humanities and Sciences, and Meta
[2] Mayo Clinic College of Medicine,Research Innovation Center at Stanford (METRICS)
[3] Monash University & Hudson Institute of Medical Research,Departments of Neurosurgery, Cancer Biology, and Neuroscience
来源
Nature Biomedical Engineering | 2018年 / 2卷
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摘要
The clinical translation of promising products, technologies and interventions from the disciplines of nanomedicine and cell therapy has been slow and inefficient. In part, translation has been hampered by suboptimal research practices that propagate biases and hinder reproducibility. These include the publication of small and underpowered preclinical studies, suboptimal study design (in particular, biased allocation of experimental groups, experimenter bias and lack of necessary controls), the use of uncharacterized or poorly characterized materials, poor understanding of the relevant biology and mechanisms, poor use of statistics, large between-model heterogeneity, absence of replication, lack of interdisciplinarity, poor scientific training in study design and methods, a culture that does not incentivize transparency and sharing, poor or selective reporting, misaligned incentives and rewards, high costs of materials and protocols, and complexity of the developed products, technologies and interventions. In this Perspective, we discuss special manifestations of these problems in nanomedicine and in cell therapy, and describe mitigating strategies. Progress on reducing bias and enhancing reproducibility early on ought to enhance the translational potential of biomedical findings and technologies.
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页码:797 / 809
页数:12
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