RESUMEN
A transition from nonhuman animal models to engineered microphysiological systems (MPS), such as organoids and organ-on-a-chip technologies, would signal a paradigm shift in biomedical research. Despite MPS' potential to more accurately model human physiology, reduce high failure rates of drugs in clinical trials, and limit unnecessary animal use, widespread adoption is hampered by public opinion and lack of scalability, standardization, and current regulatory uptake. This article suggests how 5 key concepts (awareness, access, education, application, and rewards) could help address these barriers. These concepts are part of a framework that underscores a need to integrate MPS into mainstream biomedical research and to better promote ethical responsibility for the means of biomedical innovation.
Asunto(s)
Investigación Biomédica , Modelos Animales , Investigación Biomédica/ética , Humanos , Animales , Organoides , Dispositivos Laboratorio en un Chip , Concienciación , Recompensa , Experimentación Animal/ética , Opinión Pública , Sistemas MicrofisiológicosRESUMEN
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
RESUMEN
The trend toward personalized approaches to health and medicine has resulted in a need to collect high-dimensional datasets on individuals from a wide variety of populations, in order to generate customized intervention strategies. However, it is not always clear whether insights derived from studies in patient populations or in controlled trial settings are transferable to individuals in the general population. To address this issue, a longitudinal analysis was conducted on blood biomarker data from 1032 generally healthy individuals who used an automated, web-based personalized nutrition and lifestyle platform. The study had two main aims: to analyze correlations between biomarkers for biological insights, and to characterize the effectiveness of the platform in improving biomarker levels. First, a biomarker correlation network was constructed to generate biological hypotheses that are relevant to researchers and, potentially, to users of personalized wellness tools. The correlation network revealed expected patterns, such as the established relationships between blood lipid levels, as well as novel insights, such as a connection between neutrophil and triglyceride concentrations that has been suggested as a relevant indicator of cardiovascular risk. Next, biomarker changes during platform use were assessed, showing a trend toward normalcy for most biomarkers in those participants whose values were out of the clinically normal range at baseline. Finally, associations were found between the selection of specific interventions and corresponding biomarker changes, suggesting directions for future study.