NIH Highlighted Topic: Computational Modeling of Complex Processes Across Biological Scales
Introduction
Multiscale computational models that integrate processes across different spatial and temporal levels, from molecular to organismal, to epidemiologic and from microseconds to years. They provide a comprehensive understanding of complex systems and offer an exciting opportunity to advance biomedical research. This approach helps reveal how interactions at molecular and cellular scales influence larger, population-, geographical-, or global-scale phenomena, offering insights into complex biological processes, and may help develop better and more precise biomedical interventions. By integrating processes from molecular to epidemiologic levels, multiscale computational models provide a comprehensive understanding of complex systems.
This topic encourages innovative research and collaborative approaches that integrate technologies and informatic practices to develop, improve, and disseminate multiscale computational models for human health and diseases, and their associated technologies, across the research community. The topic also supports leveraging computational multiscale models as an important component of Novel Alternative Methods (NAMs) to investigate the mechanism and safety of a medical intervention in pre-clinical, translational, and clinical development.
This topic encourages innovative research in computational modeling of complex processes across biological scales (i.e., to develop multiscale models). The topic seeks to build a collaborative community of researchers to improve the replicability and reproducibility of computational multiscale models, promoting their advancement and reuse.
See more information here, including participating NIH Institutes/Centers and their specific interests relating to the Highlighted Topic.
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Please contact Dr. Karen Cielo, Director of Research Development, if you are interested in applying or would like to discuss the opportunity.