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Digital babies created to improve infant healthcare

Researchers at University of Galway, the Heidelberg Institute for Theoretical Studies (HITS) Heidelberg University, and Heidelberg University Hospital have created digital babies to better understand infants’ health in their critical first 180 days of life. The international team created computer models that simulate the unique metabolic processes of each baby. The models can help to better understand rare metabolic diseases.


Digital twins can improve the understanding of infants’ health in their critical first 180 days. (Photo: HITS)

An international team of researchers at University of Galway, Ireland, the Heidelberg Institute for Theoretical Studies (HITS), and Heidelberg University Hospital (all Germany), have created digital babies to better understand infants’ health in their critical first 180 days of life. The team created 360 advanced computer models that simulate the unique metabolic processes of each baby. The digital babies are the first sex-specific computational whole-body models representing newborn and infant metabolism with 26 organs, six cell types, and more than 80,000 metabolic reactions. The study was published in the journal Cell Metabolism.


Lead author Elaine Zaunseder, HITS and Heidelberg University, said: “Babies are not just small adults – they have unique metabolic features that allow them to develop and grow up healthy.” Therefore, an essential part of this research work was to identify these metabolic processes and translate them into mathematical concepts that could be applied in the computational model.

Mathematical model of infant metabolism (infant-WBM) that uses flux balance analysis to predict infant growth and known biomarkers of inherited metabolic disease.


Publication: Zaunseder E et al: Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases. Cell Metabolism, 4 June 2024. (DOI: 10.1016/j.cmet.2024.05.006)


Scientific contact:

Elaine Zaunseder Engineering Mathematics and Computing Lab (EMCL), Heidelberg University https://emcl.iwr.uni-heidelberg.de/ Data Mining and Uncertainty Quantification Group (DMQ), Heidelberg Institute for Theoretical Studies (HITS); https://www.h-its.org/de/people/elaine-zaunseder/


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