Advancements in infant precision medicine through creation of ‘digital babies’
In an ambitious collaboration between the University of Galway and Heidelberg University, along with the Heidelberg Institute for Theoretical Studies and Heidelberg University Hospital, a breakthrough has been made in the realm of infant healthcare through the development of ‘digital babies’. These are sophisticated computational models that replicate the metabolic processes of newborn infants, aiming to enhance the precision in diagnosing and treating their medical conditions.
At the Digital Metabolic Twin Centre at the University of Galway, the team utilised real-world data gathered from a significant cohort of 10,000 newborns. This data encompassed various parameters including sex, birth weight, and metabolite concentrations. From this, the researchers successfully constructed 360 detailed whole-body computational models. These models are specifically designed to emulate the metabolic systems of infants over their first six months of life.
Published on 3 June 2024 in the journal Cell Metabolism, the findings of this study underscore the efficacy of these models. Not only were they capable of predicting known biomarkers for inherited metabolic diseases, but they also accurately forecasted the metabolic responses infants would have to different treatment methodologies.
Elaine Zaunseder, the lead author from Heidelberg University, highlighted the unique metabolic characteristics of babies, which are pivotal for their growth and health. She explained, “Babies require more energy for body temperature regulation due to their high surface-area-to-mass ratio and the fact that they cannot shiver during the first six months. Our task was to decode these metabolic activities and integrate them into mathematical frameworks within our computational models.”
Zaunseder also emphasised that this research marks a significant initial stride towards creating digital twins for infants. Such digital twins could potentially transform paediatric healthcare by offering customised disease management that aligns with the distinct metabolic needs of each infant.
Professor Ines Thiele, who led the project, stressed the importance of newborn screening programmes which are vital for the early detection of metabolic diseases, thus improving survival rates and health outcomes for infants. “However,” she noted, “the observed variability in disease manifestation among babies highlights the critical need for personalised treatment plans. Our models enable in-depth studies into the metabolism of both healthy and diseased infants, including those conditions screened for in newborns.”
Parallel to these developments, Imperial College London announced in May 2024 that their researchers are also working on digital twin models, specifically heart models for NHS patients suffering from pulmonary arterial hypertension. This indicates a broader trend towards adopting digital twin technology across various areas of healthcare, promising more targeted and effective treatment strategies.