Digital twins to personalize medicine
By B. Björnsson, C. Borrebaeck, Nils Elander, T. Gasslander, D. Gawel, M. Gustafsson, Rebecka Jörnsten, Eunjung Lee, Xinxiu Li, S. Lilja and 9 more. Genome Medicine, 2019
410 citations recorded by the source corpus.
Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/7b7fe33c8823d09e18430b53a862172eb28467eb
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In Molecular Biology
Citations in the corpus
- Digital twins for health: a scoping review (2024, background): “Incombination ofour perspectives with many other de fi nitions and perceptions in the literature 2,7 – 11 , we de fi ne a digital twin for healthcare as a virtual representation of a person which allows dynamic simulation of potential treatment strategy, monitoring and prediction of health…”
- Digital twin in healthcare: Recent updates and challenges (2023, methodology): “As an example, the use of the DT in treating cardiovascular disease is growing and there is an emerging interest in the application of AI in vascular surgery.(36,53) The virtual model established using DT technology can used to develop diagnostic tools.”
- Multimodal biomedical AI (2022, methodology): “In healthcare, digital twins are a promising tool for drug target discovery 65,66 .”
- Digital Twins: From Personalised Medicine to Precision Public Health (2021, background): “As a result, digital twins are being explored to assess the feasibility of creating dynamic models and simulations of humans in order to improve medical diagnostics and prognostics, treatments, and the overall wellbeing of patients [8,9,12].”
- The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities (2021, background): “Björnsson et al. [23] concentrated on protein–protein interaction (PPI) networks to diagnose and treat patients of a particular disease.”
- The next generation of evidence-based medicine (2023, positive): “…of medical analog patient-specific ‘digital twins’ is an emerging area of research that has the potential to combine polynomial data (mechanistic data, medical history, with the power of AI) and may perhaps serve to enhance N-of-1 trials in the future, to further personalize medicine 37,59,60 .”