The Potential of Digital Twins for Pediatric Rare Diseases.

WHY IT MATTERS

Digital twins could speed up diagnosis and enable personalized treatment plans for children with rare diseases, potentially reducing the years of diagnostic delay that currently affects most pediatric rare disease patients.

Scientists are developing a new technology called Digital Twins—computer models that act like virtual copies of individual patients. These virtual copies could help doctors diagnose rare childhood diseases faster and find better treatments by testing ideas on the computer before trying them on real patients. This is especially helpful for rare diseases because there aren't many patients to study, and it's hard to do traditional research on children.

The Potential of Digital Twins for Pediatric Rare Diseases. Abstract: Rare diseases affect over 300 million people globally, with approximately 75% manifesting in childhood. Their diagnosis is often delayed and approved treatments are lacking for most of the conditions. Pediatric rare diseases research is further complicated by ethical constraints and developmental diversity across childhood. Digital Twins, virtual representations of patients built from mechanistic and AI/ML models, offer a promising solution by enabling hypothesis testing, precision diagnostics, personalized therapies, and in silico trials for pediatric rare diseases. This article discusses the potential of DT applications in advancing precision medicine for pediatric rare diseases, alongside associated regulatory perspectives, modeling strategies, uncertainty analysis, as well as da Authors: Malik-Sheriff et al. Journal: CPT: pharmacometrics & systems pharmacology MeSH: Humans, Rare Diseases, Child, Precision Medicine, Computer Simulation, Artificial Intelligence