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Digital twins, synthetic patient data, and in-silico trials: can they empower paediatric clinical trials?
Open accessAbstract
Randomised controlled trials are the gold standard to assess the effectiveness and safety of clinical interventions; however, many paediatric trials are discontinued early due to challenges in patient enrolment. Hence, most paediatric clinical trials suffer from lack of adequate power. Additionally, trials are expensive and might expose patients to unproven therapies. Alternatives to overcome these issues using virtual patient data-namely, digital twins, synthetic patient data, and in-silico trials-are now possible due to rapid advances in digital health-care tools and interventions. However, such digital innovations have been rarely used in paediatric trials. In this Viewpoint, we propose using virtual patient data to empower paediatric trials. The use of virtual patient data has the advantages of decreased exposure of children to potentially ineffective or risky interventions, shorter trial durations leading to more rapid ascertainment of safety and effectiveness of interventions, and faster drug approvals. Use of virtual patient data could lead to more personalised treatment options with low costs and could result in faster clinical implementation of interventions in children. However, ethical and regulatory concerns, including replacing humans with digital data, data privacy, and security should be addressed and the safety and sustainability of digital data innovation ensured before virtual patient data are adopted widely.
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Many RCTs are underpowered, probably owing to the incentives to publish faster and reduce costs while receiving recognition for an RCT design.
“Many of these RCTs, however, are underpowered, probably owing to the incentives to publish faster and reduce costs while receiving recognition for an RCT design (Pammi et al. 2025).”
From Dental Research in the Digital Age: The Registry-Based Clinical Trial. (2026) · cites this paper as Pammi et al. 2025
The Introduction (page unavailable) says paediatric RCTs often have small samples and lack adequate power, and notes that trials are expensive and time-consuming. It does not attribute underpowering to incentives to publish faster, reduce costs, or gain recognition for an RCT design; its finding is also specific to paediatric trials rather than RCTs generally. (LLM, conf=0.89)
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Cites
Harnessing the power of synthetic data in healthcare: innovation, application, and privacy
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Cited by
Sorted by citations
Dental Research in the Digital Age: The Registry-Based Clinical Trial.
Joda, T., Settecase, E., Heitz‐Mayfield, L., Derks, J., Jung, R. E., & Zitzmann, N. U. (2026) · Clinical oral implants research · doi:10.1111/clr.70061 · Cited by 2
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Metadata
- Authors
- Pammi, M., Shah, P. S., Yang, L. K., Hagan, J., Aghaeepour, N., & Neu, J.
- Affiliations
- Baylor College of Medicine (US)
- Mount Sinai Hospital (CA)
- Stanford Medicine (US)
- University of Florida (US)
- Corresponding author
- Pammi, Mohan
- Venue
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Published
- 2025-05
- Volume
- 7
- Issue
- 5
- Pages
- 100851
- ISSN
- 2589-7500 (ISSN-L)
- PMC
- PMC12171946
- OpenAlex
- W4410290414
- Cited by
- 60
- References
- 2
- Citations by year
- 2026: 46 · 2025: 14
- FWCI
- 14.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Digital Health (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health
- National Institute of Child Health and Human Development (R01HD112886)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- digital twin, synthetic patient data, in silico clinical trials, pediatric clinical trials, trial power, patient enrollment, data privacy, personalized treatment
- MeSH terms
- Child, Clinical Trials as Topic, Computer Simulation, Humans, Pediatrics
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