Human Digital twins in Healthcare:โฃ Current Reality Falls Short of Potential, new Review Finds
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Washingtonโ D.C. – A newly published scoping โreview reveals that while interest in Human Digital Twins (HDTs) – virtual replicas of individual patients – is surging in healthcare,theโฃ vast majority of current research doesn’t meet the rigorous standards required for true clinicalโฃ application. The study, examining literature from January 2017โฃ to Julyโค 2024, highlights a โคnotable gapโ between the promiseโ of HDTs and their current implementation.
What are Human โdigital โฃTwins?
digital twins, broadly, are dynamicโ virtual models mirroring โphysical systems. Inโ healthcare, HDTs aim to provide personalized, continuouslyโค updated, andโค predictive insights to inform medical decision-making. The National Academies of sciences, Engineering, and Medicine (NASEM) has established a key definition: a true digital twinโ must possess allโ three of these characteristics โฃto be clinically useful.
the Scoping โขReviewโ Findings
researchers conducted โa systematic literatureโ search and analyzed 149 studies.The results were โฃstark. Only 18 โstudies โฃ-โค a mereโ 12.08% โฃ- fully aligned with the NASEM definitionโ of a digital twin.โ The โremaining studies fell into other categories:
- Digital shadows (9.4%): These models lack dynamicโ updating capabilities.
- General Digital Models โฃ(10.07%): โฃ these are broader models not personalized to individual โpatients.
- Virtual Patient Cohorts (10.07%): Theseโข represent groups of patients,rather than individualโ virtual counterparts.
A Critical Missing Piece: โValidationโค and Reliability
Perhaps โคthe most concerning finding is the limited focus on model reliability. โOnly two studies mentioned Verification, Validation, and Uncertainty Quantification (VVUQ) – a crucial โคNASEM standard for ensuringโค the accuracy and trustworthiness of digital twinโ predictions. Without robust VVUQ,โ the clinical utility of โHDTs remains questionable.
implications forโ the Future
this โคreview underscores โฃthe need for more โฃrigorous research and progressโ in the field of โฃHDTs. Moving forward, studies must prioritize personalization, dynamic updating, predictive capabilities, and, critically, โthoroughโฃ validation to unlock the full potential โขofโ these technologies โคforโค improving patient care.
Source: Scoping review findingsโ publishedโข [Date of publication – *add if available from original source*]
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