ReviewJournal of personalized medicine2025
Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality.
Review in Journal of personalized medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07719621 (Implication of Albuminuria Reduction and Other Cardiorenal Effects on The Risk of Heart Failure in Patients With CKD and T2D), which is not on this map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Implication of Albuminuria Reduction and Other Cardiorenal Effects on The Risk of Heart Failure in Patients With CKD and T2D
Who cites it
16 citing papers in PubMed.
- Digital Twins for Targeted Therapy in Head and Neck Cancer: From Molecular Stratification to Resistance-Aware Combination Strategies.Current oncology (Toronto, Ont.) · 2026Review
- Artificial intelligence-driven digital twins in Pharma 4.0: transforming smart manufacturing, predictive quality assurance, and personalized drug delivery.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026Review
- Validating medical digital twins for clinical decision support: beyond predictive accuracy.JAMIA open · 2026Review
- From Therapeutic Drug to Xenobiotic in Cancer Repurposing: Clozapine Mechanisms, Metabolic Liabilities, and Human-Relevant Translational Approaches.Journal of xenobiotics · 2026Review
- Narrative Review of Digital Twins in the Health Domain: Development, Application, and Evidence Consolidation.Medical sciences (Basel, Switzerland) · 2026Review
- Review
- Artificial intelligence, extended reality and computational modelling in cross-sectional cardiovascular imaging in congenital heart disease: a narrative review.Cardiovascular diagnosis and therapy · 2026Review
- Molecular Oncodiagnostics in Precision Oncology: Integrating Tumor Transcriptomics, Patient Pharmacogenetics, and Ex Vivo Chemoresistance Testing to Improve Individual Chemotherapy Response.Journal of personalized medicine · 2026Review
- Artificial Intelligence and the Transformation of Cell and Gene Therapy Development.Pharmaceutics · 2026Review
- Exercise-Based Mechanotherapy: From Biomechanical Principles and Mechanotransduction to Precision Regenerative Rehabilitation.International journal of molecular sciences · 2026Review
- Cross-fusion of digital twins and artificial intelligence in diabetes: from mechanistic elucidation to full-cycle precision management.Frontiers in endocrinology · 2026Review
- From toxicogenomics to predictive toxicology and exposomics: defining the next decade of gene-environment research.Frontiers in genetics · 2026Article
- Digital twins in precision pharmacotherapy: emerging applications, challenges, and future directions.Frontiers in digital health · 2026Review
- The representational bottleneck in rehabilitation AI: from human-cognitive proxies to pathway-based clinical representations.Frontiers in digital health · 2026Article
- Physiology-guided personalized mechanical ventilation to prevent ventilator-induced lung injury.Frontiers in medicine · 2026Review
- Digital Twins in Translational Research and Health Care: An Anthropological Perspective.Ethics & human researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital Twins (DTs) are poised to transform personalized medicine by enabling real-time, multiscale simulations of individual patients. By integrating genomics, imaging, wearable sensor data, and clinical records, DTs offer a powerful platform for predictive, adaptive, and patient-centered decision-making. Recent advances have highlighted their potential across a range of clinical domains, including cardiology, oncology, pharmacogenomics, and neurology. Yet, their routine application in clinical practice remains limited, underscoring a growing translational gap between digital innovation and healthcare delivery. In this review, we explore the scientific maturity and emerging clinical use cases of DTs, while critically analyzing the systemic, regulatory, ethical, and infrastructural barriers that hinder their widespread adoption. We outline a translational roadmap that emphasizes dynamic model validation, clinician co-development, equitable data representation, and regulatory harmonization. Uniquely, we reframe DTs as cognitive tools for clinical reasoning and decision support. We further clarify translational pathways through explicit evaluation and reporting recommendations. By positioning DTs within this practical framework, we outline how responsible, inclusive, and interdisciplinary implementation can establish them as foundational elements of 21st century precision medicine.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.