ReviewNPJ digital medicine2024
From virtual patients to digital twins in immuno-oncology: lessons learned from mechanistic quantitative systems pharmacology modeling.
Review in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
What it found
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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.
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Who cites it
60 citing papers in PubMed.
- A digital twin-enhanced decision support system improves time-in-range in type 1 diabetes: a randomized clinical trial.Scientific reports · 2025Trial
- From Biological Mechanisms to Causal Inference: Quantitative Systems Pharmacology and Causal Frameworks in Drug Development.Clinical pharmacology and therapeutics · 2026Article
- Advancing clinical trials for rare renal cell carcinoma subtypes: Consensus statements from the International Kidney Cancer Symposium North America 2025 think tank.Urologic oncology · 2026Article
- From Classical PKPD to Model-Informed Drug Development: Are "Digital Twins" a New Paradigm?Clinical pharmacology and therapeutics · 2026Article
- Quantitative Systems Pharmacology (QSP): Bridging Biology and Mechanism with Clinical Drug Development Decisions.Journal of clinical pharmacology · 2026Review
- Tele-Oncology in the Post-Pandemic Era: Clinical Integration, Access Disparities and Medico-Legal Accountability.Current oncology reports · 2026Review
- Rethinking Phase I units in the era of immuno-oncology: a three-layer framework.Journal for immunotherapy of cancer · 2026Review
- AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026Review
- Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework.Healthcare (Basel, Switzerland) · 2026Review
- Structured Schemas for Provenance-Rich, LLM-Assisted QSP Model Calibration.CPT: pharmacometrics & systems pharmacology · 2026Article
- Virus-like particles in cancer immunotherapy: bridging human and veterinary medicine through one health.Journal of nanobiotechnology · 2026Review
- Structured Schemas for Provenance-Rich, LLM-Assisted QSP Model Calibration.bioRxiv : the preprint server for biology · 2026Article
- Mechanistic learning to predict and understand minimal residual disease.bioRxiv : the preprint server for biology · 2026Article
- Digital twins and digital models of the human circulatory system.Nature reviews bioengineering · 2026Article
- A unified digital twin framework for predicting therapeutic response to central nervous system infections by pathogenic free-living amoebae.Parasitology research · 2026Review
- Comparative Molecular Insights and Computational Modeling of Multiple Myeloma and Osteosarcoma.International journal of molecular sciences · 2026Review
- Decoding immunotherapy response through computational modeling.Nature communications · 2026Review
- Article
- Review
- From Population-Based PBPK to Individualized Virtual Twins: Clinical Validation and Applications in Medicine.Journal of clinical medicine · 2026Review
Corrections and comments
- Update of
Authors and funding
4 authors.
Funding
Abstract
Virtual patients and digital patients/twins are two similar concepts gaining increasing attention in health care with goals to accelerate drug development and improve patients' survival, but with their own limitations. Although methods have been proposed to generate virtual patient populations using mechanistic models, there are limited number of applications in immuno-oncology research. Furthermore, due to the stricter requirements of digital twins, they are often generated in a study-specific manner with models customized to particular clinical settings (e.g., treatment, cancer, and data types). Here, we discuss the challenges for virtual patient generation in immuno-oncology with our most recent experiences, initiatives to develop digital twins, and how research on these two concepts can inform each other.
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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 OpenQuestion graph.