ArticleCPT: pharmacometrics & systems pharmacology2026
Physiologically Based Pharmacokinetic Virtual Twin Approach for Fludarabine Dosing in Pediatric Hematopoietic Stem Cell Transplantation.
Article in CPT: pharmacometrics & systems pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A Review of Virtual Twins in Physiologically-Based Pharmacokinetic Modeling and Simulation.Clinical pharmacology and therapeutics · 2026Review
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fludarabine (Flu), administered as a prodrug Flu monophosphate, is a lymphodepleting agent used prior to hematopoietic stem cell transplantation (HSCT) which exhibits substantial pharmacokinetics (PK) variability, contributing to suboptimal outcomes. This study developed and validated a physiologically based pharmacokinetic (PBPK) model using literature-based data and a middle-out approach for Flu and its two main metabolites in adults and children, and evaluated its performance to predict individual Flu exposures in 28 pediatric HSCT patients using a virtual twin (VT) approach using PK-Sim software. Different informed models with individual demographic and biological characteristics were assessed by comparing predicted and observed plasma exposures (AUC
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Registered trials
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