ArticleCPT: pharmacometrics & systems pharmacology2025
Numerical Verification of Tucuxi, a Promising Bayesian Adaptation Tool for Model-Informed Precision Dosing.
Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Artificial Intelligence and Predictive Modelling for Precision Dosing of Immunosuppressants in Kidney Transplantation.Pharmaceuticals (Basel, Switzerland) · 2026Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tucuxi, a Swiss-developed Model-Informed Precision Dosing (MIPD) software, aims to support clinical dosage decision-making to achieve therapeutic concentration targets. This study assessed its predictive accuracy compared to NONMEM, a gold-standard tool for Bayesian PK predictions. A panel of models was created to mimic various pharmacokinetic scenarios following oral, bolus, or intravenous administration. For each scenario, a virtual population of 4000 patients receiving doses ranging from 10 to 120 mg every 24 h was created. Sparse and rich profiles were simulated, with either one or four samples taken per patient. Tucuxi and NONMEM predicted concentrations at sampling times, trough (C
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Registered trials
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