ArticleCancer chemotherapy and pharmacology2026
Physiologically based pharmacokinetic modeling to predict human pharmacokinetics of a novel mithramycin analog for Ewing sarcoma.
Article in Cancer chemotherapy and pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Bridging tumor growth dynamics and survival in preclinical oncology drug development - a Tumor Growth Inhibition and Time-to-Event (TGI-TTE) modeling framework.Cancer chemotherapy and pharmacology · 2026Article
- Physiologically Based Pharmacokinetic Modeling to Predict Human Pharmacokinetics of a Novel Mithramycin Analog for Ewing Sarcoma.Research square · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeTo develop and qualify a physiologically based pharmacokinetic (PBPK) modeling strategy for mithramycin (MTM) and its analog, MTMSA-Trp, with the aim of projecting first-in-human plasma pharmacokinetics and supporting the translational development of MTMSA-Trp for Ewing sarcoma treatment.
methodsPBPK models were created in GastroPlus
resultsThe additional clearance approach provided the most accurate prediction of human MTM plasma PK. Across all clearance prediction methods, MTMSA-Trp was predicted to achieve 8- to 15-fold higher human plasma exposure than MTM at the same dose. Model-derived liver exposures were 2- to 4-fold higher, with a lower predicted liver partition for MTMSA-Trp; however, these tissue predictions remained sensitive to distribution assumptions. Parameter sensitivity analysis identified the blood-to-plasma ratio as the most influential parameter among those examined.
conclusionPBPK modeling supports the projection that MTMSA-Trp will achieve substantially higher plasma exposure than MTM in humans. This empirically developed workflow may inform translational efforts for the first-in-human development of MTMSA-Trp.
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