Evidence map›Paper›PMID 42745804›Full record

ArticleFrontiers in pharmacology2026

Physiologically-based pharmacokinetic model to predict loading dose polymyxin B exposure in critically ill patients with sepsis.

Yixuan Cao, Inna Galvidis, Akmal Alimov, Joseph F Standing, Maksim Burkin, Yury Surovoy

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Article in Frontiers in pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yixuan CaoUniversity College London, London, United Kingdom.
Inna GalvidisI. Mechnikov Research Institute for Vaccines and Sera, Moscow, Russia.
Akmal AlimovI. Mechnikov Research Institute for Vaccines and Sera, Moscow, Russia.
Joseph F StandingUniversity College London, London, United Kingdom.
Maksim BurkinI. Mechnikov Research Institute for Vaccines and Sera, Moscow, Russia.
Yury SurovoyMiddlesex University, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To build a physiologically based pharmacokinetic (PBPK) model to predict polymyxin B (PMB) exposure in critically ill patients with sepsis. Patients and methods: A new PBPK model was built using published data on PMB pharmacokinetics (PK) in healthy volunteers and patients with end-stage renal disease (ESRD). The model was then tested to predict individual PK curves on clinical samples from critically ill patients with sepsis (N = 15) accounting for common pathophysiological alterations observed in this cohort (changes of unbound drug fraction, protein levels, fluids shifts, renal function). The developed model was then used to predict PMB plasma and lung concentrations for probability of target attainment (PTA) analysis. Results: The PBPK model demonstrated good prediction of mean population PK parameters, including area under the concentration time curve (AUC Conclusion: The first PBPK model of PMB in critically ill patients allows good prediction of population-level PK parameters and supports a loading dose of at least 2.5 mg/kg. It also provides a mechanistic framework for future research as PMB distribution, metabolism and excretion mechanisms become better characterised.

Indexed as

critical illnessloading dosePBPKpharmacokineticspolymyxin Bsepsis

Identifiers

PMID42745804
PMCPMC13574657

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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.