ArticlePharmaceutics2019
Novel Population Pharmacokinetic Approach to Explain the Differences between Cystic Fibrosis Patients and Healthy Volunteers via Protein Binding.
Article in Pharmaceutics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
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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
11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Altered intravenous drug disposition in people living with cystic fibrosis: A meta-analysis integrating top-down and bottom-up data.CPT: pharmacometrics & systems pharmacology · 2022Pooled it
- Antibiotics in Adult Cystic Fibrosis Patients: A Review of Population Pharmacokinetic Analyses.Clinical pharmacokinetics · 2021Pooled it
- Pharmacokinetics in Patients with Cystic Fibrosis: A Systematic Review of Data Published Between 1999 and 2019.Clinical pharmacokinetics · 2020Pooled it
- Remodeling the pathological airway: advanced nanotechnology for diagnostics and therapeutics in cystic fibrosis.Journal of nanobiotechnology · 2026Review
- Anti-infectives in Pediatric Patients with Cystic Fibrosis: A Comprehensive Review of Population Pharmacokinetic Analyses.Clinical pharmacokinetics · 2025Review
- Evaluation of Complex Drug Interactions Between Elexacaftor-Tezacaftor-Ivacaftor and Statins Using Physiologically Based Pharmacokinetic Modeling.Pharmaceutics · 2025Article
- Cefiderocol pharmacokinetics during acute pulmonary exacerbations in hospitalized adult persons with cystic fibrosis.Antimicrobial agents and chemotherapy · 2025Article
- Article
- Physiologically-Based Pharmacokinetic-Led Guidance for Patients With Cystic Fibrosis Taking Elexacaftor-Tezacaftor-Ivacaftor With Nirmatrelvir-Ritonavir for the Treatment of COVID-19.Clinical pharmacology and therapeutics · 2022Article
- CFTR Modulators: Does One Dose Fit All?Journal of personalized medicine · 2021Review
- An Algorithm for Nonparametric Estimation of a Multivariate Mixing Distribution with Applications to Population Pharmacokinetics.Pharmaceutics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pharmacokinetics in patients with cystic fibrosis (CF) has long been thought to differ considerably from that in healthy volunteers. For highly protein bound β-lactams, profound pharmacokinetic differences were observed between comparatively morbid patients with CF and healthy volunteers. These differences could be explained by body weight and body composition for β-lactams with low protein binding. This study aimed to develop a novel population modeling approach to describe the pharmacokinetic differences between both subject groups by estimating protein binding. Eight patients with CF (lean body mass [LBM]: 39.8 ± 5.4kg) and six healthy volunteers (LBM: 53.1 ± 9.5kg) received 1027.5 mg cefotiam intravenously. Plasma concentrations and amounts in urine were simultaneously modelled. Unscaled total clearance and volume of distribution were 3% smaller in patients with CF compared to those in healthy volunteers. After allometric scaling by LBM to account for body size and composition, the remaining pharmacokinetic differences were explained by estimating the unbound fraction of cefotiam in plasma. The latter was fixed to 50% in male and estimated as 54.5% in female healthy volunteers as well as 56.3% in male and 74.4% in female patients with CF. This novel approach holds promise for characterizing the pharmacokinetics in special patient populations with altered protein binding.
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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.