ArticleFrontiers in pharmacology2025
QSAR-based physiologically based pharmacokinetic (PBPK) modeling for 34 fentanyl analogs: model validation, human pharmacokinetic prediction and abuse risk insights.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Dose-Finding of Alfentanil for Hysteroscopy Under Remimazolam Sedation in Obese and Normal-Weight Patients: An Up-and-Down Trial.Drug design, development and therapy · 2026Trial
- Pharmacokinetics of repeated, high-dose fentanyl administration in rats.Drug metabolism and disposition: the biological fate of chemicals · 2026Article
- Analyzing the Chemical Space of Opioid Receptor Agonists and Antagonists: Insights from Computational Models.ACS omega · 2026Article
- Antinociceptive Effect and Hyperalgesia of Fentanyl and Its Analogues.International journal of molecular sciences · 2026Article
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Authors and funding
10 authors.
Funding
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Abstract
Introduction: Fentanyl analogs, as emerging new psychoactive substances (NPS), pose a global public health threat due to widespread abuse, high toxicity, and frequent overdose fatalities. However, their structural diversity and scarce experimental pharmacokinetic (PK) data hinder hazard and abuse risk assessment. Conventional physiologically based pharmacokinetic (PBPK) models for these analogs are limited by reliance on time-consuming Methods: To address this, we developed and validated a QSAR-integrated PBPK framework (QSAR: Quantitative Structure-Activity Relationship) for predicting human PK of fentanyl analogs. The workflow included: (1) Validating the framework Results: Key results: (1) For β-hydroxythiofentanyl, all predicted rat PK parameters (area under the plasma concentration-time curve from time zero to the last measurable time point [AUC Discussion: This study demonstrates that the QSAR-PBPK framework enables rapid prediction of human pharmacokinetics (PK) for understudied fentanyl analogs without relying on scarce experimental data. For structurally similar, clinically characterized analogs (e.g., sufentanil, alfentanil), predictions of key PK parameters (e.g., T
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