ArticleMolecular diversity2021
Predicting blood-to-plasma concentration ratios of drugs from chemical structures and volumes of distribution in humans.
Article in Molecular diversity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Effects of sodium fluoride on serum concentrations of selected psychotropic drugs.Journal of forensic sciences · 2025Article
- Characterization of Lipophilicity and Blood Partitioning of Pyrrolizidine Alkaloids and Their N-Oxides In Vitro and In Silico for Toxicokinetic Modeling.Planta medica · 2025Article
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- Prediction of pharmacokinetic/pharmacodynamic properties of aldosterone synthase inhibitors at drug discovery stage using an artificial intelligence-physiologically based pharmacokinetic model.Frontiers in pharmacology · 2025Article
- Description and Modeling of Relevant Demographic and Laboratory Variables in a Large Oncology Cohort to Generate Virtual Populations.Pharmaceutics · 2024Article
- Prediction of human pharmacokinetic parameters incorporating SMILES information.Archives of pharmacal research · 2024Article
- A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.Pharmaceutical research · 2024Review
- A Tissue Distribution Study of Propafenone in an Intentional Fatal Poisoning Case.International journal of molecular sciences · 2024Article
- Comparison of maternal venous blood metabolomics collected as dried blood spots, dried blood microsamplers, and plasma for integrative environmental health research.Environment international · 2024Article
- Distribution of quetiapine between serum and whole blood in therapeutic drug-monitoring specimens.Journal of analytical toxicology · 2024Article
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Abstract
Despite their importance in determining the dosing regimen of drugs in the clinic, only a few studies have investigated methods for predicting blood-to-plasma concentration ratios (Rb). This study established an Rb prediction model incorporating typical human pharmacokinetics (PK) parameters. Experimental Rb values were compiled for 289 compounds, offering reliable predictions by expanding the applicability domain. Notably, it is the largest list of Rb values reported so far. Subsequently, human PK parameters calculated from plasma drug concentrations, including the volume of distribution (Vd), clearance, mean residence time, and plasma protein binding rate, as well as 2702 kinds of molecular descriptors, were used to construct quantitative structure-PK relationship models for Rb. Among the evaluated PK parameters, logVd correlated best with Rb (correlation coefficient of 0.47). Thus, in addition to molecular descriptors selected by XGBoost, logVd was employed to construct the prediction models. Among the analyzed algorithms, artificial neural networks gave the best results. Following optimization using six molecular descriptors and logVd, the model exhibited a correlation coefficient of 0.64 and a root-mean-square error of 0.205, which were superior to those previously reported for other Rb prediction methods. Since Vd values and chemical structures are known for most medications, the Rb prediction model described herein is expected to be valuable in clinical settings.
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