ArticleMolecular pharmaceutics2015
Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.
Article in Molecular pharmaceutics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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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.
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Who cites it
16 citing papers in PubMed, 25 citations in OpenAlex.
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- Examination of Urinary Excretion of Unchanged Drug in Humans and Preclinical Animal Models: Increasing the Predictability of Poor Metabolism in Humans.Pharmaceutical research · 2021Review
- A comprehensive review of integrative pharmacology-based investigation: A paradigm shift in traditional Chinese medicine.Acta pharmaceutica Sinica. B · 2021Review
- Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 Permeability.Pharmaceutics · 2021Article
- Genetic Diversity in Drug Transporters: Impact in African Populations.Clinical and translational science · 2020Review
- Article
- Evaluation of the Relevance of DILI Predictive Hypotheses in Early Drug Development: Review ofToxicology research · 2018Article
- Measures of BSEP Inhibition In Vitro Are Not Useful Predictors of DILI.Toxicological sciences : an official journal of the Society of Toxicology · 2018Article
- An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library.Environmental science & technology · 2017Article
- Evaluation of DILI Predictive Hypotheses in Early Drug Development.Chemical research in toxicology · 2017Article
- Drug Disposition Classification Systems in Discovery and Development: A Comparative Review of the BDDCS, ECCS and ECCCS Concepts.Pharmaceutical research · 2016Review
- BDDCS, the Rule of 5 and drugability.Advanced drug delivery reviews · 2016Review
- BDDCS Predictions, Self-Correcting Aspects of BDDCS Assignments, BDDCS Assignment Corrections, and Classification for more than 175 Additional Drugs.The AAPS journal · 2016Review
- Few Drugs Display Flip-Flop Pharmacokinetics and These Are Primarily Associated with Classes 3 and 4 of the BDDCS.Journal of pharmaceutical sciences · 2015Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.
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