ArticlePharmaceutical research2007
Computational models to assign biopharmaceutics drug disposition classification from molecular structure.
Article in Pharmaceutical research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Emerging Role of Biopharmaceutical Classification and Biopharmaceutical Drug Disposition System in Dosage form Development: A Systematic Review.Turkish journal of pharmaceutical sciences · 2022Article
- Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches.Pharmaceutics · 2022Article
- Population pharmacokinetic model selection assisted by machine learning.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Molecular docking analysis of lupeol with different cancer targets.Bioinformation · 2022Article
- Design and Synthesis of Novel Deuterated Ligands Functionally Selective for the γ-Aminobutyric Acid Type A Receptor (GABAJournal of medicinal chemistry · 2018Article
- Efficacy of Tilorone Dihydrochloride against Ebola Virus Infection.Antimicrobial agents and chemotherapy · 2018Article
- Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets.Journal of chemical information and modeling · 2015Article
- Toward predicting drug-induced liver injury: parallel computational approaches to identify multidrug resistance protein 4 and bile salt export pump inhibitors.Drug metabolism and disposition: the biological fate of chemicals · 2015Article
- BDDCS class prediction for new molecular entities.Molecular pharmaceutics · 2012Article
- BDDCS applied to over 900 drugs.The AAPS journal · 2011Article
- The BCS, BDDCS, and regulatory guidances.Pharmaceutical research · 2011Article
- Identification and validation of novel human pregnane X receptor activators among prescribed drugs via ligand-based virtual screening.Drug metabolism and disposition: the biological fate of chemicals · 2011Article
- Machine learning methods and docking for predicting human pregnane X receptor activation.Chemical research in toxicology · 2008Article
- In vitro studies are sometimes better than conventional human pharmacokinetic in vivo studies in assessing bioequivalence of immediate-release solid oral dosage forms.The AAPS journal · 2008Article
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Authors and funding
6 authors.
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Abstract
purposeWe applied in silico methods to automatically classify drugs according to the Biopharmaceutics Drug Disposition Classification System (BDDCS). MATERIALS AND
methodsModels were developed using machine learning methods including recursive partitioning (RP), random forest (RF) and support vector machine (SVM) algorithms with ChemDraw, clogP, polar surface area, VolSurf and MolConnZ descriptors. The dataset consisted of 165 training and 56 test set molecules.
resultsRF model 3, RP model 1, and SVM model 1 can correctly predict 73.1, 63.6 and 78.6% test compounds in classes 1, 2 and 3, respectively. Both RP and SVM models can be used for class 4 prediction. The inclusion of consensus analysis resulted in improved test set predictions for class 2 and 4 drugs.
conclusionsThe models can be used to predict BDDCS class for new compounds from molecular structure using readily available molecular descriptors and software, representing an area where in silico approaches could aid the pharmaceutical industry in speeding drugs to the patient and reducing costs. This could have significant applications in drug discovery to identify molecules that may have future developability issues.
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