ArticleClinical pharmacokinetics2013
Disposition pathway-dependent approach for predicting organic anion-transporting polypeptide-mediated drug-drug interactions.
Article in Clinical pharmacokinetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Quantitative Prediction of Interactions Mediated by Transporters and Cytochromes: Application to Organic Anion Transporting Polypeptides, Breast Cancer Resistance Protein and Cytochrome 2C8.Clinical pharmacokinetics · 2020Article
- A Generic Model for Quantitative Prediction of Interactions Mediated by Efflux Transporters and Cytochromes: Application to P-Glycoprotein and Cytochrome 3A4.Clinical pharmacokinetics · 2019Article
- A Prediction Model of Drug Exposure in Cirrhotic Patients According to Child-Pugh Classification.Clinical pharmacokinetics · 2015Article
- Prediction of pharmacokinetics and drug-drug interactions when hepatic transporters are involved.Clinical pharmacokinetics · 2014Review
- Physiologically based pharmacokinetic modelling and in vivo [I]/K(i) accurately predict P-glycoprotein-mediated drug-drug interactions with dabigatran etexilate.British journal of pharmacology · 2014Article
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveOrganic anion-transporting polypeptide (OATP)-mediated drug-drug interactions (DDIs) are among the most important classes of clinically relevant DDIs. Accurate prediction of the OATP-mediated DDIs is not successful due to the sequential disposition pathways of OATP substrates in humans. Intestinal and hepatic uptake transporters, efflux transporters, and cytochrome P450 (CYP) enzymes are often involved in the sequential disposition pathways of typical OATP substrates. The aim of this proof-of-concept study is to develop and validate a novel approach which can be used to predict OATP-mediated DDIs with significantly increased accuracy and decreased false-negatives.
methodsThe feasibility of using a disposition pathway-dependent prediction (DPDP) approach to predict the ratios of the area under the plasma concentration-time curve (AUC(R)) in the presence and absence of the inhibitor was investigated. A total of 62 clinical DDI studies were included in this feasibility study. The disposition pathways governing the outcome of DDIs were first identified for each substrate using the information within learning sets, and then substrate-specific algorithms were used to predict the DDI risks of the external validation set (51 DDIs).
resultsThe method predicted AUC(R) within 50-200 % for 50 studies (98 %), and the false-negative rate was 9.8 %. The DPDP approach showed significant improvement over an existing approach and was used to forecast the magnitude of 198 DDIs that have not been studied.
conclusionThis approach can be used to avoid unnecessary clinical DDI studies during new drug development.
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