The approach and the data behind this website are described in following papers

Quantitative Prediction of Adverse Event Probability Due to Pharmacokinetic Interactions.

Drug Saf. 2022 Jun 23.

Model-Based Comparative Analysis of Rifampicin and Rifabutin Drug-Drug Interaction Profile.

Antimicrob Agents Chemother. 2021 Aug 17

Does DDI-Predictor Help Pharmacists to Detect Drug-Drug Interactions and Resolve Medication Issues More Effectively?

Metabolites 2021 Mar 17;11(3):173.

Drug interactions between the emergency contraception drugs and cytochrome inducers: literature review and quantitative prediction.

Fundam Clin Pharmacol. 2020 Aug 19

Quantitative Prediction of Interactions Mediated by Transporters and Cytochromes: Application to Organic Anion Transporting Polypeptides, Breast Cancer Resistance Protein and Cytochrome 2C8.

Clin Pharmacokinet. 2019 Dec 16.

A Generic Model for Quantitative Prediction of Interactions Mediated by Efflux Transporters and Cytochromes: Application to P-Glycoprotein and Cytochrome 3A4.

Clin Pharmacokinet. 2018 Sep 8;58(4):503-523.

Identification of Cytochrome P450-Mediated Drug-Drug Interactions at Risk in Cases of Gene Polymorphisms by Using a Quantitative Prediction Model.

Clin Pharmacokinet. 2018 Dec;57(12):1581-1591

Semi-Mechanistic Model for Predicting the Dosing Rate in Children and Neonates for Drugs Mainly Eliminated by Cytochrome Metabolism

Clin Pharmacokinet. 2018 Jul;57(7):831-841

Mechanisms of drug-drug interaction between rifampicin and fusidic acid.

Br J Clin Pharmacol. 2017 Aug;83(8):1862-1864.

Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites by Physiologically Based Pharmacokinetic Models: Is it worth?

CPT Pharmacometrics Syst Pharmacol. 2017; Apr;6(4):226.

A model for predicting the interindividual variability of drug-drug interactions.

The AAPS Journal. 2017; Mar;19(2):497-509.

Quantitative Prediction of Drug Interactions Caused by CYP1A2 Inhibitors and Inducers.

Clin Pharmacokinetics 2016 Aug;55(8):977-90.

Comparison of the static in vivo approach to a physiologically based pharmacokinetic approach for metabolic drug–drug interactions prediction.

Int J Pharmacokinetics Posted online on 4 Apr 2016

A Prediction Model of Drug Exposure in Cirrhotic Patients According to Child-Pugh Classification.

Clinical Pharmacokinetics 2015 Dec;54(12):1245-58.

Pharmacokinetic drug interaction between cyclosporine and imatinib in bone marrow transplant children and model-based reappraisal of imatinib drug interaction profile.

Ther Drug Monit. 2014 Dec;36(6):724-9.

Reliability and Extension of Quantitative Prediction of CYP3A4-Mediated Drug Interactions Based on Clinical Data.

AAPS Journal 2014 Nov;16(6):1309-20.

In Vivo Quantitative Prediction of the Effect of Gene Polymorphisms and Drug Interactions on Drug Exposure for CYP2C19 Substrates.

AAPS Journal 2013 Apr;15(2):415-26.

Quantitative Prediction of the Impact of Drug Interactions and Genetic Polymorphisms on Cytochrome P450 2C9 Substrate Exposure.

Clinical Pharmacokinetics 2013 Mar;52(3):199-209.

Impact of genetic polymorphism on drug-drug interactions mediated by cytochromes: a general approach.

AAPS Journal 2013;15(4):1242-52

Quantitative prediction of cytochrome P450 (CYP) 2D6-mediated drug interactions.

Clinical Pharmacokinetics 2011 Aug;50(8):519-30.

Genotype-based quantitative prediction of drug exposure for drugs metabolized by CYP2D6.

Clinical Pharmacology And Therapeutics 2011 Oct;90(4):582-7.

General framework for the prediction of oral drug interactions caused by CYP3A4 induction from in vivo information.

Clinical Pharmacokinetics 2008;47(10):669-80.

General framework for the quantitative prediction of CYP3A4-mediated oral drug interactions based on the AUC increase by coadministration of standard drugs.

Clinical Pharmacokinetics. 2007;46(8):681-96.