Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compounds

Calculation of molecular lipophilicity: State-of-the-art and comparison of log P methods on more than 96,000 compounds

Publication: J Pharm Sci
Software: ADMET Predictor®

We first review the state-of-the-art in development of log P prediction approaches falling in two major categories: substructure-based and property-based methods.

Application of patient population-derived pharmacokinetic-pharmacodynamic relationships to tigecycline breakpoint determination for staphylococci and streptococci

Application of patient population-derived pharmacokinetic-pharmacodynamic relationships to tigecycline breakpoint determination for staphylococci and streptococci

Division: Cognigen

Correctly determined susceptibility breakpoints are important to both the individual patient and to society at large. A previously derived patient population...

Toward an In Vivo Dissolution Methodology: A Comparison of Phosphate and Bicarbonate Buffers

Toward an In Vivo Dissolution Methodology: A Comparison of Phosphate and Bicarbonate Buffers

Publication: Mol Pharm
Software: ADMET Predictor®

The purpose of this research was to evaluate the difference between the pharmaceutical phosphate buffers and the gastrointestinal bicarbonates in dissolution of ketoprofen and indomethacin...

Analysis of Risk Factors in Human Bioequivalence Study That Incur Bioinequivalence of Oral Drug Products

Analysis of Risk Factors in Human Bioequivalence Study That Incur Bioinequivalence of Oral Drug Products

Publication: Mol Pharm
Software: ADMET Predictor®

In the study of human bioequivalence (BE), newly developed oral products sometimes fail to prove BE with a reference product due to the high variability in pharmacokinetic (PK)...

Busting the Black Box Myth: Designing Out Unwanted ADMET Properties with Machine Learning Approaches

Busting the Black Box Myth: Designing Out Unwanted ADMET Properties with Machine Learning Approaches

Publication: CICSJ Bulletin
Software: ADMET Predictor®
Division: Simulations Plus

Drug design is usually understood as “an inventive process of finding new medications based on the knowledge of the biological target” – according to the...

Omeprazole: Physiologically Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-Drug Interactions (DDI)

Omeprazole: Physiologically Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-Drug Interactions (DDI)

Conference: AAPS
Division: Simulations Plus

To optimize a PBPK model of omeprazole for prediction of DDIs with respect to polymorphic expression of CYP enzymes. Omeprazole absorption and pharmacokinetics were simulated using GastroPlus™.

Azole Antifungals: Physiologically-Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-Drug Interactions (DDIs)

Azole Antifungals: Physiologically-Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-Drug Interactions (DDIs)

Division: Simulations Plus

Develop PBPK models for azole antifungals for prediction of DDIs. The absorption and pharmacokinetics of azole antifungals were simulated using GastroPlus™. The program's Advanced Compartmental and…

Azole Antifungals: Physiologically-Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-drug Interactions (DDIs)

Azole Antifungals: Physiologically-Based Pharmacokinetic (PBPK) Modeling and Prediction of Drug-drug Interactions (DDIs)

Conference: Rosenon
Software: GastroPlus®
Division: Simulations Plus

Download the poster presented at the Rosenon conference in 2009 on the development of PBPK models for common azole antifungals and DDI predictions

Use of a clinically derived exposure-response relationship to evaluate potential tigecycline-Enterobacteriaceae susceptibility breakpoints

Use of a clinically derived exposure-response relationship to evaluate potential tigecycline-Enterobacteriaceae susceptibility breakpoints

Publication: Diagn Microbiol Infect Dis
Division: Cognigen

Potential tigecycline-Enterobacteriaceae susceptibility breakpoints were evaluated using 2 approaches, which differed in the nature of the probabilities assessed by MIC value.

Prediction of drug-drug interaction (DDI) between cilostazol and substrates or inhibitors of CYP 2C19 and 3A4

Prediction of drug-drug interaction (DDI) between cilostazol and substrates or inhibitors of CYP 2C19 and 3A4

Software: GastroPlus®
Division: Simulations Plus

The aim of this study was to validate the utility of physiologically based pharamcokinetic (PBPK) models fore predictioin of DDI between cilostazol, kectoconazole, omeprazole and quindine.