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. 

Toward an improved prediction of human in vivo brain penetration

Toward an improved prediction of human in vivo brain penetration

Publication: Xenobiotica
Division: Simulations Plus

The penetration of drugs into the central nervous system is a composite of both the rate of drug uptake across the blood–brain barrier and the extent of distribution into brain tissue compartments.

General Approach to Calculation of Tissue:Plasma Partition Coefficients for Physiologically Based Pharmacokinetic (PBPK) Modeling

General Approach to Calculation of Tissue:Plasma Partition Coefficients for Physiologically Based Pharmacokinetic (PBPK) Modeling

Conference: AAPS
Software: GastroPlus®
Division: Simulations Plus

To conduct a comprehensive evaluation of methods for calculation of tissue/plasma partition coefficients with a focus on correct prediction of volume of distribution and recommendation for a general…

Role of Fraction Unbound in Plasma in Calculations of Tissue:Plasma Partition Coefficients

Role of Fraction Unbound in Plasma in Calculations of Tissue:Plasma Partition Coefficients

Conference: AAPS
Division: Simulations Plus

Previous investigations have shown that the Rodgers and Rowland method [Rodgers 2007] for prediction of tissue:plasma partition coefficients (Kps) provides good prediction for compounds with low to moderate…

Level A IVIVC Using a Comprehensive Absorption/PBPK Model for Metoprolol

Level A IVIVC Using a Comprehensive Absorption/PBPK Model for Metoprolol

Conference: AAPS
Software: GastroPlus®
Division: Simulations Plus

Wagner-Nelson,  Loo-Riegelman,  numerical  deconvolution,  and  convolution-based  methods  are conventional ways to form an in vitro-in vivo correlation (IVIVC). The ultimate goal for forming an IVIVC is to…

Beauty and the Beast?

Beauty and the Beast?

Several large Pharma companies have announced interest in acquiring small biotech companies. Many Pharma companies have reduced or eliminated drug discovery efforts, and with stock prices back at 2003 levels, there certainly is a great deal of sense in these acquisitions. But finding another way to integrate these companies and their development portfolio also makes a great deal of sense.

Kerfuffle! (pt 1)

Kerfuffle! (pt 1)

A kerfuffle is the polite term for a cascading series of errors that can be initiated by a seemingly innocuous event that then leads to other errors that seem to gain in severity and impact. Kerfuffles can appear in any line of work or play that involves a linked series of tasks with downstream implications. In fact, the modeling and simulation activities performed to support model-based drug development have the potential to produce a catalogue of kerfuffles that can culminate in the failure to deliver modeling and simulation results when they are needed for decision-making. Kerfuffles often have their origins in inadvertent oversights committed early in the study design and data collection process or in the commonplace shortcuts taken to deliver preliminary (“quick-and-dirty”) results for internal use.