Population Pharmacokinetic, Exposure-Response, and Time-To-Event Analyses of Probenecid in Symptomatic, Non-Hospitalized Patients with COVID-19

Population Pharmacokinetic, Exposure-Response, and Time-To-Event Analyses of Probenecid in Symptomatic, Non-Hospitalized Patients with COVID-19

Conference: ACoP

Probenecid, an oral uricosuric agent, is being developed as a broad-spectrum antiviral and was evaluated for potential suppressive effects of SARS-Cov-2 replication in a Phase 2 study in patients with symptomatic, mild-to-moderate COVID-19

ADMET Predictor® Tutorial Series: HTPK Part 1

ADMET Predictor® Tutorial Series: HTPK Part 1

Authors: Jamois E
Software: ADMET Predictor®
Division: Cheminformatics

In this first part of the HTPK series, we demonstrate how to run high-throughput pharmacokinetic (HTPK) simulations directly from chemical structures. Learn to calculate fraction absorbed (%FA), fraction bioavailable (%FB), and key PK parameters like Cmax, Tmax, and clearance across multiple doses.

ADMET Predictor® Tutorial Series: MedChem Studio™ Part 2

ADMET Predictor® Tutorial Series: MedChem Studio™ Part 2

Authors: Jamois E
Software: ADMET Predictor®
Division: Cheminformatics

In the second part of the MedChem Studio™ series, we demonstrate how to evaluate compound subsets and optimize virtual libraries. This tutorial covers distribution analysis to compare virtual vs. exemplified compounds and introduces matched molecular pair (MMP) analysis for property cliff detection.

ADMET Predictor® Tutorial Series: MedChem Studio™ Part 1

ADMET Predictor® Tutorial Series: MedChem Studio™ Part 1

Authors: Jamois E
Software: ADMET Predictor®
Division: Cheminformatics

In this first installment of the MedChem Studio™ series, we demonstrate powerful clustering and group analysis tools. Learn how to organize large data sets into chemotypes, align scaffolds for visual comparison, and perform R-group decomposition to identify SAR trends

ADMET Predictor® Tutorial Series: Predicting Metabolites

ADMET Predictor® Tutorial Series: Predicting Metabolites

Authors: Lawless M
Software: ADMET Predictor®
Division: Cheminformatics

In this video, we explore advanced tools for predicting drug metabolites across major enzyme classes, including Cytochrome P450 (SIP), Aldehyde Oxidase (AOX), and UGTs. You will learn how to identify atomic sites of metabolism, interpret scoring systems, and visualize structural transformations within MedChem Designer™.

ADMET Predictor® Tutorial Series: Model Editor

ADMET Predictor® Tutorial Series: Model Editor

Authors: Lawless M
Software: ADMET Predictor®
Division: Cheminformatics

In this video, we provide a detailed overview of the Model Editor, explaining how to manage prediction modules and interpret applicability domains. Key topics include descriptor sensitivity analysis (DSA), structure sensitivity analysis (SSA), and regression uncertainty.

ADMET Predictor® Tutorial Series: Predicting pKa

ADMET Predictor® Tutorial Series: Predicting pKa

Authors: Lawless M
Software: ADMET Predictor®
Division: Cheminformatics

In this video, Simulations Plus demonstrates how to predict pKa values and their critical impact on pharmacokinetic properties like solubility and permeability. You will learn how to interpret microstate displays, analyze ionization curves, and understand how pKa influences drug behavior in the GI tract.

ADMET Predictor® Tutorial Series: Working with Data and Graphs

ADMET Predictor® Tutorial Series: Working with Data and Graphs

Authors: Lawless M
Software: ADMET Predictor®
Division: Cheminformatics

In this video, Simulations Plus explains how to examine data and utilize advanced graphing tools within the platform. Key features include managing spreadsheet columns, creating custom tabs, and visualizing molecular properties through various chart types.

ADMET Predictor® Tutorial Series: Calculating Properties

ADMET Predictor® Tutorial Series: Calculating Properties

Authors: Jamois E
Software: ADMET Predictor®
Division: Cheminformatics

In this video, we explore the core functionality of calculating chemical and biological properties. It covers selecting specific models, adjusting pH settings, and configuring multi-threading to maximize processing speed.

ADMET Predictor® Tutorial Series: MedChem Designer

ADMET Predictor® Tutorial Series: MedChem Designer

Authors: Jamois E
Software: ADMET Predictor®
Division: Cheminformatics

In this video, we provide an interactive tutorial on using MedChem Designer to edit, create, and save chemical structures. You will also learn how to calculate ADMET properties directly within the designer and import structures from online resources like DrugBank.

Metabolic Profiling and Detoxification of Eupalinolide A and B in Human Liver Microsomal Systems

Metabolic Profiling and Detoxification of Eupalinolide A and B in Human Liver Microsomal Systems

Publication: Toxics
Software: ADMET Predictor®

Eupalinolide A (EA, Z-configuration) and Eupalinolide B (EB, E-configuration) are cis-trans isomeric sesquiterpenoid monomers isolated from Eupatorium lindleyanum DC. (Asteraceae).

Development of a Quantitative Systems Toxicology Model to Predict Drug-Induced Liver Injury in Pediatrics

Development of a Quantitative Systems Toxicology Model to Predict Drug-Induced Liver Injury in Pediatrics

Conference: ACoP
Software: DILIsym®, GastroPlus®

Drug-induced liver injury (DILI) is an underrecognized cause of pediatric liver disease which accounts for almost 20% of pediatric acute liver failure cases, and is a major reason for liver transplantation in the USA [1].

A Pediatric Pbpk Model of Atropine Gel To Predict Atropine Levels in Children With Neurological Disorders After Administration to Oral Cavity

A Pediatric Pbpk Model of Atropine Gel To Predict Atropine Levels in Children With Neurological Disorders After Administration to Oral Cavity

Conference: ACoP
Software: GastroPlus®

Sialorrhea, or excessive salivation, is a chronic and serious problem in children with cerebral palsy (CP) and neurodevelopmental disorders.[1–5] Sialorrhea occurs in up to 60% of children with CP...

Automated Concentration-QT data preparation, model selection and reporting in R

Automated Concentration-QT data preparation, model selection and reporting in R

Conference: International Society of Pharmacometrics
Software: Monolix®

Since the publication of the ICH E14 guidance in 2015, QT interval prolongation as-sessment can be carried out with a concentration-QTc modeling approach as part of single- or mul-tiple- dose escalation studies, instead of conducting a thorough QT/QTc study.

mlxDesignEval: A novel R package for design evaluation based on MonolixSuite, and its comparison to popED and PFIM

mlxDesignEval: A novel R package for design evaluation based on MonolixSuite, and its comparison to popED and PFIM

Conference: American Conference of Pharmacometrics
Software: Monolix®, Simulx®

Designing clinical trials to support population PK/PD modeling requires careful choices of sampling times, number of subjects, dose groups and other trial features to
ensure precise parameter estimation - with low relative standard errors [1].