In part two of the HTPK series, we explore the Parameter Sensitivity Analysis (PSA) tool to determine whether fraction absorbed is limited by solubility or permeability. The video also demonstrates how to increase simulation accuracy by integrating experimental data alongside in silico predictions
Population Pharmacokinetic, Exposure-Response, and Time-To-Event Analyses of Probenecid in Symptomatic, Non-Hospitalized Patients with COVID-19
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
Comparison of Population Pharmacokinetic Platforms, Monolix and Phoenix for Cephalexin in Infants
Cephalexin is a commonly used antibiotic for pediatric populations, however, data to guide effective oral dosing in young infants are limited.
Population Pharmacokinetics of Encorafenib and Binimetinib in Real-World Patients with BRAFV600E/K-Mutant Metastatic Melanoma
Encorafenib and binimetinib pharmacokinetic (PK) studies in real-world cancer patients remain scarce.
Integrating Systemic Toxicity and Toxicokinetic Data to Inform the Need for Subchronic Dog Studies in Human Health Safety Assessments of Agrochemicals
Regulatory testing for agrochemicals has traditionally included a 90-day toxicity study in a non-rodent species, usually the dog.
A Phase 1 Evaluation of Inhaled Oxytocin: Physiologically-Based Pharmacokinetic Model Informed Dosing of a Novelheat-Stable Oxytocin Delivery System
To develop and validate a physiologically-based pharmacokinetic (PBPK) modelenabling inhaled oxytocin dose selection for clinical evaluation.
ADMET Predictor® Tutorial Series: HTPK Part 1
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
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
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
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
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
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
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
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
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.
ADMET Predictor® Tutorial Series: Working with Files
In this video, we demonstrate how to open chemical structure files and import external property data. You will also see how to save progress using proprietary XDK session files.
Integrating Diverse Clinical Data into a Single Virtual Population with Thales™
As the complexity of drug development increases, researchers need quantitative systems pharmacology (QSP) models that incorporate virtual populations and can capture data spanning numerous clinical trial
Prediction of the Lurasidone–Posaconazole Drug–Drug Interaction Using Physiologically Based Pharmacokinetic Modeling
Lurasidone is an atypical antipsychotic drug that metabolized by cytochrome P4503A4 (CYP3A4). Posaconazole is a triazole antifungal agent known to inhibit CYP3A4activity.
Metabolic Profiling and Detoxification of Eupalinolide A and B in Human Liver Microsomal Systems
Eupalinolide A (EA, Z-configuration) and Eupalinolide B (EB, E-configuration) are cis-trans isomeric sesquiterpenoid monomers isolated from Eupatorium lindleyanum DC. (Asteraceae).
QST Modeling Using BIOLOGXsym and Mechanistic Toxicity Data from a Biomimetic Liver Microphysiology System Predicts Increased Susceptibility to Nivolumab-Mediated Hepatotoxicity in MASLD Patients
Immune checkpoint inhibitor-related hepatotoxicity is a significant clinical concern