DILIsym 8A New Features for Predicting & Understand Drug-Induced Liver Injury

DILIsym 8A New Features for Predicting & Understand Drug-Induced Liver Injury

Authors: Howell BA
Software: DILIsym®
Division: DILIsym Services

So how can DILIsym help my organization? Predict DILI liabilities beforehand and save $$$, Choose the lead candidate most likely to succeed from a DILI standpoint, Communicate with regulators on safety issues with information they have requested from others numerous times and from a platform they license (FDA) & keep patients safer.

HTPK: Conducting PK modeling and simulations at high speed

HTPK: Conducting PK modeling and simulations at high speed

Conference: AAPS
Division: Simulations Plus

HTPK lightens the burden of collecting and preparing input variables for full blown PK simulations by using structure-based predictions.

Using in-silico Models to Integrate in-vitro Data to Support Virtual Trials for Cost Effective Drug Development

Using in-silico Models to Integrate in-vitro Data to Support Virtual Trials for Cost Effective Drug Development

Authors: Lukacova V
Conference: AAPS
Software: GastroPlus®
Division: Simulations Plus

PBPK models allow incorporating different types of in vitro measurements into single platform to account for all processes affecting drug’s absorption, distribution and elimination.

Use of In Silico Mechanistic Models to Support Interspecies Extrapolation of Oral Bioavailability and Formulation Optimization: Model Example Using GastroPlus™

Use of In Silico Mechanistic Models to Support Interspecies Extrapolation of Oral Bioavailability and Formulation Optimization: Model Example Using GastroPlus™

Authors: Lukacova V
Conference: USP
Software: GastroPlus®
Division: Simulations Plus

PBPK models provide unique platform to combine information from in vitro, in silico and animal assays for accurate prediction of complex drug behavior in vivo

Applications of Multi-Class Machine Learning Models to Drug Design

Applications of Multi-Class Machine Learning Models to Drug Design

Conference: ACS
Software: ADMET Predictor®
Division: Simulations Plus

Until recently, machine learning classification models in Cheminformatics literature have generally modeled binary endpoints (active/inactive, substrate/non-substrate, toxic/non-toxic, etc.)

Using DILIsym, A Quantitative Systems Toxicology (QST) Software Tool of Drug-Induced Liver Injury (DILI), To Assess DILI Risk in Drug Development

Using DILIsym, A Quantitative Systems Toxicology (QST) Software Tool of Drug-Induced Liver Injury (DILI), To Assess DILI Risk in Drug Development

Authors: Howell BA
Conference: BIT IDDST
Software: DILIsym®
Division: DILIsym Services

A combination of multiple mechanistic, in silico modeling approaches can facilitate drug discovery (QSAR, PBPK, QSP and QST).

Incorporating Mechanistic Modeling & Simulation to Assist with Formulation Development and Regulatory Evaluations

Incorporating Mechanistic Modeling & Simulation to Assist with Formulation Development and Regulatory Evaluations

Authors: Lukacova V
Software: GastroPlus®
Division: Simulations Plus

A mechanistic, physiologically-based absorption/PK model was constructed in GastroPlus and validated across three dose levels (50, 100, and 300 mg) using in vivo data collected from tablets manufactured…

Discovery PBPK: How to Estimate the Expected Accuracy of ISIVB and IVIVB for New Chemical Entities

Discovery PBPK: How to Estimate the Expected Accuracy of ISIVB and IVIVB for New Chemical Entities

Authors: Bolger MB
Conference: Asia Pacific ISSX
Division: Simulations Plus

PBPK modeling and simulation can be successfully used in the lead optimization phase of drug discovery. Using CLloc, accurate bioavailability can be predicted for new compounds in a chemical series.

Applying the QSP Model NAFLDsym® to Predict and Understand NASH Treatments

Applying the QSP Model NAFLDsym® to Predict and Understand NASH Treatments

Authors: Siler SQ
Conference: NASH Summit
Software: DILIsym®, NAFLDsym®
Division: DILIsym Services

NAFLDsym is a mechanistic, mathematical, QSP model 1. Can predict efficacy for compounds that modulate lipids and/or lipotoxicity with v1A 2. NAFLDsym v2A will also include inflammation and fibrosis submodels…

Exploring Pharmacokinetic SARs Early in Drug Discovery

Exploring Pharmacokinetic SARs Early in Drug Discovery

Authors: Clark RD
Conference: UKQSAR
Division: Simulations Plus

Late-stage attrition due to obviously bad physicochemical properties has been reduced by application of rules-ofthumb like Lipinski’s Rule of Five. Failure due to lack of efficacy remains a major issue.