2-Day QST Virtual Workshop

September 21-22, 2020

This is a beginner’s course for clinicians, pharmaceutical/biotechnology scientists, and engineers in the areas of toxicology, clinical pharmacology, pharmacovigilance, DMPK and ADME – prior experience with DILIsym is not required.

What you will learn:
• concepts accepted by regulators related to drug-induced liver injury (DILI) monitoring and detection
• primary mechanisms often involved in DILI events
• mitochondrial dysfunction
• ROS
• bile acids
• lipotox
• in vitro assay design and execution for DILI-related mechanisms
• pharmacokinetics, including prediction of liver concentrations using GastroPlus^® and how this impacts DILI predictions

Why you should attend:
• Gain experience translating in vitro data into DILIsym parameter values, including the use of automated optimization
• Better understanding of simulating expected DILI outcomes for humans, rats, mice, and dogs
• Increase awareness of utilizing simulated populations (SimPops^®) to predict infrequent events in a diverse patient population

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Example Case Study

DSX Teaser

QSP Virtual Workshop

September 23, 2020

This is a beginner’s course for mechanistic modelers, pharmacologists, clinicians, pharmaceutical/biotechnology scientists, and engineers in the specific area of clinical and quantitative systems pharmacology (QSP) for nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH).

What you will learn:
• key components of NASH pathophysiology, including:
• steatosis
• lipotoxicity
• fibrosis
• inflammation
• examples of targets represented for in silico evaluation
• patient heterogeneity that makes these syndromes particularly challenging to develop effective treatments
• … and more!

Why you should attend:
• Gain experience translating pre-clinical and clinical data into NAFLDsym parameter values, including the use of sensitivity analyses and optimization
• Better understanding of simulating expected treatment outcomes for simulated NAFLD/NASH patients at various stages of the disease
• Increased awareness of validation and support for existing NAFLD/NASH simulated populations (SimPops) included in the software