Sessions:
Japan
Thursday, February 26, 2026 – 1:00 pm – 5:00 pm
6th Floor, Room 6A, TKP Shinagawa Conference Center
Korea
Wednesday, March 4, 2026 – 1:00 pm – 5:00 pm
37th Floor, Room Zeus, ASEM Tower
Summary
These interactive, hands-on workshop trains participants to use Certara IQ™, an AI-enabled QSP modeling platform that accelerates drug development. You will learn to build, optimize, and scale QSP models using AI-guided workflows, cloud-based simulations, and model libraries. Through the QSP case studies, you will see how Certara IQ streamlines systems pharmacology and supports confident decision-making across discovery to clinical stages.
Please select your preferred workshop location (Japan or Korea) when submitting your online registration.
Key takeaways
- Explore the latest QSP case studies and learn practical strategies to adopt QSP modeling in discovery and development projects for improved decision-making and accelerated innovation.
- Build and scale QSP models efficiently using AI-driven workflows, reusable model components, and cloud-based computing within Certara IQ.
- Optimize and validate models through automated parameter estimation, sensitivity analysis, and reproducibility tools to ensure regulatory readiness.
- Integrate QSP modeling software, Certara IQ, into cross-functional drug development workflows to enhance collaboration, data transparency, and translation from preclinical to clinical outcomes.
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Agenda
- Opportunities and challenges
- Certara IQ Application
- IQ Design Graphical Model Builder
- Generative AI for Model Validation
- (Demo) IQ Design
- Impact of QSP based EFA
- Implementing EFA with IQ Explore
- (Demo) IQ Explore
- Impact of QSP based FIH
- Intro to the First In Human Workflow
- (Demo) IQ Analyze and IQ First In Human Workflow
VP, Head of QSP Software, Certara
Dr. Apgar is the VP, Head of QSP Software at Certara, and co-founder of Applied BioMath (acquired by Certara in Dec 2023). Prior to this, Josh was a Principal Scientist in the Systems Biology Group of the Department of Immunology and Inflammation at Boehringer Ingelheim Pharmaceuticals. His work leveraged physics-based models to: translate in vitro and in vivo data, assess target feasibility, understand drug mechanism of action, and predict human doses. The ultimate goal of this work was to reduce late stage attrition in drug development through a deep and quantitative interrogation of drug pharmacology and disease pathophysiology.
Josh received his PhD from MIT in Biological Engineering where he worked on experiment design for Systems Biology, focusing on the identification of tractable experiments that could allow for the estimation of unknown parameters and reveal complex mechanisms in signal transduction networks. Before that Josh worked at Avaki to develop a highly scalable software platform to support High Performance Computing, and Enterprise Information Integration in the Life Sciences, and Engineering.
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