Daniel Kirouac, Ph.D.

Vice President of Quantitative Systems Pharmacology (QSP)

Dan brings over a decade of experience spanning academia, small biotech, big pharma, and consulting roles. Dan’s expertise includes computational modeling and translational science. His career highlights include spearheading the establishment of scientific teams, developing novel computational methods, and integrating advanced technologies into the research and development pipeline. Dan is extensively engaged in the wider scientific community. He has co-authored 27 publications and actively participated in over 30 scientific symposia worldwide, focusing on systems pharmacology, bioinformatics, and cancer therapy. Additionally, he holds an adjunct professorship at the University of British Columbia and serves on leadership committees at the University of Florida and the American Society for Clinical Pharmacology.

 

 

Recent publications by this scientist

QSP Modeling of Loncastuximab Tesirine-lpyl Combined with T Cell-Dependent Bispecific Antibodies Bridges Knowledge and Dose Regimen Strategy

June 13, 2025

Presented at ASCPT Annual Meeting 2025. The virtual population-based lymphoma QSP model enabled systematic exploration of alternate drug combinations, dosing schemes, clinical covariates and resultant effect on anti-tumor activity in silico. The results of the LOTIS-7 study (NCT04970901), a platform study evaluating loncastuximab tesirine in combination with glofitamab, will soon be available to assess the accuracy of the model predictions.

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Pharmacometric Machine Learning: Integrating Neural Networks for Flexible, Advanced Covariate Analysis

June 13, 2025

Presented at ASCPT 2025 Annual Meeting. Neural networks can be integrated with traditional pharmacometric models using several free open-source programming languages. Both Julia and R environments are suitable platforms, but there are tradeoffs regarding development speed, built-in capabilities, and documentation. DCM simplifies the covariate modeling process and uncovers complex, non-linear relationships in computationally efficient workflows.

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Making Drugs from T Cells: Mathematical Model-Informed Design and Deployment of Next Generation T Cell Therapies

March 25, 2025

Presented at the Boston Society Gene and Cell Therapy Conference 2025. The development landscape for cell therapies is rapidly evolving, driven by scientific advancements and increasing competitive pressures. Modeling and simulation technologies are playing a critical role in navigating this dynamic environment.

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