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

A Quantitative Systems Pharmacology Platform for Atopic Dermatitis and Asthma: One Immune Cascade Calibrated to Four Biologics

October 19, 2026

Timothy Knab¹, Cole Zmurchok¹, Jimena Davis¹, Dan Kirouac¹, Richard Allen², Cody Herron²
¹Metrum Research Group, Boston, MA, USA; ²Pfizer Inc., Cambridge, MA, USA

Submitted to the 2026 American Conference on Pharmacometrics (ACoP 2026), an International Conference on Pharmacometrics in the US (ICoP – US).

Atopic dermatitis (AD) and asthma share a type-2 immune axis and the same biologics: dupilumab (anti-IL-4Rα), lebrikizumab (anti-IL-13) and tezepelumab (anti-TSLP), with mepolizumab (anti-IL-5) in asthma. Published QSP models describe each disease on its own. The objectives were to build one reaction network in which the same immune cascade, placed in skin or
airway, gives AD or asthma, and calibrate it to biologic responses in both, as well as use it to compare a combination across indications and asthma phenotypes, and to rank untested targets.

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A Modular PBPK-QSP Platform in Julia for Optimizing the Therapeutic Window of Antibody-Drug Conjugates: ADC In Silico Design Engine (AIDE)

October 19, 2026

Yuezhe Li, Jimena Davis, Timothy Knab, Cole Zmurchok, and Daniel C. Kirouac

Submitted to the 2026 American Conference on Pharmacometrics (ACoP 2026), an International Conference on Pharmacometrics in the US (ICoP – US).

Antibody-drug conjugates (ADCs) are a rapidly evolving class of oncology therapeutics designed to expand the therapeutic index of potent cytotoxic payloads by leveraging the specificity of monoclonal antibodies. Despite clinical successes, many ADC candidates fail in late-stage development due to dose-limiting toxicities or insufficient efficacy. To support preclinical evaluation and de-risk ADC development, a modular, customizable PBPK-QSP platform using the open-source Julia package ModelingToolkit.jl was developed. This platform integrates a whole-body PBPK submodel to characterize ADC and payload biodistribution with a QSP submodel designed to predict both potential off-target toxicities and anti-tumor efficacy.

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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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