Matthew M. Riggs, Ph.D., FISoP

Chief Science Officer

Matt offers over 16 years of industry experience including the application of modeling and simulation for clinical pharmacology and later phase drug development decisions. Matt’s interests include the development and application of mechanistic exposure-response and systems pharmacology models to quantitatively integrate physiology, pharmacology, senescence and disease understandings; this to guide translational and clinical research toward improved preventative and interventional therapeutics.

Recent publications by this scientist

Hands-On Tutorial: Introduction to Immuno-Oncology (IO) Quantitative Systems Pharmacology (QSP) Modeling Using the Open Source Julia Programming Language

November 14, 2023

ACoP14 pre-meeting workshop. Highlights include exploring Julia as an open source alternative for QSP support of model-informed drug development, gaining insights into IO QSP modeling for antibody drug conjugate (ADCs) and bispecific mAb (bsAb) therapies to drive your own implementations of Project Optimus, and accessing open source Julia versions of two pivotal IO models and parameterizations.

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An Open Source Package Suite in Julia to Facilitate QSP Modeling and Simulation

January 30, 2024

Presented at ACoP14. Here, we introduce a pair of packages PMParameterized.jl which simplifies specification of parameters and initial conditions for Ordinary Differential Equation models, and PMSimulator.jl which enables complex dosing, inputs and events. Together these packages result in stateful, reproducible models and simulation for a quantitative systems pharmacology and pharmacometrics workflow in the Julia language.

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Quantitative Systems Pharmacology in Model-Informed Drug Development

October 24, 2023

When tailored for specific questions, QSP models enhance our grasp of clinical observations, guiding research with informed decisions, especially when they incorporate mechanistic insights. These models facilitate the integration of theory and data to test our understanding and explore the root causes of events. By offering quantifiable insights into the interactions within physiology, disease, and pharmacology, QSP models steer further research, impacting study design and biomarker selection. The presentation will encompass case studies on monoclonal antibody (mAb) development in bone health (osteoporosis), infectious disease (SARS-CoV-2), and oncology (relapsed/refractory diffuse large B-cell lymphoma).

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