Co-developed with CSL Behring, this research introduces a high-resolution model that simulates hepatocyte turnover,  episomal retention and coagulation factor IX (FIX) expression  in virtual patients treated with Etranacogene Dezaparvovec ( HEMGENIX).  The model captured clinical variability before recent clinical readouts were available, and projects FIX expression durability  over two decades.

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.

Presented at ACoP 2024. The Bone Health QSP model was extended by incorporating XLH disease mechanisms and burosumab impact on serum phosphate and other biomarkers using clinical data from adult and pediatric patients with XLH. The model reproduced clinically observed changes in pharmacodynamic markers in both adult and pediatric patients with XLH; normalization of serum phosphate with burosumab treatment was successfully replicated, facilitating a better understanding of burosumab dosing in patients with XLH going forward. The model could potentially be used to optimize treatment in the clinical setting.

Presented at ACoP 2024. This poster described a QSP model that predicted the efficacy of loncastuximab tesirine (an antibody-drug conjugate) and mosunetuzumab/ glofitamab (T cell engagers) combination therapy, following the protocol of ongoing LOTIS-7 clinical trial. The model predicted keeping patients on combination therapy for longer but reduced the loncastuximab tesirine per treatment cycle would yield more tumor volume reduction.

Presented at ACoP 2024. The poster presents a framework for pharmacometric and quantitative systems pharmacology (QSP) model composition using open-source Julia tools. This framework allows for seamless integration and reuse of independent model components, facilitating the creation of complex models from simpler ones, and demonstrating applications in drug interactions, viral dynamics, and bispecific antibody modeling.

Presented at ACCP Annual Meeting 2024, this poster highlights novel research on innovative combination therapies for relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). Our study focuses on a physiologically-based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) model for Loncastuximab Tesirine in combination with Mosunetuzumab or Glofitama.

Presented at ACCP Annual Meeting 2024, this poster highlights a combination QSP model for Loncastuximab Tesirine and Epcoritamab in relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL), predicting potential anti-tumor synergies in proposed clinical trials.

Neutralizing monoclonal antibodies (mAb) have emerged as promising therapeutics for COVID-19, with research efforts accelerated through open-access in silico models. Innovative approaches, including a physiologically-based pharmacokinetic (PBPK) model and a longitudinal SARS-CoV-2 viral dynamic model, facilitated the selection of optimal mAb candidate and therapeutic dose. By utilizing these models, the first-in-human trial of bamlanivimab (NCT04411628) initiated with a conservative dose of 700 mg, aiming to achieve maximum therapeutic effect while ensuring safety and tolerability.

Presented at AACR Annual Meeting 2024. QSP model simulations were used to predict anti-tumor efficacy and guide dosing of the antibody-drug conjugate Loncastuximab tesirine combined with T cell-dependent bispecific antibodies, Mosunetuzumab or Glofitamab for the treatment of B-cell malignancies.

Engineered T cells, particularly CAR T cells, have revolutionized hematological cancer treatment. However, their complexity poses challenges. This research explores how mathematical models, utilizing clinical data, can elucidate relationships between product characteristics, patient physiology, and clinical outcomes, thereby facilitating the development of next-generation cell therapies.

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.

Oral presentation for ACoP14 Abstract Quality Award winner. The Hierarchical Deep Compartment Modeling (HDCM) framework introduced in this abstract was developed using open-source tools in the Julia Programming Language and integrated Bayesian inference to quantify the uncertainty around the model parameters. It provides a convenient, readily accessible HDCM framework to the pharmacometrics community interested in applying deep learning to hierarchical compartmental models.

This study explores Lonca’s efficacy across varying CD19 expression levels, revealing its effectiveness in patients, regardless of low or undetectable CD19 levels by conventional methods. The study integrates quantitative systems pharmacology (QSP) modeling to predict treatment responses, indicating that CD19 expression alone may not predict Lonca’s effectiveness, however, response predictions are improved by considering CD19 surface density.

Presented at ACoP14. DQSP framework successfully implemented a UDE that characterized the PK of remoxipride and its effect on PRL release from lactotrophs to plasma. The model also characterized the positive feedback effect of plasma PRL on lactotroph PRL stimulation using an ANN.

Presented at ACoP14. The differentiation of mammalian hematopoietic stem cells (HSCs) is complex and multiscale, providing an opportunity for mathematical modeling and simulation to aid in mechanistic understanding, and ultimately, to inform drug development efforts. Historically, HSC mathematical models were focused on the development of a subset of cells, but mathematical models encompassing the overall cellular system’s complexity are rarely available. Here, an integrated quantitative systems pharmacology (QSP) model that characterizes multi-organ HSC differentiation was developed by integrating literature models and adding novel features.

Presented at ACoP14. Analysis of the QSP model found that the internalization rate of the target receptors may be an important, yet often underestimated, factor for understanding bsAb efficacy in vitro. Simulations of the model indicated that high rates of receptor turnover can increase model predictions of efficacy, particularly at higher antibody concentrations.

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.

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).

A novel QSP framework integrating PBPK modeling with tumor dynamics was developed using literature and in-house data. By employing a virtual population reflecting patients treated with Lonca, it is possible to evaluate indication, clinical population selection, influence of clinical study covariates, disease phenotypes, and CD19 expression levels on clinical responses

Antibody-drug conjugates (ADCs) are promising anti-cancer drugs but often cause toxicities in clinical use. This poster presents a new model that predicts toxicities of ADCs, including liver and lung effects for drugs like T-DM1 and T-Dxd, and high hepatotoxicity in CM.

As Julia usage continues to grow within regulated biomedical environments, it is vital to ensure analyses are traceable and reproducible. Conducting analyses in an open-science manner is also critical to expand the adoption of Julia and to facilitate the infrastructure growth of Julia as an accessible ecosystem. A step-by-step model-building example of a classic monoclonal antibody-drug conjugate PBPK/tumor dynamics system illustrates how to develop such a reproducible open-science framework.

Matthew Riggs. Presented at the third World Conference on Pharmacometrics (WCoP) virtual hybrid meeting. 31 March 2022, South Africa and online. See video here for the first half of this presentation covering “Compare and Contrast” presented by Stacey Tannenbaum, Ph.D.

WCoP2022-Riggs-CompareCollide

Tim Knab, Ahmed Elmokadem, Emmanuel Chigutsa, Eric Jordie, Matthew Riggs, Patricia Brown-Augsburger, Christopher Wiethoff, Ajay Nirula, Jenny Y Chien, Lisa O’Brien.  Poster presented at Population Approach Group Europe Annual Meeting; 2-3 and 6-7 September 2021.  Poster I-64.

Jordie EB, Gibiansky L, Knab T, Lemenuel-Diot A, Ravva P, Zwanziger E, Jolivet S, Bhardwaj R, Hernández-Sánchez J, Nasmyth-Miller C, Sturm S. Br J Clin Pharmacol. 2021;1-13. doi:10.1111/bcp.15059

Elmokadem A, Bruno CD, Housand C, Jordie EB, Chow CR, Lesko LJ, Greenblatt DJ.  J Exp Pharmacol.  2021; 1– 10. doi:10.1002/jcph.1946

Rowland Yeo K, Hennig S, Krishnaswami S, Strydom N, Ayyar VS, French J, Sinha V, Sobie E, Zhao P, Friberg LE, Mentré F.
CPT Pharmacometrics Syst Pharmacol. 2021 Jul;10(7):649-657. doi: 10.1002/psp4.12680.

Matthew M. Riggs, Howard A. Ball, Kanji Komatsu, Akihiro Yamada.  Poster presented at 2020 American Conference on Pharmacometrics (ACoP11) virtual meeting. 10 November 2020.

Model code and supporting material is available here.

Eric Burroughs Jordie, Ahmed Elmokadem, Mohammad Azab, and Aram Oganesian

Presented by Eric Jordie at American Conference on Pharmacometrics 2019.

Presented by Marc Gastonguay, Ph.D at Development of Best Practices in Physiologically Based Pharmacokinetic Modeling to Support Clinical Pharmacology Regulatory Decision -Making Sponsored by the Office of Clinical Pharmacology OTS, CDER, U.S. Food and Drug Administration (FDA) on 18 November 2019. Event information here. Slides are here

Presented by Ahmed Elmokadem, Ph.D at the 9th Annual CTSI Disease and Therapeutic Response Modeling and Simulation Symposium at Indiana University School of Medicine on November 12, 2019. Event details can be found here.

Riggs, Matthew. Presentation at ISoPNE iPSP event. Cambridge, MA. 26 Aug 2019.

Gastonguay MS, Russell S, Freling R, Riggs M, Kay K, Utsey K, Elmokadem A.

Poster presented at 2019 American Society for Clinical Pharmacology & Therapeutics (ASCPT). Washington DC. 14 March 2019.

Poster presented at ISoP Regional QSP Day 2019. Princeton, NJ. 16 July 2019.

Riggs MM. Slides presented at AAPS Forum to Connect Predictive Modelers in Boston, MA. 6 May 2019.

Riggs MM. Clin Pharmacol Ther. 98:394. 18 December 2018. doi: 10.1002/cpt.1287

Trame MN, Riggs MM, Biliouris K, Marathe D, Mettetal J, Post TM, Rizk ML, Visser SAG, Musante CJ.  CPT Pharmacometrics Syst Pharmacol. doi:10.1002/psp4.12313. 21 August 2018.

Riggs, M.  Presented at Pharmacology 2016, annual meeting of the British Pharmacological Society, London, December 2016.

Eudy RJ, Riggs MM, Baron K.  Presented at the Sanofi–MSISB Mount Sinai Systems Pharmacology Symposium, June 2016.

Baron KT and Gastonguay MR.  Presented at the 6th American Conference on Pharmacometrics (ACoP), Arlington, VA; October 2015.

Eudy RF, Gillespie WR, Riggs MM, Gastonguay MR.  Presented at the 6th American Conference on Pharmacometrics (ACoP), Arlington, VA; October 2015.

Gastonguay MR and Godfrey CJ.  American College of Clinical Pharmacology (ACCP) Workshop, September 26, 2015.

Eudy RJ, Gastonguay MR, Baron KT, and Riggs MM.  CPT: Pharmacometrics & Systems Pharmacology. 2015;4(9):527-536. doi:10.1002/psp4.12013.

Eudy RJ, Gastonguay MR, Baron KT, Riggs MM.  Presented at the Annual Meeting of the Population Group in Europe (PAGE), Hersonnisos, Greece; June 2015.

Peterson MC and Riggs MM.  CPT: Pharmacometrics & Systems Pharmacology, 2015 Mar; 4(3).

Riggs MM. Presented at Sunrise Session: Integration of Systems Modeling in Clinical Development: Successes, Challenges, and Future Outlook at the American American Society for Clinical Pharmacology and Therapeutics Annual Meeting, 2013.

Riggs M.  Presented at the Annual Meeting of the American Society for Clinical Pharmacology and Therapeutics, 2013.

Kyle T. Baron, Matthew M. Riggs, Ryoko Sawamura, Takako Shimizu, Fumihiko Okada, Jin Zhou, Takahiro Shibayama, Mendel Jansen. Presented at the American Society of Bone and Mineral Research (ASBMR), October, 2013.

Peterson MC and Riggs MM. CPT Pharmacometrics Syst Pharmacol. 2012 Nov; 1(11): e14. Published online 2012 Nov 14. doi: 10.1038/psp.2012.15

Riggs MM, Bennetts M, van der Graaf PH, and Martin SW.  CPT Pharmacometrics Syst Pharmacol. 2012 Oct; 1(10): e11. Published online 2012 Oct 17. doi: 10.1038/psp.2012.10

Riggs MM, Baron KT, Plan EL, Gastonguay MR. Presented at American Society of Bone Mineral Research (ASBMR) Annual Meeting, Minneapolis, MN; October 14, 2012 (Abstract SU0363).

Plan EL, Baron KT, Gastonguay MR, French JL, Gillespie WR, and Riggs MM. Presented at the 21st Annual Meeting of the Population Approach Group Europe (PAGE), Venice, Italy, 2012, Abstract 2592.

Riggs MM. . Presented at the AAPS Biotechnology Conference, San Diego, CA; May 22, 2012.

Riggs MM, Peterson MC, Gastonguay MR. The Journal of Clinical Pharmacology. 52(1 Suppl):45S-53S. January 2012. doi:10.1177/0091270011412967

Riggs MM. Presented at First Indiana Clinical and Translational Sciences Institute (CTSI) Symposium on Disease and Therapeutic Response Modeling. Indiana University – Purdue University Indianapolis; Indianapolis, IN; 13 November 2011.