MS06 - OTHE-06

A New Wave of Mathematical Modeling in Medicine and Pharmacy (Part 2)

Thursday, July 17 at 10:20am

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Note: this minisymposia has multiple sessions. The other session is: and Part-1.

Sungrim Seirin-Lee (Kyoto University/Graduate School of Medicine), Jaekyoung Kim (KAIST), So Miyoshi (Pfizer)

Description:

Another new wave is transforming the landscape of mathematical biology: its full-scale integration into medicine and pharmacy. The time has come for mathematical research, previously focused on theoretical studies, to make significant strides toward practical applications in collaboration with medical doctors and pharmaceutical researchers. This new paradigm aims to directly connect mathematical modeling to real-world treatment, helping patients in the present rather than only laying the groundwork for future possibilities. As this shift takes place, the role of mathematical approaches is becoming increasingly diverse. The complexities of modern medicine and pharmacy demand that mathematical models not only tackle theoretical challenges but also adapt to the nuances of clinical practice and drug development. This requires integrating multiple perspectives, including data-driven methods, predictive modeling, and tools for interpreting biological systems. Mathematics is no longer an auxiliary discipline-it is evolving into a cornerstone of innovation in medical and pharmaceutical research. Through this initiative, we aim to share cutting-edge developments in mathematical medicine and pharmacy, focusing on transformative approaches that link data, models, and real-world implementation. This mini-symposium represents an opportunity to rethink the possibilities of mathematical modeling and to explore its potential for creating tangible solutions in medicine and drug discovery.

So Miyoshi

Pfizer

"Transforming Drug Research and Development: The Paradigm Shift Driven by Mathematical Models"

Mathematical modeling and simulation technologies are playing a critical role in revolutionizing pharmaceutical research and development. Model-Informed Drug Development (MIDD), built upon the foundations of pharmacometrics and quantitative systems pharmacology (QSP), has emerged as a powerful approach to streamline the drug development process. It enables quantitative decision-making for optimizing clinical trial designs, improving dosing strategies, and ultimately accelerating the delivery of new therapies to patients. In particular, the integration of mechanistic modeling through QSP has demonstrated its value in recent real-world applications. As the pharmaceutical industry embraces MIDD, the roles of pharmacometricians, clinical pharmacologists, and systems modelers are becoming increasingly prominent across academia, regulatory agencies, and industry. This evolution calls for deeper interdisciplinary collaboration, especially with the mathematical biology community, to address the complexity of human disease and treatment responses. In this presentation, I will provide an overview of the current landscape and future directions of MIDD, illustrating its impact with practical examples from pharmaceutical development. We can shape a future in which mathematical models serve as a bridge from data to decision, accelerating the creation of innovative therapies across various disease areas.

Nessy Tania

Pfizer

"Advancing Quantitative Systems Pharmacology Model for Inflammatory Bowel Disease for Clinical Efficacy Predictions in Ulcerative Colitis"

Inflammatory Bowel Disease (IBD) is a chronic autoimmune disease associated with gastrointestinal inflammation. While therapeutic options for the disease have expanded, patient response to these treatments can be highly variable. In this presentation, I will present a mechanistic Quantitative Systems Pharmacology Model for IBD that can be connected to clinical endpoint, specifically Mayo endoscopic score for Ulcerative Colitis. As a specific case study, the application of the model and virtual population simulations to predict the effect of a novel target combination (p40 and TL1A) will be discussed. In the future, the model can be further developed to account for additional mechanisms and utilized to predict biomarker response and efficacy for novel IBD therapies.

Eamonn Gaffney

University of Oxford

"Modelling immunological systems, as exemplified by Short Peptide Vaccinations Simulations for Immuno-oncology"

A prospective immunologically-based cancer treatment is multi-peptide vaccination, targeting multiple tumour-associated peptides. However, a recent multiple short-peptide vaccination trial for renal cell carcinoma failed to show benefit, with many patients responding to only one of the administered peptides. An in-silico model is considered to enable an exploration of the determinants of the initial immunological response following multiple short peptide vaccination, suggesting mechanisms for the observed lack of benefit in the recent clinical trial. These insights may also used to suggest possible improvements to the trial design and more generally illustrate one means by which in silico studies can be used to test and improve the design of clinical trials. Further recent work investigating the modelling of immunological systems will also be surveyed.

Brian Corrigan

Metrum

"Superconvergence: Charting the Course from Lab to Global Health Outcomes in Translational Clinical Sciences for the Next Decade"

The presentation will highlight the important roles that various disciplines in Translational Clinical Sciences will play in bringing new medicines to patients over the next decade. It will examine the convergence of advances in genetics, biotechnologies, and AI on medicines development, and how these changes will impact our roles throughout the research spectrum, from non-clinical to human, from patients to practice, and from practice to our impact on population health. It will highlight the impact of new data sources, analytic and decision-making techniques, and explore patient centric approaches to Medicine development that increase trial accessibility and broaden representation in our clinical trials.

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Annual Meeting for the Society for Mathematical Biology, 2025.