Session Details
[SS09]Enhancing Drug Development and Patient Care through Model Informed Drug Development
Tue. Jul 8, 2025 4:50 PM - 6:30 PM JST
Tue. Jul 8, 2025 7:50 AM - 9:30 AM UTC
Tue. Jul 8, 2025 7:50 AM - 9:30 AM UTC
Room 01
Chair:So Miyoshi(Pfizer R&D Japan, Japan), Shingo Iwami(Nagoya University, Japan)
Mathematical modeling and simulation (M&S) have become essential in advancing the discovery and clinical development of new drugs. Recent progress in the science and technology of M&S has enabled precise modeling of relationships among pharmacokinetics (PK), pharmacodynamics (PD), mechanisms of action, physiological processes, and disease progression, allowing for accurate predictions of clinical responses and true endpoints. This approach, known as Model-Informed Drug Development (MIDD), serves as a key driver for optimizing clinical study design, improving success rates of clinical studies, and accelerating the drug development process. M&S is also instrumental in precision dosing, supporting the implementation of personalized medicine in clinical settings.
In this session, we will focus on PK/PD modeling, Quantitative Systems Pharmacology (QSP), Physiologically-Based Pharmacokinetic (PBPK) modeling and disease progression modeling, all of which are key mathematical approaches within M&S that provide precise descriptions of biological systems and disease processes. We will discuss how these quantitative methods enhance drug development and healthcare, as well as how to advance current modeling methodologies.
Furthermore, we aim to foster collaboration between pharmaceutical researchers and academic experts in mathematical biology and applied mathematics, encouraging mutual understanding of research objectives and exploring ways to bring new hope to patients and families awaiting innovative treatments.
In this session, we will focus on PK/PD modeling, Quantitative Systems Pharmacology (QSP), Physiologically-Based Pharmacokinetic (PBPK) modeling and disease progression modeling, all of which are key mathematical approaches within M&S that provide precise descriptions of biological systems and disease processes. We will discuss how these quantitative methods enhance drug development and healthcare, as well as how to advance current modeling methodologies.
Furthermore, we aim to foster collaboration between pharmaceutical researchers and academic experts in mathematical biology and applied mathematics, encouraging mutual understanding of research objectives and exploring ways to bring new hope to patients and families awaiting innovative treatments.
[SS09-05]Machine Learning-Driven Risk Stratification for Early Graft Loss in Living Donor Liver Transplantation
*Raiki Yoshimura1, Takeru Matsuura1, Shingo Iwami1 (1. Nagoya University (Japan))
[SS09-06]Prediction of antibody human pharmacokinetics using a physiologically based pharmacokinetic model coupled with multi-omics data
*Yasunori Komori1, Taichi Akahoshi1, Yoshie Takashima1, Koki Kibe1, Sotaro Naoi1, Kohji Nagano1, Kimio Terao1, Tatsuhiko Tachibana1 (1. Chugai Pharmaceutical Co., Ltd. (Japan))
[SS09-07]The estimation of the transmission mitigation in patients with COVID-19 by ensitrelvir treatment based on SARS-CoV-2 viral dynamic model
*Daichi Yamaguchi1 (1. Shionogi & Co., Ltd. (Japan))
[SS09-08]QSP support in Oncology Drug Development - Case Studies from ADC & TCE translation & Early clinical decision-making
*Rukmini Kumar1 (1. Vantage Research Inc. (India))