Speaker
Description
For over a century, the Michaelis–Menten (MM) equation has provided the foundation for modeling enzyme kinetics in biochemistry and pharmacology. Despite its remarkable success, MM relies on assumptions that may break down in physiologically relevant regimes. In this talk, we revisit these limitations and introduce the total quasi-steady-state approximation (tQSSA) as a principled generalization of MM. We show that this framework enables more accurate quantitative predictions in pharmacokinetic applications, including enzyme-mediated drug–drug interaction modeling relevant to regulatory practice. We further discuss how this deterministic reduction extends to stochastic simulations. By clarifying the validity conditions of its stochastic extension, we identify when tQSSA reliably captures intrinsic biochemical noise and propose alternative stochastic reaction functions when it does not.
Bibliography
@article{https://doi.org/10.1002/cpt.2824,
author = {Vu, Ngoc-Anh Thi and Song, Yun Min and Tran, Quyen Thi and Yun, Hwi-yeol and Kim, Sang Kyum and Chae, Jung-woo and Kim, Jae Kyoung},
title = {Beyond the Michaelis–Menten: Accurate Prediction of Drug Interactions Through Cytochrome P450 3A4 Induction},
journal = {Clinical Pharmacology \& Therapeutics},
volume = {113},
number = {5},
pages = {1048-1057},
doi = {https://doi.org/10.1002/cpt.2824},
url = {https://ascpt.onlinelibrary.wiley.com/doi/abs/10.1002/cpt.2824},
eprint = {https://ascpt.onlinelibrary.wiley.com/doi/pdf/10.1002/cpt.2824},
year = {2023}
}
@article{10.1371/journal.pcbi.1008952,
doi = {10.1371/journal.pcbi.1008952},
author = {Song, Yun Min AND Hong, Hyukpyo AND Kim, Jae Kyoung},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Universally valid reduction of multiscale stochastic biochemical systems using simple non-elementary propensities},
year = {2021},
month = {10},
volume = {17},
url = {https://doi.org/10.1371/journal.pcbi.1008952},
pages = {1-21},
number = {10},
}
@article{LEE2025107286,
title = {Beyond Michaelis-Menten: A modified enzyme kinetics equation improves drug metabolism prediction in bottom-Up PBPK modeling},
journal = {European Journal of Pharmaceutical Sciences},
volume = {214},
pages = {107286},
year = {2025},
issn = {0928-0987},
doi = {https://doi.org/10.1016/j.ejps.2025.107286},
url = {https://www.sciencedirect.com/science/article/pii/S0928098725002842},
author = {Junghyun Lee and Yun Min Song and Hwi-yeol Yun and Suein Choi and Jae Kyoung Kim},
keywords = {Michaelis-menten, Enzyme concentration, Physiologically based pharmacokinetic (PBPK) modeling, Bottom-up approach, In vitro to In vivo extrapolation (IVIVE), Induction},
}
