可识别性
计算机科学
背景(考古学)
单克隆抗体
计算生物学
数据科学
机器学习
抗体
生物
免疫学
古生物学
作者
Michelle A. Pressly,L. A. Peletier,Songmao Zheng,Vishnu Dutt Sharma,Yi Ting Lien,Weirong Wang,Honghui Zhou,Stephan Schmidt
摘要
The main objective of this tutorial is to provide the readers with a roadmap of how to establish increasingly complex target-mediated drug disposition (TMDD) models for monoclonal antibodies. To this end, we built mathematical models, each with a detailed visualization, starting from the basic TMDD model by Mager and Jusko to the well-established, physiologically based model by Li et al. in a step-wise fashion to highlight the relative importance of key physiological processes that impact mAb kinetics and system dynamics. As the models become more complex, the question of structural and parameter identifiability arises. To address this question, we work through a trastuzumab case example to guide the modeler's choice for model and parameter optimization in light of the context of use. We leave the readers of this tutorial with a brief summary of the advantages and limitations of each model expansion, as well as the model source codes for further self-guided exploration and hands-on analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI