Timothy Knab, Ph.D.

Science Advisor, Senior Scientist II

Tim joined Metrum in March 2017 after completing his Ph.D. in Chemical Engineering from the University of Pittsburgh where his dissertation was focused on modeling and controlling stress-induced hyperglycemia in critically ill patients. This work included dynamic optimization of models describing glucose-insulin dynamics and the development of model-predictive controllers and state estimators for clinical applications. Tim’s interests include the application of systems biology models to guide decision making in the drug development process and to advance treatment paradigms.

Recent publications by this scientist

Deep QSP Modeling: Leveraging Machine Learning for QSP Model Development and Evaluation

November 14, 2023

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.

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A multi-organ integrated QSP model for hematopoietic stem cell differentiation to predict the immune cell reconstitution in ex-vivo gene therapy

November 14, 2023

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.

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Exploring the Influence of Bispecific Antibody Mechanisms on In Vitro Dose Response: Insights from an Open-Science Quantitative Systems Pharmacology Model in Julia

November 14, 2023

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.

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