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PBPK modeling is used to make predictions of the absorption, distribution and elimination of a compound from an organism. It requires the building of a virtual organism using mathematical functions and a combination of known and estimated system-specific properties of the organism’s anatomy and physiology. It also requires an understanding of how compound-specific properties such as lipophilicity, molecular weight, acid/base properties, and interactions with proteins (e.g., plasma-protein binding, metabolic stability, and active transport) affect the absorption, distribution, metabolism, and excretion (ADME) of a compound within the organs and tissues of the organism.

Using the principles of PBPK modeling, we aim to answer clinically relevant questions. Examples of our current research includes:

1. Estimating physiological changes in special populations, such as infants, children, hepatic or renal impaired patients (e.g., levels of expression and/or function of proteins, including ontogenies of enzymes and transporters), and predicting the impact of the changes on the ADME of a compound in the populations.
2. Using Population Pharmacokinetic models and Bayesian forecasting, we build tools for Model Informed Precision Dosing (MIPD) and test them in real-world scenarios.

Using the principles of PBPK modeling, we aim to answer clinically relevant questions. Examples of our current research includes:

Applying clinical data about maternal drug transfer into breastmilk and using it to predict the overall drug exposure and subsequent risk for the breastfed infant. These models aid in assessing the risk of continuing breastfeeding while on drug therapy.

Estimating physiological changes in special populations, such as infants, children, hepatic or renal impaired patients (e.g., levels of expression and/or function of proteins, including ontogenies of enzymes and transporters), and predicting the impact of the changes on the ADME of a compound in the populations.

Using Population Pharmacokinetic models and Bayesian forecasting, we build tools for Model Informed Precision Dosing (MIPD) and test them in real-world scenarios

Together with from the School of Pharmacy À¶Ý®ÊÓƵ, Edginton lab completes economic evaluations for hemophilia treatments. This evaluates the clinical benefits, health-related quality of life improvements and costs of novel hemophilia treatments to determine during the funding approval process. Dr. William WL Wong’s lab provides health policy and economic evaluation expertise, while Dr. Edginton’s lab provides hemophilia expertise and clinical connections. Currently this subgroup is evaluating the cost-effectiveness of Altuviiio and gene therapy, updating crucial variables for future economic analysis, and investigating key population subgroups. For more information on this area, please review Dr. Wong’s webpage.

Mathematical models of skin penetration are chemical risk assessment tools that aid the evaluation of potential hazards posed by chemicals to human health. These models predict the ability of chemicals to permeate skin, which is crucial for determining exposure levels and guiding regulatory decisions.

We use PBPK models to simulate the movement of chemicals through the skin and their distribution within the body. These models account for various factors that influence skin penetration, including physical and chemical properties of the chemical, formulation attributes, skin conditions, ambient conditions, and application methods. Such models also enable us to account for inter-individual variability in skin physiology and interactions between applied chemicals and skin.

Our work focuses on improving model performance and reliability through advanced learning and simulation techniques through the integration of experimental legacy datasets and Bayesian Markov chain Monte Carlo methods.