Development of an ex-vivo-in-silico framework to inform medication use decisions for breastfeeding women

Children can inadvertently be exposed to the medications their mothers receive through breastmilk. As such, breastfeeding mothers need to weigh both the risks and benefits of medication use for themselves as well as their children. Unfortunately, the majority of drugs prescribed to breastfeeding women lack sufficient information to understand these risks. Due to this lack of information, women may opt to delay needed drug therapy or discontinue breastfeeding altogether — choices that can negatively impact the health of both mother and child. The proposed research program looks to address this information gap by combining lab-based studies with advanced computer modelling to predict how drug intake by the mother translates to drug exposure in the breastfed child. Lab-based studies will answer the question, “How much drug is present in breastmilk?” Whereas, advanced computing will be used to create virtual children and mothers to answer the question, “How much of the drug administered to the mother will be transferred to the breastfeeding child?” This will work ultimately serve to provide breastfeeding women and their caregivers with vital information to make the decisions regarding safe and effective drug therapy.