Prediction of Milk to Plasma ratio of drugs A Pilot Evaluation using Rapid Equilibrium Dialysis

Abstract

Breastfeeding is the optimal way to support neonatal immunity and growth. Many women take at least 1 medication during the breastfeeding period. Some medications can cross the epithelial membrane of the mammary gland and get into the milk which may lead to exposure of maternal medications to the infants and could precipitate unwanted side effects. Different factors that may affect the transfer of drugs from plasma to milk can be classified into physiological properties and physiochemical properties of the drugs. To measure the impact of these factors, different approaches such as clinical studies, animal studies, in vitro studies and computational models have been employed. There are critical limitations associated with each of these approaches. We decided to focus on developing an in vitro approach. using rapid equilibrium dialysis (RED) technique, which utilizes two chambers separated by a dialysis membrane, (one chamber represents the plasma and the other represents the milk). The purpose of this thesis is to validate an in vitro model that could help in predicting the milk-plasma ratio (M/P) of drugs with different physiochemical properties i.e., lipophilicity and plasma protein binding. Specifically, we evaluated the impact of changes in fat content in the milk and plasma protein binding on partitioning of a moderately lipid soluble drug, ketamine. This study developed a sensitive and specific way to measure ketamine and its metabolites in plasma and milk. The study documented that ketamine is not adsorbed onto the device used for partitioning studies. It also documented that plasma protein content had minimal impact on the M/P ratio. The fat content of milk significantly affected the M/P ratio partitioning. The M/P predicted by partitioning method appeared to underpredict clinically observed M/P ratio for ketamine. This observation is likely related to low fat content of the milk samples. Future studies should focus on evaluating human milk with various fat content on the M/P ratio.