Prediction of drug concentrations in milk during breastfeeding, integrating predictive algorithms within a physiologically‐based pharmacokinetic model

Abstract

There is a risk of exposure to drugs in neonates during the lactation period due to maternal drug intake. The ability to predict drugs of potential hazards to the neonates would be useful in a clinical setting. This work aimed to evaluate the possibility of integrating milk‐to‐plasma (M/P) ratio predictive algorithms within the physiologically‐based pharmacokinetic (PBPK) approach and to predict milk exposure for compounds with different physicochemical properties. Drug and physiological milk properties were integrated to develop a lactation PBPK model that takes into account the drug ionization, partitioning between the maternal plasma and milk matrices, and drug partitioning between the milk constituents. Infant dose calculations that take into account maternal and milk physiological variability were incorporated in the model. Predicted M/P ratio for acetaminophen, alprazolam, caffeine, and digoxin were 0.83 ± 0.01, 0.45 ± 0.05, 0.70 ± 0.04, and 0.76 ± 0.02, respectively. These ratios were within 1.26‐fold of the observed ratios. Assuming a daily milk intake of 150 ml, the predicted relative infant dose (%) for these compounds were 4.0, 6.7, 9.9, and 86, respectively, which correspond to a daily ingestion of 2.0 ± 0.5 mg, 3.7 ± 1.2 µg, 2.1 ± 1.0 mg, and 32 ± 4.0 µg by an infant of 5 kg bodyweight. Integration of the lactation model within the PBPK approach will facilitate and extend the application of PBPK models during drug development in high‐throughput screening and in different clinical settings. The model can also be used in designing lactation trials and in the risk assessment of both environmental chemicals and maternally administered drugs.

Application of a Physiologically Based Pharmacokinetic Approach to Predict Theophylline Pharmacokinetics Using Virtual Non-Pregnant, Pregnant, Fetal, Breast-Feeding, and Neonatal Populations

“…Secondly, the developed theophylline PBPK model in non-pregnant subjects was used to predict the theophylline PK during pregnancy by applying gestational-dependent changes in the physiological parameters of the mother and the fetus. Thirdly, the PBPK model was coupled with a lactation model ( 14 ) to predict the drug exposure in maternal plasma and milk ( 8 ). Finally, the predicted infant daily dose from the lactation model was used as a dose input for the neonatal PBPK model in neonatal subjects of different ages by accounting for neonatal age-dependent physiology changes ( 17 ).…”

“…Due to an absence of information on the milk composition of the nursing mothers included in the clinical studies, two empirical models (I and II; see below for detailed equations) were used to predict the theophylline milk-to-plasma (M/P) ratio assuming a mature milk composition ( 8 ) and the average value of milk:plasma ratio (M/P) was used in the simulations (see Discussion section).…”

“…Drug exposure to neonates after birth may happen during breastfeeding, assuming the drug reaches the milk after maternal intake. The amount of drug delivered to the breastfed neonate varies with variability in maternal physiology and milk composition as well as the breastfeeding style, i.e., frequency and fed amounts ( 7 , 8 ). Once the drug reaches the neonatal gut or systemic circulation, the exposure in neonates is influenced by the maturation of the drug absorption and disposition processes that are known to vary with the age of the newborn ( 9 – 11 ).…”

Addressing drug safety of maternal therapy during breastfeeding using physiologically‐based pharmacokinetic modeling

“…In the context of regulatory application, “well‐qualified models” are required to provide assurances that the model predictions are robust and this approach can be used to inform with confidence, high‐impact decisions as part of regulatory submissions 6 . Although it is accepted that this is an emerging and significant area of interest, evaluation of such approaches is already ongoing and results are promising 1,4 …”

“…Integration of these M/P ratio prediction algorithms within a PBPK model can facilitate simulation of drug levels in breast milk following administration of the drug in mothers 1 . Thereafter, the infant daily dose and RIDD of a drug based on ingestion via breast milk can be predicted from the simulated milk concentration profiles and used to guide neonatal/infant risk assessment where clinical lactation data are lacking.…”