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

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 pre...

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Bibliographic Details
Published in:CPT: pharmacometrics and systems pharmacology Vol. 10; no. 8; pp. 878 - 889
Main Authors: Abduljalil, Khaled, Pansari, Amita, Ning, Jia, Jamei, Masoud
Format: Journal Article
Language:English
Published: United States John Wiley & Sons, Inc 01.08.2021
John Wiley and Sons Inc
Wiley
Subjects:
Adult
Algorithms
Babies
Breast Feeding
Breastfeeding & lactation
Contraindications
Data collection
Drug development
Drug dosages
Drug therapy
Female
Humans
Infant, Newborn
Lactation
Lipids
Milk
Milk, Human - chemistry
Models, Biological
Pharmaceutical industry
Pharmaceutical Preparations - metabolism
Pharmacokinetics
Physicochemical properties
Physiology
Plasma
Research Design
Risk Assessment
Young Adult
ISSN:2163-8306, 2163-8306
Online Access:Get full text
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Summary: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.
Bibliography:Funding information
No funding was received for this work.
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ISSN:2163-8306
2163-8306
DOI:10.1002/psp4.12662