A comprehensive review on non-clinical methods to study transfer of medication into breast milk – A contribution from the ConcePTION project

Nauwelaerts, Nina; Deferm, Neel; Smits, Anne; Bernardini, Chiara; Lammens, Bart; Gandia, Peggy; Panchaud, Alice; Nordeng, Hedvig; Bacci, Maria Laura; Forni, Monica; Ventrella, Domenico; Calsteren, Kristel Van; DeLise, Anthony M.; Huys, Isabelle; Bouisset-Leonard, Michèle; Allegaert, Karel; Annaert, Pieter

doi:10.1016/j.biopha.2020.111038

Cited by 31 publications

(20 citation statements)

References 122 publications

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“…Other human PBPK models developed for therapeutic compounds do not use milk compositions to predict the milk exposure; instead, they use a predefined M/P ratio as a prior parameter 48,49 . Integrating a lactation model within a PBPK platform is a step forward in gaining insights into drug distribution into the milk during breastfeeding 3 . Lactation PBPK models have many potential practical applications and clinical settings to improve maternal adherence to the treatment and increase infants’ access to the breast milk by informing drug labels at least for those compounds with low relative infant dose.…”

Section: Discussionmentioning

confidence: 99%

“… 48 , 49 Integrating a lactation model within a PBPK platform is a step forward in gaining insights into drug distribution into the milk during breastfeeding. 3 Lactation PBPK models have many potential practical applications and clinical settings to improve maternal adherence to the treatment and increase infants’ access to the breast milk by informing drug labels at least for those compounds with low relative infant dose. Scenarios where maternal systemic drug exposure change due to comorbidity and/or comedication can also be evaluated in silico.…”

Section: Discussionmentioning

confidence: 99%

“…1 Recently, there has been an increased interest in understanding the pharmacokinetics (PKs) in lactating women and the rate, and extent, of drug distribution into the milk. 2,3 However, published research use different methodology and incomplete information on data variability, calling for a unified scientific framework. 4 The US Food and Drug Administration (FDA) has released regulatory guidelines and drafts requesting pharmaceutical companies to address the potential impact of maternal drug exposure, levels of the drug (and metabolite) appearing in breast milk, the potential effects on the feeding infants, and effects of the drug on milk production.…”

Section: Introductionmentioning

confidence: 99%

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

Abduljalil

Pansari

Ning

et al. 2021

CPT Pharmacom & Syst Pharma

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Abduljalil

Pansari

Ning

et al. 2021

CPT Pharmacom & Syst Pharma

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“…The reason for this negative correlation might be the different lipid profiles in colostrum and mature milk [ 39 ]. However, as colostrum has a lower lipid content than mature milk [ 39 , 46 ], the level of MEHP, which is hydrophobic, would be expected to be lower in colostrum than in mature milk [ 41 ]. Therefore, the distinct lipid profile in breast milk cannot explain the finding in the present study.…”

Section: Discussionmentioning

confidence: 99%

“…Secondly, it would be informative to analyze continuous milk samples from one postpartum woman due to the short half-life of DEHP in humans [ 10 ]; thirdly, the maternal urinary and serum levels of DEHP metabolites were not analyzed in this study as metabolite levels in breast milk were not well-correlated with those in urine or serum [ 58 ]. Lastly, many special maternal conditions including obesity or medication may change human milk composition [ 46 ]. We did not investigate maternal disease or medication in the present study.…”

Section: Discussionmentioning

confidence: 99%

Phthalate Exposure Pattern in Breast Milk within a Six-Month Postpartum Time in Southern Taiwan

Hung

Lin

Suen

et al. 2021

IJERPH

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Di-(2-ethylhexyl) phthalate (DEHP), a common plasticizer, has been detected in breast milk in many countries; however, whether phthalate metabolite concentration and the detection rate in breast milk change postpartum is still unknown. We measured phthalate metabolite concentrations in breast milk in the first 6 months postpartum in women enrolled in the E-Da hospital from January to July 2017. A total of 56 breastfeeding mothers and 66 samples were included in this study. We analyzed the samples’ concentration of eight phthalate metabolites using liquid chromatography mass spectrometry. The concentration of mono-2-ethylhexyl phthalate (MEHP) was significantly higher in the first month, and then decreased over time. The detection rate of ono-isobutyl phthalate (MiBP) and mono-n-butyl phthalate (MBP) was low in the first month and then increased over time. Compared with a previous study published in 2011, the levels of MEHP and MiBP in breast milk were much lower in the present study, suggesting an increased awareness of the health risks of phthalate exposure after a food scandal occurred in Taiwan. This study provides information for evaluating newborns’ exposure to different kinds of phthalate through human milk in the postpartum period.

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Prediction of basic drug exposure in milk using a lactation model algorithm integrated within a physiologically based pharmacokinetic model

Pansari

Faisal

Jamei

et al. 2022

Biopharm & Drug Disp

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Medication use during breastfeeding can be a matter of concern due to unintended infant exposure to drugs through breast milk. The available information relating to the safety of most medications is limited and may vary. More precise information is needed regarding the safety to the newborn or infants of the medications taken by the mother during breastfeeding. Physiologically based Pharmacokinetic Model (PBPK) approaches can be utilized to predict the drug exposure in the milk of breastfeeding women and can act as a supporting tool in the risk assessment of feeding infants. This study aims to assess the predictive performance of an integrated 'log transformed phase-distribution' lactation model within a PBPK platform.The model utilizes the physicochemical properties of four basic drugs, namely tramadol, venlafaxine, fluoxetine, and paroxetine, and analyses the milk compositions to predict the milk-to-plasma (M/P) ratio. The M/P prediction model was incorporated within the Simcyp Simulator V20 to predict the milk exposure and to estimate the likely infant dose for these drugs. The PBPK models adequately predicted the maternal plasma exposure, M/P ratio, and the infant daily dose to within two-fold of the clinically observed values for all four compounds. Integration of the lactation model within PBPK models facilitates the prediction of drug exposure in breast milk.The developed model can inform the design of lactation studies and assist with the neonatal risk assessment after maternal exposure to such environmental chemicals or basic drugs which diffuse passively into the milk. K E Y W O R D Slactation model, milk exposure, milk-to-plasma ratio, physiologically based pharmacokinetic model | INTRODUCTIONLactating women can be exposed to medications, either on a limited or long-term basis, depending on the need to treat acute or chronic conditions. In some cases, women may be advised to discontinue breastfeeding or to avoid taking essential medications due to the potential adverse effects on their infants. Such advice is often not based on evidence but due to a lack of adequate knowledge about drug exposure and safety in infants. Information available on the safety of most medications used during breastfeeding is limited or completely absent for the majority of drugs (Anderson, 2018;Sachs, 2013). Recently, regulatory authorities have proposed a framework for clinical lactation studies to gain knowledge on the exposure of drugs in breast milk, however, there are still many practical and ethical limitations (Anderson & Momper, 2020;Food and Drug Administration, 2019;Nauwelaerts et al., 2021).

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A comprehensive review on non-clinical methods to study transfer of medication into breast milk – A contribution from the ConcePTION project

Cited by 31 publications

References 122 publications

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

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

Phthalate Exposure Pattern in Breast Milk within a Six-Month Postpartum Time in Southern Taiwan

Prediction of basic drug exposure in milk using a lactation model algorithm integrated within a physiologically based pharmacokinetic model

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