INTRODUCTION
Breastfeeding can have positive health consequences for both the breastfed infant
and the nursing mother. However, when taking medication, there are concerns about
protecting the infant from adverse events while allowing necessary maternal therapy.
An adverse effect on a breastfeeding infant due to maternal medication may be caused
by an interplay of factors between the mother and the nursing infant, a complex scenario
that can be readily investigated using physiologically‐based pharmacokinetic (PBPK)
modeling.
Multiple factors, including genetic and environmental, contribute to the variability
associated with an individual’s response. Exposure of mothers, particularly those
with certain genotypes, to multiple medications during pregnancy and breastfeeding
may place their infants at increased risk of adverse drug reactions. Consideration
should also be given to the infant’s smaller mass and immature gastrointestinal, hepatic,
and renal function. Indeed, at this age, neonatal drug‐excretory mechanisms, both
hepatic and renal, are incompletely developed. Drugs chronically administered at that
time through breastfeeding may accumulate and reach toxic concentrations.
PBPK models which account for the complex interplay between physiological parameters
and drug‐related characteristics, represent a mechanistic approach to predict the
pharmacokinetics (PKs) of drugs in different populations, including nursing mothers
1
and infants.
2
Pediatric PBPK models account for the development of organs, including the ontogeny
of specific enzymes and transporters involved in the disposition of a specific drug.
Although knowledge gaps remain, ongoing research relating to these processes in children,
has allowed refinement of relevant physiological parameters and integration of more
complex models. Thus, PBPK models which are increasingly used in pediatric clinical
pharmacology, including drug development, are reaching maturation for applications
with high regulatory impact.
2
In this paper, we discuss how “off the shelf” PBPK models for commonly used drugs,
already robustly verified in terms of their disposition, can be used to assess safety
concerns in breastfeeding infants as a consequence of the nursing mothers taking medication(s).
Complex case studies will be used to demonstrate the validity of the approach.
CLINICAL LACTATION STUDIES IN DRUG DEVELOPMENT
In 2019, the US Food and Drug Administration (FDA) released a guidance document for
pharmaceutical companies providing recommendations on how to address the potential
impact of maternal drug exposure, including assessment of levels of the drug (and
metabolite) appearing in breast milk, the potential effects on breastfeeding infants,
and effects of the drug on milk production.
3
The FDA indicate that data from clinical lactation studies, supported by other relevant
data, including drug physicochemical properties, mechanism of drug entry into breast
milk, data from nonclinical studies, and infant factors, can be used to evaluate the
safety of a drug when used by breastfeeding mothers and to develop recommendations
to minimize infant exposure.
Key factors affecting the excretion of drugs into milk and methods of measuring the
passage of drugs into breast milk have been described previously.
4
The standard method of quantifying drug passage into breast milk is the administration
of a drug to a nursing mother, either for the purpose of the study or because she
is taking the drug therapeutically. Ideally, sufficient drug concentrations are measured
to allow calculation of an area under the milk concentration–time curve (AUC) and
an average milk concentration (AUC/milk sampling duration). Once an estimate of drug
concentration in milk is available, an infant daily dose assuming a daily milk intake
of 150 ml/kg and a milk/plasma ratio can be calculated. Thereafter, the relative infant
daily dose (RIDD; the percent of the weight‐adjusted maternal dosage consumed in breast
milk over 24 h) is determined. The World Health Organization (WHO) Working Group proposed
that drugs with an RIDD >10% may not be safe in infants, and that those with an RIDD
greater than 25% should be avoided in nursing mothers.
PREDICTING DRUG CONCENTRATIONS IN MILK
The amount of drug excreted into breast milk depends upon the composition of the milk,
the physicochemical properties of the drug, and the mechanism of transport. The higher
the lipid solubility, the greater the concentration in human milk. The majority of
drugs appear to be transported into mammary blood capillaries via passive diffusion.
In the absence of clinical lactation data, it may be possible to predict the passage
of drugs into breast milk (M/P ratio) using only the physicochemical properties of
the drug and milk characteristics. Indeed, a number of such predictive algorithms
have been developed and evaluated.
4
,
5
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. 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.
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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
PREDICTING DRUG CONCENTRATIONS IN INFANTS DURING BREASTFEEDING
When clinical lactation data are available, some of the uncertainty associated with
extrapolation of the infant daily dose is removed. Here, we present two case studies
where observed milk concentrations were available and the extrapolated infant daily
dose was used to simulate plasma concentration time profiles in infants using a pediatric
PBPK model (Johnson et al.
2
); one involves a drug–drug interaction for a combination therapy, and the other,
the complex interplay between mother/infant and the impact of their respective CYP2B6
genotypes.
Case study 1: Lumacaftor/ivacaftor
Cystic fibrosis (CF) is a life‐shortening genetic disorder caused by mutations in
the cystic fibrosis transmembrane conductance regulator (CFTR) gene. These mutations
lead to abnormal ion transport in mucous membranes throughout the body, including
the respiratory tract. As a consequence of CFTR modulator therapy, there has been
a significant increase in the quality of life for those with CF. Pregnancy was once
discouraged for women with CF but now, even with moderately severe lung disease, women
can successfully navigate pregnancy. However, with the increasing use of this medication,
there is a growing need to understand the effects of these agents during pregnancy.
The uncomplicated and successful pregnancy of a woman treated with lumacaftor/ ivacaftor,
as well as the clinical course of the infant during the first 9 months of life, was
reported recently.
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Concentrations of lumacaftor and ivacaftor in maternal plasma, cord blood, breast
milk, and infant plasma over time were recorded throughout.
A PBPK model describing the ivacaftor/lumacaftor combination that was able to capture
the induction of CYP3A4‐mediated metabolism of ivacaftor by lumacaftor for a number
of different dosage regimens, was reported previously.
8
In the case study presented here, the published PBPK models were used to predict the
exposure of both drugs in breastfeeding infants during their first 9 months of life,
thus replicating the clinical scenario.
7
Virtual neonates with time‐varying physiology, including a CYP3A4 ontogeny, were generated
and given an infant daily dose of each drug (extrapolated from the observed milk data).
As milk intake via breast‐feeding was not constant, various scenarios were assessed
(25% of dietary intake from breast milk up to 100%; Figure 1). Although data from
only a single infant were available for comparison, the results are promising especially
when considering the complexity of the situation.
FIGURE 1
Ivacaftor and lumacaftor case study. (Top) The schematic illustrates key factors considered
in the PBPK model for predicting ivacaftor and lumacaftor exposure in infants during
breastfeeding. (Bottom) Simulated and observed concentration–time profiles of ivacaftor
and lumacaftor in newborn girls being breastfed for 184 days. All simulations were
performed using the population‐based Simulator (Simcyp version 21; Sheffield, UK).
Blue lines represent simulated mean profiles following various breast milk intake
scenarios. Gray lines represent the 5th and 95th percentile of the total virtual population
(Sim‐Pediatric, 100 female subjects at birth per each scenario). Open circles represent
observed data in a full‐term newborn girl.
7
GI, gastrointestinal; PBPK, physiologically‐based pharmacokinetic
Case study 2: efavirenz
Current WHO guidelines recommend efavirenz as the preferred non‐nucleoside reverse
transcriptase inhibitor component of first‐line antiretroviral therapy for adults
across different patient populations, including nursing mothers. However, efavirenz
is not licensed for use in children <3 months old or weight ≤3.5 kg because optimal
dosing and safety have not been evaluated. Despite this, the drug is widely used by
nursing mothers. An observational study was conducted to investigate maternal plasma
and breast milk PKs of efavirenz and breastfed infants’ exposure in genetically defined
subgroups of HIV positive nursing mothers.
9
Potential variability due to genetic polymorphisms in CYP2B6, NR1I3, CYP2A6, ABCB1,
ABCB5, and ABCG2 was evaluated. CYP2B6 516G>T was independently associated with efavirenz
concentrations in maternal plasma, breast milk and infant plasma (n = 134). When stratified
according to CYP2B6 516G>T genotypes (n = 29; 11 GG, 10 GT, and 8 TT), efavirenz PK
parameters in plasma and breast milk differed significantly between patient groups.
No efavirenz‐related toxicity was reported and the RIDD was reported to be <10% in
most breastfed infants.
A robust PBPK model for efavirenz describing the CYP3A4‐ and CYP2B6‐mediated auto‐induction
during multiple dosing was reported previously.
10
In the case study presented here, the published PBPK model was used to predict the
exposure of efavirenz in maternal and infant plasma accounting for the various CYP2B6
genotypes. Virtual infants with time‐varying physiology, including a CYP2B6 ontogeny,
were generated. The infant daily doses were estimated based on the clinically observed
M/P ratio of 1.1 and efavirenz exposures in mothers carrying different CYP2B6 genotypes.
The clinically significant trend toward higher infant efavirenz exposure from GG/GG
to TT/TT composite maternal/infant CYP2B6 genotypes was captured reasonably well by
the PBPK model (Figure 2).
FIGURE 2
Efavirenz case study. (Top) The schematic illustrates key factors considered in the
PBPK model for predicting the impact of CYP2B6 polymorphism on efavirenz exposure
in infants during breastfeeding. (Bottom left) Simulated and observed efavirenz plasma
concentrations (data points) in mothers carrying various CYP2B6 516G>T genotypes;
(bottom right) simulated and observed infant efavirenz plasma concentrations (data
points) associated with composite maternal/infant CYP2B6 516G>T genotypes. The observed
maternal (age: 18–44 years) and infant (age: 0.29–75 weeks, 52% girls) data were from
Olagunju et al.
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The simulations were performed in 100 virtual female adults or pediatrics per each
CYP2B6 genotypes (Sim‐Healthy volunteers, 18–44 years old; Sim‐Pediatric, 0.29–75 weeks
old, 52% girls). GI, gastrointestinal; PBPK, physiologically‐based pharmacokinetic
Concluding remarks
Most drug labels do not provide enough information to guide a woman and her physician
in deciding whether a medication is safe during breastfeeding. PBPK modeling can be
used to predict drug exposures in both mothers and infants while accounting for complex
factors, such as genetics, comedications, and time‐varying physiology. Robust “off
the shelf” PBPK models that have been extensively verified with supporting clinical
data are already available for many commonly prescribed drugs. Along with other methods,
this approach can be used to support benefit–risk decisions for both the nursing mother
and the breastfeeding infant in early drug development and through practice.
CONFLICT OF INTEREST
K.R.Y. and X.P. are employees of Certara UK Limited (Simcyp Division) and may hold
shares in Certara. As an Associate Editor for Clinical Pharmacology & Therapeutics:
Pharmacometrics & Systems Pharmacology, K.R.Y. was not involved in the review or decision
process for this paper.