Population PK modelling and simulation based on fluoxetine and norfluoxetine concentrations in milk: a milk concentration-based prediction model

Allopregnanolone Concentrations in Breast Milk and Plasma from Healthy Volunteers Receiving Brexanolone Injection, With Population Pharmacokinetic Modeling of Potential Relative Infant Dose

Background and Objective

Women with postpartum depression (PPD) may expose their infants to antidepressants via breast milk. Brexanolone is the only FDA-approved antidepressant specifically indicated for the treatment of PPD. This open-label, phase Ib study of healthy lactating volunteers assessed pharmacokinetic (PK) properties of brexanolone and a population PK (PopPK) model determined the relative infant dose (RID) in breastfeeding mothers.

Methods

Twelve participants received a 60-h infusion of brexanolone (titration up to 90 µg/kg/h). Allopregnanolone concentration was measured in breast milk and plasma. The RID was computed using a nonlinear mixed-effects PopPK model of patients with PPD and healthy women (N = 156). Model results were extended across an integrated dataset of participants through day 7.

Results

Allopregnanolone concentration–time profiles were similar between breast milk and plasma (partition coefficient for concentration gradient [milk : plasma] 1.36). Mean (95% CI) C_max was 89.7 ng/mL (74.19–108.39), and median (95% CI) t_max was 47.8 h (47.8–55.8) in plasma. The overall PK profile was best described by a two-compartment model with linear elimination and distribution. Body weight was the only significant covariate identified. There were no apparent differences in PopPK AUC and C_max between participants with or without concomitant antidepressant treatment. Maximum RID was 1.3%.

Conclusion

The PopPK model successfully described the variability and concentration–time profiles of allopregnanolone in breast milk and plasma in healthy participants and in the plasma of brexanolone-treated patients with PPD. The rapid elimination of allopregnanolone from plasma and breast milk, and low RID, suggests the appropriateness of brexanolone weight-based dosing and supports other PK-related labeling recommendations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40262-022-01155-w.

Fluoxetine pharmacokinetics and tissue distribution suggest a possible role in reducing SARS-CoV-2 titers

Background.  Recent in vitro studies have shown fluoxetine inhibits the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen, including variants B.1.1.7 and B.1.351, SARS-CoV-2 spike mutations (E484K, K417N, N501Y), and one retrospective clinical study reported fluoxetine exposure at a median dose of 20 mg in patients with the SARS-CoV-2 coronavirus disease 2019 (COVID-19) had a significantly lower risk of intubation and death. The aim of this study is to conduct in silico population pharmacokinetic dosing simulations to quantify the percentage of patients achieving a trough level for the effective concentration resulting in 90% inhibition (EC90) of SARS-CoV-2 as reported in Calu-3 human lung cells.  Methods.  Population pharmacokinetic parameter estimates for a structural one-compartment model with first-order absorption were used to simulate fluoxetine pharmacokinetic data. A population of 1,000 individuals were simulated at standard fluoxetine doses (20 mg/day, 40 mg/day, and 60 mg/day) to estimate the percentage of the patients achieving a trough plasma level for the EC90 SARS-CoV-2 inhibitory concentration for a 10 day treatment period. All analyses were conducted via statistical programming in R.  Results.  Standard fluoxetine antidepressant doses resulted in a range of 81% to 97% of the patient population achieving a trough target plasma concentration of 23.2 ng/ml at day 10 and translates to a lung-tissue distribution coefficient of 60-times higher (EC90 of 4.02 mM). At a dose of 40 mg per day, at least 87% of patients will reach the trough target EC90 concentration within three days.   Conclusion. Overall, the findings of this population pharmacokinetic dosing study corroborates in vitro and observational clinical studies reporting the first selective serotonin reuptake inhibitor fluoxetine inhibits the SARS-CoV-2 pathogen at commonly treated doses in the practice of psychiatry.

Clinical lactation studies and the role of pharmacokinetic modeling and simulation in predicting drug exposures in breastfed infants

The relative lack of information on medication use during breastfeeding is an ongoing problem for health professionals and mothers alike. Most nursing mothers are prescribed some form of medication, yet some mothers either discontinue breastfeeding or avoid medications entirely. Although regulatory authorities have proposed a framework for clinical lactation studies, data on drug passage into breastmilk are often lacking. Model-based approaches can potentially be used to estimate the passage of drugs into milk, predict exposures in breastfed infants, and identify drugs that need clinical lactation studies. When a human study is called for, measurement of the drug concentration in milk are often adequate to characterize safety. Data from these studies can be leveraged to further refine pharmacokinetic models with subsequent Monte Carlo simulations to estimate the spread of exposure values. Both clinical lactation studies and model-based approaches have some limitations and pitfalls which are discussed.

Predicting Escitalopram Exposure to Breastfeeding Infants: Integrating Analytical and In Silico Techniques

BACKGROUND

Escitalopram is used for post-partum depression; however, there are limited pharmacokinetic data of escitalopram in milk and plasma of infants breastfed by women taking the drug.

OBJECTIVE

The objective of this study was to apply physiologically-based pharmacokinetic (PBPK) modelling to predict infant drug exposure (plasma area under the curve from time zero to infinity [AUC_∞]) based on drug monitoring data of escitalopram in breast milk.

METHODS

Using a newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, we quantified escitalopram concentrations in milk samples of 18 breastfeeding women with escitalopram therapy at steady state, collected at three to five time points. The escitalopram concentrations in breast milk were used with infant feeding parameters from the literature to simulate infant daily dose. We used PK-Sim^® to develop an adult PBPK model for escitalopram and extrapolated it to a population of 1600 infants up to 12 months of age. An integration of the simulated infant daily dose and the virtual infants with variable physiological-pharmacological parameters was used to predict drug exposure (plasma AUC_∞) distribution in the population of infants breastfed by women receiving escitalopram 20 mg/day.

RESULTS

Escitalopram concentrations in milk were 50 ± 17 ng/mL (mean ± standard deviation). The simulated infant plasma AUC_∞ following escitalopram exposure through breast milk was low, with a median of 1.7% (range 0.5-5.9%) of the corresponding maternal plasma AUC_∞, indicating no substantial exposure.

CONCLUSIONS

Infant exposure levels to escitalopram in breast milk are low. A PBPK modeling approach can be used to translate data on drug monitoring in milk into a population distribution of infant plasma levels for drug safety assessment.

Emerging Research Paradigm for Infant Drug Exposure Through Breast Milk

Background:

Information on drug secretion into milk is insufficient due to the exclusion of lactating women from clinical trials and drug development processes. As a result, non-adherence to the necessary drug therapy and discontinuation of breastfeeding occur, even if the predicted level of infant exposure is low. In contrast, inadvertent infant exposure to drugs in breast milk continues to happen due to lack of rational risk assessment, resulting in serious toxicity cases including death. This problem is multifactorial, but one of the key elements is the lack of pharmacokinetic information on drug secretion into milk and resultant infant exposure levels, the first line of evidence for risk assessment.

Methods:

Basic PK principles in drug excretion into milk were explained. The literature was scanned to identify approaches for PK data acquisition in this challenging field.

Results:

This review describes the feasibility to develop such approaches, and the knowledge gaps that still exist. A combination of population pharmacokinetics approach (to estimate averages and variations of drug concentration profiles in milk) and physiologically-based pharmacokinetics modeling of infants (to predict the population profiles of infant drug exposure levels) appears useful.

Conclusions:

In order to facilitate participant enrollment and PK data acquisition in a timely manner, networks of investigators become crucial.

Quetiapine Excretion Into Human Breast Milk

BACKGROUND

Risk assessment of the use of quetiapine during breastfeeding is challenging owing to a paucity of data.

METHODS

A pharmacokinetic study was conducted in lactating women who were taking quetiapine. The primary endpoint was to determine quetiapine concentration profiles in milk and estimated infant exposure levels. Multiple milk and a single blood quetiapine concentrations were determined using a highly sensitive liquid chromatography with tandem mass spectroscopy method.

RESULTS

Nine subjects receiving fast-release quetiapine (mean dose, 41 mg/d) were analyzed at steady state. The mean milk/plasma drug concentration ratio at 2-hour postdose was 0.47 (SD, 0.50; range, 0.13-1.67). The mean milk concentration of each patient was 5.7 ng/mL (SD, 4.5; range, 1.4-13.9 ng/mL). The mean infant quetiapine dose via milk per body weight relative to weight-adjusted maternal dose was 0.16 % (SD, 0.08; range, 0.04%-0.35%).

CONCLUSIONS

Infant exposure levels to quetiapine via milk are predicted to be very small.

Drugs in Lactation

One impediment to breastfeeding is the lack of information on the use of many drugs during lactation, especially newer ones. The principles of drug passage into breastmilk are well established, but have often not been optimally applied prospectively. Commonly used preclinical rodent models for determining drug excretion into milk are very unreliable because of marked differences in milk composition and transporters compared to those of humans. Measurement of drug concentrations in humans remains the gold standard, but computer modeling is promising. New FDA labeling requirements present an opportunity to apply modeling to preclinical drug development in place of conventional animal testing for drug excretion into breastmilk, which should improve the use of medications in nursing mothers.

Modeling drug passage into human milk

Breastfeeding has positive health consequences for both the breastfed infant and the nursing mother.(1,2) Although information on drug use during lactation is available through sites such as LactMed,(3) available information is often incomplete. Unlike pregnancy, in which large numbers of pregnant women need to be studied to assure safety, measurement of drug concentrations in breastmilk in a relatively few subjects can provide valuable information to assess drug safety. This article reviews methods of measuring and predicting drug passage into breastmilk.

Pharmacokinetics of Transfer of Azithromycin into the Breast Milk of African Mothers

Azithromycin (AZI) is used for its antibiotic and antimalarial properties in pregnancy. Reported estimates of AZI breast milk transfer, based on concentrations in mostly single samples from small numbers of women, have suggested that infant intake is safe. To better characterize infant intake and the associated potential benefits and risks, AZI was measured by liquid chromatography-mass spectrometry in four breast milk samples taken over 28 days postpartum from each of 20 Gambian women given 2 g AZI during labor. A population pharmacokinetic model utilizing published parameters for AZI disposition in pregnancy, the present breast milk concentrations, and increasing/decreasing sigmoid maximum-effect (Emax) functions adequately described temporal changes in the milk/plasma ratio. The median estimated absolute and relative cumulative infant doses were 4.5 mg/kg of body weight (95% prediction interval, 0.6 to 7.0 mg/kg) and 15.7% (95% prediction interval, 2.0 to 27.8%) of the maternal dose, respectively; the latter exceeded the recommended 10% safety limit. Although some infants with bacterial infections may benefit from AZI in breast milk, there is a risk of hypertrophic pyloric stenosis with a worst-case number needed to harm of 60 based on the present and available epidemiologic data. (This study has been registered at ClinicalTrials.gov under registration no. NCT01800942.).