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

Abstract

Aims: Population pharmacokinetic (pop PK) modelling can be used for PK assessment of drugs in breast milk. However, complex mechanistic modelling of a parent and an active metabolite using both blood and milk samples is challenging. We aimed to develop a simple predictive pop PK model for milk concentration-time profiles of a parent and a metabolite, using data on fluoxetine (FX) and its active metabolite, norfluoxetine (NFX), in milk.

Methods: Using a previously published data set of drug concentrations in milk from 25 women treated with FX, a pop PK model predictive of milk concentration-time profiles of FX and NFX was developed. Simulation was performed with the model to generate FX and NFX concentration-time profiles in milk of 1000 mothers. This milk concentration-based pop PK model was compared with the previously validated plasma/milk concentration-based pop PK model of FX.

Results: Milk FX and NFX concentration-time profiles were described reasonably well by a one compartment model with a FX-to-NFX conversion coefficient. Median values of the simulated relative infant dose on a weight basis (sRID: weight-adjusted daily doses of FX and NFX through breastmilk to the infant, expressed as a fraction of therapeutic FX daily dose per body weight) were 0.028 for FX and 0.029 for NFX. The FX sRID estimates were consistent with those of the plasma/milk-based pop PK model.

Conclusions: A predictive pop PK model based on only milk concentrations can be developed for simultaneous estimation of milk concentration-time profiles of a parent (FX) and an active metabolite (NFX).

Keywords: breast milk; fluoxetine; modelling; population pharmacokinetics; simulation.

Figure 1

Goodness-of-fit plots. The observed milk FX (Figure 1A) and NFX (Figure 1B) concentrations are plotted against the mean population predicted values (left), and the individually predicted (Post Hoc) predictive values (right). Figure 1C shows weighted residuals of FX (left) and NFX (right)

Figure 2

Visual predictive check (VPC) in FX (panel A) and NFX (panel B). Observed FX or NFX concentrations are shown (white circles) with the median (solid line), 2.5th percentile (lower broken line), and 97.5th percentile predictions from the model. NF or NFX concentrations from the published article are also shown (black circles). Data points in those articles without specified post-dose sampling time are shown outside the 24 h time frame. Concentrations described as ‘peak’ without specific post-dose time are plotted at 7 h post-dose because a reported average post-dose time of a peak concentration of FX was 6 to 8 h . (A) —, median (model prediction); - - -, 2.5th–97.5th percentile (model prediction); ○, observed FX data (present study); •, observed FX data from other studies (external validation). (B) —, median (model prediction); - - -, 2.5th–97.5th percentile (model prediction); ○, observed NFX data (present study); •, observed NFX data from other studies (external validation)

Figure 3

A histogram of simulated relative infant dose (sRID) of FX, NFX, and FX + NFX. One thousand infants were simulated using the final model with randomly assigned feeding parameters according to characteristics of milk intake of infants aged between 4 weeks and 6 months ,. The simulation results are shown as the probability distribution of infant exposure levels in the form of a histogram of sRID of FX (panel A), NFX (panel B), and FX+NFX (panel C). sRID is a dose the infant would ingest per day, which is expressed as % of the standard dose kg⁻¹ of the mother (see Methods). Median (open triangles) and 99th percentile values (closed triangles) of sRID were also shown. NFX results were converted to FX equivalent on a molar basis. In Figure 3A, FX simulation results are shown with a histogram of the previous study , which was based on a model of blood and milk FX concentrations. (A) , present study; , median (2.8%); , 99th percentile (8.3%); , Panchaud et al. . (B) , median (2.9%); , 99th percentile (15.0%). (C) , median (5.9%); , 99th percentile (23.0%)