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The population pharmacokinetic models developed by Monfort et al.1 and Weisskopf et al.2 as part of the SSRI-Breast Milk study (NCT01796132) both identified breast milk fat content as a significant covariate influencing the milk-to-plasma ratio (MPR): doubling fat increased sertraline MPR by 95%1 and escitalopram/S-desmethylcitalopram MPR by 28%/18%.2 While we agree with the reassuring clinical conclusions regarding low infant drug exposure, we draw attention to an analytical limitation that may confound the fat-MPR covariate relationship in both studies. Both studies measured macronutrients using the Human Milk Analyser (Miris, Uppsala, Sweden).1, 2 The Miris HMA™ obtained FDA authorization through the de novo pathway3 and was required to perform interference testing per CLSI EP07, the FDA-recognized consensus standard for in vitro diagnostic devices.4 Among 30 substances tested at two clinically relevant concentrations each, both sertraline (50 and 150 μg/L) and citalopram (250 and 750 μg/L) produced a negative bias on fat measurements. The User Manual states: ‘Macronutrient analysis by Miris HMA™ is not recommended on milk that may contain any of these drugs’.5 Escitalopram, the S-enantiomer of citalopram, was not separately tested but would be expected to have equivalent mid-infrared spectroscopic properties given an identical molecular structure. The same testing included paroxetine (50–150 μg/L) and fluoxetine (100–300 μg/L), neither of which produced measurable interference.5 Of the antidepressants tested, only those identified as interferents have published data from this cohort showing fat as a significant covariate for drug transfer (Table 1). The primary concern is that fat measurements in the drug-exposed samples cannot be considered reliable. The Miris HMA™ produces a negative bias on fat in the presence of sertraline and citalopram, meaning every sample in these studies was analysed with a device documented to misread the very analyte used as the key covariate. The magnitude of the resulting bias on the fat measurement is indeterminate; it depends on the concentration-dependence of the interference, which was not characterized in the interference testing and cannot be inferred from the 2-point data available. Whether the true fat-MPR effect size is consistent with the published estimates cannot be determined without further investigation to confirm fat values in drug-containing samples. This concern is not limited to the Miris HMA™; near-infrared analysers such as the SpectraStar 2400, which have not undergone FDA authorization or CLSI EP07 interference testing, may be subject to similar or greater pharmaceutical interference given that near-infrared spectroscopy is generally more susceptible to matrix effects than mid-infrared analysis.6, 7 Beyond the research context, the Miris HMA™ is used clinically for targeted fortification of preterm infant feeds and donor milk quality control, where sertraline, citalopram and the antibiotics identified as interferents are commonly prescribed, making accurate macronutrient measurement in medication-exposed samples a practical as well as scientific concern. We suggest that future studies should (1) use reference chemistry to confirm infrared findings in medication-exposed samples; (2) perform concentration-dependent interference testing in human milk matrix; and (3) acknowledge documented interference limitations. We emphasize that the primary clinical conclusions of low infant exposure to sertraline and escitalopram through breast milk are supported by validated LC–MS/MS measurements and are unaffected by this concern. However, the mechanistic interpretation that fat content drives drug partitioning into breast milk warrants re-evaluation using methods not subject to documented interference from the drugs being studied. Sincerely, Kaytlin Krutsch, PhD, PharmD, MBA, BCPS Director, InfantRisk Center of Excellence Associate Professor, Texas Tech University Health Sciences Center School of Medicine The authors acknowledge the use of Claude (Anthropic, 2025) to assist with manuscript preparation. All factual claims, analytical reasoning and scientific interpretations were independently verified by the authors, who take full responsibility for the accuracy and integrity of this work. No funding was received for this letter. KK is the Director of the InfantRisk Center of Excellence at TTUHSC. She reports consulting fees, royalties and industry-sponsored research unrelated to this work. She holds a provisional patent for milk testing technology submitted by TTUHSC and stock ownership in Milk Monitor LLC, which holds licensing rights to the patented technology. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.