Evidence map›Paper›PMID 40632507›Full record

ArticleCPT: pharmacometrics & systems pharmacology2025

Predicting Drug Transfer Into Human Milk With the Simcyp Simulator: A Contribution From the ConcePTION Project.

Julia Macente, Nina Nauwelaerts, Justine Marine Badée, Rodolfo Hernandes Bonan, Miao-Chan Huang, Martje Van Neste, Anne Smits, Karel Allegaert, Hedvig Nordeng, Markus Hovd and 2 more

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Julia MacenteDrug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0002-4452-5867
Nina NauwelaertsDrug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0001-5301-6813
Justine Marine BadéePharmacokinetic Sciences, BioMedical Research, Novartis, Basel, Switzerland.ORCID 0009-0001-5385-0223
Rodolfo Hernandes BonanBioNotus CommV, Niel, Belgium.ORCID 0000-0001-5944-2602
Miao-Chan HuangDrug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0002-8645-039X
Martje Van NesteClinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0002-0424-450X
Anne SmitsClinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0002-0710-6698
Karel AllegaertClinical Pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0001-9921-5105
Hedvig NordengDepartment of Pharmacy, University of Oslo, Oslo, Norway.ORCID 0000-0001-6361-2918
Markus HovdDepartment of Pharmacy, University of Oslo, Oslo, Norway.ORCID 0000-0002-6077-0934
Frederico Severino MartinsDepartment of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, Universidade de São Paulo, São Paulo, Brazil.ORCID 0000-0001-5555-8771
Pieter AnnaertDrug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.ORCID 0000-0003-3525-7351

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Physiologically-based pharmacokinetic (PBPK) modeling can support decision-making on maternal medication use during breastfeeding. This study aimed to enhance lactation PBPK models in two ways. First, the utility of integrating permeability- versus perfusion-limited distribution to human milk was explored using the Simcyp Simulator. Secondly, for permeability-limited models, drug-specific bidirectional intrinsic clearance across the blood-milk barrier, predicted from drug physicochemical properties, was incorporated into lactation PBPK models. Initially, reference PBPK models were developed and verified against published clinical data. Geometric Mean Fold Error (GMFE; ~accuracy) and Average Fold Error (AFE; ~bias) for these models ranged from 1.13-1.51 and 0.68-1.42, respectively. These verified models were then extended to lactation PBPK models applying either permeability- or perfusion-limited assumptions for drug distribution across the blood-milk barrier. The lactation PBPK models were applied to predict drug concentrations in human milk and relative infant doses (RID) for 11 small molecule drugs with diverse physicochemical and disposition profiles. The models successfully predicted observed plasma PK, human milk concentration-time profiles, and milk-to-plasma ratios. Nine drugs had RID values below the safety threshold of 25%, while levetiracetam and nevirapine showed relatively higher RIDs (up to 21%). Based on these findings, a decision tree is proposed to guide the selection between permeability- or perfusion-limited distribution models in future lactation PBPK applications using Simcyp. This workflow can be extended beyond the 11 model drugs evaluated, supporting broader infant risk assessment for maternal medication during lactation.

Indexed as

Milk, HumanModels, BiologicalPharmacokineticsBreast FeedingComputer SimulationFemaleHumansLactationPermeabilityPharmaceutical PreparationsPharmaceutical Preparationsbreastfeedingdaily infant dosagedrug human milk exposurematernal medicationmilk‐to‐plasma ratioperinatal pharmacologyphysiologically‐based pharmacokinetic (PBPK) modeling and simulationrelative infant dosage

Identifiers

PMID40632507
PMCPMC12439289

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.