Women commonly take medication during lactation. Currently, there is little information about the exposure-related safety of maternal medicines for breastfed infants. The aim was to explore the performance of a generic physiologically-based pharmacokinetic (PBPK) model to predict concentrations in human milk for ten physiochemically diverse medicines. First, PBPK models were developed for “non-lactating” adult individuals in PK-Sim/MoBi v9.1 (Open Systems Pharmacology). The PBPK models predicted the area-under-the-curve (AUC) and maximum concentrations (C_max) in plasma within a two-fold error. Next, the PBPK models were extended to include lactation physiology. Plasma and human milk concentrations were simulated for a three-months postpartum population, and the corresponding AUC-based milk-to-plasma (M/P) ratios and relative infant doses were calculated. The lactation PBPK models resulted in reasonable predictions for eight medicines, while an overprediction of human milk concentrations and M/P ratios (>2-fold) was observed for two medicines. From a safety perspective, none of the models resulted in underpredictions of observed human milk concentrations. The present effort resulted in a generic workflow to predict medicine concentrations in human milk. This generic PBPK model represents an important step towards an evidence-based safety assessment of maternal medication during lactation, applicable in an early drug development stage.

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.

Developed at Bayer Technology Services, PK‐Sim and MoBi transitioned into the Open Systems Pharmacology (OSP) Suite, released as free open‐source software in 2017. An active community with stakeholders from academia, industries, and regulators contributes to the continuous improvement of open‐source model‐informed drug development (MIDD). This perspective summarizes the latest advancements presented at the second OSP Community Conference (OSP‐CC) hosted from 29 to 30th of September 2025 at Sanofi Paris, that gathered over 100 attendees from more than 40 institutions.

De modo a entender melhor a influência de reforços no solo com o uso de solo melhorado. Foi realizado um estudo numérico sobre a influência da inserção de blocos de solo-cimento como reforço no topo de estacas carregadas horizontalmente, usando modelos 3D em elementos finitos, avaliando o efeito de diferentes dimensões de reforços no solo local. Os modelos simulados foram calibrados a partir dos resultados de provas de carga estática realizadas em estacas do tipo escavada de concreto armado, com e sem a utilização do reforço em solo-cimento instalado no topo. Os modelos numéricos foram construídos no software Simulia™ Abaqus® v.6.13. O comportamento constitutivo do concreto e do solo-cimento foi considerado como Concrete Damaged Plasticity (CDP) e o solo foi considerado com o modelo constitutivo de Mohr-Coulomb. Foram então simuladas computacionalmente diferentes dimensões do reforço em relação ao diâmetro da estaca, identificando sua influência na curva carga deslocamento. Como resultado, o reforço de bloco de solo-cimento melhora o desempenho da estaca, reduzindo em até 79,8% os deslocamentos horizontais identificados com o maior reforço analisado.