ArticleEnvironmental science & technology2026
DYNAMEX: A Time-Resolved Model for Predicting Distribution of Chemicals in In Vitro Cell Assays.
Article in Environmental science & technology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
High-throughput in vitro cell assays are promising tools for predicting chemical-induced health effects in humans. Quantifying freely dissolved medium (Cfree,medium) and cellular concentrations is essential for robust quantitative in vitro-in vivo extrapolation (QIVIVE), but the miniaturized format of 384- and 1536-well plates makes these metrics challenging to measure directly. We developed DYNAMEX (dynamic NAM exposure), a time-resolved kinetic model simulating chemical fate in cell assays, accounting for volatilization, medium binding, well-plate sorption, and cellular uptake, including growth dilution. The model accurately captured uptake kinetics for neutral compounds and newly measured PFAS cellular uptake kinetics, reproduced empirical thresholds for volatilization losses, and predicted free fractions in medium across 51 compounds (RMSE = 0.49 log10 units) and cellular-to-nominal concentration ratios across 17 compounds (RMSE = 0.56 log10 units) under different bioassay conditions. Simulations across 113 chemicals and varying assay setups showed that, under standard assay conditions using 10% FBS, equilibrium mass balance modeling predicted Cfree,medium within 10% for 83 of 113 compounds and is sufficient for most applications. Kinetic modeling is required when volatilization or well-plate sorption causes substantial mass losses, particularly under serum-free conditions and in miniaturized formats, or when low membrane permeability limits cellular uptake within the assay duration, as observed for several hydrophobic ionizable organic chemicals. The model provides a mechanistic framework to improve in vitro dosimetry, guide assay design, and support integration of time-resolved exposure metrics into QIVIVE and in vivo modeling workflows.
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