cells. However, we cannot exclude possible long-term neurodegenerative effects because inflammation was observed in vitro. Our simple TK model can be parameterized for other glycol ethers and used in parallel with in vitro data for systematically screening for neurotoxicity. If further developed, this approach could be adapted to predict brain neurotoxicity from exposure to organic solvents

Culot, M

Hechon, J

Heymans, M

Hopf, N, B

Reale, E

Sandstrom, J

Tschudi-Monnet, F

Vernez, D

Wellens, S

International audiencecells. However, we cannot exclude possible long-term neurodegenerative effects because inflammation was observed in vitro. Our simple TK model can be parameterized for other glycol ethers and used in parallel with in vitro data for systematically screening for neurotoxicity. If further developed, this approach could be adapted to predict brain neurotoxicity from exposure to organic solvents

HAL-Artois

Predicting human neurotoxicity of propylene glycol methyl ether (PGME) by implementing in vitro neurotoxicity results into toxicokinetic modelling

Although organic solvents have been associated with CNS toxicity, neurotoxicity testing is rarely a regulatory requirement. We propose a strategy to assess the potential neurotoxicity of organic solvents and predict solvent air concentrations that will not likely produce neurotoxicity in exposed individuals. The strategy integrated an in vitro neurotoxicity, an in vitro blood-brain barrier (BBB), and an in silico toxicokinetic (TK) model. We illustrated the concept with propylene glycol methyl ether (PGME), widely used in industrial and consumer products. The positive control was ethylene glycol methyl ether (EGME) and negative control propylene glycol butyl ether (PGBE), a supposedly non-neurotoxic glycol ether. PGME, PGBE, and EGME had high passive permeation across the BBB (permeability coefficients (P &lt;sub&gt;e&lt;/sub&gt; ) 11.0 × 10 &lt;sup&gt;-3&lt;/sup&gt; , 9.0 × 10 &lt;sup&gt;-3&lt;/sup&gt; , and 6.0 × 10 &lt;sup&gt;-3&lt;/sup&gt; cm/min, respectively). PGBE was the most potent in in vitro repeated neurotoxicity assays. EGME's main metabolite, methoxyacetic acid (MAA) may be responsible for the neurotoxic effects reported in humans. No-observed adverse effect concentrations (NOAECs) for the neuronal biomarker were for PGME, PGBE, and EGME 10.2, 0.07, and 79.2 mM, respectively. All tested substances elicited a concentration-dependent increase in pro-inflammatory cytokine expressions. The TK model was used for in vitro-to-in vivo extrapolation from PGME NOAEC to corresponding air concentrations (684 ppm). In conclusion, we were able to predict air concentrations that would not likely result in neurotoxicity using our strategy. We confirmed that the Swiss PGME occupational exposure limit (100 ppm) will not likely produce immediate adverse effects on brain cells. However, we cannot exclude possible long-term neurodegenerative effects because inflammation was observed in vitro. Our simple TK model can be parameterized for other glycol ethers and used in parallel with in vitro data for systematically screening for neurotoxicity. If further developed, this approach could be adapted to predict brain neurotoxicity from exposure to organic solvents

Reale, E.

Sandstrom, J.

Culot, M.

Hechon, J.

Wellens, S.

Heymans, M.

Tschudi-Monnet, F.

Vernez, D.

Hopf, N.B.

Serveur académique lausannois

English

Predicting human neurotoxicity of propylene glycol methyl ether (PGME) by implementing in vitro neurotoxicity results into toxicokinetic modelling.

https://serval.unil.ch/resource/serval:BIB_7A0512F4231F.P001/REF.pdf

Predicting human neurotoxicity of propylene glycol methyl ether (PGME) by implementing in vitro neurotoxicity results into toxicokinetic modelling

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HAL-Artois

Serveur académique lausannois