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Mark A. Sochaski

Researcher at Research Triangle Park

Publications -  21
Citations -  1196

Mark A. Sochaski is an academic researcher from Research Triangle Park. The author has contributed to research in topics: No-observed-adverse-effect level & Population. The author has an hindex of 11, co-authored 21 publications receiving 1037 citations.

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Incorporating Human Dosimetry and Exposure into High-Throughput In Vitro Toxicity Screening

TL;DR: In this paper, metabolic clearance and plasma protein binding were used to parameterize a population-based in vitro-to-in vivo extrapolation model for estimating the human oral equivalent dose necessary to produce a steady-state in vivo concentration equivalent to in vitro AC50 (concentration at 50% of maximum activity) and LEC (lowest effective concentration).
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Incorporating High-Throughput Exposure Predictions With Dosimetry-Adjusted In Vitro Bioactivity to Inform Chemical Toxicity Testing

TL;DR: In this study, in vitro hepatic clearance and plasma protein binding were measured to estimate OEDs for a subset of Phase II chemicals and high-throughput exposure predictions generated using probabilistic modeling and Bayesian approaches generated by the U.S. Environmental Protection Agency (EPA) ExpoCast program were provided.
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Relative Impact of Incorporating Pharmacokinetics on Predicting In Vivo Hazard and Mode of Action From High-Throughput In Vitro Toxicity Assays

TL;DR: Comparison of the oral equivalent doses for the in vitro assays with the in vivo dose range that resulted in adverse effects identified more coincident in vitro Assays across chemicals than expected by chance, suggesting that the approach may also be used to identify potential molecular initiating events leading to adversity.
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Incorporating Population Variability and Susceptible Subpopulations into Dosimetry for High-Throughput Toxicity Testing

TL;DR: This study successfully combines isozyme and physiologic differences to quantitate subpopulation pharmacokinetic variability and provides a viable approach that could be employed within a high-throughput risk assessment framework.