CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495

Conception, synthèse et évaluation d'inhibiteurs mixtes de la transcriptase inverse du VIH

PARIS-BIUP (751062107) / SudocSudocFranceF

Microphysiological flux balance platform unravels the dynamics of drug induced steatosis

Drug development is currently hampered by the inability of animal experiments to accurately predict human response. While emerging organ on chip technology offers to reduce risk using microfluidic models of human tissues, the technology still mostly relies on end-point assays and biomarker measurements to assess tissue damage resulting in limited mechanistic information and difficulties to detect adverse effects occurring below the threshold of cellular damage. Here we present a sensor-integrated liver on chip array in which oxygen is monitored using two-frequency phase modulation of tissue-embedded microprobes, while glucose, lactate and temperature are measured in real time using microfluidic electrochemical sensors. Our microphysiological platform permits the calculation of dynamic changes in metabolic fluxes around central carbon metabolism, producing a unique metabolic fingerprint of the liver's response to stimuli. Using our platform, we studied the dynamics of human liver response to the epilepsy drug Valproate (Depakine) and the antiretroviral medication Stavudine (Zerit). Using E6/E7(LOW) hepatocytes, we show TC50 of 2.5 and 0.8 mM, respectively, coupled with a significant induction of steatosis in 2D and 3D cultures. Time to onset analysis showed slow progressive damage starting only 15-20 hours post-exposure. However, flux analysis showed a rapid disruption of metabolic homeostasis occurring below the threshold of cellular damage. While Valproate exposure led to a sustained 15% increase in lipogenesis followed by mitochondrial stress, Stavudine exposure showed only a transient increase in lipogenesis suggesting disruption of -oxidation. Our data demonstrates the importance of tracking metabolic stress as a predictor of clinical outcome

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite.

In this article, the “ Acknowledgments ” section was missing the text below: H.C., D.P.R., and H.Z. at Rutgers University at Camden were partially supported by the NIEHS (grants R01ES031080 and R15ES023148).The authors regret the error