The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.

All areas of the modern society are affected by fluorine chemistry. In particular, fluorine plays an important role in medical, pharmaceutical and agrochemical sciences. Amongst various fluoro-organic compounds, trifluoromethyl (CF3) group is valuable in applications such as pharmaceuticals, agrochemicals and industrial chemicals. In the present study, following the strict OECD modelling principles, a quantitative structure-toxicity relationship (QSTR) modelling for the rat acute oral toxicity of trifluoromethyl compounds (TFMs) was established by genetic algorithm-multiple linear regression (GA-MLR) approach. All developed models were evaluated by various state-of-the-art validation metrics and the OECD principles. The best QSTR model included nine easily interpretable 2D molecular descriptors with clear physical and chemical significance. The mechanistic interpretation showed that the atom-type electro-topological state indices, molecular connectivity, ionization potential, lipophilicity and some autocorrelation coefficients are the main factors contributing to the acute oral toxicity of TFMs against rats. To validate that the selected 2D descriptors can effectively characterize the toxicity, we performed the chemical read-across analysis. We also compared the best QSTR model with public OPERA tool to demonstrate the reliability of the predictions. To further improve the prediction range of the QSTR model, we performed the consensus modelling. Finally, the optimum QSTR model was utilized to predict a true external set containing many untested/unknown TFMs for the first time. Overall, the developed model contributes to a more comprehensive safety assessment approach for novel CF3-containing pharmaceuticals or chemicals, reducing unnecessary chemical synthesis whilst saving the development cost of new drugs.

The estimation of acute oral toxicity (LD50) of G-series organophosphorus-based chemical warfare agents using quantitative and qualitative toxicology in silico methods.

The idea of this study was the estimation of the theoretical acute toxicity (t-LD50, rat, oral dose) of organophosphorus-based chemical warfare agents from the G-series (n = 12) using different in silico methods. Initially identified in Germany, the G-type nerve agents include potent compounds such as tabun, sarin, and soman. Despite their historical significance, there is a noticeable gap in acute toxicity data for these agents. This study employs qualitative (STopTox and AdmetSAR) and quantitative (TEST; CATMoS; ProTox-II and QSAR Toolbox) in silico methods to predict LD50 values, offering an ethical alternative to animal testing. Additionally, we conducted quantitative extrapolation from animals, and the results of qualitative tests confirmed the acute toxicity potential of these substances and enabled the identification of toxicophoric groups. According to our estimations, the most lethal agents within this category were GV, soman (GD), sarin (GB), thiosarin (GBS), and chlorosarin (GC), with t-LD50 values (oral administration, extrapolated from rat to human) of 0.05 mg/kg bw, 0.08 mg/kg bw, 0.12 mg/kg bw, 0.15 mg/kg bw, and 0.17 mg/kg bw, respectively. On the contrary, compounds with a cycloalkane attached to the phospho-oxygen linkage, specifically methyl cyclosarin and cyclosarin, were found to be the least toxic, with values of 2.28 mg/kg bw and 3.03 mg/kg bw. The findings aim to fill the knowledge gap regarding the acute toxicity of these agents, highlighting the need for modern toxicological methods that align with ethical considerations, next-generation risk assessment (NGRA) and the 3Rs (replacement, reduction and refinement) principles.

Evaluation of in silico model predictions for mammalian acute oral toxicity and regulatory application in pesticide hazard and risk assessment.

The United States Environmental Protection Agency (USEPA) uses the lethal dose 50% (LD50) value from in vivo rat acute oral toxicity studies for pesticide product label precautionary statements and environmental risk assessment (RA). The Collaborative Acute Toxicity Modeling Suite (CATMoS) is a quantitative structure-activity relationship (QSAR)-based in silico approach to predict rat acute oral toxicity that has the potential to reduce animal use when registering a new pesticide technical grade active ingredient (TGAI). This analysis compared LD50 values predicted by CATMoS to empirical values from in vivo studies for the TGAIs of 177 conventional pesticides. The accuracy and reliability of the model predictions were assessed relative to the empirical data in terms of USEPA acute oral toxicity categories and discrete LD50 values for each chemical. CATMoS was most reliable at placing pesticide TGAIs in acute toxicity categories III (>500-5000 mg/kg) and IV (>5000 mg/kg), with 88% categorical concordance for 165 chemicals with empirical in vivo LD50 values ≥ 500 mg/kg. When considering an LD50 for RA, CATMoS predictions of 2000 mg/kg and higher were found to agree with empirical values from limit tests (i.e., single, high-dose tests) or definitive results over 2000 mg/kg with few exceptions.

A comprehensive prediction system for silkworm acute toxicity assessment of environmental and in-silico pesticides.

The excessive application and loss of pesticides poses a great risk to the ecosystem, and the environmental safety assessment of pesticides is time-consuming and expensive using traditional animal toxicity tests. In this work, a pesticide acute toxicity dataset was created for silkworm integrating extensive experiments and various common pesticide formulations considering the sensitivity of silkworm to adverse environment, its economic value in China, and a gap in machine learning (ML) research on the toxicity prediction of this species, which addressed the previous limitation of only being able to predict toxicity classification without specific toxicity values. A new comprehensive voting model (CVR) was developed based on ML, combined with three regression algorithms, namely, Bayesian Ridge (BR), K Neighbors Regressor (KNN), Random Forest Regressor (RF) to accurately calculate lethal concentration 50 % (LC50). Three conformal models were successfully constructed, marking the first combination of conformal models with confidence intervals to predict silkworm toxicity. Further, the mechanism by analyzing structural alerts was summarized, and identified 25 warning structures, 24 positive compounds and 14 negative compounds. Importantly, a novel comprehensive prediction system was constructed that can provide LC50 and confidence intervals, structural alerts analysis, lipid-water partition coefficient (LogP) and similarity analysis, which can comprehensively evaluate the ecological toxicity risk of substances to make up for the incomplete toxicity data of new pesticides. The validity and generalization of the CVR model were verified by an external validation set. In addition, five new, low-toxic and green pesticide alternatives were designed through 50,000 cycles. Moreover, our software and ST Profiler can provide low-cost information access to accelerate environmental risk assessment, which can predict not only a single chemical, but also batches of chemicals, simply by inputting the SMILES / CAS / (Chinese / English) name of chemicals.

Acute Toxicity Assays with the Artemia salina Model: Assessment of Variables.

The use of the brine shrimp Artemia salina (Leach) in acute toxicity assays has great potential due to its simplicity, low cost and reproducibility. In the current study, some of the variables that can influence the reliability of the assay in terms of test organism survival, were evaluated as part of its implementation in our laboratory. The quality and type of water used, the buffer components and other parameters (salinity, pH and dissolved oxygen level), were all evaluated for optimisation purposes. DMSO (dimethyl sulphoxide) was used as the test substance in the toxicity assay, to evaluate the concentration limits as a solvent in sample preparation. Regarding the buffer salinity, pH and dissolved oxygen level, we found that a 25% to 30% deviation from the standard values did not affect the survival of the nauplii (the first-instar larval stage) under assay conditions. In summary, we corroborate the potential use of this model for the prediction of the toxic potential of substances, to inform future testing strategies.

An improved method for toxicological profiling of chemical substances.

Toxicity profiling is an integral part of the drug discovery pipeline. The 3Rs principle-Replacement, Reduction, and Refinement, is considered a golden rule in determining the most appropriate approach for toxicity studies. The acute toxicity study with proper estimate of median lethal dose (LD50) is usually an initial procedure for the determination of most suitable test doses for preclinical toxicological and pharmacological profiling. Several methods, which have been devised to determine the LD50, are faced with the challenge of using a large number of animals and time constraints. Despite the inherent advantage of the newer OECD Test Guidelines, the increasing concerns among toxicologists, the regulatory authorities and the general public, on the need to adhere to 3Rs principle, necessitated the need for an improved approach. Such an approach should not only minimize the time and number of animals required, but also take into cognizance animal welfare, and give accurate, comparable, and reproducible results across laboratories. While taking advantage of the inherent merits of the existing methods, here is presented the mathematical basis and evaluation of an improved method for toxicity profiling of test substances and estimation of LD50. The method makes use of the generated Table of values for the selection of appropriate test doses. Our proposed method has capacities to optimize the time and number of animal use, ensure more reliable and reproducible results across laboratories, allow for easy selection of doses for subsequent toxicity profiling, and be adaptable to other biological screening beyond toxicity studies.

Evaluation of the fish acute toxicity test for pesticide registration.

The U.S. Environmental Protection Agency (USEPA) uses the in vivo fish acute toxicity test to assess potential risk of substances to non-target aquatic vertebrates. The test is typically conducted on a cold and a warm freshwater species and a saltwater species for a conventional pesticide registration, potentially requiring upwards of 200 or more fish. A retrospective data evaluation was conducted to explore the potential for using fewer fish species to support conventional pesticide risk assessments. Lethal concentration 50% (LC50) values and experimental details were extracted and curated from 718 studies on fish acute toxicity submitted to USEPA. The LC50 data were analysed to determine, when possible, the relative sensitivity of the tested species to each pesticide. One of the tested freshwater species was most sensitive in 85% of those cases. The tested cold freshwater species was the most sensitive overall among cases with established relative sensitivity and was within 3X of the LC50 value of the most sensitive species tested in 98% of those cases. The results support potentially using fewer than three fish species to conduct ecological risk assessments for the registration of conventional pesticides.

The application of acute oral toxicity computational models in dangerous goods classification.

Acute oral toxicity (AOT) data inform the acute toxicity potential of a compound and guides occupational safety and transportation practices. AOT data enable the categorization of a chemical into the appropriate AOT Globally Harmonized System (GHS) category based on the severity of the hazard. AOT data are also utilized to identify compounds that are Dangerous Goods (DGs) and subsequent transportation guidance for shipping of these hazardous materials. Proper identification of DGs is challenging for novel compounds that lack data. It is not feasible to err on the side of caution for all compounds lacking AOT data and to designate them as DGs, as shipping a compound as a DG has cost, resource, and time implications. With the wealth of available historical AOT data, AOT testing approaches are evolving, and in silico AOT models are emerging as tools that can be utilized with confidence to assess the acute toxicity potential of de novo molecules. Such approaches align with the 3R principles, offering a reduction or even replacement of traditional in vivo testing methods and can also be leveraged for product stewardship purposes. Utilizing proprietary historical in vivo AOT data for 210 pharmaceutical compounds (PCs), we evaluated the performance of two established in silico AOT programs: the Leadscope AOT Model Suite and the Collaborative Acute Toxicity Modeling Suite. These models accurately identified 94% and 97% compounds that were not DGs (GHS categories 4, 5, and not classified (NC)) suggesting that the models are fit-for-purpose in identifying PCs with low acute oral toxicity potential (LD50 >300 mg/kg). Utilization of these models to identify compounds that are not DGs can enable them to be de-prioritized for in vivo testing. This manuscript provides a detailed evaluation and assessment of the two models and recommends the most suitable applications of such models.

Development a high-throughput zebrafish embryo acute toxicity testing method based on OECD TG 236.

The Organization for Economic Co-operation and Development (OECD）Test Guideline (TG) 236 for zebrafish embryo acute toxicity testing was adopted for chemical toxicity assessment in 2013. Due to the increasing demand for prediction and evaluation of the acute toxicity using zebrafish embryos, we developed a method based on OECD 236 test guideline with the aim to improve the testing efficiency. We used 4-128 cell stage zebrafish embryos and performed an exposure assay in a 96-well microtiter plate, observing the lethality endpoints of embryos at 48-h postexposure. A total of 32 chemicals (two batches) were used in the comparison study. Our results indicated that the logarithmic LC50 (half lethal concentration) obtained by the modified method exhibited good correlation with that obtained by the OECD 236 testing method, and the R2 of the linear regression analysis was 0.9717 (0.9621 and 0.9936 for the two batches, respectively). Additionally, the intra- and inter-laboratory coefficient of variation (CVs) for the LC50 from the testing chemicals (17 chemicals in second batch) was less than 30%, except for CuSO4. Therefore, the developed method was less time-consuming and demonstrated a higher throughput for toxicity testing compared to the prior method. We argue the developed method could be used as an additional choice for high-throughput zebrafish embryo acute toxicity test.

High-Fidelity Drug-Induced Liver Injury Screen Using Human Pluripotent Stem Cell-Derived Organoids.

BACKGROUND & AIMS: Preclinical identification of compounds at risk of causing drug induced liver injury (DILI) remains a significant challenge in drug development, highlighting a need for a predictive human system to study complicated DILI mechanism and susceptibility to individual drug. Here, we established a human liver organoid (HLO)-based screening model for analyzing DILI pathology at organoid resolution. METHODS: We first developed a reproducible method to generate HLO from storable foregut progenitors from pluripotent stem cell (PSC) lines with reproducible bile transport function. The qRT-PCR and single cell RNA-seq determined hepatocyte transcriptomic state in cells of HLO relative to primary hepatocytes. Histological and ultrastructural analyses were performed to evaluate micro-anatomical architecture. HLO based drug-induced liver injury assays were transformed into a 384 well based high-speed live imaging platform. RESULTS: HLO, generated from 10 different pluripotent stem cell lines, contain polarized immature hepatocytes with bile canaliculi-like architecture, establishing the unidirectional bile acid transport pathway. Single cell RNA-seq profiling identified diverse and zonal hepatocytic populations that in part emulate primary adult hepatocytes. The accumulation of fluorescent bile acid into organoid was impaired by CRISPR-Cas9-based gene editing and transporter inhibitor treatment with BSEP. Furthermore, we successfully developed an organoid based assay with multiplexed readouts measuring viability, cholestatic and/or mitochondrial toxicity with high predictive values for 238 marketed drugs at 4 different concentrations (Sensitivity: 88.7%, Specificity: 88.9%). LoT positively predicts genomic predisposition (CYP2C9∗2) for Bosentan-induced cholestasis. CONCLUSIONS: Liver organoid-based Toxicity screen (LoT) is a potential assay system for liver toxicology studies, facilitating compound optimization, mechanistic study, and precision medicine as well as drug screening applications.

The use of Bayesian methodology in the development and validation of a tiered assessment approach towards prediction of rat acute oral toxicity.

There exists consensus that the traditional means by which safety of chemicals is assessed-namely through reliance upon apical outcomes obtained following in vivo testing-is increasingly unfit for purpose. Whilst efforts in development of suitable alternatives continue, few have achieved levels of robustness required for regulatory acceptance. An array of "new approach methodologies" (NAM) for determining toxic effect, spanning in vitro and in silico spheres, have by now emerged. It has been suggested, intuitively, that combining data obtained from across these sources might serve to enhance overall confidence in derived judgment. This concept may be formalised in the "tiered assessment" approach, whereby evidence gathered through a sequential NAM testing strategy is exploited so to infer the properties of a compound of interest. Our intention has been to provide an illustration of how such a scheme might be developed and applied within a practical setting-adopting for this purpose the endpoint of rat acute oral lethality. Bayesian statistical inference is drawn upon to enable quantification of degree of confidence that a substance might ultimately belong to one of five LD50-associated toxicity categories. Informing this is evidence acquired both from existing in silico and in vitro resources, alongside a purposely-constructed random forest model and structural alert set. Results indicate that the combination of in silico methodologies provides moderately conservative estimations of hazard, conducive for application in safety assessment, and for which levels of certainty are defined. Accordingly, scope for potential extension of approach to further toxicological endpoints is demonstrated.

Potential of the zebrafish (Danio rerio) embryo test to discriminate between chemicals of similar molecular structure-a study with valproic acid and 14 of its analogues.

Valproic acid is a frequently used antiepileptic drug and known pediatric hepatotoxic agent. In search of pharmaceuticals with increased effectiveness and reduced toxicity, analogue chemicals came into focus. So far, toxicity and teratogenicity data of drugs and metabolites have usually been collected from mammalian model systems such as mice and rats. However, in an attempt to reduce mammalian testing while maintaining the reliability of toxicity testing of new industrial chemicals and drugs, alternative test methods are being developed. To this end, the potential of the zebrafish (Danio rerio) embryo to discriminate between valproic acid and 14 analogues was investigated by exposing zebrafish embryos for 120 h post fertilization in the extended version of the fish embryo acute toxicity test (FET; OECD TG 236), and analyzing liver histology to evaluate the correlation of liver effects and the molecular structure of each compound. Although histological evaluation of zebrafish liver did not identify steatosis as the prominent adverse effect typical in human and mice, the structure-activity relationship (SAR) derived was comparable not only to human HepG2 cells, but also to available in vivo mouse and rat data. Thus, there is evidence that zebrafish embryos might serve as a tool to bridge the gap between subcellular, cell-based systems and vertebrate models.

Evaluation of the predictivity of Acute Oral Toxicity (AOT) structure-activity relationship models.

Several public efforts are aimed at discovering patterns or classifiers in the high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. The current study sought to assess and compare the predictions of the Globally Harmonized System (GHS) categories and Dangerous Goods (DG) classifications based on Lethal Dose (LD50) from several available tools (ACD/Labs, Leadscope, T.E.S.T., CATMoS, CaseUltra). External validation was done using dataset of 375 substances to demonstrate their predictive capacity. All models showed very good performance for identifying non-toxic compounds, which would be useful for DG classification, developing or triaging new chemicals, prioritizing existing chemicals for more detailed and rigorous toxicity assessments, and assessing non-active pharmaceutical intermediates. This would ultimately reduce animal use and improve risk assessments. Category-to-category prediction was not optimal, mainly due to the tendency to overpredict the outcome and the general limitations of acute oral toxicity (AOT) in vivo studies. Overprediction does not specifically pose a risk to human health, it can impact transport and material packaging requirements. Performance for compounds with LD50 ≤ 300 mg/kg (approx. 5% of the dataset) was the poorest among all groups and could be potentially improved by including expert review and read-across to similar substances.

Evaluation of hepatoprotective effects of crude methanolic extract of Datura metel L. in mice.

Datura metel has been recommended in several human disorders including a remedy for liver toxicity. The current study was designed to evaluate the hepatoprotective effect of methanolic extract of D. metel in animal model. Acute toxicity of methanolic crude extract of Datura metel (MEDM) was studied in animals in various doses 500-2000 mg/kg. Mice of either sex were divided into groups (n=6). One group received normal saline intraperitonially as negative control, while other gentamicin 100mg/kg for 8 days as positive control. 3rd group received 50mg/kg silymarin as standard, 4th group received 100mg/kg of MEDM, 5th group received 200mg/kg MEDM while 6th group received 300mg/kg MEDM and gentamicin 100mg/kg for 8 days. The blood samples were collected on 9th day and the animals were then dissected and the liver of all the animals were isolated. MEDM was found safe in acute toxicity test at various doses up to 2000 mg/kg. The levels of serum glutamic pyruvic transaminase and alkaline phosphatase were elevated significantly with gentamicin treatment which significantly down-regulated by MEDM (100, 200 and 300 mg/kg) in a dose dependent manner.. The histological examination showed that the MEDM has markedly treated the inflammatory infiltrate, fatty changes and congested blood vessels which were induced by gentamicin.  The findings of our study thus proved the absolute of MEDM in acute toxicity test; followed by significant hepatoprotective effect in gentamicin induced hepatotoxic mice.

In vivo acute toxicity, laxative and antiulcer effect of the extract of Dryopteris Ramose.

Dryopteris ramosa (D. ramosa) is one of the most traded medicinally important plants of Himalayan region. Apart from other uses, D. ramosa is traditionally also used to treat gastric ulcers and as a laxative. The present study was designed to investigate the role of methanolic crude extract of Dryopteris Ramosa (MEDR) in acute toxicity, against loperamide induced constipated mice model, antiulcer effect of methanolic extract of D. Ramosa and cholinomimetic like effect of methanolic extract of D. Ramosa. The crude extract was investigated for the presence of active compounds (secondary metabolites) such as alkaloids, flavonoids, carbohydrates, glycosides, terpenoids, phenolic compounds, saponins, and tannins following the standard methods. The antiulcer effect was investigated in mice using the ethanol induced ulcer model at various doses i.e. 50 mg/kg, 100 mg/kg and 200 mg/kg doses. Constipation was induced in the mice via loperamide (3mg/kg body weight). The control group received normal saline. Different doses of plant extracts (50, 100, 150 and 200 mg/kg body weight/day) were administered for 7 days. Various parameters like feeding characteristics, gastrointestinal transit ratio, body weight, fecal properties and the possible mechanism of action of D. Ramosa on intestinal motility were monitored. Various Phytochemicals like saponins, glycosides, flavonoids, tannins, phenols, carbohydrate, alkaloids and triterpenes were found in D. Ramosa. The acute toxicity study showed that MEDR was associated with no mortality except mild and moderate sedation at the highest tested doses (1500 and 2000 mg/kg). MEDR also showed significant antiulcer activity against ethanol-induced ulcerogenesis. The extract enhanced the intestinal motility, normalized the body weight of constipated mice and increased the fecal volume which are indications of laxative property of the herb. The 200 mg/kg body weight dose of the extract was found effective. The presence of various Phytochemicals such as flavonoids, glycosides and tannins might be responsible for the antiulcer activity of D. Ramosa. This study provides the scientific background for the folkloric use of D. Ramosa as antiulcer agent. The laxative action of the extract compares positively with Duphalac, (standard laxative drug). These findings have therefore evidence scientific background to the folkloric use of the herb as a laxative agent.

Comparison of the Effects of Intraperitoneal Injection with Carbon Tetrachloride on Acute Liver Toxicity in Male and Female Kunming Mice.

BACKGROUND Acute chemical liver injury needs to be further explored. The present study aimed to compare the effects of intraperitoneal injection with carbon tetrachloride on acute liver toxicity after 24 h in male and female Kunming mice. MATERIAL AND METHODS In this study, female and male mice were simultaneously divided into 3 different groups. Each group was treated differently, and after 24 h, blood samples were collected to check for changes in the activity of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), which were used to assess liver toxicity. Liver samples were used for hematoxylin-eosin staining, and periodic acid Schiff reagent staining was performed to detect the pathological changes of each group. The expression level of biomarker molecules in liver cells was also systematically analyzed. RESULTS Our results showed that, compared with male mice, female mice showed more serious damage: reduced glycogen and higher degree of necrosis, and the levels of heatshock protein 27 (HSP27), heat-shock protein 70 (HSP70), proliferating cell nuclear antigen (PCNA) and B cell lymphoma/lewkmia-2 (Bcl-2) were significantly lower than in the male group (P<0.05 or P<0.01), while the results of Bcl-2-associated X protein (Bax), cysteinyl aspartate specific proteinase 3 (Caspase3), and cytochrome P450 2E1 (CYP2E1) were the opposite (P<0.05 or P<0.01). CONCLUSIONS The findings from this study showed that, compared with male mice, at 24 h after CCl4 toxicity, female mice showed more severe changes of hepatocyte necrosis and PAS-positivity, with significantly reduced expression of HSP27, HSP70, PCNA, and Bcl-2, and significantly increased expression of Bax, caspase-3, and CYP2E1.

In silico prediction of the full United Nations Globally Harmonized System eye irritation categories of liquid chemicals by IATA-like bottom-up approach of random forest method.

As an alternative to in vivo Draize rabbit eye irritation test, this study aimed to construct an in silico model to predict the complete United Nations (UN) Globally Harmonized System (GHS) for classification and labeling of chemicals for eye irritation category [eye damage (Category 1), irritating to eye (Category 2) and nonirritating (No category)] of liquid chemicals with Integrated approaches to testing and assessment (IATA)-like two-stage random forest approach. Liquid chemicals (n = 219) with 34 physicochemical descriptors and quality in vivo data were collected with no missing values. Seven machine learning algorithms (Naive Bayes, Logistic Regression, First Large Margin, Neural Net, Random Forest (RF), Gradient Boosted Tree, and Support Vector Machine) were examined for the ternary categorization of eye irritation potential at a single run through 10-fold cross-validation. RF, which performed best, was further improved by applying the 'Bottom-up approach' concept of IATA, namely, separating No category first, and discriminating Category 1 from 2, thereafter. The best performing training dataset achieved an overall accuracy of 73% and the correct prediction for Category 1, 2, and No category was 80%, 50%, and 77%, respectively for the test dataset. This prediction model was further validated with an external dataset of 28 chemicals, for which an overall accuracy of 71% was achieved.

Automated read-across workflow for predicting acute oral toxicity: I. The decision scheme in the QSAR toolbox.

A decision-scheme outlining the steps for identifying the appropriate chemical category and subsequently appropriate tested source analog(s) for data gap filling of a target chemical by read-across is described. The primary features used in the grouping of the target chemical with source analogues within a database of 10,039 discrete organic substances include reactivity mechanisms associated with protein interactions and specific-acute-oral-toxicity-related mechanisms (e.g., mitochondrial uncoupling). Additionally, the grouping of chemicals making use of the in vivo rat metabolic simulator and neutral hydrolysis. Subsequently, a series of structure-based profilers are used to narrow the group to the most similar analogues. The scheme is implemented in the OECD QSAR Toolbox, so it automatically predicts acute oral toxicity as the rat oral LD50 value in log [1/mol/kg]. It was demonstrated that due to the inherent variability in experimental data, classification distribution should be employed as more adequate in comparison to the exact classification. It was proved that the predictions falling in the adjacent GSH categories to the experimentally-stated ones are acceptable given the variation in experimental data. The model performance estimated by adjacent accuracy was found to be 0.89 and 0.54 while based on R2. The mechanistic and predictive coverages were >0.85.

Increasing confidence in waiving dermal toxicity studies: A comparison of oral and dermal acute data with alternative approaches for agrochemicals and products.

The refinement of OECD 402 study design and criteria under which the study can be waived has been welcomed in some regulatory regions but met with uncertainty in others. To address these human safety concerns, previously available in vivo acute oral and acute dermal toxicity data was evaluated from a total of 597 agrochemical active ingredients and products. It was identified that all active ingredients and 99.6% of products had an acute dermal classification equal to or less toxic than their acute oral classification, confirming that waiving the acute dermal study and basing the outcome on the acute oral toxicity result has no impact on human health assessment. Additionally, automated Acute Toxicity Estimate (ATE) calculations were conducted on 440 products to evaluate if the predicted dermal toxicity resulted in the same in vivo classification. 93% of ATE predictions provided excellent correlation to the in vivo result and 6.4% resulted in a more conservative prediction. It is therefore clear that the results of this investigation, should remove any regulatory concerns and that OECD 402 can be confidently eliminated in its entirety from testing requirements globally.

Sarsasapogenin and fluticasone combination improves DNFB induced atopic dermatitis lesions in BALB/c mice.

OBJECTIVE: Atopic dermatitis (AD) is a pruritic, chronic, relapsing inflammatory skin disease. The research aims to study the effects of Sarsasapogenin and its combination with Fluticasone in 2, 4-Dinitrofluorobenzene (DNFB) induced atopic dermatitis in BALB/c mice. MATERIAL AND METHODS: Thirty male Balb/c mice were divided into 5 groups: (i) Normal control (NC), (ii) Disease control (DNFB), (iii) Sarsasapogenin (SG) (50 µg/mice), (iv) Fluticasone (FC) (50 µg/mice), (v) Sarsasapogenin + Fluticasone (SG + FC) combination (25 µg/mice). Dermatitis was induced by repeated application of DNFB in Balb/c mice. On topical application of SG, FC, and SG + FC combination on the ear and skin lesions, body weight, ear weight, ear thickness, erythema score, spleen weight, cytokines, immunoglobulin E (IgE) levels, nitric oxide (NO) level, hematological parameters, and oxidative stress markers were evaluated. Histological analysis of the ear tissue was also done. RESULTS: The results stated that SG and SG + FC treatment to mice considerably decrease the ear weight, ear thickness, spleen weight, serum IgE, cytokines, NO levels, and restoration of antioxidant stress markers with elevation in the hematological parameters. The observations were further confirmed by histopathological analysis of ear tissue. CONCLUSION: These data specify that SG has been demonstrated as a probable therapy for the treatment of allergic skin diseases in combination with FC by decreasing its dose from 50 to 25 µg/mice to avoid the chronic side effects of FC. Hence, it can be concluded that SG and SG + FC combination significantly improved the AD-like symptoms in the DNFB sensitized mice through mitigating the production of proinflammatory mediators and restoration of oxidative stress markers.