Introduction: Genotoxicity testing is critical for evaluating the safety of chemicals, pharmaceuticals, and environmental pollutants. The comet assay, or Single Cell Gel Electrophoresis (SCGE), is a widely employed method for detecting DNA damage at the single-cell level due to its sensitivity and simplicity. However, conventional manual scoring is labor-intensive, prone to observer bias, and limits the assay’s reliability and throughput. This study investigates the application of artificial intelligence (AI) and machine learning (ML) to enhance the comet assay's sensitivity, specificity, and efficiency. Methods: HepG2 cells were treated with genotoxic agents, cisplatin and doxorubicin, to induce DNA damage, followed by comet assay analysis with epifluorescence microscopy. Three ML models Support Vector Machine (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN) were employed to classify comet images based on DNA damage severity. Results and Discussion: Among these, the CNN model demonstrated superior performance, achieving 92.5% accuracy and the highest correlation ( r = 0.94) with expert annotations. The AI model also quantified key parameters, including tail length, tail moment, and DNA content in the tail, offering enhanced sensitivity and specificity over manual scoring. Cross-validation and external testing validated the robustness and generalizability of the CNN model across diverse datasets. Furthermore, the AI-driven approach facilitated high-throughput analysis and minimized inter-observer variability, addressing longstanding challenges in comet assay evaluation. These results underscore the transformative potential of AI in genotoxicity testing, providing a scalable and reliable framework for advancing in vitro toxicology.

Introduction: Drug-induced liver injury (DILI) is a significant cause of drug attrition and market withdrawal, underscoring the importance of the early assessment of hepatotoxicity during drug development. Disruption of bile acid (BA) homeostasis can precipitate liver injury, making the regulation of BA by the liver essential to prevent DILI. Conventional bile salt export pump (BSEP) inhibition assays have poor predictive value, as they do not consider the BA feedback mechanism that mitigates hepatotoxicity. In this study, we present an innovative approach for the preclinical evaluation of the BA-induced hepatotoxic potential of drug candidates. Methods: The C-DILI™ Assay employs two distinct media conditions to differentiate between BA-dependent and BA-independent cytotoxicity by measuring LDH release and ATP depletion in sandwich-cultured human hepatocytes. Seventy-one drugs were evaluated, including 49 unblinded and 22 blinded compounds with varied BSEP inhibition profiles and DILI risk. Results and Discussion: The assay successfully identified 14 drugs with BA-dependent and 7 with BA-independent hepatotoxicity. For instance, troglitazone (Trog) demonstrated BA-dependent cytotoxicity, whereas cyclosporine A exhibited BA-independent cytotoxicity. Notably, antagonism of farnesoid X receptor (FXR) emerged as a common mechanism underlying BA-dependent toxicity, consistent with FXR’s critical role in BA homeostasis. In the blinded assessment, the assay detected nine drugs with BA-dependent cytotoxicity, affirming its utility in elucidating this mechanism of liver toxicity. Of these, six drugs had documented preclinical or clinical hepatotoxicity findings, thus corroborating the strategy’s value in preclinical safety evaluation. This approach provides a comprehensive and clinically relevant framework for the preclinical prediction of BA-dependent liver toxicity, thereby strengthening preclinical DILI safety assessments. Given the varied clinical presentations and mechanisms of DILI, this strategy should be integrated into a multifaceted preclinical DILI assessment paradigm.

Introduction: Volatile organic compounds (VOCs) are ubiquitous in indoor air spaces, including the most sensitive medical environments. In assisted reproductive technology facilities, VOCs are known to greatly decrease embryo implantation rates and may impact embryo growth rate as well as miscarriage rates. There is reason to believe that the observed impacts of VOCs translate into parallel industries as well, such as the emerging cell and gene therapy industry. Previous modeling efforts on VOC transport into cell culture media components have provided estimates on the expected equilibrium concentrations from airborne VOC exposure. However, a fundamental knowledge gap remains regarding the rate of VOC partitioning into cell cultures. Materials and Methods: In this work, we present an enhanced modeling approach to quantify the partitioning kinetics of selected VOCs in cell cultures consisting of a multiphase system with an oil overlay and a water-based culture media, as well as a water-based media without overlay. Results: Preliminary results from eight prevalent and cytotoxic VOCs indicate rapid equilibration into the system with equilibrium achieved within a timescale of seconds to minutes. Discussion: These results suggest that practitioners must take steps to maintain VOC-free air for the protection of cell cultures to avoid adverse outcomes, as open-air processes may be compromised even during brief exposure to VOCs. Conclusion: VOCs have been modeled to rapidly equilibrate into cell cultrue systems, potentially disrupting normal cellular development.

Introduction: This scientific publication presents the third prevalidation study of the deiodinase 1 Sandell–Kolthoff (DIO1-SK) assay, investigating its robustness and accuracy. The study compares the released iodide as the original read-out of the assay with concentrations of the thyroid hormones reversed triiodothyronine and 3,3′-diiodo-L-thyronine as the substrate and the product of the enzymatic reaction, respectively. Moreover, it is examining the impact of iodine-releasing substances, evaluating the alkaline phosphatase (ALP) assay as a specificity test, and investigating the temporal robustness of the assay. Methods: The study utilized a comparative analysis between the SK method and solid-phase-extraction liquid chromatography MS/MC to evaluate the concordance between the released iodide and thyroid hormone levels. The effects of iodine-releasing substances on the SK reaction were examined, and the ALP assay was used to assess specificity and microsome integrity. The temporal robustness of the DIO1-SK assay was investigated by varying incubation times. Results and Discussion: The comparative analysis revealed a strong concordance between released iodide and thyroid hormone levels, validating the read-out of the SK assay. Iodide-releasing substances were found to interfere with the SK reaction, specifically impacting the iodide release activity and should be tested for their potential to react with dithiothreitol. The ALP assay showed clear limitations in assessing test system integrity and substance specificity. The DIO1-SK assay demonstrated robustness to different incubation times, indicating its stability and reliability. Conclusion: The findings of this study characterize the robustness of the DIO1-SK assay, its limitations, and potential areas for improvement. Considering the identified limitations with iodine-containing substances, the DIO1-SK assay serves as a reliable tool to investigate the influence of substances on DIO1 activity and thus is an assay addressing one key event of impacting the thyroid hormone homeostasis, which can lead to endocrine disruption.