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.

Toward Quantitative Models in Safety Assessment: A Case Study to Show Impact of Dose-Response Inference on hERG Inhibition Models

Due to challenges with historical data and the diversity of assay formats, in silico models for safety-related endpoints are often based on discretized data instead of the data on a natural continuous scale. Models for discretized endpoints have limitations in usage and interpretation that can impact compound design. Here, we present a consistent data inference approach, exemplified on two data sets of Ether-à-go-go-Related Gene (hERG) K+ inhibition data, for dose-response and screening experiments that are generally applicable for in vitro assays. hERG inhibition has been associated with severe cardiac effects and is one of the more prominent safety targets assessed in drug development, using a wide array of in vitro and in silico screening methods. In this study, the IC₅₀ for hERG inhibition is estimated from diverse historical proprietary data. The IC₅₀ derived from a two-point proprietary screening data set demonstrated high correlation (R = 0.98, MAE = 0.08) with IC_50s derived from six-point dose-response curves. Similar IC₅₀ estimation accuracy was obtained on a public thallium flux assay data set (R = 0.90, MAE = 0.2). The IC₅₀ data were used to develop a robust quantitative model. The model's MAE (0.47) and R² (0.46) were on par with literature statistics and approached assay reproducibility. Using a continuous model has high value for pharmaceutical projects, as it enables rank ordering of compounds and evaluation of compounds against project-specific inhibition thresholds. This data inference approach can be widely applicable to assays with quantitative readouts and has the potential to impact experimental design and improve model performance, interpretation, and acceptance across many standard safety endpoints.

Evaluating Confidence in Toxicity Assessments Based on Experimental Data and In Silico Predictions

Understanding the reliability and relevance of a toxicological assessment is important for gauging the overall confidence and communicating the degree of uncertainty related to it. The process involved in assessing reliability and relevance is well defined for experimental data. Similar criteria need to be established for in silico predictions, as they become increasingly more important to fill data gaps and need to be reasonably integrated as additional lines of evidence. Thus, in silico assessments could be communicated with greater confidence and in a more harmonized manner. The current work expands on previous definitions of reliability, relevance, and confidence and establishes a conceptional framework to apply those to in silico data. The approach is used in two case studies: 1) phthalic anhydride, where experimental data are readily available and 2) 4-hydroxy-3-propoxybenzaldehyde, a data poor case which relies predominantly on in silico methods, showing that reliability, relevance, and confidence of in silico assessments can be effectively communicated within Integrated approaches to testing and assessment (IATA).

Impact of Dose Delays and Alternative Dosing Regimens on Pertuzumab Pharmacokinetics

PERJETA (pertuzumab), administered with Herceptin (trastuzumab), is used in the treatment of human epidermal growth factor receptor 2-positive breast cancer. Pertuzumab is currently approved with an initial loading dose of 840 mg, followed by a 420-mg maintenance dose intravenously every 3 weeks. A reloading dose is required if there is a ≥6-week delay in treatment. In response to the potential treatment disruption due to COVID-19, the impact of dose delays and alternative dosing regimens on intravenous pertuzumab for human epidermal growth factor receptor 2-positive breast cancer treatment is presented. Simulations were conducted by using the validated population pharmacokinetic model for pertuzumab, and included (1) 4-, 6-, and 9-week dose delays of the 840 mg/420 mg every 3 weeks dosing regimen and (2) 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks alternative dosing regimens. Simulations were compared with the currently approved pertuzumab dosing regimen. The simulations in 1000 virtual patients showed that a dose reload (840 mg) is required following a dose delay of ≥6 weeks to maintain comparable Ctrough (lowest concentration before the next dose is given) levels to clinical trials. The 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks alternative dosing regimens decrease median steady-state Ctrough by ≈40% compared with the approved regimen, and <90% of patients will be above the target Ctrough . Thus, the alternative 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks pertuzumab dosing regimens are not recommended. Flexibility for intravenous PERJETA-based regimens is available with an alternative route of pertuzumab administration (subcutaneous vs intravenous).

Clinical Outcomes between Stand-Alone Zero-Profile Spacers and Cervical Plate with Cage Fixation for Anterior Cervical Discectomy and Fusion: A Retrospective Analysis of 166 Patients

Stand-alone (SA) zero-profile implants are an alternative to cervical plating (CP) in anterior cervical discectomy and fusion (ACDF). In this study, we investigate differences in surgical outcomes between SA and CP in ACDF. We conducted a retrospective analysis of 166 patients with myelopathy and/or radiculopathy who had ACDF with SA or CP from Jan 2013-Dec 2016. We measured surgical outcomes including Bazaz dysphagia score at 3 months, Nurick grade at last follow-up, and length of hospital stay. 166 patients (92F/74M) were reviewed. 92 presented with radiculopathy (55%), 37 with myelopathy (22%), and 37 with myeloradiculopathy (22%). The average operative time with CP was longer than SA (194 ± 69 vs. 126 ± 46 min) (p < 0.001), as was the average length of hospital stay (2.1 ± 2 vs. 1.5 ± 1 days) (p = 0.006). At 3 months, 82 patients (49.4%) had a follow-up for dysphagia, with 3 patients reporting mild dysphagia and none reporting moderate or severe dysphagia. Nurick grade at last follow-up for the myelopathy and myeloradiculopathy cohorts improved in 63 patients (85%). Prolonged length of stay was associated with reduced odds of having an optimal outcome by 0.50 (CI = 0.35-0.85, p = 0.003). Overall, we demonstrate that there is no significant difference in neurological outcome or rates of dysphagia between SA and CP, and that both lead to overall improvement of symptoms based on Nurick grading. However, we also show that the SA group has shorter length of hospital stay and operative time compared to CP.

Application of the hard and soft, acids and bases (HSAB) theory as a method to predict cumulative neurotoxicity

Xenobiotic electrophiles can form covalent adducts that may impair protein function, damage DNA, and may lead a range of adverse effects. Cumulative neurotoxicity is one adverse effect that has been linked to covalent protein binding as a Molecular Initiating Event (MIE). This paper describes a mechanistic in silico chemical screening approach for neurotoxicity based on Hard and Soft Acids and Bases (HSAB) theory. We evaluated the applicability of HSAB-based electrophilicity screening protocol for neurotoxicity on 19 positive and 19 negative reference chemicals. These reference chemicals were identified from the literature, using available information on mechanisms of neurotoxicity whenever possible. In silico screening was based on structural alerts for protein binding motifs and electrophilicity index in the range of known neurotoxicants. The approach demonstrated both a high positive prediction rate (82-90 %) and specificity (90 %). The overall sensitivity was relatively lower (47 %). However, when predicting the toxicity of chemicals known or suspected of acting via non-specific adduct formation mechanism, the HSAB approach identified 7/8 (sensitivity 88 %) of positive control chemicals correctly. Consequently, the HSAB-based screening is a promising approach of identifying possible neurotoxins with adduct formation molecular initiating events. While the approach must be expanded over time to capture a wider range of MIEs involved in neurotoxicity, the mechanistic nature of the screen allows users to flag chemicals for possible adduct formation MIEs. Thus, the HSAB based toxicity screening is a promising strategy for toxicity assessment and chemical prioritization in neurotoxicology and other health endpoints that involve adduct formation.

CRISPR-Generated Nrf2a Loss- and Gain-of-Function Mutants Facilitate Mechanistic Analysis of Chemical Oxidative Stress-Mediated Toxicity in Zebrafish

The transcription factor Nrf2a induces a cellular antioxidant response and provides protection against chemical-induced oxidative stress, as well as playing a critical role in development and disease. Zebrafish are a powerful model to study the role of Nrf2a in these processes but have been limited by reliance on transient gene knockdown techniques or mutants with only partial functional alteration. We developed several lines of zebrafish carrying different null (loss of function, LOF) or hyperactive (gain of function, GOF) mutations to facilitate our understanding of the Nrf2a pathway in protecting against oxidative stress. The mutants confirmed Nrf2a dependence for induction of the antioxidant genes gclc, gstp, prdx1, and gpx1a and identified a role for Nrf2a in the baseline expression of these genes, as well as for sod1. Specifically, the 4-fold induction of gstp by tert-butyl hydroperoxide (tBHP) in wild type fish was abolished in LOF mutants. In addition, baseline gstp expression in GOF mutants increased by 12.6-fold and in LOF mutants was 0.8-fold relative to wild type. Nrf2a LOF mutants showed increased sensitivity to the acute toxicity of cumene hydroperoxide (CHP) and tBHP throughout the first 4 days of development. Conversely, GOF mutants were less sensitive to CHP toxicity during the first 4 days of development and were protected against the toxicity of both hydroperoxides after 4 dpf. Neither gain nor loss of Nrf2a modulated the toxicity of R-(-)-carvone (CAR), despite the ability of this compound to potently induce Nrf2a-dependent antioxidant genes. Similar to other species, GOF zebrafish mutants exhibited significant growth and survival defects. In summary, these new genetic tools can be used to facilitate the identification of downstream gene targets of Nrf2a, better define the role of Nrf2a in the toxicity of environmental chemicals, and further the study of diseases involving altered Nrf2a function.

Toward Less Hazardous Industrial Compounds: Coupling Quantum Mechanical Computations, Biomarker Responses, and Behavioral Profiles To Identify Bioactivity of SN2 Electrophiles in Alternative Vertebrate Models

Sustainable molecular design of less hazardous chemicals promises to reduce risks to public health and the environment. Computational chemistry modeling coupled with alternative toxicology models (e.g., larval fish) present unique high-throughput opportunities to understand structural characteristics eliciting adverse outcomes. Numerous environmental contaminants with reactive properties can elicit oxidative stress, an important toxicological response associated with diverse adverse outcomes (i.e., cancer, diabetes, neurodegenerative disorders, etc.). We examined a common chemical mechanism (bimolecular nucleophilic substitution (S_N2)) associated with oxidative stress using property-based computational modeling coupled with acute (mortality) and sublethal (glutathione, photomotor behavior) responses in the zebrafish (Danio rerio) and the fathead minnow (Pimephales promelas) models to identify whether relationships exist among biological responses and molecular attributes of industrial chemicals. Following standardized methods, embryonic zebrafish and larval fathead minnows were exposed separately to eight different S_N2 compounds for 96 h. Acute and sublethal responses were compared to computationally derived in silico chemical descriptors. Specifically, frontier molecular orbital energies were significantly related to acute LC₅₀ values and photomotor response (PMR) no observed effect concentrations (NOECs) in both fathead minnow and zebrafish. This reactivity index, LC₅₀ values, and PMR NOECs were also significantly related to whole body glutathione (GSH) levels, suggesting that acute and chronic toxicity results from protein adduct formation for S_N2 electrophiles. Shared refractory locomotor response patterns among study compounds and two alternative vertebrate models appear informative of electrophilic properties associated with oxidative stress for S_N2 chemicals. Electrophilic parameters derived from frontier molecular orbitals were predictive of experimental in vivo acute and sublethal toxicity. These observations provide important implications for identifying and designing less hazardous industrial chemicals with reduced potential to elicit oxidative stress through bimolecular nucleophilic substitution.

Kinetics of Glutathione Depletion and Antioxidant Gene Expression as Indicators of Chemical Modes of Action Assessed in Vitro in Mouse Hepatocytes with Enhanced Glutathione Synthesis

Here we report a vertically integrated in vitro - in silico study that aims to elucidate the molecular initiating events involved in the induction of oxidative stress (OS) by seven diverse chemicals (cumene hydroperoxide, t-butyl hydroperoxide, hydroquinone, t-butyl hydroquinone, bisphenol A, Dinoseb, and perfluorooctanoic acid). To that end, we probe the relationship between chemical properties, cell viability, glutathione (GSH) depletion, and antioxidant gene expression. Concentration-dependent effects on cell viability were assessed by MTT assay in two Hepa-1 derived mouse liver cell lines: a control plasmid vector transfected cell line (Hepa-V), and a cell line with increased glutamate-cysteine ligase (GCL) activity and GSH content (CR17). Changes to intracellular GSH content and mRNA expression levels for the Nrf2-driven antioxidant genes Gclc, Gclm, heme oxygenase-1 ( Hmox1), and NADPH quinone oxidoreductase-1 ( Nqo1) were monitored after sublethal exposure to the chemicals. In silico models of covalent and redox reactivity were used to rationalize differences in activity of quinones and peroxides. Our findings show CR17 cells were generally more resistant to chemical toxicity and showed markedly attenuated induction of OS biomarkers; however, differences in viability effects between the two cell lines were not the same for all chemicals. The results highlight the vital role of GSH in protecting against oxidative stress-inducing chemicals as well as the importance of probing molecular initiating events in order to identify chemicals with lower potential to cause oxidative stress.

Multifunctional photoactive and selective adsorbent for arsenite and arsenate: Evaluation of nano titanium dioxide-enabled chitosan cross-linked with copper

A novel multifunctional sorbent material of nano-titanium dioxide-enabled chitosan beads cross-linked with copper (CuTICB) is capable of photo-oxidation of As(III) to the less-toxic and more easily adsorbed As(V) in UV light and selective adsorption of arsenite (As(III)) and arsenate (As(V)) in the presence of phosphate, a strong adsorptive competitor and inhibitor of arsenic removal performance. CuTICB is an attractive sorbent as simultaneous photo-oxidation and adsorption reduces treatment time and cost while selective adsorption improves removal efficiency of arsenic in typical environmental conditions where competitive ions are predominant. In CuTICB, nano-titanium dioxide (n-TiO₂) anatase photo-oxidizes As(III) to As(V) through generation of reactive oxygen species. Additionally, Cu-chitosan bidentate crosslinkers form through Lewis acid-base coordinate bonding between Cu(II) and chitosan amine groups resulting in cationic behavior that electrostatically favors As(V) chelation even when phosphate concentrations are orders of magnitude higher. The influence of copper and n-TiO₂ loading on arsenic photo-oxidation and selective removal over phosphate was explored to optimize CuTICB design using batch experiments under varying systems conditions. For a system requiring both photo-oxidation and selective adsorption, it was found that copper and n-TiO₂ act non-linearly and synergistically, where maximum loadings of both does not yield the optimal selectivity or removal efficacy.

Abstract WMP31: Vessel Wall Enhancement is Associated With Clinical and Imaging Markers of Aneurysm Instability

Objective: It remains unclear whether patients with unruptured intracranial aneurysms (UICAs) should be treated. Vessel wall enhancement (VWE) in vessel wall MRI is emerging as a useful biomarker of aneurysm instability. We sought to evaluate whether VWE correlates with clinical and radiological markers of aneurysm instability in patients with UICAs.

Methods: We conducted a retrospective analysis of a prospective cohort of patients with UICAs imaged with vessel wall MRI. Two blinded reviewers evaluated the presence of VWE. Univariate and multivariate logistic regression modelling was utilized to assess for association between VWE and (1) presence of cranial nerve palsy (CNP) and thunderclap headache on presentation, two well-established clinical markers of aneurysm instability; and (2) aneurysm size, a well-established radiological marker of aneurysm instability.

Results: 94 patients with UICAs were included in the analysis; of these, 34 (36%) had VWE, 60 (64%) did not, 10 (11%) had CNP, 14 (15%) presented with thunderclap headache, and 40 (43%) had aneurysms >7mm in size. Inter-rater reliability for VWE ascertainment was excellent (kappa 0.86, 95%CI 0.75-0.97). 9 out of 10 patients (90%) with CNP had VWE (association testing not possible due to sparse counts). In multivariable analysis, thunderclap headache (OR 8.55, 95%CI 1.89-45.64; p=0.007) and aneurysm size (1.26, 95%CI 1.10-1.50; p=0.003) were independently associated with VWE.

Conclusions: VWE independently associates with clinical and radiological markers of aneurysm instability. Prospective studies are needed to evaluate the clinical utility of this imaging biomarker.

Channel Interactions and Robust Inference for Ratiometric β-lactamase Assay Data: a Tox21 Library Analysis

Ratiometric β-lactamase (BLA) reporters are widely used to study transcriptional responses in a high-throughput screening (HTS) format. Typically, a ratio readout (background/target fluorescence) is used for toxicity assessment and structure-activity modeling efforts from BLA HTS data. This ratio readout may be confounded by channel-specific artifacts. To maximize the utility of BLA HTS data, we analyzed the relationship between individual channels and ratio readouts after fitting 10,000 chemical titration series screened in seven BLA stress-response assays from the Tox21 initiative. Similar to previous observations, we found that activity classifications based on BLA ratio readout alone are confounded by interference patterns for up to 85% (50 % on average) of active chemicals. Most Tox21 analyses adjust for this issue by evaluating target and ratio readout direction. In addition, we found that the potency and efficacy estimates derived from the ratio readouts may not represent the target channel effects and thus complicates chemical activity comparison. From these analyses we recommend a simpler approach using a direct evaluation of the target and background channels as well as the respective noise levels when using BLA data for toxicity assessment. This approach eliminates the channel interference issues and allows for straightforward chemical assessment and comparisons.

Toward the Design of Less Hazardous Chemicals: Exploring Comparative Oxidative Stress in Two Common Animal Models

Sustainable molecular design of less hazardous chemicals presents a potentially transformative approach to protect public health and the environment. Relationships between molecular descriptors and toxicity thresholds previously identified the octanol-water distribution coefficient, log D, and the HOMO-LUMO energy gap, ΔE, as two useful properties in the identification of reduced aquatic toxicity. To determine whether these two property-based guidelines are applicable to sublethal oxidative stress (OS) responses, two common aquatic in vivo models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio), were employed to examine traditional biochemical biomarkers (lipid peroxidation, DNA damage, and total glutathione) and antioxidant gene activation following exposure to eight structurally diverse industrial chemicals (bisphenol A, cumene hydroperoxide, dinoseb, hydroquinone, indene, perfluorooctanoic acid, R-(-)-carvone, and tert-butyl hydroperoxide). Bisphenol A, cumene hydroperoxide, dinoseb, and hydroquinone were consistent inducers of OS. Glutathione was the most consistently affected biomarker, suggesting its utility as a sensitivity response to support the design of less hazardous chemicals. Antioxidant gene expression (changes in nrf2, gclc, gst, and sod) was most significantly (p < 0.05) altered by R-(-)-carvone, cumene hydroperoxide, and bisphenol A. Results from the present study indicate that metabolism of parent chemicals and the role of their metabolites in molecular initiating events should be considered during the design of less hazardous chemicals. Current empirical and computational findings identify the need for future derivation of sustainable molecular design guidelines for electrophilic reactive chemicals (e.g., SN2 nucleophilic substitution and Michael addition reactivity) to reduce OS related adverse outcomes in vivo.

Toward safer multi-walled carbon nanotube design: Establishing a statistical model that relates surface charge and embryonic zebrafish mortality

Given the increased utility and lack of consensus regarding carbon nanotube (CNT) environmental and human health hazards, there is a growing demand for guidelines that inform safer CNT design. In this study, the zebrafish (Danio rerio) model is utilized as a stable, sensitive biological system to evaluate the bioactivity of systematically modified and comprehensively characterized multi-walled carbon nanotubes (MWNTs). MWNTs were treated with strong acid to introduce oxygen functional groups, which were then systematically thermally reduced and removed using an inert temperature treatment. While 25 phenotypic endpoints were evaluated at 24 and 120 hours post-fertilization (hpf), high mortality at 24 hpf prevented further resolution of the mode of toxicity leading to mortality. Advanced multivariate statistical methods are employed to establish a model that identifies those MWNT physicochemical properties that best estimate the probability of observing an adverse outcome. The physicochemical properties considered in this study include surface charge, percent surface oxygen, dispersed aggregate size and morphology and electrochemical activity. Of the five physicochemical properties, surface charge, quantified as the point of zero charge (PZC), was determined as the best predictor of mortality at 24 hpf. From a design perspective, the identification of this property-hazard relationship establishes a foundation for the development of design guidelines for MWNTs with reduced hazard.