Toxicologic Pathology最新文献

Recent trends in toxicological pathology include implementation of digital platforms that have gained rapid momentum in the field. Are we ready to fully implement this new modality? This opinion piece provides some practical perspectives on digital pathology such as its cost limitations, relative time requirements, and a few technical issues, some of which are encountered for specific lesions, that warrant caution. Although the potential for digital pathology assessment with whole slide images has made great strides, we are of the opinion that it is not yet ready for complete replacement of glass slides in toxicologic pathology safety assessments.

Thyroid tissue is sensitive to the effects of endocrine disrupting substances, and this represents a significant health concern. Histopathological analysis of tissue sections of the rat thyroid gland remains the gold standard for the evaluation for agrochemical effects on the thyroid. However, there is a high degree of variability in the appearance of the rat thyroid gland, and toxicologic pathologists often struggle to decide on and consistently apply a threshold for recording low-grade thyroid follicular hypertrophy. This research project developed a deep learning image analysis solution that provides a quantitative score based on the morphological measurements of individual follicles that can be integrated into the standard pathology workflow. To achieve this, a U-Net convolutional deep learning neural network was used that not just identifies the various tissue components but also delineates individual follicles. Further steps to process the raw individual follicle data were developed using empirical models optimized to produce thyroid activity scores that were shown to be superior to the mean epithelial area approach when compared with pathologists' scores. These scores can be used for pathologist decision support using appropriate statistical methods to assess the presence or absence of low-grade thyroid hypertrophy at the group level.

Enhanced histopathology of the immune system uses a precise, compartment-specific, and semi-quantitative evaluation of lymphoid organs in toxicology studies. The assessment of lymphocyte populations in tissues is subject to sampling variability and limited distinctive cytologic features of lymphocyte subpopulations as seen with hematoxylin and eosin (H&E) staining. Although immunohistochemistry is necessary for definitive characterization of T- and B-cell compartments, routine toxicologic assessments are based solely on H&E slides. Here, a deep learning (DL) model was developed using normal rats to quantify relevant compartments of the spleen, including periarteriolar lymphoid sheaths, follicles, germinal centers, and marginal zones from H&E slides. Slides were scanned, destained, dual labeled with CD3 and CD79a chromogenic immunohistochemistry, and rescanned to generate exact co-registered images that served as the ground truth for training and validation. The DL model identified individual splenic compartments with high accuracy (97.8% Dice similarity coefficient) directly from H&E-stained tissue. The DL model was utilized to study the normal range of lymphoid compartment area and cellularity. Future implementation of our DL model and expanding this approach to other lymphoid tissues have the potential to improve accuracy and precision in enhanced histopathology evaluation of the immune system with concurrent gains in time efficiency for the pathologist.

Pathology, a fundamental discipline that bridges basic scientific discovery to the clinic, is integral to successful drug development. Intrinsically multimodal and multidimensional, anatomic pathology continues to be empowered by advancements in molecular and digital technologies enabling the spatial tissue detection of biomolecules such as genes, transcripts, and proteins. Over the past two decades, breakthroughs in spatial molecular biology technologies and advancements in automation and digitization of laboratory processes have enabled the implementation of higher throughput assays and the generation of extensive molecular data sets from tissue sections in biopharmaceutical research and development research units. It is our goal to provide readers with some rationale, advice, and ideas to help establish a modern molecular pathology laboratory to meet the emerging needs of biopharmaceutical research. This manuscript provides (1) a high-level overview of the current state and future vision for excellence in research pathology practice and (2) shared perspectives on how to optimally leverage the expertise of discovery, toxicologic, and translational pathologists to provide effective spatial, molecular, and digital pathology data to support modern drug discovery. It captures insights from the experiences, challenges, and solutions from pathology laboratories of various biopharmaceutical organizations, including their approaches to troubleshooting and adopting new technologies.

Before the COVID-19 pandemic, digital pathology was increasingly used in veterinary education, diagnostics, and research. The pandemic accelerated this adoption as institutions needed to maintain operations amidst lockdowns. It also enabled pharmaceutical companies to conduct peer reviews digitally, circumventing travel restrictions. At the 2023 Society of Toxicologic Pathology Annual Symposium, a Town Hall Meeting highlighted the current use of digital pathology. A majority of the respondents viewed whole slide images (WSI) favorably. Many institutions use digital pathology primarily for non-GLP and GLP conforming primary reads and peer reviews. Takeda has long utilized digital pathology, incorporating scanners and an image management repository, and recently adopted a cloud-based platform tailored for toxicologic pathology, enhancing efficiency and collaboration. Digital pathology not only saves time but also reduces travel needs and environmental impact. Technological advancements and wider adoption are expected to further enhance the field, promising significant benefits for the overall digital pathology infrastructure.

Mass spectrometry imaging (MSI) was used to investigate and provide insights into observed biliary pathology found in dogs and rats after administration of two different compounds. Both compounds were associated with peribiliary inflammatory infiltrates and proliferation of the bile duct epithelium. However, MSI revealed very different spatial distribution profiles for the two compounds: Compound A showed significant accumulation within the bile duct epithelium with a much higher concentration than in the parenchymal hepatocytes, while Compound T exhibited only a slight increase in the bile duct epithelium compared to parenchymal hepatocytes. These findings implicate cholangiocyte uptake and accumulation as a key step in the mechanism of biliary toxicity. In both cases, compounds are shown at the site of toxicity in support of a direct mechanism of toxicity on the biliary epithelium. MSI is a powerful tool for localizing small molecules within tissue sections and improvements in sensitivity have enabled localization down to the cellular level in some cases. MSI was also able to identify biomarker candidates of toxicity by differential analysis of ion profiles comparing treated and control cholangiocytes from tissue sections.

The virtual control group (VCG) concept was originally developed in the IMI2 project eTRANSAFE, using data of control animals which pharmaceutical companies have accrued over decades from animal toxicity studies. This control data could be repurposed to create virtual control animals to reduce or replace concurrent controls in animal studies. Initial work demonstrated the general feasibility of the VCG concept, but implementation requires significant further collaborative efforts. The new Innovative Health Initiative (IHI) project VICT3R aims to address these challenges and to obtain regulatory acceptance for the VCG concept. To achieve these goals, VICT3R will build a database comprising high-quality, standardized, and duly annotated control animal data from past and forthcoming toxicity studies. The VICT3R project will create workflows and computational tools to generate adequate VCGs based on statistical and artificial intelligence (AI) approaches. The validity, reproducibility, and robustness of the resulting VCGs will be assessed by comparing the performance of their use with that of real control groups.

The Golden Syrian hamster is a well-characterized rodent model for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2)-associated pneumonia. We sought to characterize the pulmonary disease course during SARS-CoV-2 infection (strain USA-WA1/2020) in the hamster model using micro-computed tomography (micro-CT) and compare radiologic observations with histopathologic findings. We observed a range of radiologic abnormalities, including ground glass opacities (GGOs), consolidations, air bronchograms, and pneumomediastinum. The appearance, distribution, and progression of these abnormalities in hamsters were similar to those observed in the lungs of coronavirus disease 2019 (COVID-19) patients by clinical CT and chest X-rays, and correlated with clinical signs and weight loss during the course of disease. Histopathological analysis of infected hamsters revealed lung pathology characteristic of COVID-19 pneumonia, and we observed a strong association between CT and histopathologic scorings. We also analyzed accumulation of air in the thoracic cavity by both manual and automated threshold-based segmentation and found that automated analysis significantly decreases the time needed for data analysis. Data presented here demonstrate that micro-CT imaging can be a major tool in preclinical investigative studies using animal models by providing early and detailed assessment of disease severity and outcomes.

The so-called undruggable space is an exciting area of potential growth for drug development. Undruggable proteins are defined as those unable to be targeted via conventional small molecule drugs. New modalities are being developed to potentially target these proteins. Targeted protein degradation (TPD) is one such new modality, which over the last two decades has moved from academia to industry. TPD makes use of the endogenous degradation machinery present in all cells, in which E3 ubiquitin ligases mark proteins for degradation via ubiquitin attachment. This session explored the challenges and perspectives of using protein degraders as novel therapeutic agents. The session began with a general introduction to the modality, followed by considerations in evaluating their on- and off-target toxicities including data from an IQ Consortium working group survey. Unique absorption, distribution, metabolism, and excretion (ADME) properties of degrader molecules were presented in relation to their effect on drug development and nonclinical safety assessment. The role of transgenic models in evaluating hemotoxicity associated with cereblon-based therapies was then discussed. A case study to derisk dose-limiting thrombocytopenia was also presented. Finally, a regulatory perspective on the challenges of having toxicity associated with protein degraders was presented.

Adeno-associated virus (AAV) gene therapy vectors are an accepted platform for treating severe neurological diseases. Test article (TA)-related and procedure-related neuropathological effects following administration of AAV-based vectors are observed in the central nervous system (CNS) and peripheral nervous system (PNS). Leukocyte accumulation (mononuclear cell infiltration > inflammation) may occur in brain, spinal cord, spinal nerve roots (SNRs), sensory and autonomic ganglia, and rarely nerves. Leukocyte accumulation may be associated with neuron necrosis (sensory ganglia > CNS) and/or glial changes (microgliosis and/or astrocytosis in the CNS, increased satellite glial cellularity in ganglia and/or Schwann cellularity in nerves). Axonal degeneration secondary to neuronal injury may occur in the SNR (dorsal > ventral), spinal cord (dorsal and occasionally lateral funiculi), and brainstem centrally and in nerves peripherally. Patterns of AAV-associated microscopic findings in the CNS and PNS differ for TAs administered into brain parenchyma (where tissue at the injection site is affected most) versus TAs delivered into cerebrospinal fluid (CSF) or systemically (which primarily impacts sensory ganglion neurons and their processes in SNR and spinal cord). Changes related to the TA and procedure may overlap. While often interpreted as adverse, AAV-associated neuronal necrosis and axonal degeneration of limited severity generally do not preclude clinical testing.