Toxicologic Pathology最新文献

Sharing pathology data is critical for educational and scientific purposes. Since most pharmaceutical or (agro)chemical companies outsource nonclinical safety assessment studies to contract research organizations (CROs), the pathology data of those studies are not owned by the investigator but is the legal property of the respective company sponsoring the work. Although some companies have installed policies that govern sharing of pathology data, many companies generally do not allow the external use of data by either the CRO-based study pathologist or the sponsor pathologist. Policies for governing the external use of data vary significantly. In this article, we present an overview of the different approaches taken across different companies (CROs, pharmaceutical/chemical companies, or other institutes) for sharing pathology material for educational and/or scientific purposes. The results of a survey and interviews with legal departments of different companies will be presented (anonymously) and discussed. In addition, the importance of sharing pathology data is addressed, as well as the challenges and opportunities this presents. Suggestions will be provided regarding what material should be made available and what will be needed to achieve agreement for this to happen.

One of the emerging concepts on the reduction of animal use in non-clinical studies is the use of virtual control group (VCG) to replace concurrent control group (CCG). The VCG involves the generation of a control data from historical control data to match a specific study design. This review focuses on two recently published proof-of-concept (POC) studies conducted in rats. One major issue that was consistently seen across these POC studies was the non-reproducibility of some quantitative endpoints between the CCG and the VCG, with clinical pathology parameters being the most affected. The inconsistencies observed with the clinical pathology parameters when using VCGs may lead to: (1) misconception about the accuracy and sensitivity of traditional clinical pathology biomarkers and its implications on safety monitoring in the clinic; (2) inability to correctly identify and characterize organ dysfunctions; (3) interference with the weight-of-evidence approach used in identifying hazards in toxicologic clinical pathology and toxicology studies at large; and (4) wrong interpretations and data reproducibility issues. Other alternatives to reduce animal use in toxicology studies are also discussed including blood microsampling for toxicokinetics, scientifically justified use of recovery animals, and appropriate use and continuous investments in new alternative methods.

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.

Microscopic observation data collected from approximately 1800 male and female Sprague Dawley (SD) control rats used on 104-week carcinogenicity studies performed at North American Labcorp Early Development, Inc, Madison, WI, were retrospectively evaluated for spontaneous nonneoplastic findings. This study provides incidence of the most common spontaneous nonneoplastic microscopic findings in each organ system of SD rats encountered during 104-week carcinogenicity studies. Some of the most common spontaneous background findings were cardiomyopathy; chronic progressive nephropathy; uterine cystic endometrial hyperplasia; prostate inflammation; pulmonary alveolar macrophage infiltrates; hepatocyte vacuolation, bile duct hyperplasia, and basophilic foci in the liver; pancreatic fibrosis; splenic extramedullary hematopoiesis and pigment; decreased lymphocytes and epithelial hyperplasia in the thymus; ventral brain compression; cystic degeneration and hyperplasia of the adrenal cortex; and mammary gland hyperplasia. The most common nonneoplastic findings in male SD rats were chronic progressive nephropathy (80.9%) and rodent progressive cardiomyopathy (73.2%). The most common nonnenoplastic findings in female SD rats were cystic degeneration of the adrenal cortex (64.7%) and ventral compression of the brain due to pituitary neoplasms (62.7%).

Nonhuman primates (NHPs) have been and remain a highly valuable animal model with an essential role in translational research and pharmaceutical drug development. Based on current regulatory guidelines, the nonclinical safety of novel therapeutics should be evaluated in relevant nonclinical species, which commonly includes NHPs for biotherapeutics. Given the practical and ethical limitations on availability and/or use of NHPs and in line with the widely accepted guiding "3Rs" (replace, reduce, and refine) principles, many approaches have been considered to optimize toxicity study designs to meaningfully reduce the number of NHPs used. Standard general toxicity studies usually include four groups of equal size, including one group of vehicle control animals. Here, we describe an approach to achieve an overall significant reduction in control animal use, while also resolving many of the issues that may limit application of fully virtual control animals. We propose in Good Laboratory Practice (GLP)-compliant toxicity studies to maintain concurrent control group animals for the in-life phase of the studies, but to limit euthanasia to a subset of control animals. The nonterminated control animals can then be returned to the facility colony for reuse in subsequent studies. The proposed study design could lead to a 15% to 20% reduction in NHP usage. The scientific, logistical, and animal welfare considerations associated with such an approach and suggested solutions are discussed in detail.

Small interfering RNAs (siRNAs) have been successfully used as therapeutics to silence disease-causing genes when conjugated to ligands or formulated in lipid nanoparticles to target relevant cell types for efficacy while sparing other cells for safety. To support the development of new methods for delivery of siRNA therapeutics, we developed and characterized a panel of antibodies generated against chemically modified nucleotides used in therapeutic siRNA molecules, identifying a monoclonal antibody that detects a broad range of siRNA representing distinct sequences and modification patterns. By integrating this anti-siRNA antibody with additional reagents, we created a multiplex siRNA immunoassay that simultaneously quantifies siRNA uptake, trafficking, and silencing activity. Using immunohistochemistry (IHC), we applied our method on tissues from mice treated with unconjugated, GalNAc-conjugated, or cholesterol-conjugated siRNAs and quantitatively assessed the biodistribution and activity of siRNAs in various organs. In addition, we used high-content imaging (HCI) and applied our multiplex siRNA immunoassay in tissue culture to enable simultaneous quantification of siRNA uptake, activity, and intracellular colocalization with endosome markers. These methods provide a robust platform for testing nucleic acid delivery methods in vitro and in vivo, allowing precise analysis and visualization of the pharmacokinetics and pharmacodynamics of siRNA therapeutics with cellular and subcellular resolution.

Hematoxylin and eosin (H&E) staining is a suitable approach for detecting substantial structural changes in neural tissues but is less sensitive for identifying subtle alterations to subcellular structures and various chemical constituents, including myelin. Neurohistological methods to better evaluate myelin integrity by light microscopy include acidophilic dyes (eg, eriochrome cyanine R, toluidine blue [used with hard plastic sections]); lipoprotein-binding dyes (eg, Luxol fast blue [LFB], Weil's iron hematoxylin); lipid impregnation with metals (eg, Marchi's, which uses osmium tetroxide for en bloc staining before embedding); and immunohistochemical (IHC) methods to highlight various antigens (eg, myelin basic protein [MBP] and peripheral myelin protein 22 [PMP22]). Some IHC methods reveal enhanced marker expression in damaged myelin (eg, matrix metalloproteinase-9 [MMP9], S100). In neuropathology investigations, H&E is the first-tier screening method, whereas myelin stains (often LFB alone or in combination with dyes that highlight other structural elements) are second-tier procedures performed in combination with other neurohistological procedures to examine neuroaxonal injury and/or glial responses. The choice of myelin method depends on such considerations as cost, institutional preference, the procedure (fixation and embedding medium), and the study objective.

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.