Pharmaceutical companies routinely screen compounds for hemodynamics related safety risk. secondary pharmacology is initially used to prioritize compounds while studies are later used to quantify and translate risk to humans. This strategy has shown limitations but could be improved via the incorporation of molecular findings in the animal-based toxicological risk assessment.
View Article and Find Full Text PDFThe lessons learned from reviewing national risk assessments to modernise the Australian Standard for the post-mortem inspection and disposition judgement of beef, sheep, goat, and pig carcases are discussed. The initial risk profiles identified priorities for quantitative assessments. Broadly, the main difficulty encountered was the paucity of quantified performance for the current inspection.
View Article and Find Full Text PDFCardiotoxicity can be defined as "chemically induced heart disease", which can occur with many different drug classes treating a range of diseases. It is the primary cause of drug attrition during pre-clinical development and withdrawal from the market. Drug induced cardiovascular toxicity can result from both functional effects with alteration of the contractile and electrical regulation in the heart and structural changes with morphological changes to cardiomyocytes and other cardiac cells.
View Article and Find Full Text PDFCreation of disease models utilizing hiPSCs in combination with CRISPR/Cas9 gene editing enable mechanistic insights into differential pharmacological responses. This allows translation of efficacy and safety findings from a healthy to a diseased state and provides a means to predict clinical outcome sooner during drug discovery. Calcium handling disturbances including reduced expression levels of the type 2 ryanodine receptor (RYR2) are linked to cardiac dysfunction; here we have created a RYR2 deficient human cardiomyocyte model that mimics some aspects of heart failure.
View Article and Find Full Text PDFStructural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT.
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