This thesis describes the generation of cell-of-origin based models, using mesenchymal stem cells, to further elucidate the underlying mechanism of molecular alterations of the bone-forming tumours... Show moreThis thesis describes the generation of cell-of-origin based models, using mesenchymal stem cells, to further elucidate the underlying mechanism of molecular alterations of the bone-forming tumours osteoid osteoma, osteoblastoma and osteosarcoma. Furthermore, we describe the identification of novel treatment options for osteosarcoma using 2D and 3D in vitro models. Show less
Balak, J.R.A.; Juksar, J.; Carlotti, F.; Nigro, A. lo; Koning, E.J.P. de 2019
Purpose of Review Novel 3D organoid culture techniques have enabled long-term expansion of pancreatic tissue. This review comprehensively summarizes and evaluates the applications of primary tissue... Show morePurpose of Review Novel 3D organoid culture techniques have enabled long-term expansion of pancreatic tissue. This review comprehensively summarizes and evaluates the applications of primary tissue-derived pancreatic organoids in regenerative studies, disease modelling, and personalized medicine.Recent Findings Organoids derived from human fetal and adult pancreatic tissue have been used to study pancreas development and repair. Generated adult human pancreatic organoids harbor the capacity for clonal expansion and endocrine cell formation. In addition, organoids have been generated from human pancreatic ductal adenocarcinoma in order to study tumor behavior and assess drug responses.Summary Pancreatic organoids constitute an important translational bridge between in vitro and in vivo models, enhancing our understanding of pancreatic cell biology. Current applications for pancreatic organoid technology include studies on tissue regeneration, disease modelling, and drug screening. Show less
The introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds... Show moreThe introduction of more relevant cell models in early preclinical drug discovery, combined with high-content imaging and automated analysis, is expected to increase the quality of compounds progressing to preclinical stages in the drug development pipeline. In this review we discuss the current switch to more relevant 3D cell culture models and associated challenges for high-throughput screening and high-content analysis. We propose that overcoming these challenges will enable front-loading the drug discovery pipeline with better biology, extracting the most from that biology, and, in general, improving translation between in vitro and in vivo models. This is expected to reduce the proportion of compounds that fail in vivo testing due to a lack of efficacy or to toxicity. Show less
Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the... Show moreDrug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of harmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity. Show less
