Sentence examples for models for toxicity from inspiring English sources

When it comes to predictive modelling, in order to develop accurate predictive models for toxicity values, high quality data is required.

Nonetheless, metabolomics is a powerful tool which may increase the knowledge of how metabolites are altered in living organisms in response to exposures, mechanisms of toxicity, biomarkers of toxic effects, and can be used in developing models for toxicity prediction.

The statistics demonstrate how ensemble machine learning methods can be used to increase the capability of consensus QSAR models for toxicity prediction.

Animal studies, which are at the basis of QSAR models for toxicity, cannot alone guarantee the production of all necessary data.

For example, different virus features with respect to particle size, presence/absence of an envelope, and host species imply specific requirements for measures to ensure sterility, for handling, and for determination of appropriate animal models for toxicity testing, respectively.

In vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing.

RPE-1 cells represent an ideal model for toxicity tests, given that epithelial cells are the most abundant healthy cell type found in the immediate proximity of tumors.

PON1 knockout (PON1−/−) mice, which lack PON1, represent a highly sensitive mouse model for toxicity associated with exposure to CPF or CPO.

In the framework of the TOXDROP STREP consortium (http://toxdrop.vitamib.com/) hsp22 and hsp70-EGFP DNA vector constructs were thus introduced in HepG2 cell line which is considered a suitable liver model for toxicity testing [10], [14], [15] and has been used for benchmarking studies [16].

Here we modified the parameters of the underlying model for toxicity and efficacy (PSA dynamics) models for two purposes.

A baseline clinical model for toxicity was determined using logistic regression and backward stepwise selection used to identify relevant clinical characteristics to be included in the model.