Analysis and Modelling-Predictive Methods to Risk Assessment

Our focus is on complex contexts.
We don't just run an experiment and return you some file with a data dump.
We carry out an integrated analysis to make sense of the data.
In the first instance we also carefully plan an intelligent experimental design that generates the data.

We use
Experienced Application Scientists

We apply
Apply Scientific Informatics to Experimental Analysis and Reporting

We develop
Predictive Methods to Risk Assessment

Scientific applications increasingly involve the integration of diverse sources of evidence.
e.g., Weight of Evidence in Risk Assessment including genomics data, metabolic network models, pathway-anchored in vitro assays

Heterogenous Evidence must often be combined from different disciplines.
e.g., chemistry, biology and computer science in drug discovery

Complex models must integrate data from different spatial and temporal dimensions.
e.g., cancer models using epidemiology, tissue, cellular and molecular biology data.

If you want to carry out an integrated, intelligent analysis or safety assessment - contact us for a complete solution!