Advanced data analytics in life science is becoming a core element in modern data driven life science research. Our research focus on data from high-throughput molecular techniques to develop computational models to understand, simulate and predict behaviour of complex biological systems.
We focus on chemometrics as an overall framework that includes Design of experiments (DOE), multivariate data analysis, AI/machine learning and bioengineering tools, all this in collaboration with leading academic institutions and industry partners. Our vision is the prevention and efficient and affordable treatment of diseases worldwide.
Chemometrics has been part of our DNA for more than 50 years when Svante Wold and Rolf Carlson led a movement that has transformed the pharmaceutical industry and modern drug development and manufacturing. In addition, we focus on “omics” disciplines, particularly phenotypic profiling such as metabolomics. Such methodologies have consistently demonstrated improved biological interpretation, identification of biomarkers and understanding mechanisms in disease, ranging from large scale biology studies to smaller clinical studies.
Taking a systems biology approach, we target the integration of biological information across multiple phenotypic and “omics” platforms. Here, we are continuously developing multivariate tools and strategies to analyse and integrate omics data for quality control and enhancing the interpretation of biological data. This includes time series dynamic modeling of biological events and in silico cell painting of virtual fluorescent channels as part of our computational workflow. Here, domain expertise are critical elements for success.