Jos Weusten

Background

About Jos Weusten

I am working in the field of applied mathematics and statistics in an industrial environment since 1993, and I still enjoy my work. I started in the field of medical diagnostics (Organon Teknika / BioMérieux), and worked for several years in the chemical company DSM (at the analytical-chemical department DSM Resolve). Although I liked working for DSM, I was very happy to be able to return to the field of medical applications, at Philips Handheld Diagnostics in Eindhoven, in April 2016. I had a great time. Unfortunately, Philips decided to terminate this business. Since January 2018 I joined the Center for Mathematical Sciences of MSD, where I found a new and challenging position. Over the years, the work I have done consisted of all kinds of different activities in the wide area of applied mathematics and statistics. To give an impression: from straightforward analysis of DoE studies to the implementation of multivariate SPC techniques; from the automation of simple routine analyses in Excel in VisualBasic applications to the development of algorithms for clinical diagnostics or for two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS); from developing statistical routines for assessing clinical sensitivity of diagnostics to modeling PCR profiles in forensic DNA analyses; and (last but not least) developing useful models to calculate risks of transfusion mediated infections in blood transfusions. Giving courses in applied statistics (basic statistics, design of experiments) is also an interesting part of the work. I hope to contribute in a relevant way to the research projects I am involved in. It gives me a lot of satisfaction to perform a decent statistical analysis of experimental data and to explain it to the experimentalist in such a way that (s)he understands the concepts without requiring too much mathematical detail. During the last years I started working on the application of advanced kinetic models for the analysis of stability data of pharmaceutical products. Applying concepts of Bayesian analyses in pharmaceutical statistics is an important topic as well. Both against a background of trying to extract the maximum amount of information from available data.