The focus of this group is on active contribution to the development of mathematical and computational methods useful for the pharmaceutical sciences. The group‘s members are specialized in computational chemistry, pharmacometrics, virus- and other biomedical modelling and numerical analysis. As the group’s research is purely in silico, we have no laboratory equipment. Our particular research directions include
(i) construction of appropriate mathematical models with efficient parameter estimation for the activation and gene regulating effect of membrane and nuclear receptors validated with in vitro, in vivo and clinical data, taking into account high parameter variability, population models, time-delays, mixed time-scales and spatial resolution
(ii) reliable calculations and predictions of NMR chemical shifts for the structural characterization of phosphorylated intrinsically disordered proteins
(iii) viral infection models (not restricted to the SARS-covid 19 virus) for in vitro and possibly in vivo data.
Beside these main directions requiring the development of problem-taylored mathematical techniques, more general methods from statistics and data mining are planned to be applied in several pharmaceutical areas such as pharmaceutical technology, drug discovery and social pharmacy.
The main goal is to extend the team, among others through education of doctoral and postdoctoral students, to a group that is able to not only offer computational services to various areas of pharmaceutical sciences, but to actually evolve the currently available methods. Urgent issues that need attention in an environment where big data become increasingly important, are reduction of computational costs, guarantees of reliable and accurate results and efficient parameter estimation.