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PharmaImage are covering both incremental improvements of our research services for the pharmaceutical industry as well as (applied) research on and the development of entirely new medical products/health care services using neuroimaging and biomarker-based strategies. R&D intensity is high with about 20% of revenues.

Current Incremental Product Development

XNAT software platform: PI PharmaImage is currently developing together with its partner Radiologics Inc. (St. Louis USA) an extension (EEG plugin) of the XNAT imaging data bank administration software platform ( The EEG plugin allows it to manage importing, archiving, processing and securely distributing electrophysiological data in the same way like imaging data. Physiological data (EEG, ECG, skin conductance, eye movements, oxgen saturation etc.) can be managed both as stand-alone data sets together with associated data (e.g. clinical data) but also as tightly connected data in the time domain (e.g. simultaneously acquired functional fMRI/EEG).

Current Research & Development

Personalized Risk Prediction of Post-operative Cognitive Impairment: Cognitive impairment is increasingly prevalent in our aging society. Impaired cognitive capacity can be the consequence of age-associated primary brain disorders (depression, Alzheimer’s dementia (AD), cerebrovascular disease etc.) and/or secondary brain disorders due to medical conditions such as diabetes, inflammation or treatment interventions and life style factors. Postoperative Cognitive Impairment is a disorder of cognitive function following surgery and it is particularly frequent in elderly patients. This condition often has an acute phase of Postoperative Delirium (POD) which then may be followed by a more chronic phase of Postoperative Cognitive Dysfunction (POCD), which tends to persist over time ressembling chronic dementia. The incidence of POD ranges from 10 to 45% and of POCD from 10 to 25 %. Increased age, as well as a range of medical conditions, may predispose patients to POD/POCD. At present, it is not possible to predict the risk of developing post-operative cognitive impairment in an individual patient prior to surgery. Since this would be highly desirable to guide the decision-making process before surgery (e.g. conservative vs. surgical intervention), developing diagnostics tools for risk prediction is an unmet medical need. The socioeconomic implications of postoperative cognitive impairments, especially in an aging society such as the European Union or the US, also have a profound societal impact. POD/POCD are associated with increased morbidity and mortality, associated longer and more costly hospital treatment as well as subsequent higher dependency on social support needs. The European research consortium „Biomarker Development for Postoperative Cognitive Impairment in the Elderly“ (BioCog) is funded by the European Community as part of the Seventh Framework Program ( This is worldwide the largest project ever conducted in surgical patients to identify biomarkers for risk prediction of cognitive impairments. In Total 1100 patients have been included in the study.. PI PharmaImage is currently developing, together with its academic and industry partners including its sister company PI Health Solutions GmbH, a (mutivariate) risk prediction algorithm for the personalized risk prediction of post-operative cognitive impairment. Risk prediction will be based on clinical and neuropsychological parameters, neuroimaging biomarkers as well as molecular biomarkers incl. the application of omics-based strategies. It is the explicit aim of this R&D project to develop a risk prediction algorithm for the clinical practice taking into account practicability and economic usefulness. It is a key feature of the BioCog project that we do not simply identify risk parameters but that we also generate a sufficiently large population-based reference databank which allows it to locate an individual pre-operative elderly patient on the multi-parameter risk continuum (clinical, cognitive performance, neuroimaging and molecular biomarkers). It is expected that the outcome of this project will have a tremendous effect on the clinical care of elderly patients. In addition, the outcome of BioCog should have a considerable impact on economic health care decisions (cost-benefit analysis of surgical interventions). Moreover, the risk prediction algorithm will be very helpful for future drug development studies, i.e., to develop drugs for the treatment of post-operative cognitive impairment – drugs that are currently not yet available.