The term biomarker is broadly defined and ranges from genetic and biochemical to immunological markers. Biomarkers are objectively measurable characteristics which offer indications of healthy or pathological functions. Predictive or prognostic markers enable doctors treating patients to identify those patients in whom there is a high degree of probability that a therapy will either fail or succeed, or they can supply indications of side-effects and resistances. The evidence for the biomarker is provided by means of a so-called companion diagnostic test.
Insights from biobanks on the prevalence of a marker are important for a number of reasons. For example, they enable an answer to be given in the pre-clinical phase to the question of whether transferability to clinical routine is even helpful or probable. Prevalence can also be used to better stratify clinical trials, both among test subjects and in comparative groups. Patients can thus be selected for participation in clinical trials who have a real chance of benefiting from the new therapy on the basis of their marker profile. This will improve the overall assessment of suitability for therapeutic interventions. Clinical biobanks which also process further-reaching data from day-to-day medical practice, not only facilitate further insights through correlations with these characteristics but also enable the marker's predictive quality to be better assessed.
The suitability of the therapeutic application of a biomarker is also based on the validity of longitudinal information on its stability and dynamism through stages of the illness. As the treatment of an illness is not always conducted in one sector only, information before and after the acute clinical phase is steadily gaining in importance. There is therefore an increasing need of longitudinal sampling and to follow patients to enable us to register changes to the biomarker (e.g. status of expression or mutation).
Against this background, it becomes clear how important it is that all the therapies a patient has received, are recorded. This is the only way to correlate the dynamics of a biomarker with all therapeutic interventions. Besides the prospect of discovering biomarkers, longitudinal sampling also plays an important role from a pharmacogenetic perspective. As we know, pharmacogenetics examine differences in the efficacy and side-effects of a drug. As here too there may be changes over time, research is focusing increasingly on the period after an acute clinical intervention.
The combining of biomarker data with pre-acute, post-acute and acute clinical information is the best approach for today's research into new therapies. However, there are serious problems in obtaining and processing this information comprehensively. To do so, it is vital to bring together numerous players across all sectors: practicing doctors from several disciplines (general practitioners, specialists), hospitals, rehabilitation clinics, pathologists, radiologists, etc. Health systems around the world are marked by their high degree of complexity.
Besides separation by sector, the spatial distribution of service provision also poses a hurdle. It is therefore often desirable for a large chain of hospitals as the umbrella body behind several institutions to take on the task of aggregating, providing and processing the medical information in conjunction with other providers of medical services. Because besides their spatial distribution, a chain of hospitals is more likely to be able to access cases on a scale that is now required in biomarker research.