How difficult is the validation of clinical biomarkers?

Recent developments of introducing stratified medicine/personal health care have led to an increased demand for specific biomarkers. However, despite the myriads of biomarkers claimed to be fit for all sorts of diseases and applications, the scientific integrity of the claims and therefore their credibility is far from satisfactory. Biomarker databases are met with scepticism. The reasons for this lack of faith come from different directions: lack of integrity of the biospecimen and meta-analysis of data derived from biospecimen prepared in various ways cause incoherence and false indications. Although the trend for antibody-independent assays is on the rise, demand for consistent performance of antibodies (both in choice of antibody and how to apply it in the correct dilution where applicable) in immune assays remains unmet in too many cases. Quantitative assays suffer from a lack of world-wide accepted criteria when the immune assay is not ELISA-based. Finally, statistical analysis suffer from coherence both in the way software packages are being scrutinized for mistakes in the script and remaining invisible after small-scale analysis, and in the way appropriate queries are fed into the packages in search for output that is fit for the types of data put in. Wrong queries would lead to wrong statistical conclusions, for example when data from a cohort of patients with different backgrounds are being analysed, or when one seeks an answer from software that was not designed for such query.