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Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung disease mostly due to smoking and until now diagnosed by spirometry (post bronchodilator FEV1/FVC <70%). However, in spite of the usefulness of FEV1 as diagnostic and prognostic tool, it has proven to be a weak indicator of future exacerbations, unable to predict lung function decline within COPD patients, as well as unable to identify the smokers “susceptible” to developing COPD at an early stage. Thus, there is an urgent need for biomarkers that address these questions and support clinical decision making in the diagnosis and treatment of (early) COPD. In this respect, considerable efforts have been devoted to identifying protein biomarkers that enable a better understanding of this complex disease and leading to better diagnostic and prognostic tools. However, in spite of the wide range of candidates that have been suggested as potentially useful COPD biomarkers, most remained at the level of the initial discovery, and only fibrinogen has been approved by the Food and Drug Administration (FDA) as predictor for all-cause mortality and COPD exacerbations. There is thus a need for future investigations of these biomarkers in large-scale and well characterized studies in order to prove their usefulness as surrogate endpoints. Based on this, the aim of the present review is to advance COPD biomarker development by providing a comprehensive overview of protein biomarker candidates which have been evaluated in clinical studies and prioritize them according to their potential of becoming valid, clinically useful COPD biomarkers.

Solid organ transplantation has emerged as the “gold standard” therapy for end-stage organ failure as it improves both quality of life and survival. Despite the progress in short-term graft survival, that is closely associated with the impressive reduction of acute rejections within the first year, long-term graft and patient survival remain almost un-changed and unsatisfactory. Incomplete control of chronic allograft injury but particularly the adverse effects of long-term immunosuppression, such as graft toxicity, diabetes, cardiovascular events, infections, and tumours continue to challenge the long-term success. In general, immunosuppression is applied as one-size-fits-all strategy. This can result in over- and under-immunosuppression of patients with low and high alloresponsiveness, respectively. Trial- and -error strategies to minimize or even completely wean of immunosuppression have a high failure rate. Consequently, there is an unmet medical need to develop biomarkers allowing objective risk stratification of transplant patients. To achieve this goal, we engaged in an academic-industrial partnership. The central focus of the European-wide BIO-DrIM consortium (BIOmarker-Driven IMmmunosuppression) is the implementation of biomarker-guided strategies for personalizing immunosuppression to improve the long-term outcome and to decrease the adverse effects and costs of chronic immunosuppression in solid organ transplant patients. The concept includes four innovative investigator-driven clinical trials designed by the consortium.

Precision medicine aims to provide the precise treatment for the patient with the right dose at the right point of time. Biomarkers (BM) are vital for the identification of patients who would benefit the most from individualized treatment. In addition, they help to enable the prediction of prognosis, the detection of early therapeutic and adverse effects, and may serve as surrogate endpoints in clinical trials. BM are becoming essential tools to increase productivity in drug discovery and impressively enhance the way medicine is practiced. However, the identification, sufficient validation and implementation of such BM are challenging. This process requires expertise from different areas and high resource investments. Collaborations of different partners may be helpful to overcome these challenges. In the past decade, collaborations between diagnostics and pharmaceutical companies as well as industrial–academic collaborations have been increasingly pursued. Moreover, public funding may offer support and open new opportunities to form such consortia. Herein we give an overview of the different types of collaborations, their opportunities and challenges, and describe experiences in forming strategic partnerships with other companies.

Gene expression profiles in blood are increasingly being used to identify biomarkers for different affective disorders. We have selected a set of 29 genes to generate expression profiles for healthy control subjects as well as for patients diagnosed with acute post-traumatic stress disorder (PTSD) and with borderline personality disorder (BPD). Measurements were performed by quantitative polymerase chain reaction (qPCR). Using the actual data in an anonym-ous form we constructed a series of artificial data sets with known gene expression profiles. These sets were used to test 14 classification algorithms and feature selection methods for their ability to identify the correct expression patterns. Application of the three most effective algorithms to the actual expression data showed that control subjects can be dis-tinguished from BPD patients based on differential expression levels of the gene transcripts Gi2, GR and MAPK14, targets that may have links to stress related diseases. Controls can also be distinguished from acute PTSD patients by differential expression levels of the transcripts for ERK2 and RGS2 that are known to be associated with mood disord-ers and social anxiety. We conclude that it is possible to identify informative transcription profiles in blood samples from individuals with affective disorders.

Immunosuppression (IS) following solid organ transplantation is indicated to avoid rejection but puts a sig-nificant burden on patients and healthcare systems due to life-long medication dependency and associated costs. Or-gan-tolerance with low or no IS medication has been observed, and might be forecasted with the help of appropriate biomarkers. Individualized treatments raise the question whether benefits of individualization outweigh the costs of stratification. This article outlines the importance of early economic evaluation in the context of biomarker-guided IS and discusses challenges that an economic evaluation should address, using the BIO-DrIM project as a reference exam-ple. We report on design aspects and health-economic study integration into several newly designed biomarker trials. In these studies, health-economic endpoints were defined to measure benefits of individualization and to compare them to the costs associated with stratification. Key economic outcomes to be collected are resource consumption and patient quality of life. Test accuracy of the biomarker-stratification is critical for the clinical success and the health-economic viability of an individualized reduced IS regime. However, IS regimes are not well standardized, rendering comparator choice difficult. The multi-national character of the trials adds further complexity that needs to be addressed. Develop-ers of biomarker tests should stress the importance of integrating health-economic evaluations early into prod-uct-development.

The last decade has seen an extraordinary amount of effort devoted in biomedical research to the field of biomarkers. There have been some notable successes with novel markers being adopted into clinical practice bringing clear clinical benefit to some patients — particularly with the increasing numbers of medicines being approved with companion diagnostics. However, it is fair to say that there has not yet been the numbers of clinically valuable biomarkers brought to medical practice that the research effort would seem to warrant. This paper evaluates examples of successful biomarkers, markers which might be considered partial successes and a few problematic examples and ar-gues that more effort spent in the validation phase of marker development, and less in the discovery phase might be a more efficient way to allocate research resources.