Integration of multidisciplinary sciences: Identification, validation, development and marketing of disease-specific biomarkers are integrated processes in molecular biology, involving new biotechnologies, clinical sciences, regulatory policies, and clinical applications. “Omic” science and technology play important roles in the identification and discovery of biomarkers. The Omic scope includes genomics, proteomics, metabolomics, pharmacogenomics, transcriptomics, and other high-throughput methodologies. Selected biomarker candidates can be validated and evaluated using computational biology, high-throughput image analysis, molecular genetics, specimens from human tissue banks, mathematical medicine and biology, protein expression and profiling, and systems biology. Clinical bioinformatics have been suggested as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics, helping to understand the role of selected biomarker candidates in clinical settings, disease development and progression, and therapeutic strategies, mapping relationships of drug and biomarker candidates with clinical examinations, pathology data, biochemical analysis, and imaging and therapies . An example of targeted biomarker validation has been the study drug localization, is tissues, using imaging data of targeted tumor regions in various lung compartments. Another example is selectivity and precision of proteomic analyses in patients with chronic lung diseases and cancer . Panels of disease-specific protein biomarkers that define the disease stage were selected in chronic obstructive pulmonary disease. By targeted proteomic analysis, a digital evaluation score system was developed for assessing severity of disease, useful, bioinformatics information, and lung function [5, 6]. A number of new integrated scientific areas have been created during the identification and development of disease-specific biomarkers. Genomic medicine was proposed to bring biomarkers into the mainstream of clinical practice and improve therapies and quality of patient life, although such strategies are in the very early stages. Systems clinical medicine has been defined as one of new strategic areas for development of disease biomarkers, involving integration of systems biology, clinical phenotypes, high-throughout technologies, bioinformatics and computational science in order to improve diagnosis, prognosis and therapies of diseases . Next generation sequencing for genomic analysis of individual genomes has been used for single nucleotide polymorphism discovery and estimates of allele frequency, gene ontology analysis of the target genes, analysis of the microRNAs expression, sequencing platforms for mRNA biomarker analysis, genome-wide analysis, and the exploration of the proteome, all of which should lead to the identification of useful protein biomarkers.