The first attempt to understand the proteomecomposition occurred in 1975 with theuse of two-dimensional gel electrophoresis to separate andquantitate proteins from an Escherichia coli whole-cell lysate. Proteomics is not a mature science yet and it has much more to reveal than today, but very soon.

Proteomics is the study of the proteome, a set of proteins produced by a species, an individual, an organ, a cell, and that changes or differs from cell to cell and over time. It is not only about identification, structure but it includes how these proteins interact with each other and which roles they play. Proteomics has the potential value to uncover the nature of the organism and to understand its intricacy. Studying all the proteins of a cell rather than each of them is to draft a more global, integratedand comprehensive view of the biology than genomics or transcriptomics allow. The human genome contains about 20 000 – 25 000 coding genes (genome) that leads to about 100 000 transcripts (transcriptome) and up to about 1 000 000 proteins (proteome).

The exploration of the proteome is a (very) complex journey. It is notably about proteins expression profiling, e.g., disease mechanism, proteins mining, e.g., drug target identification and validation, but it also relates to functional proteins, structural proteins, proteins interaction and trafficking, or proteins translation. The number of proteins makes it complex, but the limitations of the needed techniques too.While advances in mass spectrometry along with data analytics in the past decade have made proteomics a powerful tool in discovery, challenges remain from limited sensitivity, reproducibility, scalability and automation. Additionally, the quantity of data acquired or generated through these upgraded techniques brings new challenges on data processing, sharing and analysis. It is very much likely that proteomics has entered a data overflow era. The technical advancement in mass spectrometry may far exceed our ability to handle the results properly.

"Extensive collaborations between proteomic scientists and clinicians will enhance the pace of translating laboratory findings to the clinics for the benefit of many patients with high medical nees."

In Life Sciences, main proteomics applications are in drug discovery (drug target identification and validation, toxicology) and in clinical diagnostics (biomarkers, phenotypes of drug responders, side effects).Proteomics has been recentlyofsome successful help in Infectious Diseases, Oncology, Rare Diseases and Degenerative Diseases but promoting proteomics as a masterpiece in drugs development requires to (1) continue advances in mass spectrometry instruments and experimental methodologies(2) improvepublic Electronic Health Records systems (3) increase Biobanks in public and private structures to foster clinical proteomics research (4) extensively enlarge partnerships between proteomic scientist and clinicians to tackle medical needs (5) establish and develop high-quality PPI knowledge databases and ease their access to researchers (6)facilitate proteogenomic concepts for diseaseswith clear genetic backgrounds (7) combine techniques of exploration with computational approaches, including machine learning and artificial intelligence, to foster analysis capabilities and to enable (new) biology hypothesis, disease modeling, target discovery and validation.

Leading a translational sciences department and being involved in computational modeling I would certainly companion (4) and (7). Extensive collaborations between proteomic scientists and clinicians will enhance the pace of translating laboratory findings to the clinics for the benefit of many patients with high medical needs. Computational modeling will provide the best approach to gain the needed understanding and integration of all omics to predict the response in patients to treatments and to propose an optimal Precision Medicine.

Today, the entire human genome can be sequenced in a couple of days. I have every reason to believethat mass spectrometry-based proteomics or any related emerging techniques will followthe same path. The amazing development seen in the proteome exploration over the past decade gives confidence that it will reach throughput and sensitivity comparable with thoseof genomics and revolutionize mechanistic studies of diseases and development of their treatments. It will besoon used routinely in biomedical research and for bedside disease diagnosis by health care professionals.