Precision Medicine for Endocrinology

In recent decades, major biotechnological advances have been achieved following the sudden escalation of disease-related molecular information, with the potential for greatly advancing patient care. The human genome was depicted in 2000 and followed by the completion of the Human Genome Project in 2003. Scientists have ignited a firestorm of breakthroughs and upsure genomic information, by laying out, in order, the 3.2 billion units of human DNA. Innovative omics technologies including whole-genome single nucleotide polymorphism (SNP) chips, RNA interference high-throughput screening, microarrays and next-generation sequencing have also rapidly surfaced offering enormous potential in this field. This genomic revolution era offers unlimited possibilities and unlimited possibilities including the development of individualized medical necessities for each human based on his unique genomic information. Personalized medicine today is commonly defined as a combination of molecular profiling and traditional diagnostic and therapeutic strategies precisely adapted to the individual requirements of patients. The fundamental idea behind personalized medicine is to couple large amounts of data available from the human genome with established clinical-pathological indexes to devise diagnostic, prognostic, and therapeutic policies specifically adapted to each patients needs and the ensuing research wave of the molecular basis of disease. Eventfully, precision medicine facilitates more accurate diagnosis and therapy at the intrinsic molecular level, promoting the individual bation and this allows the customization of healthcare and incorporation of electronic medical information obtained both on an individual and on the more comprehensive global scale. The success of precision medicine faces many challenges. First, the establishment of frameworks for organizing, compiling, and elucidating the influx of data that can keep apace with rapid scientific innovations. Second, the shift toward a deeper understanding of disease, based on molecular biology, requires necessitates reclassification of disease states incorporating this knowledge, i.e modernization of the World Health Organization’s International Classification of Diseases, for which there is a need for a reconsidered categorization classification based on intrinsic biology and traditional signs and symptoms. Thirdly, precision medicine will require promotion of handling of multi-parametric data and some proficiency in interpreting -omics data, dealing with the anticipated complexity and volume of new information. Addressing these challenges will require effective clinical decision support tools and new educational models.