Pharmacogenetics, pharmacogenomics and ayurgenomics for personalized medicine: a paradigm shift.

The value of health care can be increased tremendously through individualized medicine. With the promise of individualized medicine, healthcare professionals will be able to better predict disease risk, prevent development of disease and manage treatments more efficiently thereby allowing people to be healthier and active longer. The developments in the area of pharmacogenetics/pharmacogenomics can help the physicians achieve the target of personalized medicine. Personalized medicine will come to mean not just the right drug for the right individual, but the right drug for the specific disease affecting a specific individual. The use of personalized medicine will make clinical trials more efficient by lowering the costs that would arise due to adverse drug effects and prescription of drugs that have been proven ineffective in certain genotypes. The genotypic experiments have laid valuable insights into genetic underpinnings of diseases. However it is being realized that identification of sub-groups within normal controls corresponding to contrasting disease susceptibility could lead to more effective discovery of predictive markers for diseases. However there are no modern methods available to look at the inter-individual differences within ethnically matched healthy populations. Ayurveda, an exquisitely elaborate system of predictive medicine which has been practiced for over 3500 years in India, can help in bridging this gap. In contrast to the contemporary system of medicine, the therapeutic regimen in Ayurveda is implicated on tridoshas and prakriti. According to this system, every individual is born with his or her own basic constitution, which to a great extent regulates inter-individual variability in susceptibility to diseases and response to external environment, diet and drugs. Thus the researchers in India have demonstrated that integration of this stratified approach of Ayurveda into genomics i.e. Ayurgenomics could complement personalized medicine.