Personalized medicine has the potential of revolutionizing patient care. This treatment modality prescribes therapies specific to individual patients based on pharmacogenetic and pharmacogenomic information. The mapping of the human genome has been an important milestone in understanding the interindividual differences in response to therapy. These differences are attributed to genotypic differences, with consequent phenotypic expression. It is important to note that targeted therapies should ideally be accompanied by a diagnostic marker. However, most efforts are being directed toward developing both these separately; the former by pharmaceutical companies and the later by diagnostic companies. Further, this companion strategy will be successful only when the biomarkers assayed are differentiated on a value-based approach rather than a cost-based approach, especially in countries that reimburse disease management costs. The advantages of using personalized therapies are manifold: targeted patient population; avoidance of drug-related toxicities and optimization of costs in nonresponder patients; reduction in drug development costs, and fewer patients to be tested in clinical trials. The success of personalized therapy in future will depend on a better understanding of pharmacogenomics and the extension of these scientific advances to all countries.

Asian Indians who have settled overseas and those in urban India have increased risk of coronary events. Reasons for this increased risk are thought to be genetic but are yet unclear. Advances in molecular cardiology have revealed a number of single nucleotide polymorphisms associated with atherosclerosis. In this review, gene polymorphisms that have been associated with coronary diseases among Indians are discussed. Topics include the genes involved in hyperlipidemia, hypertension, and homocysteine. Mutations in the low-density lipoprotein receptor (LDLR) gene resulting in familial hypercholesterolemia have strong association with premature atherosclerosis. Common polymorphism of the apolipoproteins (apo) B-100 and E genes have been associated with variation in lipid and lipoprotein levels. Recently identified polymorphisms in the apoC3 (T-455C, C-482T), and cholesteryl ester transfer protein (CETP) (B1/B2 allele) genes are associated with increased triglycerides and reduced high-density lipoprotein (HDL)-levels, a feature now also common among Asian Indians. Angiotensin-converting enzyme-deletion (DD) polymorphism has been shown to influence beta-blocker therapy in heart failure. Mutations in methylenetetrahydrofolate reductase (C667T), cystathionine beta-synthase (T833C), and methionine synthase (A2756G) genes cause hyperhomocysteinemia, an independent risk factor for atherothrombosis. As the genetics of atherosclerosis continues to evolve, these factors along with the newer emerging factors may become a part of the routine assessment, aiding prediction of future coronary events.

Aim:This systematic literature review was conducted to identify, evaluate, and characterize the variety, quality, and intent of the health economics and outcomes research studies being conducted in India.Materials and Methods:Studies published in English language between 1999 and 2012 were retrieved from Embase and PubMed databases using relevant search strategies. Two researchers independently reviewed the studies as per Cochrane methodology; information on the type of research and the outcomes were extracted. Quality of reporting was assessed for model-based health economic studies using a published 100-point Quality of Health Economic Studies (QHES) instrument.Results:Of 546 studies screened, 132 were included in the review. The broad study categories were cost-effectiveness analyses [(CEA) 54 studies], cost analyses (19 studies), and burden of illness [(BOI) 18 studies]. The outcomes evaluated were direct and indirect costs, and incremental cost-effectiveness ratio (ICER), quality-adjusted life years (QALYs), and disability-adjusted life years (DALYs). Direct medical costs assessed cost of medicines, monitoring costs, consultation and hospital charges, along with direct non-medical costs (travel and food for patients and care givers). Loss of productivity and loss of income of patients and care givers were identified as the components of indirect cost. Overall, 33 studies assessed the quality of life (QoL), and the WHO Quality of Life-BREF (WHOQOL-BREF) was the most commonly used instrument. Quality assessment for modeling studies showed that most studies were of high quality [mean (range) QHES score to be 75.5 (34-93)].Conclusions:This review identified various patterns of pharmacoeconomic studies and good-quality CEA studies. However, there is a need for better assessment of utilization of healthcare resources in India.

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