Sunita is a molecular biologist, with a Ph.D. from Mumbai University, India. She was awarded the ‘Young Scientist Award’ for her doctoral research on ‘Homocysteine as a Risk Factor in Coronary Heart Disease’. She has more than 15 years of experience, spanning across cardiovascular research, molecular diagnostics, medical communications and pharmacoeconomic analyses. She has worked in well-known tertiary hospitals and multinational pharmaceutical companies in India, and is one of the pioneers of professional medical communications in the country. She has been on the panel of expert reviewers for global therapy teams and also for peer-reviewed journals. She has several publications and presentations to her credit and is a regular speaker at clinical research/medical communications forums in India. She is presently leading the Healthcare domain within Capita India.


The present systematic review aims to assess published medical literature for an overview on personalized medicine with focus on current perspectives. Studies are being retrieved from Pubmed, Cochrane and Embase databases using relevant search strategies. Pre-specified inclusion and exclusion criteria will identify studies from 2005 to the present on the basis of study types assessing the role of personalized medicine in the management of diseases. The outcomes of interest are current focus (clinical and economic) of personalized medicine, targeted monitoring, biomarkers and diagnostic tests. Two researchers are independently reviewing the studies and data will be extracted from the final list of included studies. Though there have been reviews focusing on targeted therapies and accompanying diagnostics, these are mostly aligned to specific disease areas. This review will probably provide a wider perspective of personalized medicine, especially the current trends. Our systematic review hopes to demonstrate the challenges with estimating the economic benefits of such therapies. We have identified more than 600 studies to review. The final number of studies to be included in our analysis may be around 20-30. The data from published studies will hopefully answer some of the prevailing uncertainties regarding personalized therapies and provide a better perspective on the clinical and economic evaluations of such therapies.

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