Analysis of hospital based Ayurvedic clinical practice to gain Real World data knowledge

Abstract

Various electronic equipment like computers, mobile devices, wearables, and other sensors collect and store huge amounts of health-related data. This explosion of data carries potential to better design and conduct clinical studies to answer questions previously thought infeasible. Advancement of cutting-edge analytical capabilities is allowing researchers to analyze and comprehend this data at greater depths, permitting medical product development and approval at an accelerated speed. Real world data (RWD) is the information relating to patient health status and/or the delivery of health care routinely collected from a variety of sources like epidemiological studies, clinical practice, already published articles to answer questions previously thought infeasible. newlineApproval of Ibrance by US FDA for male breast cancer, a drug already approved for females and French health authorities allowing a Real World Evidence (RWE) study of 600+ patients, over a period of 18 months, for a conditional re-imbursement scheme in COPD, are a couple of recent examples of approvals using RWD data. A study carried out by Clarivate Analytics, USA, reports 27 (non-exhaustive list), lt5% of all approved drugs, examples of drug approvals by US FDA, EMA, Japan s PMDA and Health Canada, across broad spectrum of medicines between years 1998 and 2019 using RWD from Electronic Health Records and registries. These data were used either as primary data, when non-comparative data were available to demonstrate tolerability and efficacy, or as a supportive data when validating findings. This provides increasing usage of naturally reported data in drug approvals in modern biomedicine. These examples provide evidence of novel use of data, which may have otherwise gone unused. The power available to society would have never been unearthed if not for this way of use of RWD. newline