The Department of Biotechnology has invited researchers, scientists and clinicians to collaborate in multicentric projects focusing on ‘Cardiovascular health and diseases’ as part of chronic and lifestyle disease program.
The aim is to gain insights into the pathophysiology of cardiovascular complications and understanding cardiac functions and develop early risk-assessment strategies to prevent the multi dimensional complexities associated with CVD, the Expression of Interest (EOI) document said.
Recent comprehensive research analysis on Global burden of the Diseases for the period from 1990 to 2019 has identified cardiovascular disease as the topmost causes of morbidity and mortality in India.
It is found that besides the role of metabolic drivers in cardiovascular events, economic, social and environmental factors also contribute to biological pathways leading to cardiovascular diseases, the document said.
Long-term cardiac complications have been learnt to be associated with post Covid-19 pandemic with worse outcomes in many cases.
This also envisages the need for better biological models of the myocardium for understanding cardiac functions and to study CV consequences of viral infections, individuals for CVD for early-risk assessment reduce the disease burden, the document said.
Against this backdrop, the Department of Biotechnology invited EoI from the private and public academic institutions.
The Expressions of Interest (EOIs) has been invited for developing multi-centric collaborative projects involving basic scientists and clinicians in specific areas such as cardiovascular consequences of viral infection, including post Covid impact and Models for understanding cardiac function and drug discovery.
The projects can also be developed for Cardio-metabolic Health-Unmet Need and prevention strategies which can include identifying the highest risk populations (in the paediatric, adolescent and adult populations among others ) for CVD and heart failure and earlier identification of patients at risk novel biomarker identification or predictive algorithms to assess changes in risk. PTI