Personalized Medicine
Bodhayan Prasad, RKMV 2006
The eleventh session of the Praktani Adda uncovered the essence of stratified healthcare and precision medicine. The session conducted by Bodhayan Prasad, a 2006 pass out of Ramakrishna Mission Vidyapith Deoghar, delved into personalized medicine and dealt with the issue of multimorbidity (occurrence of multiple long-lasting diseases) as a significant challenge of the ageing population.
Bodhayan is a Final year PhD researcher in Stratified/Personalised/Precision Medicine at Northern Ireland Centre for Stratified Medicine (NICSM), Ulster University, based at Clinical Translational and Innovation Center (C-TRIC), Altnagelvin Area Hospital site in Derry/Londonderry, Northern Ireland, UK.
His research is focused on stratifying patients with multiple chronic conditions (multimorbidity) based on genomics, proteomics, clinical healthcare record and response to treatment data. To start with, the session deliberated on the difference between diagnostic, which according to the speaker, is the scrutiny of an ailment after it has impacted a patient and prognosis, which is about predicting how an illness can affect a patient.
The session, based on the study of Rheumatoid Arthritis, which happens to be the specialization of the speaker, deliberated on the advances in the field of personalized medicine and how it can be the future of medical treatment based on gene sequencing.
The session explained in detail, taking into consideration TNF treatment meted out to elderly patients suffering from Rheumatoid Arthritis. It explained how personalized medicine is not a fancy term associated with luxury but a need of the hour to bring down multiple drugs administered in such patients given the current diagnostical practice based on hit and trial treatment of the condition.
With proper examples and details, Bodhayan explained how personalized medicine could bring down the cost of a particular treatment and provide much-needed relief to a patient in a shorter period.
The session focused on stratifying patients with multiple chronic conditions (multimorbidity) based on genomics, proteomics, clinical healthcare record and response to treatment data. It highlighted the need for developing computational methods for analyzing big data sets in Personalized Medicine by applying bioinformatics and machine learning algorithms to make the treatment of chronic illnesses more affordable and, most minor harmful for the patients.
