ANALYTICS FOR PHARMACEUTICALS- AN ANECDOTE

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As one of my reader requested for application of analytics in the field of Pharmaceuticals, I am briefing a short article on it as per my knowledge.

CLINICAL TRIALS

Most crucial step in Pharma Industry is ‘Clinical Trials’. The ‘Control and Experimental Group’ who are subjected to trials should meet the criteria before undergoing the trials. Big data and Analytics helps us to filter out patients according to our requirements. This helps us to monitor the patients and predict the side effects of the drugs.

PREDICTIVE ANALYTICS

Using variables like lifestyle, genetics, medical history, health etc. we can predict the suitability of drug on particular patients, with the help of ‘Predictive Analytics’. We can design a model, which will consider all the details that help in real-time monitoring of the patients by providing individual care.

DECISION MAKING

Big Data Analytics can be used for ‘Strategy Building’ by pharma companies to focus on specific geographical areas and markets to promote their drugs. This will help pharma companies to come up with extremely targeted marketing and sales goals, thereby saving both on time and effort.

CORRECTING ERRORS

Errors in a selection of ‘Human Subjects’ for trials cost pharma companies huge amounts. Solution to this problem lies in the data produced by the company itself and by analyzing these data, patients can be categorized into clusters. Thereby right cluster of subjects can be chosen for the test and eliminate the errors.

EFFICIENCY OF CLINICAL TRIALS

Data is produced from clinical trials, hospital research, physician notes, sales data, patients demographic etc. Analyzing this data helps in Improving the design of clinical-trial and outcomes as well as higher efficiency. Clinical trials will become much highly adaptable to respond to drug-safety signals, which are seen only in small, but subpopulations of patients, which are identifiable.

NEW INSIGHTS

By analyzing the data from marketing and sales, markets can be clustered into groups which help in finding new dimensions in the market thereby creating a new type of drugs which will be more effective for that segment of customers.

 

I would like to conclude this article by Thanking Manoj sir for guiding me on the right path regarding this topic.

Thanks for reading. If you have any further doubts or need any analysis of data, Please contact us on ‘Amrita Analytics Lab’ website.

 

-Avinash Reddy

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