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Predictive Analytics and the Pharmaceutical Industry

By Lainey Kasian, Media Analytics Executive



By now, we are all probably used to seeing advertisements for things based on our recent purchase or even search history. These are created by companies like Google that employ the power of predictive analytics. Predictive analytics is a specific subset of data analytics that is focused on making predictions about future outcomes using analytic techniques like statistical modeling and machine learning. This is a fast-growing field because organizations can use these predictions to sift through both current and historical data to detect helpful trends and forecast events and conditions


We most often see examples of this in retail advertising, but it is also gaining traction in the pharmaceutical industry for interesting reasons. Companies can use predictive analytics to give patients recommendations, to assist in the selection of patients for clinical trials, and most obviously for performance evaluation


Predictive analysis in the pharmaceutical industry could look at data tables with information about a patient’s symptoms, test results, family history, and previous conditions and generate the best diagnosis as well as propose the most effective medication for the situation. This advances beyond current recommendations because it would automatically be able to combine allergies, past records, and known reactions for each individual patient.


The way things are now, selection for clinical trial participation follows more of a first-come, first-served approach than relying on actual scientific evidence. Predictive analytics could drastically change this approach and greatly benefit the results of clinical trials. Analytics could use data to identify patients with the highest probability of benefitting from the treatment. Using data to make these decisions could cut down on the underrepresentation of groups and allow for maximum insights about the new drug to be observed. Overall, employing data to make these decisions would ensure that a lot more factors are being accounted for when deciding who to include in new clinical trials.


Lastly, and most obviously, data can just be used to evaluate the performance of a new product. In analytics terms, this means that you would evaluate how well a model fits the data. In the pharmaceutical world, this means seeing how well a certain drug would fit the data and cure symptoms.


Overall, predictive analytics are powerful tools that can be applied to many different industries. The implementation of predictive analytics into the pharmaceutical world has numerous benefits and beneficial uses. While we might currently see predictive analytics as a little invasive and creepy, they can also be used to do tremendous good in medical fields.  



© 2019 by Sasha Kagan

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