Artificial Intelligence Is Making Its Way Into Pharmacy

According to Mckinsey, data and machine learning in pharma can generate up to $100 billion, annually. This will come from better decision making, optimized innovations, and increased efficiency in clinical trials.

Many big organizations have already begun integrating machine learning in healthcare. These corporations are trying to identify ways to collect and analyse all the data the healthcare industry has to improve analysis of prevention methods and treatments. In fact, many pharmacy colleges in Bangalore are also teaching students the importance of combining machine learning and medicine.

There are three major areas where machine learning is already making a mark:


Identifying and diagnosing an ailment can be time consuming which is why it’s at the forefront of machine learning research. Organizations are focusing on integrating cognitive computing and genomic tumour sequencing to prescribe the right medication. Google’s DeepMind Health is working towards developing a technology that can address macular degeneration in ageing eyes.

Personalized Treatments

Personalized medication is another area of focus for most organizations. They are currently working on supervised learning. This allows doctors and pharmacists to choose the right set of diagnosis based on symptoms and genetic makeup of patients. IBM Watson Oncology is working on a model that uses patients medical information and history to help choose the best treatment options.

Clinical Trial Research

Applying machine learning to clinical trials research has multiple benefits. Using predictive analytics can help choose the best candidate for a clinical trial. For instance, examining the genetic information of an area will result in picking the right candidate for a trial and make the overall trial quick, and cost-effective.

There are various other areas where machine learning is seeping in. If you are planning to pursue a degree from one of the best pharmacy colleges in Bangalore or another city, it is essential to understand the importance of machine learning and big data in the pharmaceutical industry.

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