It’s amazing how a single entity can impact almost every aspect of an entire industry, especially something as large as the pharmaceutical industry. Yet, the industry itself, perhaps because of its size, has been slow in welcoming the potential of artificial intelligence’s (AI) influence on so many areas of the business.

This may seem strange to say but an industry that is almost a $1 trillion in size may not yet have the resources, access to embrace, and fully optimize AI. Because artificial intelligence can be modeled in so many ways, it may be socially and institutionally difficult to get the right people to understand how it works, making adoption a bit more difficult. In addition, IT infrastructures at most pharma companies were not put in place with AI in mind. This means data storing and interoperability become problematic. Gains will have to be made in how information is sorted and processed in order to be used efficiently.

But all of this is changing. Investment in AI and machine learning is expected to grow at a rate of 48% from 2019-2025. The general feeling is that those in pharma that don’t embrace AI will fall behind.

As it is right now, these are just some of the ways AI is available to be applied to the pharma industry:

Drug discovery – AI is starting to play a huge role in drug discovery from compound selection, predicting the responses of drugs, to detecting biomarkers. The pharmaceutical industry, in general, has so much data available—AI can utilize that clinical data for the retrospective analysis searching for potential new uses for specific drugs. Furthermore, AI has the potential to disrupt other areas of drug development which can lead to faster development and lower overall costs.

Digital Pathology – AI can be used in digital pathology for tissue classification, pattern recognition, morphometric phenotyping, and biomarker detection. When combined with a pathologist it has the potential to improve patient management and personalized medicine as well as improve clinical and diagnostic efficiency. AI can also help manage the large quantity of data produced by digital pathology workflows, which can lead to new medical breakthroughs.

Genomics – AI can be used to identify patterns and new models in genomic data sets which can translate to better treatments.  Companies are leveraging machine learning and AI to interpret genomic variations and their effects on cellular responses, to drive clinical workflows as well as in gene editing.

Radiology – When used in diagnostic imaging, AI can be used to more accurately and precisely segment different body parts. This has the potential to help a radiologist locate tumors more efficiently and minimize the chances of misdiagnosis.  When working in tandem, a radiologist guided by an automated AI solution can review cases much faster with the potential for lower rates of error.

Clinical trials – AI can be used by drug companies to increase the likelihood of success in clinical trials.  If AI can be used to predict better responders to a therapy, it can lead to better patient recruitment leading to more efficient trials.

The pharmaceutical industry has been responsible for many life-saving, life-enhancing advancements and AI in pharma can assist the industry in doing much more.

Through new drug development, the testing of drugs and so on, the pharma industry will see a shortening of the time frame between investment and the return on investment that can only help this indispensable industry move forward. AI can even be applied to optimizing marketing strategies and decision-making regarding drug campaigns, which is another major expenditure for the industry, especially in the United States. AI will play a role in developing new products and getting those products to the right people at the right time.

Alan Jerusalmi is vice president of business development pharma services at RSIP Vision. He is a performance-driven professional with 16 years of experience in the healthcare and life sciences industry. He oversees business development within the pharma services sector. At RSIP Vision, Jerusalmi implements complex strategies in the areas of pharma drug development, immuno-oncology, genomics, bioinformatics, and biomarker discovery. 

Source:https://www.managedhealthcareexecutive.com/news/opinion-pharma-needs-go-big-artificial-intelligence