Machine learning and artificial intelligence (AI) are having a dramatic impact on the life sciences industry. Many major life sciences companies have either partnered with an AI startup or acquired one. Many life sciences professionals have experimented with AI technologies in the workplace at one time or another. So why all the excitement?
Perhaps the best answer has to do with AI-powered drug discovery. The time to develop a new drug can run anywhere from 10-15 years, and the costs of gaining final approval from regulators can be staggering. By one estimate, pharmaceutical and biotech companies in the U.S. spend $75 billion annually on R&D to develop new drugs. The primary appeal of AI is a way to dramatically shorten the development cycle and also reduce the cost of getting approval.
And here is where AI and machine learning technologies really excel, because they are very good at making sense of incomprehensible amounts of data. Not only can they detect trends in a sea of data, but also they can predict the outcomes of trials with stunning accuracy.
Another key area for machine learning and AI technology in the life sciences industry involves greater drug personalization. It’s not just that AI-powered machines can find potential drug solutions faster and cheaper – they can also find solutions that are completely personalized and customized to a specific user. Machine learning really enhances the overall R&D process by being able to predict drug performance. Think about all the warnings on medications or treatments: depending on unique genetic code and physical condition, medication will likely impact you differently than it does someone else. And that’s where AI can make a huge difference – by personalizing medicine based on your unique identity at the molecular level, it can improve the overall treatment process.
And, of course, AI and machine learning can play a very important role in patient diagnostics. UK researchers at Oxford, for example, have used AI systems to diagnose heart disease and lung cancer faster than human practitioners can. One of the keys here is the ability of machine learning algorithms to study images and learn what a “healthy” person looks like and what a “sick” person looks like. Over time, the algorithm actually learns how to detect early warning signals of potential sickness just by studying images of a heart or a pair of lungs.
Just about any data-rich process within the life sciences industry can be made better through the use of machine learning and AI technologies. AI systems can collect, analyze and integrate text and data from just about any source. And they are also becoming much better at analyzing unstructured data that even humans might have a hard time analyzing. Thanks to AI and machine learning, the life sciences industry should see an accelerated pace of innovation in 2019 and beyond. That’s good news for people everywhere if it can bring down the cost of healthcare and lead to more effective treatments and possibly even cures.
To learn more about how you can incorporate intelligent technologies such as AI and ML into your business, contact Crescense today!