How 3 Companies Use AI to Forge Advances in Healthcare
How 3 Companies Use AI to Forge Advances in Healthcare

How 3 Companies Use AI to Forge Advances in Healthcare

When you think of artificial intelligence (AI), you might not immediately think of the healthcare sector.

However, that would be a mistake. AI has the potential to do everything from predicting readmissions, cutting human error and managing epidemics to assisting surgeons to carry out complex operations.

Here we take a closer look at three intriguing stocks using AI to forge new advances in treating and tackling disease. To pinpoint these three stocks, we used TipRanks’ data to scan for ‘Strong Buy’ stocks in the healthcare sector. These are stocks with substantial Street support, based on ratings from the last three months. We then singled out stocks making important headways in AI and machine learning.

BioXcel Therapeutics Inc.

This exciting clinical stage biopharma is certainly unique. BioXcel (BTAI) applies AI and big data technologies to identify the next wave of neuroscience and immuno-oncology medicines. According to BTAI this approach uses “existing approved drugs and/or clinically validated product candidates together with big data and proprietary machine learning algorithms to identify new therapeutic indices.”

The advantage is twofold: “The potential to reduce the cost and time of drug development in diseases with substantial unmet medical need,” says BioXcel. Indeed, we are talking $50 – 100 million of the cost (over $2 billion) typically associated with the development of novel drugs. Right now, BioXcel has several therapies in its pipeline including BXCL501 for prostate and pancreatic cancer. And it seems like the Street approves. The stock has received five buy ratings in the last three months with an average price target of $20.40 (115% upside potential).

“Unlocking efficiency in drug development” is how H.C Wainwright analyst Ram Selvaraju describes Bioxcel’s drug repurposing and repositioning. “The approach BioXcel Therapeutics is taking has been validated in recent years by the advent of several repurposed products that have gone on to become blockbuster franchises (>$1 billion in annual sales).” However, he adds that “we are not currently aware of many other firms that are utilizing a systematic AI-based approach to drug development, and certainly none with the benefit of the prior track record that BioXcel Therapeutics’ parent company, BioXcel Corp., possesses.”

Microsoft Corp.

Software giant Microsoft (MSFT) believes that we will soon live in a world infused with artificial intelligence. This includes healthcare.

According to Eric Horvitz, head of Microsoft Research’s Global Labs, “AI-based applications could improve health outcomes and the quality of life for millions of people in the coming years.” So it’s not surprising that Microsoft is seeking to stay ahead of the curve with its own Healthcare NExT initiative, launched in 2017. The goal of Healthcare NExT is to accelerate healthcare innovation through artificial intelligence and cloud computing. This already encompasses a number of promising solutions, projects and AI accelerators.

Take Project EmpowerMD, a research collaboration with UPMC. The purpose here is to use AI to create a system that listens and learns from what doctors say and do, dramatically reducing the burden of note-taking for physicians. According to Microsoft, “The goal is to allow physicians to spend more face-to-face time with patients, by bringing together many services from Microsoft’s Intelligent Cloud including Custom Speech Services (CSS) and Language Understanding Intelligent Services (LUIS), customized for the medical domain.”

On the other end of the scale, Microsoft is also employing AI for genome mapping (alongside St Jude Children’s Research Hospital) and disease diagnostics. Most notably, Microsoft recently partnered with one of the largest health systems in India, Apollo Hospitals, to create the AI Network for Healthcare. Microsoft explains: “Together, we will be developing and deploying new machine learning models to gauge patient risk for heart disease in hopes of preventing or reversing these life-threatening conditions.”

Read the source article at TheStreet.com.