Artificial intelligence (AI) has had major impacts in the health care industry, affecting providers and patients alike. However, it also aids the pharmaceutical sector in finding and creating the drugs that support health care through the treatment and management of diseases. Here’s a closer look at some positive changes AI could bring this year.
1. More Applications of AI for Drug Discovery
Uncovering effective drugs can be a time-consuming process. However, AI could make it faster and more fruitful.
A recent partnership between Roche, its U.S. subsidiary Genentech and clinical-stage biotech company Recursion will involve using AI to find new drug targets and accelerate this phase of development. The arrangement could lead to up to 40 programs for neurology and cancer drugs over the next decade.
However, experts warn that applying AI to drug discovery could also have a dark side. One pharmaceutical company previously used AI to find beneficial therapeutics. However, it also relied on the technology to uncover new toxic nerve agents to use as bioweapons.
In less than six hours, the algorithms had found 40,000 molecules that fit the researchers’ desired parameters. They warned that their experiment should be a wake-up call. Depending on AI to find new drugs is promising, but some people could misuse the method’s potential.
2. Greater Interest in Combining Big Data and AI
It’s not difficult to identify some overlap between big data and AI. For example, they’re both capable of processing large amounts of information far faster than humans could without help.
A recent study of health care professionals determined AI and big data as the top two technologies likely to have the most significant impact on the pharmaceutical sector this year.
The possibilities are virtually endless for how companies might combine the two. One option could be to identify harmful trends of people using drugs in ways not advised on the labeling. Data indicates more than 70,630 Americans died in 2019 from drug overdoses. Product misuse is not the culprit in all such fatalities, but it often plays a significant role.
Bristol-Myers Squibb recently teamed up with a startup called Cortical.io to better identify when people use drugs in ways not intended by the manufacturer. This collaboration involved using AI algorithms to screen 2.2 million Reddit posts that discussed medications during one trial. The goal was to spot potential instances of misuse of six different drugs.
There’s no universally successful way to curb drug overdoses. However, pharmaceutical company representatives that understand probable misuse trends can act to minimize them.
3. Focusing on Collaboration Instead of Competition
The people who work at Big Pharma companies often see individuals from other organizations in the industry as competitors. AI won’t eliminate that reality, but it’s decreasing it.
In one recent example, five core partners, including four international pharmaceutical companies, plan to create an AI startup that makes and optimizes antibodies. The hope is that tweaks to existing antibody therapies could make new ones that are more efficient and effective.
Another pairing will see two pharmaceutical companies working together to develop an AI-driven digital pathology platform for improved cancer care. The artificial intelligence aspects will reportedly enhance clinical trials and enable the creation of individual therapies based on a patient’s biology and tumor composition.
Thanks to efforts like these, the decision-makers at more pharmaceutical companies could realize it pays off to work together. After all, most Big Pharma organizations have tremendous resources. Pooling them could lead to faster, more beneficial results for the health care industry at large.
An Exciting Future for AI in Big Pharma
These examples are just a sampling of what people can expect this year as more pharmaceutical company leaders explore how AI could help their processes. Creating new drugs is often a significant gamble with numerous unknown factors. Artificial intelligence could remove or reduce many of them, leading to impressive outcomes much faster than before.