AI is used in a variety of ways in the pharma industry. Some key ones include the following:

• Discovering new drugs. For that, huge data sets have to be analyzed, which works best with the help of Artificial Intelligence algorithms that detect patterns and that can help link/match data. AI algorithms can, for example, sort sets of genomics data to search for genes that may play a role in the development of drugs, thereby finding risk factors, as well as potential treatment approaches, such as blocking specific proteins, enzymes, and so on. The most promising approaches then still have to be tested in vitro and in vivo, but so-called in silico (“chip-based”) analysis can do a lot of the sorting, prioritizing, and so on, and thus helps reduce costs and shorten timelines — since bringing new drugs to the market can be extremely costly and take many years, possibly even decades, AI offers a lot of value here.
• Better understanding of how drugs work. AI can predict what side effects drugs may cause, what dosing should look like for optimal outcomes, and so on. This helps reduce risks when drugs are tested in humans later on, and it again shortens timelines and brings down costs.
• Reduce human workloads for documentation and other bureaucratic tasks. The pharma industry is heavily regulated — after all, patients want drugs that are both effective and safe, but this heavy regulation causes huge regulatory workloads that cause massive costs for pharma companies. Artificial intelligence tools can help by making these processes quicker and less costly.
• By analyzing large data sets, AI tools can help control the safety of drugs that are already in use. Adverse effects that have been reported can be analyzed for patterns, helping identifying potential problems, e.g. if a drug is generally safe to take but not in combination with certain other drugs, or if it can cause problems in patients with specific health issues.

One good example of how it’s already working is Halicin, an antibiotics candidate that could treat multi-resistant bacteria. It was discovered via AI. This drug candidate had originally been aimed at treating diabetes (which didn’t work), but MIT scientists using a Deep Learning AI algorithm found out that it could be used as an antibiotic instead.

Benefit from AI-Focused Pharma

Directly buying shares of pharma companies that have embraced AI is the best place to start. Stocks like Bristol-Myers Squibb (NYSE: BMY) or Pfizer (NYSE: PFE) already use AI in drug discovery and other tasks.

Investors can also opt for the shares of companies that power this trend from the tech side, such as NVIDIA (NASDAQ: NVDA). With its high-end GPUs that are used to train advanced AI algorithms, NVIDIA is a key player when it comes to advancing the pharma industry with AI tools.

NVDA collaborates with companies, such as Novo Nordisk (NYSE: NVO), on drug discovery built an AI supercomputer for Eli Lilly (NYSE: LLY), and offers its AI models to a wide range of other pharma companies.

Investors that are interested in broader exposure to the world of tech and Artificial Intelligence should take a look at our top picks.