One of the biggest tasks in the pharma industry, and one of the largest cost centers, is drug development. This is a lengthy and highly expensive process — after all, many high-skilled specialists are needed, and they naturally demand high salaries.

It also means some drugs that start the trials will fail. Knowing more quickly if a drug is worth spending time on, or whether there’s a better outcome for a different malady, would be a great advantage.

AI can help with drug development by identifying potential targets and potential mechanisms for new drugs to have a positive impact on the human body. When it comes to analyzing what potential, active ingredients could look like, Artificial Intelligence helps as well. AI can analyze vast sets of data and simulate what so-far-untested molecules could do.

This gives scientists sets of potential drug agents in a shorter time compared to previous processes, and they can then focus on the most promising candidates — thereby hopefully developing more powerful and easier-to-tolerate drugs in a shorter period of time.

When it comes to testing drug candidates, AI is of use as well. AI can analyze the large data sets that are generated by drug trials, e.g. in order to find safety issues early on. It can also analyze outcomes efficiently and fast, e.g. to see what sub-sets of the patient population the drug looks most promising for, or whether any combinations with other drugs should be avoided, and so on.

Last but not least, AI helps with another major cost driver for pharmaceutical companies: Regulation and compliance. Drugs are rightfully well-regulated, but this causes significant costs for pharma companies that do not generate a lot of value for patients. By automating some of these processes via Artificial Intelligence, pharma companies can bring down their operating expenses and put more resources towards production, drug development, and so on, where value for patients is being generated.

Pfizer (NYSE: PFE) is deploying AI today. It uses IBM’s (NYSE: IBM) Watson in drug discovery and works with NVIDIA (NASDAQ: NVDA) via the AI Accelerator initiative, to optimize manufacturing.

Merck (NYSE: MRK) is another big pharma company that uses AI today, including its own AI platform called GPTeal that’s used by tens of thousands of employees to boost their productivity by automating a wide range of different routine tasks.

Getting Invested in AI in the Pharma Industry

Investors can opt to invest in many different pharma companies, as PFE, MRK, and many of their peers use artificial intelligence in some way or another, and that trend will only grow in the coming years.

This exposes investors to pharma-specific issues, such as patent expirations that regularly result in sales declines for key drugs, which is why investing in pharma stocks directly may not be the best choice for everyone.

Investors can also invest in the companies that power AI in the pharma industry without being pharma companies themselves. AI can only be used when high-powered chips train the required algorithms, and that’s where companies like NVDA come into play. IBM, as mentioned above, is another tech company with AI-in-pharma exposure, as its Watson platform helps with drug discovery (as well as many other scientific tasks across other industries).

Investors can also choose among our top Artificial Intelligence picks to benefit from increased AI use in the pharma industry, as well as from general growth in the world of Artificial Intelligence.