#Product Trends
Uses of AI, Cloud Computing, and Quantum Computers in the Pharmaceutical Industry
How drug companies look to computers to bring new drugs to market quickly and with less expense.
Pharmaceutical companies are always on the lookout for ways to speed up the drug development and approval processes and reduce expenses. R&D for each new drug can cost each from nearly $1 billion dollars to over $2 billion. That’s not including the clinical trials mandated by the FDA. Those can cost between $7 million to $19 million in phase 2, and jump over an eye-watering $52 million in phase 3. (There are four phases.)
Worse, only 12-13 percent of new drugs navigate on average the entire 10-15 year long process to hit the market shelves.
Here are three ways – all technological – pharmaceutical companies are looking to cut that price tag down.
Artificial Intelligence: Sorting Data for Solutions
Drug companies produce huge amounts of information. These can range from the make-up of a particular molecule to the survey results by trial volunteers.
Much of that information is stored raw in databases like data lakes. No human being can sort and analyze all that info in a reasonable amount of time. So companies are turning to artificial intelligence (AI) to search and sort through all that data.
Finding new drugs (or the possibilities to one) tops that list. The AI, for example, would have to figure out how a specific molecule works to produce a particular result in a drug. No specific program to reach the solution is provided; instead, the machine itself would have to come up with one on its own. Researchers can then use the newly generated algorithms to create new, similar drugs, and be confident with their effects.
AIs are also helping determine the effects of these potential drugs before testing on living things. How this works is a program with deep-learning (DL) capability would examine a million images of cells to learn the different parts. It would then apply the knowledge in discerning the differences between normal, healthy cells and abnormal ones. This information could be useful in figuring out the effects of a new drug in combating cancer cells.
Another way AIs are being used is to assist in the all-important clinical trials. They can sort patient data obtained from an EMR and similar sources for the most well-qualified volunteers. This can drastically increase the success of trials throughout all four phases. Studies have shown that without the assistance, around 80 percent of trials fail because companies could not find the right candidates to meet the trials’ deadlines.
Managing chronic diseases to even predicting the next epidemic are also being considered for these advanced applications.
Cloud Computing: Managing Data for Solutions
The data lakes mentioned earlier can be built and stored using cloud computing. This offers several advantages:
Drug companies avoid the need for a costly in-house network and IT department for its management. This includes expensive hardware and software which can quickly become obsolete.
Scale operations as desired. Need more storage to house a new AI algorithm? Just notify the cloud provider. Need even more space as well as computational power to run said AI’s machine and deep learning programs? Again, contact the provider. Hyperscale cloud providers Amazon, Google, and Microsoft are just a few of the companies with networks large enough to handle many large drug companies’ operations.
Spread tasks globally. Employees can work collaboratively from home or other remote locations, which became vital during the 2020 COVID-19 pandemic and the lockdowns that followed. Partners like small biotech firms, academic groups, and even rival drug companies will be able log on 24/7 with their medical panel PC to work on mutual goals with minimal costs. Cooperation like this cuts both costs and time on drug development and approval.
Quantum Computing: Apply Physics to Drug Chemistry
As said earlier, drug companies generate massive amounts of information. Drug discovery, analytics, testing, and processing all strain even today’s best supercomputers. In response, pharmaceutical companies are hoping quantum computing is the breakthrough they’ll need to deal with this bottleneck.
Quantum computers are being eyed to assist in two distinct – but – related ways.
Today’s supercomputers can take months to years to perform the necessary calculations of all the molecular interactions of a drug like aspirin. Quantum computers, on the other hand, would take seconds. This would drastically decrease both time and money spent in finding new drug molecules for commercial products.
The second is how those drugs interact with the human body. Quantum computers
could potentially calculate all the possible effects of a new drug on the human body. They do so using in silico models (virtual humans) housed within their algorithms. This could reduce or even eliminate human trials forever.