Artificial intelligence (AI) has been touted as being the next biggest technology. That isn’t entirely an over-exaggeration. The technology will help pave the way for a lot of different industries. AI gets thrown around a lot when talking about health care and all the wonderful things it can accomplish. Sometimes it’s a lot of empty promises because it’s still a technology that people are learning to understand and how to utilize.
First, let me define AI. Oxford Reference defines AI as:
The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
It makes sense that AI would be helpful in advancing medicine, treatments, and providing patients with the best alternative. This is why AI in health care is soaring and is expected to rise from $1.3 billion in 2019 to $10 billion by 2024. That’s a huge surge in five short years. AI is opening more and more doors every day in health care. Researchers and developers are learning new ways to incorporate the technology into their work to better improve results in their studies.
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According to Bloomberg, machine learning has the potential to make the drug-development process faster and remove some of the trial and error that is involved with developing drug candidates. There are some drugs that have relied on early-stage AI tools in their human trials to help discover the best candidates for advanced trials.
First Human Drug Developed by AI
Billions of dollars and countless hours get spent on developing new drugs, and the majority of those drugs fail before they even reach human trials. That’s why in recent years researchers and developers have decided to start exploring other ways to use artificial intelligence to discover new drug candidates. And now, we’re starting to see the success of using AI.
This AI is called Smart Algorithms for Medical Discovery (SAM) and is the work of researchers at Australia’s Flinders University. The team of researchers was able to teach it to create the vaccine by feeding SAM information on chemical compounds that were known to activate the human immune system as well as compounds that would have no effect on the immune system.
They then began developing a computer program that would generate trillions of chemical compounds and allow SAM to decide which of those compounds would be promising for drug candidates. The team synthesized some of SAM’s top candidates and tested them on human blood cells in a lab — and one of those candidates was a flu vaccine “turbocharger,” which was later shown to be incredibly effective in animals.
The clinical trials of this new vaccine in human patients have begun across the U.S. If all goes well, people will be inflicted by fewer types of flu, ultimately showing that AI-developed drugs have a great chance of being effective. And we could very well start to see more AI-developed drugs in the future.
A company called Recursion has become part of a wave of new drug discovery startups, combining biology and bioinformatics with artificial intelligence to identify promising drug candidates. Recursion uses its technology in drug repurposing. It does this by scanning existing molecules. The company has expanded into the discovery of novel compounds for rare diseases and beyond.
Recursion recently raised $121 million in a Series C financing, which will support the company’s machine learning-enabled drug discovery platform. The company announced that it plans to prioritize rare disease candidates in its pipeline while also looking for deals to sign with other companies across therapeutic areas, including immuno-oncology, oncology, aging, and inflammation.
AI is creating amazing possibilities for new drug candidates that will alter our lives as humans. I have a feeling we’re going to hear more success stories like those of Australia’s Flinders University and Recursions.
Until next time,
Pro Trader Today