A company is looking to improve medicines by making them in the nearly weightless environment of space.
Microgravity research could potentially lead to many more discoveries like this one, or even the development of brand-new drugs, but ISS astronauts only have so much time for commercial experiments.
“There are many high-performance products that are only possible to make in zero-gravity, which is a manufacturing capability that cannot be replicated in any factory on Earth.”-- Will Bruey.
The only options for accessing microgravity (or free fall) outside of orbit, meanwhile, are parabolic airplane flights and drop towers, and those are only useful for experiments that require less than a minute in microgravity — Merck’s ISS experiment took 18 days.
The idea: In 2021, California startup Varda Space Industries announced its intention to build the world’s first space factory, to manufacture not only pharmaceuticals but other products that could benefit from being made in microgravity, such as semiconductors and fiber optic cables.
This factory would consist of a commercial satellite platform attached to two Varda-made modules. One module would contain equipment capable of autonomously manufacturing a product. The other would be a reentry capsule to bring the finished goods back to Earth.
“There are many high-performance products that are only possible to make in zero-gravity, which is a manufacturing capability that cannot be replicated in any factory on Earth,” said CEO Will Bruey, who’d previously developed and flown spacecraft for SpaceX.
“We have a team stacked with aerospace talent in the prime of their careers, focused on getting working hardware to orbit as quickly as possible,” he continued.
“[Pharmaceuticals] are the most valuable chemicals per unit mass. And they also have a large market on Earth.” -- Will Bruey, CEO of Varda Space.
What’s new? At the time, Varda said it planned to launch its first space factory in 2023, and, in what feels like a first for a space startup, it has actually hit that ambitious launch schedule.
“We have ACQUISITION OF SIGNAL,” the startup tweeted soon after the Falcon 9 launch on June 12. “The world’s first space factory’s solar panels have found the sun and it’s beginning to de-tumble.”
During the satellite’s first week in space, Varda will focus on testing its systems to make sure everything works as hoped. The second week will be dedicated to heating and cooling the old HIV-AIDS drug ritonavir repeatedly to study how its particles crystalize in microgravity.
After about a month in space, Varda will attempt to bring its first space factory back to Earth, sending it through the atmosphere at hypersonic speeds and then using a parachute system to safely land at the Department of Defense’s Utah Test and Training Range.
Looking ahead: Ultimately, Varda’s space factories could end up serving dual purposes as manufacturing facilities and hypersonic testbeds — the Air Force has already awarded the startup a contract to use its next reentry capsule to test hardware for hypersonic missiles.
But as for manufacturing other types of goods, Varda plans to stick with drugs for now.
“[Pharmaceuticals] are the most valuable chemicals per unit mass,” Bruey told CNN. “And they also have a large market on Earth.”
“You’re not going to see Varda do anything other than pharmaceuticals for the next minimum of six, seven years,” added Delian Asparouhov, Varda’s co-founder and president.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.