A model of a human kidney.
Science's dream of creating perfect custom organs on demand as soon as a patient needs one is still a long way off. But tiny versions are already serving as useful research tools and stepping stones toward full-fledged replacements.
Although organoids cannot yet replace kidneys, they are invaluable tools for research.
The Lowdown
Australian researchers have grown hundreds of mini human kidneys in the past few years. Known as organoids, they function much like their full-grown counterparts, minus a few features due to a lack of blood supply.
Cultivated in a petri dish, these kidneys are still a shadow of their human counterparts. They grow no larger than one-sixth of an inch in diameter; fully developed organs are up to five inches in length. They contain no more than a few dozen nephrons, the kidney's individual blood-filtering unit, whereas a fully-grown kidney has about 1 million nephrons. And the dish variety live for just a few weeks.
An organoid kidney created by the Murdoch Children's Institute in Melbourne, Australia.
Photo Credit: Shahnaz Khan.
But Melissa Little, head of the kidney research laboratory at the Murdoch Children's Institute in Melbourne, says these organoids are invaluable tools for research. Although renal failure is rare in children, more than half of those who suffer from such a disorder inherited it.
The mini kidneys enable scientists to better understand the progression of such disorders because they can be grown with a patient's specific genetic condition.
Mature stem cells can be extracted from a patient's blood sample and then reprogrammed to become like embryonic cells, able to turn into any type of cell in the body. It's akin to walking back the clock so that the cells regain unlimited potential for development. (The Japanese scientist who pioneered this technique was awarded the Nobel Prize in 2012.) These "induced pluripotent stem cells" can then be chemically coaxed to grow into mini kidneys that have the patient's genetic disorder.
"The (genetic) defects are quite clear in the organoids, and they can be monitored in the dish," Little says. To date, her research team has created organoids from 20 different stem cell lines.
Medication regimens can also be tested on the organoids, allowing specific tailoring for each patient. For now, such testing remains restricted to mice, but Little says it eventually will be done on human organoids so that the results can more accurately reflect how a given patient will respond to particular drugs.
Next Steps
Although these organoids cannot yet replace kidneys, Little says they may plug a huge gap in renal care by assisting in developing new treatments for chronic conditions. Currently, most patients with a serious kidney disorder see their options narrow to dialysis or organ transplantation. The former not only requires multiple sessions a week, but takes a huge toll on patient health.
Ten percent of older patients on dialysis die every year in the U.S. Aside from the physical trauma of organ transplantation, finding a suitable donor outside of a family member can be difficult.
"This is just another great example of the potential of pluripotent stem cells."
Meanwhile, the ongoing creation of organoids is supplying Little and her colleagues with enough information to create larger and more functional organs in the future. According to Little, researchers in the Netherlands, for example, have found that implanting organoids in mice leads to the creation of vascular growth, a potential pathway toward creating bigger and better kidneys.
And while Little acknowledges that creating a fully-formed custom organ is the ultimate goal, the mini organs are an important bridge step.
"This is just another great example of the potential of pluripotent stem cells, and I am just passionate to see it do some good."
AI was integral to creating Moderna's mRNA vaccine against COVID.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
