Conner Curran, now 10 years old, can walk more than two miles after gene therapy treatment for his Duchenne's muscular dystrophy.
That the medical world is on the cusp of a successful treatment for a crippling and deadly disease is the culmination of more than 35 years of work by Dr. Jude Samulski, a professor of pharmacology at the University of North Carolina School of Medicine in Chapel Hill. More recently, he's become a leading gene therapy entrepreneur.
But Samulski likens this breakthrough to the frustrations of solving a Rubik's cube. "Just because one side is now all the color yellow does not mean that it is completely aligned," he says.
Although Conner's life and future have dramatically improved, he's not cured. The gene therapy tamed but did not extinguish his disorder: Conner is now suffering from the equivalent of Becker's muscular dystrophy, a milder form of the disease with symptoms that appear later in life and progress more slowly. Moreover, the loss of muscle cells Conner suffered prior to the treatment is permanent.
"It will take more time and more innovations," Samulski says of finding an even more effective gene therapy for muscular dystrophy.
Conner's family is still overjoyed with the results. "Jude's grit and determination gave Conner a chance at a new life, one that was not in his cards before gene therapy," says his mother Jessica Curran. She adds that "Conner is more confident than before and enjoys life, even though he has limitations, if compared to his brothers or peers."
Conner Curran holding a football post gene therapy treatment.
Courtesy of the Curran family
For now, the use of gene therapy as a treatment for diseases and disorders remains relatively isolated. On paper at least, progress appears glacially slow. In 2018, there were four FDA-approved gene therapies (excluding those reliant on bone marrow/stem cell transplants or implants). Today, there are 10. One therapy is solely for the cosmetic purpose of reducing facial lines and folds.
Nevertheless, experts in the space believe gene therapy is poised to expand dramatically.
"Certainly in the next three to five years you will see dozens of gene therapies and cell therapies be approved," says Dr. Pavan Cheruvu, who is CEO of Sio Gene Therapies in New York. The company is developing treatments for Parkinson's disease and Tay-Sachs, among other diseases.
Cheruvu's conclusion is supported by NEWDIGS, a think tank at the Massachusetts Institute of Technology that keeps tabs on gene therapy developments. NEWDIGS predicts there will be at least 60 gene therapies approved for use in the U.S. by the end of the decade. That number could be closer to 100 if Chinese researchers and biotech ventures decide the American market is a good fit for the therapies they develop.
"We are watching something of a conditional evolution, like a dot-com, or cellphones that were sizes of shoeboxes that have now matured to the size of wafers. Our space will follow along very similarly."
Dr. Carsten Brunn, a chemist by training and CEO of Selecta Biosciences outside of Boston, is developing ways to reduce the immune responses in patients who receive gene therapy. He observes that there are more than 300 therapies in development and thousands of clinical trials underway. "It's definitely an exciting time in the field," he says.
That's a far cry from the environment of little more than a decade ago. Research and investment in gene therapy had been brought low for years after the death of teenager Jesse Gelsinger in 1999 while he had been enrolled in a clinical trial to treat a liver disease. Gene therapy was a completely novel concept back then, and his death created existential questions about whether it was a proper pathway to pursue. Cheruvu, a cardiologist, calls the years after Gelsinger's death an "ice age" for gene therapy.
However, those dark years eventually yielded to a thaw. And while there have been some recent stumbles, they are considered part of the trial-and-error that has often accompanied medical research as opposed to an ominous "stop" sign.
The deaths of three patients last year receiving gene therapy for myotubular myopathy – a degenerative disease that causes severe muscle weakness – promptly ended the clinical trial in which they were enrolled. However, the incident caused few ripples beyond that. Researchers linked the deaths to dosage sizes that caused liver toxicity, as opposed to the gene therapy itself being an automatic death sentence; younger patients who received lower doses due to a less advanced disease state experienced improvements.
The gene sequencing and editing that helped create vaccines for COVID-19 in record time also bolstered the argument for more investment in research and development. Cheruvu notes that the field has usually been the domain of investors with significant expertise in the field; these days, more money is flowing in from generalists.
The Challenges Ahead
What will be the next step in gene therapy's evolution? Many of Samulski's earliest innovations came in the laboratory, for example. Then that led to him forming a company called AskBio in collaboration with the Muscular Dystrophy Association. AskBio sold its gene therapy to Pfizer five years ago to assure that enough could be manufactured for stage 3 clinical trials and eventually reach the market.
Cheruvu suggests that many future gene therapy innovations will be the result of what he calls "congruent innovation." That means publicly funded laboratories and privately funded companies might develop treatments separately or in collaboration. Or, university scientists may depend on private ventures to solve one of gene therapy's most vexing issues: producing enough finished material to test and treat on a large scale. "Manufacturing is a real bottleneck right now," Brunn says.
The alternative is referred to in the sector as the "valley of death": a lab has found a promising treatment, but is not far enough along in development to submit an investigational new drug application with the FDA. The promise withers away as a result. But the new abundance of venture capital for gene therapy has made this scenario less of an issue for private firms, some of which have received hundreds of millions of dollars in funding.
There are also numerous clinical challenges. Many gene therapies use what are known as adeno-associated virus vectors (AAVs) to deliver treatments. They are hollowed-out husks of viruses that can cause a variety of mostly mild maladies ranging from colds to pink eye. They are modified to deliver the genetic material used in the therapy. Most of these vectors trigger an antibody reaction that limits treatments to a single does or a handful of smaller ones. That can limit the potential progress for patients – an issue referred to as treatment "durability."
Although vectors from animals such as horses trigger far less of an antibody reaction in patients -- and there has been significant work done on using artificial vectors -- both are likely years away from being used on a large scale. "For the foreseeable future, AAV is the delivery system of choice," Brunn says.
Also, there will likely be demand for concurrent gene therapies that can lead to a complete cure – not only halting the progress of Duchenne's in kids like Conner Curran, but regenerating their lost muscle cells, perhaps through some form of stem cell therapy or another treatment that has yet to be devised.
Nevertheless, Samulski believes demand for imperfect treatments will be high – particularly with a disease such as muscular dystrophy, where many patients are mere months from spending the remainder of their lives in wheelchairs. But Samulski believes those therapies will also inevitably evolve into something far more effective.
"We are watching something of a conditional evolution, like a dot-com, or cellphones that were sizes of shoeboxes that have now matured to the size of wafers," he says. "Our space will follow along very similarly."
Jessica Curran will remain forever grateful for what her son has received: "Jude gave us new hope. He gave us something that is priceless – a chance to watch Conner grow up and live out his own dreams."
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.
