David and Jen on their wedding day, and Jen undergoing treatment for her rare sarcoma.
It was 15 years ago this month, but I'll never forget those words. When my wife Jen and I asked her oncologist about our plans to start a family, he calmly replied, "Well, I wouldn't do so unless Dave is prepared to be a single father."
About 50 percent of all people with cancer have a rare type, like the one Jen was fighting.
Time stood still. The danger crystalized — we were in a battle for my beautiful bride's life, and the odds were not in our favor.
We felt every emotion expected. Anger, sadness, confusion, frustration, and especially fear. But we made a very intentional choice to take that fear, put it to the side, and do everything we could to live our lives together to the fullest.
We focused first on Jen's health and learned everything we could about MFH Sarcoma. I was with her every step of the way — for hundreds of medical appointments, six intense surgeries, and twenty different types of chemotherapy. During such a challenging time, our choice to reject fear allowed us to live our best lives. Our careers blossomed, we enjoyed several international vacations, and Jen inspired thousands of fellow patients through her blog and speeches.
When we researched treatment options we learned that Jen was not alone. About 50 percent of all people with cancer have a rare type, like the one Jen was fighting. However, rare cancers don't get the funding they desperately need so effective treatment options are hard to find. The lack of funding felt unfair — and urgent. We didn't worry about everything that can go wrong when starting a new venture. Instead, we jumped in head first and convinced a small group of friends and family to ride stationary bikes with us to raise money for rare cancer research.
Jen Goodman Linn, riding a stationary bike for Cycle for Survival.
(Courtesy David Linn)
From those humble beginnings, Cycle for Survival grew steadily. After starting from scratch, Jen and I ran Cycle for Survival on our own for two years. We quickly realized that if we wanted to help as many people as possible, we needed the best partners. In 2009, we agreed that Memorial Sloan Kettering Cancer Center would take over the ownership of Cycle for Survival and Equinox officially became the Founding Partner. Flash forward to today, and Cycle for Survival has raised more than $220 million! I'm proud that 100% of every donation, yes every penny, goes directly into life-saving rare cancer research within six months of the annual indoor cycling events, which now take place in 17 cities nationwide.
While Cycle for Survival's trajectory was heading straight up, Jen's health struggle was devastatingly swinging up and down. With her incredible spirit and tenacity, Jen would beat the cancer through chemo and surgery, but then it would frustratingly come back again and again. After going into remission six times, it returned with such a vengeance in 2011 that even the world's leading doctors were forced to say, "I'm sorry, there's nothing more we can do."
Those were the most difficult words I've ever heard, by far. I hope no other family has to hear these crushing words.
When Jen died soon after, I didn't know what would happen to me, to my life, and to Cycle for Survival. I do remember making two very important choices at the time. First, I chose to get out of bed and put one foot in front of the other. It wasn't easy. Tears, pain, and grief would hit at any hour of the day or night. I did have a great support network of family and friends who kept me moving forward. One friend in particular changed the route of her morning runs so that I would join her and start getting back to exercising.
My second key choice was to stay involved with Cycle for Survival. At times, it was an excruciatingly difficult decision because I felt the depth of my loss each and every time I stepped into one of the events. However, it was also rewarding and energizing because I could see firsthand how many people it was helping, even though it was too late for Jen.
I began to travel across the country with the Cycle for Survival staff. My hope was to spread the word about rare cancers; along the way I met a lot of wonderful people who shared their stories with me. What I soon realized is that each of us faces obstacles in our lives. For me, it was losing the person who I wanted to spend my life with. For others, it might be challenges with their kids or in their professional lives. The common theme is that we don't have control over the fact that we have to face these challenges. But the biggest lesson I've learned is that we very much do have a choice in how we react.
I made the choice to do everything I can to help rare cancer patients and their families and it has been transformative and healing for me. The small group who rode in the first Cycle for Survival event has grown into a powerful movement of nearly 40,000 riders making a real difference. If Jen were diagnosed today, there are new treatments available– including genomic sequencing, targeted therapies, and immunotherapies – that could help her. Those weren't even options a short time ago. That's the result of funding research.
A recent Cycle for Survival event shows the passion and power of the community.
(Courtesy David Linn)
I also want to share one more choice I made. Remember that friend who changed the route of her morning runs so I could start exercising after Jen died? Well, over the years friendship grew into love, and we're now building a home together and can't wait to see what the future holds for us.
So with all that in mind I ask – when you face those inevitable challenges in your life, how will you choose to react? Remember that even in the midst of hopelessness, you can find choices. Those will be the decisions that define and guide you.
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.
