Paul Conyngham, a rising star in entrepreneurship, is expanding his company based on his experiences developing personalized treatments that integrate LLM medicines, analytics, established therapies, and private lab services. His mission is to help more people, similar to what he did for his dog, Rosie. Rosie’s story has gained significant attention, generating business and drawing interest from LLM companies. But, the question remains—does it all actually work?
The tale of Rosie, a dog whose owner crafted a custom mRNA vaccine using LLM technology, has sparked considerable discussion, and while it may continue to educate, it also divides opinions.
The medical field is often criticized for its corrupt practices.
Then there’s Sid Sijbrandij, the founder of GitHub and a billionaire who, after being diagnosed with osteosarcoma years ago, initially relied on standard treatments that failed to halt cancer’s advance. In response, he gathered an innovative medical team, employed AI extensively, and worked to maximize every diagnostic test available. He even open-sourced his medical records, showcasing a remarkable level of initiative.
This determination has led to advancements in treatment protocols, as Sijbrandij shares his journey on X and his website, where he reveals that his cancer is now in remission.
Here’s the uplifting part
Interestingly, both stories share similarities—they involve wealthy tech entrepreneurs battling cancer and they both hold promises of hope. Their timing is also noteworthy.
There are tough, perhaps uncomfortable, questions to confront regarding media realities. The baby boomer generation seems eager to protect their financial gains as they head into retirement. Just how genuine is the push for voluntary vaccinations, and the optimistic outlook that accompanies it?
At the close of 2024, Sijbrandij shifted from CEO of GitLab to Chairman of the Board, stating that he wishes to devote more time to his cancer treatment and health.
In a detailed essay on X, Conyngham explains how chatbots have assisted him in saving his dog and shares the extraordinary treatments he undertook. He openly admitted to dedicating over 100 hours each week to complex paperwork. Most people simply don’t have that kind of time. While he didn’t specify costs, it’s worth noting that many Americans struggle financially after meeting monthly expenses. In his essay, he notes what the chatbots didn’t do:
The chatbots did not collect samples or isolate and sequence DNA. They didn’t physically manufacture the vaccine or manage its distribution. We needed talented scientists, including Professor Paul Thorderson and Rachel from the UNSW mRNA Institute, who produced the vaccine, along with Mr. Aravena and Dr. Jose Granados from the University of Queensland, who managed it, and Professor Martin Smith, an expert in bioinformatics.
Of course, not everyone is convinced. Critics are emerging.
Time to evaluate the hype
Last week, Sam Altman spoke about how important it is not to leave credit, cash, or public goodwill on the table. He noted being impressed by a meeting with Conyngham, highlighting how he utilized ChatGPT and other LLMs to develop an mRNA vaccine protocol for Rosie. It seemed like an uplifting story at first.
However, as the initial excitement faded, a slew of critical responses surfaced against this seemingly frivolous admission.
Biomedical engineer Patrick Heiser commended Sijbrandij’s presentation for self-managing osteosarcoma, yet he estimated it cost “tens of millions.” In his view, personalized AI medicine is not quite a reality yet. As for Rosie’s case, he pointed to a notable absence of risk protocols and sufficient evidence regarding what treatments were effective.
Another doctor and entrepreneur, Egan Peltan, echoed concerns about Conyngham’s methods. He argued that there is no proof that Conyngham’s procedures, outside of FDA-approved alpha-PD-1 for dogs, impacted disease progression, suggesting a partial response to alpha-PD-1 is the most plausible explanation.
Previously, I interpreted this heartwarming story as a hopeful glimpse into what AI medicine might offer for decentralized and potentially more affordable medical treatments.
Yet, we must first overcome a deeply entrenched and often flawed system marred by medical errors that have become a leading cause of death. The pharmaceutical regulations appear to reinforce systemic issues within healthcare. Will we eventually see a tiered system where only the wealthy can benefit from advanced treatment options while the average citizen remains in the dark? It’s a glaring possibility, and the healthcare industry remains one of the most corrupt.
