In 2018, I made the difficult decision to disclose to my 10- and 12-year-old children that I had metastatic male breast cancer, and the prognosis was grim – I was expected to live only 32 to 42 months. As a man with a rare form of cancer, there were no clinical trials available for me. However, my oncologist, Saundra Buys from the University of Utah, gave me a crucial piece of advice – to focus on utilizing existing medicines in better ways.
This advice led me to collaborate with a group of innovative scientists – Bob Gatenby, Joel Brown, Sandy Anderson, Dawn Lemanne, and Carlo Maley – to adapt agricultural principles used to combat pests to my cancer care. This unconventional approach has kept me alive for over six years, with the disease growing in me, but not in the typical way you would expect.
Metastatic cancer remains a nearly universally fatal diagnosis due to the phenomenon of evolution. Cancer cells evolve resistance to treatments, rendering them ineffective over time. This is similar to how pests become resistant to pesticides on farms. Farmers have developed strategies such as rotating pesticides and minimizing usage to combat this issue. My colleagues applied these concepts to mathematical models of cancer, creating algorithms that help determine the best timing, order, and dosage of drugs to prevent resistance from developing.
By using these algorithms, we avoid the pitfalls of traditional oncology where treatments inadvertently reward resistant cancer cells. My personal management plan involves rotating 15 drugs from different classes, minimizing drug use, and constantly monitoring the disease to adjust treatment as needed. While this approach has extended my life beyond the initial prognosis, it requires proper testing in a clinical trial, which comes with significant costs.
To incentivize clinical trials for innovative cancer treatments, the biomedical field could adopt strategies from the tech industry, such as profiting from proprietary data and algorithms rather than drug patents. The FDA would need to adapt its framework to accommodate AI technologies that can autonomously interact with patients and providers, optimizing personalized care.
Unfortunately, recent FDA layoffs and grant cuts have hindered progress in this area at a time when we have the potential to transform lethal cancers into manageable diseases using existing medicines. Developing “algorithms-as-drugs” technologies offers a revolutionary approach to cancer care, but further support is needed to bring these solutions to more patients.
As one in five people will develop cancer in their lifetime, it’s crucial to embrace new approaches that offer more cost-effective and life-extending treatments. I am dedicated to supporting the advancement of these technologies through startup companies and outreach efforts, with the goal of helping more patients benefit from these innovative solutions.
Christopher Gregg, Ph.D., a professor at the University of Utah, leads efforts to share knowledge in the field of cancer care and has financial interests in several healthcare technology companies. He encourages a shift towards new approaches in cancer treatment to improve outcomes for patients.