Just a few years ago, there weren’t many people outside of a science lab who stopped to ponder the potential positive aspects of Artificial Intelligence (AI). At least not out loud. Most of the talk of AI, at least publicly, was about the potential harms, of which there are indeed a few.
But that has changed fast. The cancer universe is now all a-buzz and listening closely. Cancer scientists, especially, are now embracing AI. And for good reason. As we speak, there is one company that is the clear leader in this new science of using AI technology to solve cancer’s most critical issues for the good of cancer patients.
That company is Paige, the New York-based AI concern. I’ve become enamored and borderline-obsessed with this company, whose technologies are giving us all a peak into the future of cancer diagnostics and treatment.
The company has already shown us a good portion of what the future of cancer will look like. But they just keep topping themselves. And the latest news is especially hopeful.
OmniScreen Has Arrived
Paige has just rolled out OmniScreen, a pioneering new AI-driven biomarker module that can evaluate more than 505 genes and identify 1,228 molecular biomarkers from standard pathology slides. What does this mean for cancer patients? Potentially everything.
Cancer diagnosis is all about getting the very latest and most accurate information about each cancer landscape and then finding the best treatment.
OmniScreen is able to analyze digital images of cancer tissue slides that are stained using hematoxylin and eosin (H&E). In cancer’s complicated system, gene mutations are a key element in deciding what type of cancer a patient has and what treatments will be most effective.
By deploying Paige’s unprecedented three million slides, this represents an enormous step forward in the accuracy, speed, and cost-effectiveness of cancer diagnosis and treatment selection. It’s a gargantuan step forward for the cancer science community. It simply supplies so much more relevant information.
Microsoft and Memorial Sloan Kettering on Board
Smartly, Microsoft and Sloan Kettering are also a part of the Paige story, and that tells me that virtually the whole world is now watching. But of course they are. At some point in your life, you will be touched by cancer. A friend. A relative. Or yourself. It is of course another coup and shows that there is no question which cancer-focused AI company is leading the pack.
Paige is all about finding the smartest way to treat patients.
“This is good for patients if you have the wrong cancer drug, if the treatment is not as effective,” Razik Yousfi, Paige’s CEO and chief technology officer, told Breaking Cancer News.
He added that this fast, state-of-the-art technology will also likely bring the cost down, something that patients will appreciate. When you screen patients using Omniscreen, it can quickly identify which patients are negative for certain mutations and use these to select patients for more complex, expensive testing.
Cheaper and Better
In research, Omniscreen gives cancer researchers a convenient, fast and cheaper approach to studying cancer and building better and more effective markers to improve cancer care. And while it sounds very high-tech, it works rather simply and can and will save and extend lives.
Unlike traditional methods that require separate models for each biomarker or cancer type, Paige OmniScreen employs a single AI module capable of predicting a broad spectrum of clinically relevant molecular biomarkers across multiple cancer types.
By replicating a targeted biomarker gene panel of 505 genes, it can simultaneously predict 1,228 biomarkers in the 15 most common cancers, including actionable targets such as BRAF, EGFR, KRAS, MET and FGFR3.
Additionally, it links phenotypes with genetic patterns, simplifying the diagnosis of conditions defined by specific genetic markers. This capability unlocks deeper, more comprehensive insights into cancer biology and paves the way for new treatment strategies.
This technology accelerates drug development by identifying new potential indications through pan-tumor screening for targeted genetic mutations and enhances patient selection for clinical trials.
By pre-screening patients before costly molecular tests, Paige OmniScreen offers substantial cost savings for clinical trials and laboratories, ultimately making personalized therapies more accessible and affordable for a broader range of patients.
An Enormous Advancement in Personalized Medicine
“The development of our digital biomarker panel represents a significant advancement in personalized medicine, addressing many of the challenges associated with traditional molecular biomarker tests,” said Yousfi in a press statement.
“Our innovative approach minimizes the need for extensive tissue samples, making it particularly useful in cases where biopsy tissue is limited. This first of its kind AI-module offers detailed insights into cancer biology and potential treatment avenues by predicting the activity of canonical signaling pathways, DNA repair mechanisms, and genomic instability measures.”
Canonical signaling pathways are established pathways with common or standard features. For example, in gene regulation, canonical refers to the most common mechanism of gene expression regulation.
Dr. David Klimstra, Founding Medical Officer of Paige, said in a press statement, “Such comprehensive analysis is crucial in identifying genetic alterations and holds immense potential for guiding therapy selection, improving treatment efficacy, and accelerating patient screening for clinical trials.”
He added, “By enabling the quick identification of cases that warrant further genomic testing, we’re enhancing clinical decision-making, reducing turnaround times, and lowering testing costs—all while ensuring the highest standards of patient care. This is a game-changer in the pursuit of better cancer treatments and improved patient outcomes.”
Meanwhile, scientists at the Faculty of Medicine and the University Hospital of Cologne, led by Privatdozent Dr. Yuri Tolkach and Professor Dr. Reinhard Büttner, have developed a platform that opens up new diagnostic possibilities.
They wrote in a press release that using artificial intelligence (AI) methods, the platform enables fully automated and precise analysis of tissue sections from patients with lung cancer.
The platform is based on the now common digitization of existing histological data.
