NPR reports that the shamed Theranos founder/CEO is providing advice to Evans, but the startup denies that claim
Prison bars can’t block Elizabeth Holmes from finding her way back into the news spotlight. The disgraced founder and former CEO of Theranos is reportedly advising her partner Billy Evans on his new artificial intelligence (AI) diagnostic startup company, named Haemanthus after the blood lily.
According to sources who spoke with NPR, Evans’ new company Haemanthus, Inc. is developing a blood testing device and has patented a process that uses Raman spectroscopy, which, according to NPR, “has been shown to help diagnose ALS, also called Lou Gehrig’s disease, as well as some forms of cancer. It has also been used to discover improvised explosive devices on battlefields.”
Evans has already raised millions of dollars for the fledgling startup, NPR reported, adding that a source claimed finances for the company have come from “mostly friends, family, and other supporters so far.”
According to Newsweek, Evans’ goal is to raise $50 million toward the development of a “medical testing product.”
The company will “do medical tests using bodily fluids,” Newsweek reported, adding, “An image of the alleged device published by The New York Times is eerily similar to Theranos’ ‘Edison’ testing machine.”
Elizabeth Holmes is currently housed in a federal facility in Bryan, Texas. Sources told NPR that she has been “providing advice” to Billy Evans, her partner, on his new AI/medical testing company Haemanthus, which denied those claims stating on X that Holmes “has no role, now or future.” (Photo copyright: Wikimedia Commons.)
Haemanthus Denies Holmes’ Involvement
Holmes has reportedly been providing insight to Evans throughout her prison term, though her role with his budding company is unclear, NPR noted.
As previously reported by Dark Daily, Holmes is “barred from receiving payments from federal health programs for services or products, which significantly restricts her ability to work in the healthcare sector.”
Haemanthus denied Holmes’ involvement with the company, claiming that she “has no formal role” and that “Haemanthus is not Theranos 2.0,” Fortune reported.
Previous lengthy posts by Haemanthus on social media platform X fully denied any involvement with Holmes but have since been deleted. The company now uses their platform to curtly retort the significance of Holmes’ involvement, leaning on their advancements and high standards. “Skepticism is rational. We must clear a higher bar,” they said. “When The NY Times contacted us, we invited them to see our lab, tech, and team. They declined. The headline was already written. Our reality inconvenient.”
Further posts on X showcase Haemanthus’ desire to have the same groundbreaking prowess Holmes clung to throughout her Theranos venture. The company claims to have developed “the world’s first AI-native sensors for health,” adding, “Our technology captures thousands of biomarkers simultaneously.”
And the Holmes Saga Continues
Haemanthus is comprised of about a dozen people, including individuals who “worked with Evans at Luminar Technologies, which develops sensor technology for autonomous vehicles, according to the company’s patent and Delaware incorporation paperwork,” NPR reported.
Holmes is currently serving an 11-year federal prison sentence for her role in fraud involving Silicon Valley startup Theranos, which boasted clinical laboratory blood-test breakthroughs that turned out to be riddled with faulty equipment and fraudulent results.
Though whistleblowers brought Holmes scheme to the light, she has never admitted wrongdoing for her actions and continues to claim her innocence. In May, the Ninth Circuit of Appeals denied her request for a rehearing of her case.
Study findings could lead to new clinical laboratory diagnostics that give pathologists a more detailed understanding about certain types of cancer
New studies proving artificial intelligence (AI) can be used effectively in clinical laboratory diagnostics and personalized healthcare continue to emerge. Scientists in the UK recently trained an AI model using machine learning and deep learning to enable earlier, more accurate detection of 13 different types of cancer.
DNA stores genetic information in sequences of four nucleotide bases: A (adenine), T (thymine), G (guanine) and C (cytosine). These bases can be modified through DNA methylation. There are millions of DNA methylation markers in every single cell, and they change in the early stages of cancer development.
One common characteristic of many cancers is an epigenetic phenomenon called aberrant DNA methylation. Modifications in DNA can influence gene expression and are observable in cancer cells. A methylation profile can differentiate tumor types and subtypes and changes in the process often come before malignancy appears. This renders methylation very useful in catching cancers while in the early stages.
However, deciphering slight changes in methylation patterns can be extremely difficult. According to the scientists, “identifying the specific DNA methylation signatures indicative of different cancer types is akin to searching for a needle in a haystack.”
Nevertheless, the researchers believe identifying these changes could become a useful biomarker for early detection of cancers, which is why they built their AI models.
“Computational methods such as this model, through better training on more varied data and rigorous testing in the clinic, will eventually provide AI models that can help doctors with early detection and screening of cancers,” said Shamith Samarajiwa, PhD (above), Senior Lecturer and Group Leader, Computational Biology and Genomic Data Science, Imperial College London, in a news release. “This will provide better patient outcomes.” With additional research, clinical laboratories and pathologists may soon have new cancer diagnostics based on these AI models. (Photo copyright: University of Cambridge.)
The researchers then used a combination of machine learning and deep learning techniques to train an AI algorithm to examine DNA methylation patterns of the collected data. The algorithm identified and differentiated specific cancer types, including breast, liver, lung and prostate, from non-cancerous tissue with a 98.2% accuracy rate. The team evaluated their AI model by comparing the results to independent research.
In their Biology Methods and Protocols paper, the authors noted that their model does require further training and testing and stressed that “the important aspect of this study was the use of an explainable and interpretable core AI model.” They also claim their model could help medical professionals understand “the underlying mechanisms that contribute to the development of cancer.”
Using AI to Lower Cancer Rates Worldwide
According to the Centers for Disease Control and Prevention (CDC), cancer ranks as the second leading cause of death in the United States with 608,371 deaths reported in 2022. The leading cause of death in the US is heart disease with 702,880 deaths reported in the same year.
Globally cancer diagnoses and death rates are even more alarming. World Health Organization (WHO) data shows an estimated 20 million new cancer cases worldwide in 2022, with 9.7 million persons perishing from various cancers that year.
The UK researchers are hopeful their new AI model will help lower those numbers. They state in their paper that “most cancers are treatable and curable if detected early enough.”
More research and studies are needed to confirm the results of this study, but it appears to be a very promising line of exploration and development of using AI to detect, identify, and diagnose cancer earlier. This type of probing could provide pathologists with improved tools for determining the presence of cancer and lead to better patient outcomes.
