Breast Cancer Screening in the Future with a Simple Blood Test?
Tübingen-based startup aims to detect breast cancer earlier
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Physicist Marc Mausch founded the company Earlytrace in Tübingen. He is pursuing a completely new approach to the early detection of breast cancer: As a complement to mammography, breast ultrasound, and biopsy, he aims to use artificial intelligence to identify parameters that, based on a simple blood sample, will one day enable the detection of tumors. Marc Mausch’s story is one of many successful startup stories in the STERN BioRegion.
Marc Mausch, Chief Executive Officer
Copyright: Universitätsklinikum Tübingen
Breast cancer is the most common type of cancer among women. According to the Robert Koch Institute (RKI), more than 70,000 women are diagnosed with it every year in Germany alone. The sooner this malignant disease is detected and treated, the greater the chances of recovery. To optimize treatment outcomes, screening tests are designed to detect tumors as early as possible. Among the best-known cancer screening methods, in addition to physical examination, are breast ultrasound and, above all, mammography, in which the breasts are X-rayed. Marc Mausch, a physicist from Tübingen, is now pursuing an old idea with a new approach through his company Earlytrace: A simple blood test should be sufficient to detect the disease even earlier than was previously possible.
The Idea – How Did the Company Get Started?
It may not have been written in the stars, but it was fate that led Marc Mausch to attend a lecture at the University of Tübingen in January 2024. “The lecture was about the idea that biological data in the blood can indicate whether a person will develop a disease in the near future—such as cancer,” explains Mausch. For him, having spent his entire career to date working with data analysis in the broadest sense, it was the spark that ignited a business idea. The physicist works in the “Methods in Medical Informatics” department at the University of Tübingen’s Medical Faculty. “I was working on data analysis related to topics such as Long COVID, but also cancer. This involved not only research but also infrastructure, data quality, and data hosting—in other words, all the IT-related issues that go along with it,” says Mausch.
Yet Marc Mausch is by no means a “nerd” who knows nothing but his computer screen and numbers. He had already successfully founded a company before: www.arztkonsultation.de was the first digital service provider for virtual consultations in 2013 and remains successful on the market today. However, Mausch left the company after a few years because he was certain that the intersection of IT and medicine would present further exciting challenges for him: “I went into research to identify innovative topics in this field—but always with the intention of turning new ideas into commercially viable solutions.” And there it was, the idea: to develop an alternative or supplement to existing breast cancer screening methods. With this, Marc Mausch also won over the jury at the 2024 AI Incubator hosted by Cyber Valley in the state of Baden-Württemberg: “Earlytrace” not only got its name there, but also won the audience award. “That program marked the beginning of the Earlytrace story,” says Mausch. “We put together a team and began to systematically analyze all the data available to us.”
The “Need” – Who Benefits from the Idea?
Earlytrace aims to provide women with a pain-free, side-effect-free breast cancer screening—as a supplement or alternative to already proven methods: As is well known, mammography screening has been in place in Germany for over 20 years, recommending that women between the ages of 50 and 75 undergo a breast X-ray every two years. Studies show that the benefits of the screening significantly outweigh the associated radiation risk. According to the RKI, the relative 5-year survival rate for breast cancer is currently over 80 percent; this means that out of 100 women with breast cancer, more than 80 are still alive after five years. Regardless of the radiation exposure, however, mammography is an uncomfortable procedure for many women because the breast tissue is compressed to allow for a clearer image. “A simple blood test that already provides reliable indications of possible breast cancer can be a real alternative and a great relief,” explains Mausch—and emphasizes that Earlytrace does not make the diagnosis. “We provide clues—patterns—to the doctors, who then have to evaluate them: Women with this blood profile often also have breast cancer. Everything else is up to the doctor to decide.” The doctor would then, for example, recommend a mammogram or a biopsy.
In the somewhat more distant future, Mausch would even like to be able to predict that a patient is highly likely to develop breast cancer—in other words, to predict the disease before a tumor is even present. Even now, the Earlytrace method is designed to provide information at a very early stage—that is, long before a tumor can be felt—about whether breast cancer might develop. Unlike mammography, the blood test cannot identify exactly where in the breast the tumor is located. Mausch therefore sees his solution as a complement to mammography or ultrasound—for example, for tests between mammography appointments.
The USP – What Is the Innovation?
“Earlytrace isn’t a single grand idea, but rather consists of many small building blocks—none of which is groundbreaking on its own, but which, taken together, can become a major innovation in diagnostics,” explains Mausch. One of these building blocks is the analysis of raw data from the blood sample using artificial intelligence. Another is the entire IT infrastructure for interpreting the data, which is intended for physicians who generally have no IT training themselves. The plan is for doctors to send their patients’ blood samples to their usual laboratories. These laboratories will deliver the processed data via a special interface—yet another building block of innovation—which the doctor can then access. A possible result might read, for example: “With a 97 percent probability, this patient’s blood test shows changes that could indicate the presence of breast cancer.” In this case, treatment at a very early stage would significantly improve the probability of survival.
What sounds so obvious and straightforward is, in reality, the result of extensive research. “An elevated cholesterol level can be detected immediately in a blood test, but with complex diseases like cancer, it’s not that simple,” says Mausch. “There isn’t just one value, but many that influence one another. Here’s an example: Value A is dangerous, but only in the range between 60 and 80, and only if Value B is below 10 percent. But if Value B is above 30 percent, and at the same time C is below 10, then A suddenly becomes dangerous if it’s above 120. So it’s very complex.” To enable doctors to interpret such massive data sets comprising hundreds of parameters, Earlytrace uses AI to create simple new parameters—another building block of innovation—that are then easier to interpret in terms of breast cancer probability. “There are countless biomarkers, and nature thus provides us with veiled information that we cannot initially decipher. But we can interpret it if we can break it down into two or three dimensions. And then we can understand it.”
“Milestones” – What’s Next?
Currently, the Earlytrace team is still in the midst of analyzing the data: “We’ve identified various data points that show great promise. Once we’re satisfied with the metrics, we’ll publish a scientific paper,” announces Marc Mausch. For him, founding the company is—for now—his second main focus. His first is at the university, where he pursues his research, which naturally also revolves around data analysis in the medical field. Following the planned publication, Mausch will focus more intensively on building the IT infrastructure and the interfaces between clinical practice and the lab.
Earlytrace, which currently has two employees, is still financed by private funds. “After winning the People’s Choice Award at Cyber Valley’s AI Incubator 2024, there were definitely interested parties who wanted to participate in further financing,” reports Mausch. “But until we’ve checked off our scientific publication, we won’t be able to make any time-related commitments. And that naturally deters potential investors.” He admits that he was initially more enthusiastic about data analysis: “In Germany, it’s difficult to obtain the data needed for medical research. I come from a physics background; I used to study stars and pulsars, where the data was always open and accessible to everyone.” He is certain, however, that he will find the connections he needs in the BioRegion STERN to reach for the stars once again.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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