Alzheimer’s disease (AD) diagnostics are entering a transformative phase, marked by the rise of blood-based biomarkers and artificial intelligence (AI). While disease detection often occurs after symptoms emerge, new technologies provide hope for early and precise diagnosis. Companies such as Danaher Diagnostics are leading this shift, working alongside academic and pharmaceutical partners to bring scalable, non-invasive tools to the clinic.
Nicole Selenko-Gebauer, MD Group Vice President and Chief Innovation Officer, Diagnostics Danaher Diagnostics
In this Innovation Spotlight, Nicole Selenko-Gebauer, the Diagnostics group vice president and chief innovation officer at Danaher Diagnostics, highlights the on-going collaborative efforts aimed at improving AD therapeutic outcomes by making timely intervention possible.
How is AD currently detected?
Patients with AD are most often identified after they have begun to show symptoms. Testing may begin with a cognitive assessment to evaluate memory, thinking, and problem-solving abilities. More advanced diagnostic approaches may include cerebrospinal fluid biomarker analysis or neuroimaging such as positron emission tomography.
Today, we are in an exciting new chapter with the development of blood tests for AD. These tests are designed to be minimally invasive and scalable, offering potential use in both research settings and, in the future, clinical care environments. At Danaher Diagnostics, we’re encouraged by the progress being made in this area, including at one of our operating companies, Beckman Coulter Diagnostics. This company is in a leading position in the development of highly sensitive instruments capable of testing for AD biomarkers and immunoassays targeting proteins known to be involved in the pathobiology of AD. Launched in 2023, Beckman Coulter’s DxI 9000 Analyzer has been adopted by researchers globally for its precision and reliability. The instrument’s menu of research use only (RUO) assays continues to grow and on September 10, 2025 Beckman Coulter announced the launch of the industry’s first high-throughput, fully automated BD-Tau RUO immunoassay test, marking a major milestone in blood-based biomarker innovation.
How is AD treated, and how might diagnostics data be used to improve therapeutic decision-making?
Once patients are diagnosed, several treatment options exist, including cholinesterase inhibitors such as donepezil, rivastigmine, and galantamine that aim to improve memory and thinking skills, glutamine regulators intended to reduce damage to nerve cells, and disease-modifying therapies that target amyloid or tau pathology in the brain, which are believed to contribute to AD.
As with other forms of dementia, AD is complex, and patients often exhibit multiple co-morbidities which can make diagnosis and treatment decisions challenging. Further, individual patients experience AD differently and may move along the continuum of disease progression faster or slower based on their own unique biological profile. We know today that clinical symptoms do not always correlate directly with imaging findings and biomarker levels, indicating that a breadth of information tailored to individual patients will be needed to guide care and treatment. As the science advances, so will our ability to diagnose AD definitively, using clinically validated biomarkers that clearly indicate the stage of disease progression, patient response to therapy, and other critical insights. We will need to integrate a mosaic of different biomarker targets and outcomes into care guidance.
How would earlier AD diagnosis help patients?
Although there is not yet a cure for AD, available therapeutics are known to have the most benefit and better tolerability when applied early in the disease. Novel disease-modifying anti-amyloid therapies have been shown to slow down disease progression. Thus, it is critical to be able to detect AD before clinical symptoms become too severe. Novel treatment experiments even use therapies in patients who show AD signs in imaging or blood biomarkers before they experience cognitive decline. These “hit hard and early” treatment strategies are established in other diseases such as chronic inflammation and multiple sclerosis, and thus are aimed at delaying the onset of clinical symptoms in AD.
What does an ideal AD diagnostic look like?
An ideal AD diagnostic is non-invasive, affordable, and accessible to patients in the locations where they typically receive healthcare. Because AD is complex, we know that the ideal diagnostic solution is unlikely to focus on one molecule, one biomarker, or one imaging result, but will instead be multimodal.
What are the current areas of innovation, and how are collaborations between academia and industry moving AD diagnostics forward?
I often say that in science, we don’t win alone, we win as a team by connecting the dots. At Danaher, our partnerships with academia and pharma are crucial to our mission. Although Danaher is large and we have fantastic scientists on our team, we must collaborate to connect early innovation to downstream therapies and treatment. We are partnering with academic leaders to define the core research questions we are invested in. We are also building a community of pharma partners to bring these research questions into clinical practice, improving patients’ lives in the ways that matter most. In my experience, I’ve found that asking the right questions leads to progress. Sharing that curiosity with world leaders in the field is a privilege.
An example of collaboration is our Beacon partnership with Washington University in St. Louis, aimed at addressing two key challenges in AD research: identifying and validating new diagnostic markers for AD to enable the next generation of precision therapies and sharpening insights on how patients progress from mild cognitive impairment to later-stage dementias.
These types of collaborations are tremendously valuable as they connect leading-edge researchers with the resources and capabilities of industry, which is best equipped to scale and commercialize discoveries. For patients waiting for cures, these types of collaborations mean getting access to new healthcare innovations sooner.
What novel biomarkers are emerging as promising candidates for AD diagnosis?
The research community is still learning which biomarkers are the most reliable indicators of AD, and our perspective is that it’s just too early to choose one method over another until there is more conclusive data. However, there are five proteins that are most often identified as indicators of AD pathology, associated with risk of developing AD, or are markers of neurodegeneration and inflammation. These proteins include amyloid-beta 42 peptide (Aβ42), phosphorylated tau 217 (p-Tau217), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and apolipoprotein ε4 (APOE ε4).
BD-Tau, which Beckman Coulter launched as the first-in-industry RUO assay, specifically binds to brain-derived tau, and is therefore assumed to be less influenced by confounding signals from peripheral sources.
Through collaborations with academic institutions and AI innovators, Danaher Diagnostics is accelerating the discovery of AD biomarkers and scaling next-generation diagnostics.
©iStock, BlackJack3D
How is modern technology such as AI helping biomarker discovery and diagnostic development?
AI has become indispensable with the proliferation of so much data in healthcare. Algorithms in machine learning and deep learning are now used to accelerate the cycle from therapeutic target discovery to early diagnosis. As more biomarkers and multimodal signatures of AD are discovered, there is potential to leverage AI to predict the risk of disease onset and progression, guide patients throughout their journey, and help accelerate drug development.
One notable partnership driven by Leica Biosystems, another diagnostics company that is part of Danaher, aims to leverage AI to advance next-generation companion diagnostics. Leica Biosystems is collaborating with Indica Labs to apply an AI-powered digital pathology platform that leverages deep learning to provide reproducible, scalable assessments that support both clinical trials and basic research.
In other research partnerships, we are seeking to further combine AI innovation with our biomarker research, as we know every patient offers a unique mosaic of data that computational models can decode more quickly. The more we learn, the more we realize that we are only at the beginning of understanding this complex disease.
What hurdles need to be overcome to go from innovation to a real-world diagnostic?
The challenges we face to bring an AD test from early-stage innovation to application are not insignificant. First, the test must be validated with clinical trials and then we must obtain regulatory approval, which can take years. But perhaps more challenging is ensuring that the healthcare system is ready for such a test. Are we prepared for the potential demand? Have physicians and medical technologists been educated and trained on the test and how to interpret results? Has the new test been integrated into the clinical workflow, so we’re prepared to process diagnostic results and integrate them into a patient’s medical record? It’s also important to note the ethical considerations that must be considered, including how to support patients through the journey of being diagnosed with AD, and addressing the stigma as well as the unknown that unfortunately still exists and could impact a patient’s personal or professional life following diagnosis.
How do you envision the future of AD diagnostics evolving over the next 5-10 years?
At Danaher, we are working to create a world where screening for AD is as routine as a colonoscopy or mammogram. Our vision is for diagnostic testing for neurodegenerative conditions to be accessible and affordable, so clinicians can make informed treatment decisions when these interventions can have the greatest impact on a patient’s future health.
By partnering side-by-side with pharmaceutical innovation, we’re working toward a future where early detection and patient subtyping by biomarker profiles enables precise, disease-modifying therapies to be applied to individual patients based on their disease characterization. We’re at an exciting moment where we see what once was considered fiction is now becoming reality—targeted therapies delivered to the right patient, at the right time, so that they can receive the greatest benefit.
