Lab professionals will learn more at the upcoming 30th annual edition of the event
Big changes and challenges are coming for the clinical laboratory anatomic pathology industry, and with them a slew of opportunities for lab and pathology practice leaders. At the upcoming 30th Annual Executive War College on Diagnostics, Pathology, and Clinical Laboratory Management, expert speakers and panelists will focus on the three most disruptive forces.
There will be more than 169 presenters at this year’s Executive War College. Those speakers include:
David Dexter, MD, clinical and laboratory pathology at M Health Fairview, and Sam Terese, president and CEO at Alverno Laboratories, who will present a strategic case study about the support labs can provide to parent hospitals when navigating new waters.
Paul Wilder, executive director of CommonWell Health Alliance, who will speak on the effort to improve the transferability and portability of patient and healthcare data in ways that improve the quality of care.
“Since the inception of The Dark Report in 1995 there has been continual change both within the US healthcare system and within the profession of laboratory medicine,” noted Robert L. Michel, Dark Daily’s editor-in-chief and creator of the Executive War College. “Now, three decades later, the following three items are imperatives for all labs: controlling costs; having adequate lab staff across all positions; and having enough capital to acquire and deploy new diagnostic technologies, along with the latest information technologies.”
“Most clinical laboratory managers would agree that many of the same operational pain points faced by labs in the 1990s exist today,” said Robert L. Michel (above), founder of the Executive War College. In an interview with Dark Daily, Michel broke down the nuances of this triad of forces and what participants in the Executive War College can expect. (Photo copyright: LabX.)
Forces at Work in Clinical Labs and Pathology Groups
Here’s a more detailed look at each of the forces that Michel noted.
Force 1: An acute shortage of experienced lab scientists
“When you look at the supply-demand for laboratory personnel in the United States today, it is recognized that demand exceeds supply, and that gap continues to widen,” Michel noted. “For example, in the case of anatomic pathologists, the increased number of case referrals grows faster than medical schools can train new pathologists. Currently, the ability of pathology laboratories large and small to hire and retain an adequate number of pathologists is a challenge.”
Executive War College attendees can expect panelists and speakers to highlight creative problem solving techniques to circumvent the challenges labor shortages cause.
Force 2: New applications of artificial intelligence
“Today every instrument vendor, every automation supplier, every software supplier, every service supplier is telling labs that they have artificial intelligence (AI) baked inside,” Michel observed. “It is important for lab managers to understand that a variety of technologies are used by different AI solutions.”
Clinical laboratory managers and pathologists interested in acquiring a deeper understanding of where to start with AI in their lab will find numerous sessions on artificial intelligence at this year’s Executive War College. “There will be a number of sessions this year where clinical labs discuss their success deploying various AI solutions,” Michel said.
Force 3: Financial stress across the entire US healthcare system
“It’s recognized that a significant number of US hospitals and integrated delivery networks (IDNs) are struggling to maintain adequate operating margins,” Michel noted. “This obviously impacts the clinical laboratories serving these hospitals. If the hospitals’ cash flows and operating profit margins are being squeezed, typically the administration comes to the lab team and says, ‘Your budget for next year will be x% less than this year.’
“There are many IDNs and hospital labs where budget cuts have happened for multiple years,” Michel continued. “As a consequence, labs in these hospitals must be nimble to maintain a high-quality menu of diagnostic tests. Several years of such budget cuts by the parent hospital can undermine the ability of the clinical lab team to offer competitive salary packages to attract and retain the clinical lab scientists, pathologists, and clinical chemists they need.”
Recognizing Opportunities in Today’s Lab Market
The good news is that—despite the negative forces acting upon the US healthcare system today—clinical laboratories, genetic testing companies, and anatomic pathology groups have a path forward.
“This path forward is informed by two longstanding precepts recognized by innovative managers. One precept is ‘Change creates new winners and losers.’ The other precept is ‘Change creates opportunity,’” Michel said. “Savvy lab leaders recognize the powerful truths in each precept.
“As healthcare has changed over the past four decades, nearly all the regional and national laboratories that were dominant in 1990, for example, don’t exist today!” he noted. “And yet, even as these lab organizations disappeared, new clinical lab organizations emerged that recognized healthcare’s changes and organized themselves to serve the changing needs of hospitals, office-based physicians, payers, and patients.”
All of these critical topics and more will be covered during the 30th Annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management on April 29-30, 2025, at the Hyatt Regency in New Orleans. Signup today to bring your lab’s management team by registering at https://www.executivewarcollege.com.
The trade association is publicly promoting the benefits of biomarker testing and AI’s benefits to diagnostics
One of the core tenets to getting federal lawmaker support for business is to tell them what an industry does. In that vein, the American Clinical Laboratory Association (ACLA) has released a new promotion that highlights applications of companion diagnostics, rapid whole genome sequencing, drug screening, biomarker testing, and infectious disease management.
One of the end goals? To sway Congress to take action against proposed reimbursement cuts to clinical lab test rates.
The ACLA campaign, known as the “Power of Knowing,” took center stage during a panel discussion at the ACLA Annual Meeting, held Feb. 27 in Washington, DC. One objective, panelists said, is to draw attention to the profession’s role in prevention and early detection of diseases, according to report from Medtech Insight.
“The association is working hard to demonstrate to policymakers the value of clinical laboratory testing through the Power of Knowing as they make policy decisions on reimbursement and clinical laboratory infrastructure that’s necessary for robust patient access to these innovative diagnostics,” said panel moderator Elyse Oveson, according to Medtech Insight. Oveson serves as ACLA chief of advocacy operations.
In March 2024, ACLA released digital ads urging Congress to pass the Saving Access to Laboratory Services Act (SALSA), which would have prevented a 15% cut in Medicare reimbursement for approximately 800 laboratory tests.
“A sustainable reform of the Medicare payment system for clinical laboratory services is vital to protect and enhance patient care, foster innovation, and ensure the stability of clinical laboratories nationwide,” ACLA president Susan Van Meter said at the time.
“If patients don’t have their biomarkers profiled for them at diagnosis and again at progression, there’s a very real chance that they would be put on the incorrect therapy that could lead to them having real harm in their health. So, we view biomarkers as critical,” said Nikki Martin (above), senior director of precision medicine initiatives for the LUNGevity Foundation, during the 2025 ACLA Annual Meeting. (Photo copyright: LinkedIn.)
Martin told attendees that biomarker tests should be part of the standard of care in lung cancer diagnosis, Medtech Insight reported. These tests analyze blood or other patient samples to identify molecules associated with specific diseases.
“For patients with non-small cell lung cancer, biomarkers are everything,” said Martin during the panel discussion. Many patients with advanced metastatic cancer, she said, “are not receiving comprehensive biomarker testing, and if they’re not, then they’re at risk of having much worse outcomes.”
Edelmayer discussed progress in developing biomarker tests for early diagnosis of Alzheimer’s disease. “The momentum is palpable among the research community,” she said. “We’re now starting to see the shift into implementation and more types of tools and technologies being available to clinicians to help patients.”
However, Edelmayer acknowledged that progress in developing Alzheimer’s tests and treatments has been slow.
“There’s never going to be a single test to help diagnose Alzheimer’s disease,” she said. “We recognize that it’s going to be a combination approach.”
New Video Campaign
The campaign’s latest advertising is summed up in a 90-second sizzle reel in which clinical laboratory leaders discuss various ways in which the profession supports healthcare.
One theme in the video is the growing use of artificial intelligence (AI) in the profession. “AI-enabled diagnostics are tools that use machine learning to analyze vast amounts of data from patient records to genomic profiles,” said Kate Sasser, PhD, chief scientific officer of Tempus, in the video. “These systems can recognize patterns in the data that humans may not easily see and help clinicians detect diseases earlier and more accurately.”
“By harnessing these cutting-edge tools, we can move closer to a world where treatments are no longer one size fits all but are instead tailored to the unique genetic and molecular profile of each patient,” said Elias Zerhouni, MD, president and vice chairman of OPKO Health, in a recent video produced as part of the ACLA’s Power of Knowing campaign.
The campaign website includes additional videos as well as downloadable graphics that can be shared on social media.
Pathologists and clinical laboratories will play a key role in collecting the data needed to create a person’s digital twin
Digital twins is a promising new technology that is making a big impact in healthcare. This development is significant because clinical laboratory test results will be among the most important sets of data to go into the creation of a patient’s “digital twin.”
A digital twin is defined by IBM as “a virtual representation of an object or system designed to reflect a physical object accurately. It spans the object’s lifecycle, is updated from real-time data, and uses simulation, machine learning, and reasoning to help make decisions.”
“We define a digital twin for healthcare as a virtual representation of a person which allows dynamic simulation of potential treatment strategy, monitoring and prediction of health trajectory, and early intervention and prevention, based on multi-scale modeling of multi-modal data such as clinical, genetic, molecular, environmental, and social factors, etc.,” wrote the authors of a review article published in NPJ Digital Medicine titled, “Digital Twins for Health: A Scoping Review.”
“The concept of digital twin for health (DT4H) holds great promise to revolutionize the entire healthcare system, including management and delivery, disease treatment and prevention, and health well-being maintenance, ultimately improving human life,” wrote study lead Eva Katsoulakis, MD (above), clinical informaticist and radiation oncologist at Tampa General Hospital in Florida, et al, in a review article she and her team published in NPJ Digital Medicine. Clinical laboratory test data will be a key element in the creation of a patient’s digital twin. (Photo copyright: Tampa General Hospital.)
Development of Digital Twins
Something akin to digital twins was first used in 1960 at NASA when replicas of spacecrafts currently on a mission in space were duplicated and studied on Earth. In 1991, Michael Grieves introduced the concept to manufacturing while at University of Michigan’s College of Engineering. The technology was later coined “digital twins” by John Vickers, a principal technologist in advanced manufacturing at NASA in 2010, IBM noted.
The increased use of digital twins in healthcare has brought some brilliant advancements. Examples, as reported by Computer Weekly, include:
Surgery and treatment: Boston Children’s Hospital uses digital twins to examine the complexities of heart procedures in reference to oxygen, blood flow, and valve pressure. Real-time analysis helps with surgeries and treatments, allowing clear visualization at all angles.
Metabolic analysis to tackle kidney failures: Digital twins are being used in Singapore to “Replicate metabolic fluxes to predict chronic kidney disease in type 2 diabetes mellitus.” Doctors there hope to curb the spike of chronic kidney disease found in type 2 diabetes mellitus. Their country has seen cases double in the last 40 years.
Bacterial predictions, E. coli: Bacteria behavior is being analyzed in computational simulations as part of a Simulating Microbial Systems (SMS) program. Run by the US Defense Advanced Research Projects Agency, the “SMS seeks interdisciplinary, comprehensive, and integrated workflows to generate unknown parameters from new data to inform computational models that can predict E. coli.”
Full body data: Precisely personalized care is the goal of European Virtual Human Twins Initiative, a project from the European Commission. The group creates digital twins and updates them with an individual’s personal conditions and health information that shifts as they age, keeping prevention as a focal point.
Respiratory viral pathogens: The complexities and variety of causes behind respiratory infections makes it an ideal area for digital twins. Its use in hospital ICUs can help doctors consider pneumonia treatment outlooks and develop plans for spread of infection.
Pharmaceuticals: Many pharma companies are opting to use digital twins since drug development is highly expensive and animal testing does not always provide clear data compared to human testing. Examples include Orion Pharma, which paired with AstraZeneca and Bayer to create digital twins that “capture genetic and molecular interactions that causally drive clinical and physiological outcomes.” Immunology company, Sanofi, also is using digital twins as “an essential first step to improve efficacy and safety.”
Future of Digital Twins in Healthcare
While digital twin development within healthcare is still in early stages, it promises to pioneer much change.
“When you have this model, you can personalize with certain features, certain anatomy, then you can try things. In heart surgery, you can’t try 20 different things, you only have one shot,” Ellen Kuhl PhD, professor of engineering and bioengineering at Stanford University, told Computer Weekly.
As technology advances and personalized healthcare continues to trend, it is likely digital twins will have a long-term place in medical practices. Astute clinical laboratory professionals will watch the expansion of this trend, since lab data will play such a key role in its development.
New guidelines come on the heels of recommendations covering post-market modifications to AI products, including those incorporated into systems used by clinical laboratories
Artificial intelligence (AI) is booming in healthcare, and as the technology finds its way into more medical devices and clinical laboratory diagnostic test technologies the US Food and Drug Administration (FDA) has stepped up its efforts to provide regulatory guidance for developers of these products. This guidance will have an impact on the development of new lab test technology that uses AI going forward.
In December, the FDA issued finalized recommendations for submitting information about planned modifications to AI-enabled healthcare products. Then, in January, the federal agency issued draft guidance that covers product management and marketing submission more broadly. It is seeking public comments on the latter document through April 7.
“The FDA has authorized more than 1,000 AI-enabled devices through established premarket pathways,” said Troy Tazbaz, director of the Digital Health Center of Excellence at the FDA’s Center for Devices and Radiological Health, in a press release announcing the draft guidance.
This guidance “would be the first to provide total product life cycle recommendations for AI-enabled devices, tying together all design, development, maintenance and documentation recommendations, if and when finalized,” Healthcare IT News reported.
“Today’s draft guidance brings together relevant information for developers, shares learnings from authorized AI-enabled devices, and provides a first point-of-reference for specific recommendations that apply to these devices, from the earliest stages of development through the device’s entire life cycle,” said Troy Tazbaz (above), director of the Digital Health Center of Excellence at the FDA Center for Devices and Radiological Health, in a press release. The new guidance will likely affect the development of new clinical laboratory diagnostic technologies that use AI. (Photo copyright: LinkedIn.)
Engaging with FDA
One key takeaway from the guidance is that manufacturers “should engage with the FDA early to ensure that the testing to support the marketing submission for an AI-enabled device reflects the agency’s total product lifecycle, risk-based approach,” states an analysis from consulting firm Orrick, Herrington and Sutcliffe LLP.
Another key point is transparency, Orrick noted. For example, manufacturers should be prepared to offer details about the inputs and outputs of their AI models and demonstrate “how AI helps achieve a device’s intended use.”
Manufacturers should also take steps to avoid bias in data collection for these models. For example, they should gather evidence to determine “whether a device benefits all relevant demographic groups similarly to help ensure that such devices are safe and effective for their intended use,” Orrick said.
New Framework for AI in Drug Development
On the same day that FDA announced the device guidelines, the agency also proposed a framework for regulating use of AI models in developing drugs and biologics.
“AI can be used in various ways to produce data or information regarding the safety, effectiveness, or quality of a drug or biological product,” the federal agency stated in a press release. “For example, AI approaches can be used to predict patient outcomes, improve understanding of predictors of disease progression and process, and analyze large datasets.”
The press release noted that this is the first time the agency has proposed guidance on use of AI in drug development.
These include “bias and reliability problems due to variability in the quality, size, and representativeness of training datasets; the black-box nature of AI models in their development and decision-making; the difficulty of ascertaining the accuracy of a model’s output; and the dangers of data drift and a model’s performance changing over time or across environments. Any of these factors, in FDA’s thinking, could negatively impact the reliability and relevancy of the data sponsors provide FDA.”
The FDA also plans to participate in direct testing of AI-enabled healthcare tools. In October, the FDA and the Department of Veterans Affairs (VA) announced that they will launch “a joint health AI lab to evaluate promising emerging technologies,” according to Nextgov/FCW.
Elnahal said the facility will allow federal agencies and private entities “to test applications of AI in a virtual lab environment.” The goal is to ensure that the tools are safe and effective while adhering to “trustworthy AI principles,” he said.
“It’s essentially a place where you get rapid but effective evaluation—from FDA’s standpoint and from VA’s standpoint—on a potential new application of generative AI to, number one, make sure it works,” he told Nextgov/FCW.
He added that the lab will be set up with safeguards to ensure that the technologies can be tested safely.
“As long as they go through the right security protocols, we’d essentially be inviting parties to test their technology with a fenced off set of VA data that doesn’t have any risk of contagion into our actual live systems, but it’s still informative and simulated,” he told Nextgov/FCW.
There has been an explosion in the use of AI, machine learning, deep learning, and natural language processing in clinical laboratory diagnostic technologies. This is equally true of anatomic pathology, where AI-powered image analysis solutions are coming to market. That two federal agencies are motivated to establish guidelines on working relationships for evaluating the development and use of AI in healthcare settings tells you where the industry is headed.
Although it is a non-specific procedure that does not identify specific health conditions, it could lead to new biomarkers that clinical laboratories could use for predictive healthcare
Researchers from the Mayo Clinic recently used artificial intelligence (AI) to develop a predictive computational tool that analyzes an individual’s gut microbiome to identify how a person may experience improvement or deterioration in health.
Dubbed the Gut Microbiome Wellness Index 2 (GMWI2), Mayo’s new tool does not identify the presence of specific health conditions but can detect even minor changes in overall gut health.
Built on an earlier prototype, GMWI2 “demonstrated at least 80% accuracy in differentiating healthy individuals from those with any disease,” according to a Mayo news release. “The researchers used bioinformatics and machine learning methods to analyze gut microbiome profiles in stool samples gathered from 54 published studies spanning 26 countries and six continents. This approach produced a diverse and comprehensive dataset.”
“Our tool is not intended to diagnose specific diseases but rather to serve as a proactive health indicator,” said senior study author Jaeyun Sung, PhD (above), a computational biologist at the Mayo Clinic Center for Individualized Medicine: Microbiomics Program in the news release ease. “By identifying adverse changes in gut health before serious symptoms arise, the tool could potentially inform dietary or lifestyle modifications to prevent mild issues from escalating into more severe health conditions, or prompt further diagnostic testing.” For microbiologists and clinical laboratory managers, this area of new knowledge about the human microbiome may lead to multiplex diagnostic assays. (Photo copyright: Mayo Clinic.)
Connecting Specific Diseases with Gut Microbiome
Gut bacteria that resides in the gastrointestinal tract consists of trillions of microbes that help regulate various bodily functions and may provide insights regarding the overall health of an individual. An imbalance in the gut microbiome is associated with an assortment of illnesses and chronic diseases, including cardiovascular issues, digestive problems, and some cancers and autoimmune diseases.
To develop GMWI2, the Mayo scientists provided the machine-learning algorithm with data on microbes found in stool samples from approximately 8,000 people collected from 54 published studies. They looked for the presence of 11 diseases, including colorectal cancer and inflammatory bowel disease (IBS). About 5,500 of the subjects had been previously diagnosed with one of the 11 diseases, and the remaining people did not have a diagnosis of the conditions.
The scientists then tested the efficacy of GMWI2 on an additional 1,140 stool samples from individuals who were diagnosed with conditions such as pancreatic cancer and Parkinson’s disease, compared with those who did not have those illnesses.
The algorithm gives subjects a score between -6 and +6. People with a higher GMWI2 score have a healthier microbiome that more closely resembles individuals who do not have certain diseases.
Likewise, a low GMWI2 score suggests the individual has a gut microbiome that is similar to those who have specific illnesses.
Highly Accurate Results
According to their study, the researchers determined that “GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence,” they wrote in Nature Communications.
Launched in 2020, the original GMWI (Gut Microbiome Wellness Index) was trained on a much smaller number of samples but still showed similar results.
The researchers tested the enhanced GMWI2 algorithm across various clinical schemes to determine if the results were similar. These scenarios included individuals who had previous fecal microbiota transplants and people who had made dietary changes or who had exposure to antibiotics. They found that their improved tool detected changes in gut health in those scenarios as well.
“By being able to answer whether a person’s gut is healthy or trending toward a diseased state, we ultimately aim to empower individuals to take proactive steps in managing their own health,” Sung said in the news release.
The Mayo Clinic team is developing the next version of their tool, which will be known as the Gut Microbiome Wellness Index 3. They plan to train it on at least 12,000 stool samples and use more sophisticated algorithms to decipher the data.
More research and studies are needed to determine the overall usefulness of Mayo’s Gut Microbiome Wellness Index and its marketability. Here is a world-class health institution disclosing a pathway/tool that analyzes the human microbiome to identify how an individual may be experiencing either an improvement in health or a deterioration in health.
The developers believe it will eventually help physicians determine how patients’ conditions are improving or worsening by comparing the patients’ microbiomes to the profiles of other healthy and unhealthy microbiomes. As this happens, it would create a new opportunity for clinical laboratories to perform the studies on the microbiomes of patients being assayed in this way by their physicians.
