Two studies show the accuracy of perception-based systems in detecting disease biomarkers without needing molecular recognition elements, such as antibodies
Researchers from multiple academic and research institutions have collaborated to develop a non-conventional machine learning-based technology for identifying and measuring biomarkers to detect ovarian cancer without the need for molecular identification elements, such as antibodies.
Traditional clinical laboratory methods for detecting biomarkers of specific diseases require a “molecular recognition molecule,” such as an antibody, to match with each disease’s biomarker. However, according to a Lehigh University news release, for ovarian cancer “there’s not a single biomarker—or analyte—that indicates the presence of cancer.
“When multiple analytes need to be measured in a given sample, which can increase the accuracy of a test, more antibodies are required, which increases the cost of the test and the turnaround time,” the news release noted.
Unveiled in two sequential studies, the new method for detecting ovarian cancer uses machine learning to examine spectral signatures of carbon nanotubes to detect and recognize the disease biomarkers in a very non-conventional fashion.
“Carbon nanotubes have interesting electronic properties,” said Daniel Heller, PhD (above), in the Lehigh University news release. “If you shoot light at them, they emit a different color of light, and that light’s color and intensity can change based on what’s sticking to the nanotube. We were able to harness the complexity of so many potential binding interactions by using a range of nanotubes with various wrappings. And that gave us a range of different sensors that could all detect slightly different things, and it turned out they responded differently to different proteins.” This method differs greatly from traditional clinical laboratory methods for identifying disease biomarkers. (Photo copyright: Memorial Sloan-Kettering Cancer Center.)
Perception-based Nanosensor Array for Detecting Disease
In the Science Advances paper, the researchers described their development of “a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids.
“Perception-based machine learning (ML) platforms, modeled after the complex olfactory system, can isolate individual signals through an array of relatively nonspecific receptors. Each receptor captures certain features, and the overall ensemble response is analyzed by the neural network in our brain, resulting in perception,” the researchers wrote.
“This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements,” the researchers concluded.
In the Nature Biomedical Engineering paper, the researchers described a fined-tuned toolset that could accurately differentiate ovarian cancer biomarkers from biomarkers in individuals who are cancer-free.
“Here we show that a ‘disease fingerprint’—acquired via machine learning from the spectra of near-infrared fluorescence emissions of an array of carbon nanotubes functionalized with quantum defects—detects high-grade serous ovarian carcinoma in serum samples from symptomatic individuals with 87% sensitivity at 98% specificity (compared with 84% sensitivity at 98% specificity for the current best [clinical laboratory] screening test, which uses measurements of cancer antigen 125 and transvaginal ultrasonography,” the researchers wrote.
“We demonstrated that a perception-based nanosensor platform could detect ovarian cancer biomarkers using machine learning,” said Yoona Yang, PhD, a postdoctoral research associate in Lehigh’s Department of Chemical and Biomolecular Engineering and co-first author of the Science Advances article, in the news release.
How Perception-based Machine Learning Platforms Work
According to Yang, perception-based sensing functions like the human brain.
“The system consists of a sensing array that captures a certain feature of the analytes in a specific way, and then the ensemble response from the array is analyzed by the computational perceptive model. It can detect various analytes at once, which makes it much more efficient,” Yang said.
“SWCNTs have unique optical properties and sensitivity that make them valuable as sensor materials. SWCNTS emit near-infrared photoluminescence with distinct narrow emission bands that are exquisitely sensitive to the local environment,” the researchers wrote in Science Advances.
“Carbon nanotubes have interesting electronic properties,” said Daniel Heller, PhD, Head of the Cancer Nanotechnology Laboratory at Memorial Sloan Kettering Cancer Center and Associate Professor in the Department of Pharmacology at Weill Cornell Medicine of Cornell University, in the Lehigh University news release.
“If you shoot light at them, they emit a different color of light, and that light’s color and intensity can change based on what’s sticking to the nanotube. We were able to harness the complexity of so many potential binding interactions by using a range of nanotubes with various wrappings. And that gave us a range of different sensors that could all detect slightly different things, and it turned out they responded differently to different proteins,” he added.
The researchers put their technology to practical test in the second study. The wanted to learn if it could differentiate symptomatic patients with high-grade ovarian cancer from cancer-free individuals.
The research team used 269 serum samples. This time, nanotubes were bound with a specific molecule providing “an extra signal in terms of data and richer data from every nanotube-DNA combination,” said Anand Jagota PhD, Professor, Bioengineering and Chemical and Biomolecular Engineering, Lehigh University, in the news release.
This year, 19,880 women will be diagnosed with ovarian cancer and 12,810 will die from the disease, according to American Cancer Society data. While more research and clinical trials are needed, the above studies are compelling and suggest the possibility that one day clinical laboratories may detect ovarian cancer faster and more accurately than with current methods.
Screening and analysis of ocean samples also identified a possible missing link in how the RNA viruses evolved
An international team of scientists has used genetic screening and machine learning techniques to identify more than 5,500 previously unknown species of marine RNA viruses and is proposing five new phyla (biological groups) of viruses. The latter would double the number of RNA virus phyla to 10, one of which may be a missing link in the early evolution of the microbes.
Though the newly-discovered viruses are not currently associated with human disease—and therefore do not drive any current medical laboratory testing—for virologists and other microbiologists, “a fuller catalog of these organisms is now available to advance scientific understanding of how viruses evolve,” said Dark Daily Editor-in-Chief Robert Michel.
“While scientists have cataloged hundreds of thousands of DNA viruses in their natural ecosystems, RNA viruses have been relatively unstudied,” wrote four microbiologists from Ohio State University (OSU) who participated in the study in an article they penned for The Conversation.
The OSU study authors included:
Ahmed Zayed, PhD, research scientist, Dept. of Microbiology, OSU.
Matthew Sullivan, PhD, Professor of Microbiology and Director of the Center of Microbiome Science at OSU.
“RNA viruses are clearly important in our world, but we usually only study a tiny slice of them—the few hundred that harm humans, plants and animals,” explained Matthew Sullivan, PhD (above), Director, Center of Microbiome Science, in an OSU news story. Sullivan led the OSU research team. “We wanted to systematically study them on a very big scale and explore an environment no one had looked at deeply, and we got lucky because virtually every species was new, and many were really new,” he added. (Photo copyright: University of Ohio.)
RNA versus DNA Viruses
In contrast to the better-understood DNA virus, an RNA virus contains RNA instead of DNA as its genetic material, according to Samanthi Udayangani, PhD, in an article she penned for Difference Between. Examples of RNA viruses include:
One major difference, she explains, is that RNA viruses mutate at a higher rate than do DNA viruses.
The OSU scientists identified the new species by analyzing a database of RNA sequences from plankton collected during a series of ocean expeditions aboard a French schooner owned by the Tara Ocean Foundation.
“Plankton are any aquatic organisms that are too small to swim against the current,” the authors explained in The Conversation. “They’re a vital part of ocean food webs and are common hosts for RNA viruses.”
The team’s screening process focused on the RNA-dependent RNA polymerase (RdRp) gene, “which has evolved for billions of years in RNA viruses, and is absent from other viruses or cells,” according to the OSU news story.
“RdRp is supposed to be one of the most ancient genes—it existed before there was a need for DNA,” Zayed said.
The RdRp gene “codes for a particular protein that allows a virus to replicate its genetic material. It is the only protein that all RNA viruses share because it plays an essential role in how they propagate themselves. Each RNA virus, however, has small differences in the gene that codes for the protein that can help distinguish one type of virus from another,” the study authors explained.
The screening “ultimately identified over 44,000 genes that code for the virus protein,” they wrote.
Identifying Five New Phyla
The researchers then turned to machine learning to organize the sequences and identify their evolutionary connections based on similarities in the RdRp genes.
“The more similar two genes were, the more likely viruses with those genes were closely related,” they wrote.
The technique classified many of the sequences within the five previously known phyla of RNA viruses:
But the researchers also identified five new phyla—including two dubbed “Taraviricota” and “Arctiviricota”—that “were particularly abundant across vast oceanic regions,” they wrote. Taraviricota is named after the Tara expeditions and Arctiviricota gets its name from the Arctic Ocean.
They speculated that Taraviricota “might be the missing link in the evolution of RNA viruses that researchers have long sought, connecting two different known branches of RNA viruses that diverged in how they replicate.”
In addition to the five new phyla, the researchers are proposing at least 11 new classes of RNA viruses, according to the OSU story. The scientists plan to issue a formal proposal to the International Committee on Taxonomy of Viruses (ICTV), the body responsible for classification and naming of viruses.
Studying RNA Viruses Outside of Disease Environments
“As the COVID-19 pandemic has shown, RNA viruses can cause deadly diseases. But RNA viruses also play a vital role in ecosystems because they can infect a wide array of organisms, including microbes that influence environments and food webs at the chemical level,” wrote the four study authors in The Conversation. “Mapping out where in the world these RNA viruses live can help clarify how they affect the organisms driving many of the ecological processes that run our planet. Our study also provides improved tools that can help researchers catalog new viruses as genetic databases grow.”
This remarkable study, which was partially funded by the US National Science Foundation, will be most intriguing to virologists and microbiologists. However, clinical laboratories also should be interested in the fact that the catalog of known viruses has just expanded by 5,500 types of RNA viruses.
Columbia University’s MediSCAPE enables surgeons to examine tissue structures in vivo and a large-scale clinical trial is planned for later this year
Scientists at Columbia University in New York City have developed a high-speed 3D microscope for diagnosis of cancers and other diseases that they say could eventually replace traditional biopsy and histology “with real-time imaging within the living body.”
The technology is designed to enable in situ tissue analysis. Known as MediSCAPE, the microscope is “capable of capturing images of tissue structures that could guide surgeons to navigate tumors and their boundaries without needing to remove tissues and wait for pathology results,” according to a Columbia University news story.
“The way that biopsy samples are processed hasn’t changed in 100 years, they are cut out, fixed, embedded, sliced, stained with dyes, positioned on a glass slide, and viewed by a pathologist using a simple microscope. This is why it can take days to hear news back about your diagnosis after a biopsy,” said Hillman in the Columbia news story.
“Our 3D microscope overcomes many of the limitations of prior approaches to enable visualization of cellular structures in tissues in the living body. It could give a doctor real-time feedback about what type of tissue they are looking at without the long wait,” she added in I News.
Hillman’s team previously used the technology—originally dubbed SCAPE for “Swept Confocally Aligned Planar Excitation” microscopy—to capture 3D images of neurological activity in living samples of worms, fish, and flies. In their recent study, the researchers tested the technology with human kidney tissue, a human volunteer’s tongue, and a mouse with pancreatic cancer.
“This was something I didn’t expect—that I could actually look at structures in 3D from different angles,” said nephropathologist and study co-author Shana M. Coley, MD, PhD (above), Director, Transplant Translational Research and Multiplex Imaging Center at Arkana Laboratories, in the Columbia news story. At the time of the Columbia study, Coley was an assistant professor at Columbia University and a renal pathologist at the Columbia University Medical Center. “We found many examples where we would not have been able to identify a structure from a 2D section on a histology slide, but in 3D we could clearly see its shape. In renal pathology in particular, where we routinely work with very limited amounts of tissue, the more information we can derive from the sample, the better for delivering more effective patient care,” she added. (Photo copyright: Arkana Laboratories.)
How MediSCAPE Works
Unlike traditional 3D microscopes that use a laser to scan tiny spots of a tissue sample and then assemble those points into a 3D image, the MediSCAPE 3D microscope “illuminates the tissue with a sheet of light—a plane formed by a laser beam that is focused in a special way,” I News reported.
The MediSCAPE microscope thus captures 2D slices which are rapidly stacked into 3D images at a rate of more than 10 volumes per second, according to I News.
“One of the first tissues we looked at was fresh mouse kidney, and we were stunned to see gorgeous structures that looked a lot like what you get with standard histology,” said optical systems engineer and the study’s lead author, Kripa Patel, PhD, in the Columbia news story. “Most importantly, we didn’t add any dyes to the mouse—everything we saw was natural fluorescence in the tissue that is usually too weak to see.
“Our microscope is so efficient that we could see these weak signals well,” she continued, “even though we were also imaging whole 3D volumes at speeds fast enough to rove around in real time, scanning different areas of the tissue as if we were holding a flashlight.”
A big advantage of the technology, Hillman noted, is the ability to scan living tissue in the body.
“Understanding whether tissues are staying healthy and getting good blood supply during surgical procedures is really important,” she said in the Columbia news story. “We also realized that if we don’t have to remove (and kill) tissues to look at them, we can find many more uses for MediSCAPE, even to answer simple questions such as ‘what tissue is this?’ or to navigate around precious nerves. Both of these applications are really important for robotic and laparoscopic surgeries, where surgeons are more limited in their ability to identify and interact with tissues directly.”
Clinical Trials and FDA Clearance
Early versions of the SCAPE microscopes were too large for practical use by surgeons, so Columbia post-doctoral research scientist Wenxuan Liang, PhD, co-author of the study, helped the team develop a smaller version that would fit into an operating room.
Later this year, the researchers plan to launch a large-scale clinical trial, I News reported. The Columbia scientists hope to get clearance from the US Food and Drug Administration (FDA) to develop a commercialized version of the microscope.
“They will initially seek permission to use it for tumor screening and guidance during operations—a lower and easier class of approval—but ultimately, they hope to be allowed to use it for diagnosis,” Liang wrote.
Charles Evans, PhD, research information manager at Cancer Research UK, told I News, “Using surgical biopsies to confirm a cancer diagnosis can be time-consuming and distressing for patients. And ensuring all the cancerous tissue is removed during surgery can be very challenging unaided.”
He added, “more work will be needed to apply this technique in a device that’s practical for clinicians and to demonstrate whether it can bring benefits for people with cancer, but we look forward to seeing the next steps.”
Will the Light Microscope be Replaced?
In recent years, research teams at various institutions have been developing technologies designed to enhance or even replace the traditional light microscope used daily by anatomic pathologists across the globe.
And digital scanning algorithms for creating whole-slide images (WSIs) that can be analyzed by pathologists on computer screens are gaining in popularity as well.
Such developments may spark a revolution in surgical pathology and could signal the beginning of the end of the light microscope era.
Surgical pathologists should expect to see a steady flow of technologically advanced systems for tissue analysis to be submitted to the FDA for pre-market review and clearance for use in clinical settings. The light microscope may not disappear overnight, but there are a growing number of companies actively developing different technologies they believe can diagnose either or both tissue and digital images of pathology slides with accuracy comparable to a pathologist.
UW scientists believe their at-home test could help more people on anticoagulants monitor their clotting levels and avoid blood clots
In a proof-of-concept study,researchers at the University of Washington (UW) are developing a new smartphone-based technology/application designed to enable people on anticoagulants such as warfarin to monitor their clotting levels from the comfort of their homes. Should this new test methodology prove successful, clinical laboratories may have yet one more source of competition from this at-home PT/INR test solution.
PT/INR (prothrombin time with an international normalized ratio) is one of the most frequently performed clinical laboratory blood tests. This well-proven assay helps physicians monitor clotting in patients taking certain anticoagulation medications.
However, the process can be onerous for those on anticoagulation drugs. Users of this type of medication must have their blood tested regularly—typically by a clinical laboratory—to ensure the medication is working effectively. When not, a doctor visit is required to adjust the amount of the medication in the bloodstream.
Alternatively, where a state’s scope of practice law permits, pharmacists can perform a point-of-care test for the patient, thus allowing the pharmacist to appropriately adjust the patient’s prescription.
Though in the early stages of its development, were the UW’s new smartphone-based blood clotting test to be cleared by the federal Food and Drug Administration (FDA), then users would only need to see a doctor when their readings went and stayed out of range, according to Clinical Lab Products (CLP).
Enabling Patients to Test Their Blood More Frequently
More than eight million Americans with mechanical heart valves or other cardiac conditions take anticoagulants, and 55% of people taking those medication say they fear experiencing life-threatening bleeding, according to the National Blood Clot Alliance.
They have reason to be worried. Even when taking an anticoagulation drug, its level may not stay within therapeutic range due to the effects of food and other medications, experts say.
“In the US, most people are only in what we call the ‘desirable range’ of PT/INR levels about 64% of the time. This number is even lower—only about 40% of the time—in countries such as India or Uganda, where there is less frequent testing. We need to make it easier for people to test more frequently,” said anesthesiologist and co-author of the study Kelly Michaelsen, MD, PhD, UW Assistant Professor of Anesthesiology and Pain Medicine, in a UW news release.
“Back in the day, doctors used to manually rock tubes of blood back and forth to monitor how long it took a clot to form. This, however, requires a lot of blood, making it infeasible to use in home settings,” said senior study author Shyam Gollakota, PhD (above), professor and head of the Networks and Mobile Systems Lab at UW’s Paul G. Allen School of Computer Science and Engineering, in the UW news release. “The creative leap we make here is that we’re showing that by using the vibration motor on a smartphone, our algorithms can do the same thing, except with a single drop of blood. And we get accuracy similar to the best commercially available techniques [used by clinical laboratories].” (Photo copyright: University of Washington.)
How UW’s Smartphone-based Blood Clotting Test Works
The UW researchers were motived by the success of home continuous glucose monitors, which enable diabetics to continually track their blood glucose levels.
According to the Nature Communications paper, here’s how UW’s “smartphone-based micro-mechanical clot detection system” works:
Samples of blood plasma and whole blood are placed into a thimble-size plastic cup.
The cup includes a small copper particle and thromboplastin activator.
When the smartphone is turned on and vibrating, the cup (which is mounted on an attachment) moves beneath the phone’s camera.
Video analytic algorithms running on the smartphone track the motion of the copper particle.
If blood clots, the “viscous mixture” slows and stops.
PT/INR values can be determined in less than a minute.
“Our system visually tracks the micro-mechanical movements of a small copper particle in a cup with either a single drop of whole blood or plasma and the addition of activators,” the researchers wrote in Nature Communications. “As the blood clots, it forms a network that tightens. And in that process, the particle goes from happily bouncing around to no longer moving,” Michaelsen explained.
The system produced these results:
140 de-identified plasma samples: PT/INR with inter-class correlation coefficients of 0.963 and 0.966.
79 de-identified whole blood samples: 0.974 for both PT/INR.
Another At-home Test That Could Impact Clinical Laboratories
The UW scientists intend to test the system with patients in their homes, and in areas and countries with limited testing resources, Medical Device Network reported.
Should UW’s smartphone-based blood-clotting test be cleared by the FDA, there could be a ready market for it. But it will need to be offered it at a price competitive with current clinical laboratory assays for blood clotting, as well as with the current point-of-care tests in use today.
Nevertheless, UW’s work is the latest example of a self-testing methodology that could become a new competitor for clinical laboratories. This may motivate medical laboratories to keep PT/INR testing costs low, while also reporting quick and accurate results to physicians and patients on anticoagulants.
Alternatively, innovative clinical laboratories could develop a patient management service to oversee a patient’s self-testing at home and coordinate delivery of the results with the patient’s physician and pharmacist. This approach would enable the lab to add value for which it could be reimbursed.
Labcorp, the commercial laboratory giant headquartered in Burlington, N.C., has billions of diagnostic test results archived. It takes samplings of those results and runs them through a machine learning algorithm that compares the data against a condition of interest, such as chronic kidney disease (CKD). Machine learning is a subdiscipline of AI.
Based on patterns it identifies, the machine learning algorithm can predict future test results for CKD based on patients’ testing histories, explained Stan Letovsky, PhD, Vice President for AI, Data Sciences, and Bioinformatics at Labcorp. Labcorp has found the accuracy of those predictions to be better than 90%, he added.
Labcorp also has created an AI-powered dashboard that—once layered over an electronic health record (EHR) system—allows physicians to configure views of an individual patient’s existing health data and add a predictive view based on the machine learning results.
For anatomic pathologists, this type of setup can quickly bring a trove of data into their hands, allowing them to be more efficient with patient diagnoses. The long-term implications of using this technology are significant for pathology groups’ bottom line.
Stan Letovsky, PhD (above), Vice President for AI, Data Sciences, and Bioinformatics at Labcorp, discussed AI developments in digital pathology during his keynote address at the 2022 Executive War College in New Orleans. “The best thing as a community that we can do for patients and their physicians with AI is to identify care gaps early on,” he said, adding, “If pathologists want to grow and improve their revenue, they have to be more productive.” (Photo copyright: Dark Intelligence Group).
Mayo Clinic Plans to Digitize 25 Million Glass Slides
In other AI developments, Mayo Clinic in Rochester, Minn., has started a project to digitally scan 25 million tissue samples on glass slides—some more than 100 years old. As part of the initiative, Mayo wants to digitize five million of those slides within three years and put them on the cloud, said pathologist and physician scientist Jason Hipp, MD, PhD, Chair of Computational Pathology and AI at Mayo Clinic.
“We want to be a hub within Mayo Clinic for digital pathology,” Hipp told Executive War College attendees during his keynote address.
Hipp views his team as the bridge between pathologists and the data science engineers who develop AI algorithms. Both sides must collaborate to move AI forward, he commented, yet most clinical laboratories and pathology groups have not yet developed those relationships.
“We want to embed both sides,” Hipp added. “We need the data scientists working with the pathologists side by side. That practical part is missing today.”
The future medical laboratory at Mayo Clinic will feature an intersection of pathology, computer technology, and patient data. Cloud storage is a big part of that vision.
“AI requires storage and lots of data to be practical,” Hipp said.
27th annual meeting of medical laboratory and pathology managers delivers insights on the path ahead for diagnostics, ranging from the supply chain shortage and the ‘Great Resignation’ to advances in artificial intelligence and whole genome sequencing in service of precision medicine
What’s coming as healthcare providers move to post-COVID-19 pandemic workflows will be of keen interest to clinical laboratory leaders attending this critical event. Several new and dynamic market changes are reshaping the development of, ordering, and reimbursement for medical laboratory tests. They include:
Millennials as change agents in how care is accessed and delivered.
New buyers of large volumes of clinical lab tests, such as retail pharmacies.
How clinical laboratories can earn new sources of revenue while supporting precision medicine.
Clinical Labs Should Prepare for the ‘Coming Roller Coaster Ride’
Robert L. Michel, Editor-in-Chief of Dark Daily’s sister publication, The Dark Report, and Founder of the Executive War College, described the “coming roller coaster ride” for the pathology and clinical laboratory industries.
Amid the usual operational issues labs deal with (e.g., workforce shortages, supply chain disruptions, regulatory pressures), he noted the emergence of new and powerful forces pulling clinical laboratories and pathology groups in all directions.
“One primary factor is how Millennials will use healthcare differently than Gen Xers and Baby Boomers,” Michel noted. “Similarly, Millennials will make up 75% of the pathologists and the lab workforce by 2025.
“Another major force for change will be new buyers of clinical laboratory tests,” he continued. “For example, expect to see national retail pharmacy chains build thousands of primary care clinics in their retail pharmacies. These clinics will need lab tests and will become major buyers of near-patient analyzers and lab tests.
“A third interesting factor is that a new class of in vitro diagnostics (IVD) manufacturers are developing analyzers and test systems that use minimal amounts of specimens and return answers in minutes. Primary care clinics in retail pharmacies will be interested in buying these lab testing solutions,” Michel concluded.
Robert L. Michel (above), Editor-in-Chief of The Dark Report and Founder of the Executive War College, has studied and worked with leaders of clinical laboratories and pathology groups for more than four decades. During his keynote address, he predicted that powerful economic forces are about to be unleashed on the traditional market for clinical laboratory testing. Those forces include the use of artificial intelligence (AI) in digital pathology, primary care in retail pharmacies, and increased focus on precision medicine. (Photo copyright: The Dark Intelligence Group.)
Peer-to-Peer Learning Opportunities
With approximately 90 presenters scheduled, clinical laboratory leaders from such prestigious institutions as Johns Hopkins Hospital, Mayo Clinic, United Indian Health Services, and more will facilitate peer-to-peer learnings throughout the conference.
In addition, several sessions and panel Q/A discussions will cover critical legal and regulatory issues and payer challenges facing the industry.
New Technologies, Workflows, Analytics
The 2022 Executive War College master classes, breakouts, panel discussions, and benefactor sessions will highlight several significant themes:
Lab data analytics and utilization. Sessions this year are heavily weighted toward data analytics, aggregation, and utilization. Look for case studies demonstrating the value of lab data, and where and how data has become actionable and monetized. As Dark Daily previously reported, useful data structures have been difficult to achieve for clinical laboratories; however, the case studies featured during this week’s conference will demonstrate signs of progress and highlight lessons learned.
Automation. Several case studies are planned that focus on expansion and modernization using laboratory automation. From Butler Health System, an independent hospital system in western Pa., Robert Patterson, MD, Medical Director of Pathology, Laboratory Medicine, and Laboratory Outreach, will detail steps Butler took that enabled its labs to better compete with other area health systems and national reference laboratories. Likewise, Eric Parnell, System Supervisor of Microbiology for Bronson Healthcare in southern Mich., will discuss his lab’s transition to and implementation of total laboratory automation.
Genetic testing and next-generation sequencing (NGS). Quickly becoming the foundational disruptor technology on which many new and powerful clinical laboratory tests and procedures are based, genomic testing has now become accessible and affordable. Many clinical laboratories and pathology groups are using molecular diagnostics testing to deliver clinical value to referring physicians.
Other sessions include:
Launching and scaling clinical NGS testing in a clinical environment (featuring a project at Rady Children’s Hospital in San Diego).
How labs and payers can work together to achieve better outcomes and health equity using genomic testing.
Effective ways to repurpose PCR and other genetic test instruments to build specimen volume and increase lab revenue.
Paths Forward for Clinical Labs and Pathology Groups
Another important topic being discussed at the 2022 Executive War College is how to position clinical laboratories and pathology groups for the next phase of modern healthcare.
Attracting capital for clinical labs and pathology groups.
Emerging concepts in growth strategies.
Business valuation factors.
Unexpected disruptions during sales closings.
These are just a few highlights of the informative sessions and expert speakers scheduled during this week’s 27th annual Executive War College in New Orleans. Look for more coverage in Dark Daily during the days ahead and in upcoming editions of our sister publication The Dark Report.
Full details about the 2022 Executive War College can be found by clicking on this link. (Or copy/paste this URL into your web browser: http://www.executivewarcollege.com.)
Speakers, session topics, and the conference agenda can be viewed by clicking on this link. (Or copy/paste this URL into your web browser: https://executivewarcollege.darkintelligencegroup.com/executive-war-college-agenda-2022.)
