A new partnership between Intermountain Health and Testmate Health aims to bring rapid, lab-quality STI testing out of the central lab and into underserved communities, addressing persistent gaps in diagnosis and follow-up care.
Testmate Health and Intermountain Health have entered a strategic partnership and investment aimed at accelerating access to rapid, low-cost molecular testing for sexually transmitted infections (STIs) across the US.
For clinical laboratory leaders, the collaboration signals a growing push to move high-quality molecular diagnostics closer to patients, particularly those belonging to underserved and high-risk populations.
STIs continue to represent a major public health challenge, with an estimated 80% of chlamydia and gonorrhea infections going undiagnosed each year. Delays in testing and treatment are especially common among college students, LGBTQ+ populations, and patients served by rural or resource-limited clinics. The two organizations say their partnership is designed to close those gaps by making accurate, lab-quality testing available outside of traditional laboratory environments.
Bringing Molecular Diagnostics Beyond the Central Lab
Under the agreement, Intermountain Health will support the deployment of Testmate’s single-use, reader-free molecular tests for Chlamydia trachomatis and Neisseria gonorrhoeae. The tests are designed to deliver results in under 30 minutes and do not require central lab infrastructure. They can be used with urine or swab samples, offering flexibility for a range of care settings.
Karen Brownell, vice president of Lab Services at Intermountain Health said, “When these STI tests become FDA-approved in the US, Testmate’s innovative approach to molecular diagnostics will allow us to deliver lab-quality results outside traditional lab settings, directly impacting communities that have historically lacked access to timely testing.” (Photo credit: ContactOut)
Addressing Access, Turnaround Time, and Follow-Up
Testmate’s leadership emphasized that reducing barriers to testing is central to improving outcomes. Rapid turnaround times may help clinicians initiate treatment during the same visit, reducing loss to follow-up—a persistent issue in STI management.
The organizations say combining Testmate’s physician-developed diagnostics with Intermountain’s clinical infrastructure could also lower overall healthcare costs by enabling earlier detection and treatment.
For laboratory leaders, the collaboration highlights a broader trend toward decentralized molecular testing and point-of-care strategies that complement, rather than replace, core laboratory services. As health systems look to improve access and equity while managing costs, partnerships like this one may foreshadow how labs extend their impact beyond traditional walls.
What the VA’s New Baylor Genetics Contract Means for Clinical Lab Leaders.
For clinical laboratory leaders tracking the growing role of precision medicine in federal healthcare systems, the US Department of Veterans Affairs (VA) has taken another significant step toward broad genomic integration.
Baylor Genetics announced it has been awarded a multi-year national contract to provide pharmacogenomic (PGx) testing and germline genetic testing—including hereditary cancer analysis—to veterans across the VA’s nationwide network.
The company did not disclose the value of the multi-year award. However, federal contract filings indicate that at least one delivery order for PGx testing issued to Baylor Genetics in September was valued at $11.4 million, according to GovTribe.com, which tracks federal contract data.
Targeted Testing to Personalize Care Across the VA
Under the agreement, Baylor Genetics will supply PGx testing designed to help VA clinicians understand how a patient’s genetic makeup may influence their response to medications, particularly those used for mental health conditions. By identifying gene variants that affect drug metabolism and effectiveness, PGx insights can help shorten the time to symptom relief, reduce adverse effects, and support more individualized treatment plans.
The contract also includes hereditary cancer testing to identify genetic risk, inform active surveillance strategies, and guide care decisions for both patients and potentially at-risk family members.
Kengo Takishima, chairman and CEO of Baylor Genetics, noted, “By providing high-quality genetic insights, we aim to empower VA providers with the tools they need to improve treatment outcomes and ensure that those who have served our country receive the best possible care.”
These testing services will be available to all veterans across the VA system.
For lab leaders, the agreement signals continued federal investment in genomic tools that can shape personalized care at scale and highlights the expanding opportunities for laboratories positioned to support large, integrated health networks with advanced testing capabilities.
Teen researchers in suburban Atlanta may have cracked one of diagnostics’ toughest challenges: early Lyme detection. Their CRISPR test shows promise for identifying infection long before standard tools can.
For laboratory leaders navigating a rapidly shifting diagnostics landscape, a new signal of future innovation is emerging from an unexpected place: a suburban high school lab in Georgia. Lambert High School’s student researchers have engineered a CRISPR-based prototype that may detect Lyme disease days after infection—a potential breakthrough that, if validated, underscores how quickly synthetic biology is advancing and how early the next generation is entering the field.
Clinical laboratory professionals will be happy to note the promising work that the next generation of lab scientists has started.
The students, all part of Lambert High School’s elite synthetic biology team near Atlanta, set out to solve what senior Claire Lee called one of medicine’s most stubborn blind spots. “We’re doing something in our high school lab that could potentially have a huge impact for, like, millions of people,” she said. “This thing could help save lives.”
Using CRISPR, the powerful gene-editing tool, the teens developed a prototype test that appears capable of detecting Lyme disease just two days after infection, far earlier than the two-week window required by current assays. Although based on simulated blood serum and still in proof-of-concept stages, their findings were compelling enough to earn praise from scientists and secure a top-10 finish at the International Genetically Engineered Machine (iGEM) competition in Paris.
High School Genetic Engineers With an Ambitious Plan
Led by team captains Sean Lee and Avani Karthik, the CRISPR-based system targets a protein produced in the earliest moments of Lyme infection. “One of the biggest problems with Lyme is the lack of, like, being able to diagnose it,” Karthik said. They even met one patient who went “15 years without a diagnosis.”
Their idea was to use CRISPR to cut away extraneous DNA, revealing the protein so it could be detected with a rapid, kit-style test which is much like the COVID-19 diagnostic format. The students also explored using a different CRISPR system to block Lyme-causing bacteria as a potential therapeutic alternative to antibiotics.
But the team’s vision initially met resistance. Biotechnology teacher Kate Sharer said she warned students, “This project in particular, I told them: this is very high risk, high reward.” She admitted, “I couldn’t imagine any of this working,” though she supported their efforts. External experts were similarly cautious. As co-captain Sean Lee recalled,
“They did tell us in the beginning that this might not be so feasible because you’re trying to tackle such a big thing.”
A Top-Notch Lab Inside a Public School
Lambert’s program stands out nationally. Its county-funded, corporate-supported lab rivals those at universities, and the school draws families who relocate specifically for opportunities like iGEM. The team—entirely Asian-American this year and mostly children of immigrants—accepts roughly 10 members from about 100 applicants. Students pitch project ideas, test into the program, and endure what the team calls “insanely long hours.”
In September, after months of work, the students saw the data they had hoped for. Their system flagged early Lyme markers in as little as two days. It wasn’t human-blood–validated, but it was enough to push the project forward.
They spent the last weeks before the competition building a website, compiling results and pulling all-nighters to finalize their presentation.
Showdown in Paris
Arriving in Paris in late October, Lambert joined more than 400 teams from around the globe. Projects ranged from designing Mars-ready crops to developing enzymes to fight indoor mold. Janet Standeven, who oversees iGEM’s high school division and founded Lambert’s program, said she believes synthetic biology education is essential.
Janet Standeven noted that when federal funding for statewide programs was cut, she felt “absolutely devastated” and “angry,” though a judge has since temporarily restored the support. (Photo credit: Engineering Biology Research Consortium)
Stanford professor and iGEM co-founder Drew Endy warned that the U.S. risks losing ground in biotechnology as China accelerates national investment. “It’s urgent that leadership of the next generation of biotechnology has a strong presence in America,” he said. After seeing Lambert’s work, he added, “They appear to have developed a better diagnostic for Lyme disease than anything I’ve seen before.”
China’s Great Bay team ultimately won the grand prize. Lambert, nominated in five categories, earned the award for best software tool and finished among the top 10 high school teams worldwide—the only American team to do so.
For the Lambert students, the recognition mattered, but the mission mattered more. As Claire Lee put it, working on a test with the potential to save lives made every long night “worth it.”
A new open-source platform enhances the interpretability of CBC-based machine-learning models for sepsis prediction, offering improved transparency and clinical utility.
Laboratory leaders watching the evolution of clinical AI tools now have a new development to track: a fully open-source web application designed to make machine-learning–based sepsis prediction more interpretable and accessible.
A new study in The Journal of Applied Laboratory Medicine introduces SBC-SHAP, an interactive platform that visualizes how complete blood count (CBC) values influence individual patient risk scores.
The researchers say the tool was created to address a longstanding barrier: although CBC-based sepsis prediction models have shown promise, clinicians often struggle to understand why those models flag a patient as high-risk. As the study notes, prior lab approaches “do not explain how a specific value, such as white blood cell count, contributes to risk predictions.” Compounding the issue, some existing tools “required programming expertise that many clinicians lack.”
A New Way to View CBC-Based Sepsis Risk
Early sepsis detection remains a priority for hospitals, given that faster recognition leads to earlier intervention and improved outcomes. CBC parameters—white blood cells, red blood cells, hemoglobin, mean corpuscular volume, platelets—are routinely available and could serve as early indicators. Yet, the complexity of machine-learning (ML) algorithms has limited the usefulness of CBC-based prediction.
To tackle this issue, the research team developed a graph-based approach that incorporates time-series information into ML models, enabling predictions that account for trends rather than isolated values. The authors also evaluated whether adding specific ratios to a healthy reference baseline could bolster performance.
According to the paper, the new approach “increased the sensitivity at 80% specificity across all ML models from 78.2% to 82.9% on an internal dataset.” When tested on an external dataset from an independent tertiary-care center, sensitivity improved “from 65.4% to 73.4%.”
Interpretable Outputs Meant for Real Clinical Use
The web tool itself, dubbed SBC-SHAP, was built to interpret the ML predictions. It offers clinicians an interactive view showing how age, sex, and specific CBC values contribute to a risk score.
In an example, the authors highlight that the tool “breaks out patient age, sex, and hemoglobin values and how white blood cells, red blood cells, and mean corpuscular volume indicate patient risk.” Another example shows how clinicians can adjust or “correct prior values for a more accurate estimate of sepsis risk.”
Users can drill into individual CBC measurements, view explanations for each predicted risk value, and filter cases depending on whether particular test results are available. As the authors put it, the platform allows clinicians to “investigate how specific feature values contribute to predicted sepsis risks” and tailor the view for “diverse use cases.”
The tool is open-source and freely accessible, which researchers say is central to making
ML-enhanced diagnostics feasible for everyday practice.
For laboratory directors and diagnostic strategy teams, SBC-SHAP illustrates where AI in laboratory medicine is heading. Leaders are now seeing tools that not only predict, but also explain. As clinical teams grow increasingly cautious about “black-box” algorithms, transparent ML models that show their work may gain faster adoption.
This study also reinforces the ongoing importance of well-curated CBC data. By leveraging widely available hematology parameters, the authors demonstrate that meaningful AI-driven risk stratification does not always require advanced or specialty assays.
As labs plan their digital and clinical decision-support strategies, tools like SBC-SHAP signal a shift toward accessible, clinician-friendly ML applications. The researchers highlight the tool’s potential to support real-time decision-making, noting that it allows users to explore predictions and feature contributions without needing specialized programming skills.
Researchers from the London School of Hygiene and Tropical Medicine project that bloodstream infections caused by resistant bacteria will spike among adults aged 74 and older by 2030.
For laboratory leaders, new modeling research underscores a mounting challenge in infectious disease surveillance: the rise of drug-resistant bloodstream infections (BSIs) across Europe. According to a study published in PLOS Medicine, the rate of BSIs caused by antimicrobial-resistant bacteria is expected to climb sharply over the next five years—driven largely by an aging population.
A news release from CIRAP explained that researchers from the London School of Hygiene and Tropical Medicine analyzed data from more than 12 million blood cultures collected across 29 European countries between 2010 and 2019. Using those findings, they projected BSI rates through 2050 across 38 bacteria–antibiotic combinations, revealing what they called a “clear and consistent relationship” between infection rates, age, and sex. “With substantial sub- and national-variation, the consistency and clear shape of some relationships provide evidence for the inclusion of age and sex in any predictions of future AMR burden,” the authors wrote.
BSI Rates Expected to Increase
The study’s forecasts are sobering. By 2030, BSI rates are expected to increase dramatically among older adults (74 years and up), while stabilizing or even declining among younger groups. Incidence is also predicted to rise faster in men than in women across most bacterial species. Even under optimistic public health scenarios, the team found that achieving a 10% reduction in infections by 2030 would only be feasible for about two-thirds of bacteria–antibiotic pairings.
Senior study author Gwen Knight, PhD, noted, “Combining these factors with demographic and infection trends really highlighted how challenging it will be to reverse the steady rise in bloodstream infections across Europe.” (Photo credit: London School of Hygiene and Tropical Medicine)
For laboratories, the findings highlight the growing importance of targeted surveillance, age-stratified reporting, and real-time resistance data to guide treatment and public health interventions. As Knight and her colleagues conclude, intervention strategies must account for demographic shifts—because the burden of resistance, much like the population it affects, is rapidly aging.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
The IVD industry’s consolidation surge continues unabated, as advances in AI-driven genomics and a flurry of private equity deals reshape the sector for a data-driven decade ahead.
The in vitro diagnostics (IVD) market is entering a new phase of transformation, defined by innovation at the technology level and consolidation at the corporate level, as strategic buyers and investors reshape the competitive landscape.
In the latest move, QIAGEN announced plans to acquire Parse Biosciences for up to $280 million, a deal that will expand QIAGEN’s Sample technologies into the rapidly growing single-cell sequencing market. The acquisition gives QIAGEN access to Parse’s Evercode technology and massive-scale datasets—critical assets as AI-driven drug discovery and predictive biology become central to life sciences. The move underscores QIAGEN’s bet that future diagnostic and therapeutic breakthroughs will hinge on scalable, data-rich technologies rather than traditional instrument-based models.
The Dark Report noted recently in its ranking of top IVD companies that Qiagen was #10, a jump of three spots up from its prior ranking.
Alex Rosenberg, PhD, CEO and co-founder of Parse Biosciences added, “As our team joins QIAGEN, we want to accelerate that mission and extend the reach of our technology to more customers around the world. QIAGEN’s strong commitment to Sample technologies and its global infrastructure make it an ideal partner for our next stage of growth.” (Photo credit: Parse Biosciences)
M&A Highlights
The QIAGEN–Parse deal follows months of high-profile M&A activity reshaping the diagnostics sector.
In October, Hologic agreed to an $18.3 billion buyout by Blackstone and TPG, marking one of the largest private equity transactions in healthcare this year. The move takes a top-15 IVD and imaging company private, reflecting both investor confidence in the steady revenues of women’s health diagnostics and a broader pattern of capital consolidation in the space. Analysts suggest that private equity firms are seeking predictable, cash-generating platforms while large corporations increasingly focus on growth through specialization or divestment.
That strategy is on display at Siemens Healthineers, which is reportedly exploring a $7 billion divestiture of its diagnostics division to firms including Blackstone, KKR, and CVC Capital Partners. Such a sale would streamline Siemens’ portfolio around imaging and oncology technologies, while potentially placing one of the world’s largest IVD suppliers under new ownership.
Taken together, these deals highlight a defining moment for the diagnostics industry. Major corporations are repositioning their portfolios around data, AI, and precision medicine, while investors are moving aggressively to capture value in an industry that proved its resilience during and after the pandemic.
For laboratory leaders, the implications are clear: consolidation is accelerating, supply chains and vendor relationships may shift, and innovation is increasingly concentrated among fewer, but more powerful, players.
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This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
