Initial analyses also shows AI screening lowers associated radiologist image reading workload by half
Both radiologists and pathologists analyze images to make cancer diagnoses, although one works with radiological images and the other works with tissue biopsies as the source of information. Now, advances in artificial intelligence (AI) for cancer screenings means both radiologists and pathologists may soon be able to detect cancer more accurately and in significantly less time.
Pathologists may find it instructive to learn more about how use of this technology shortened the time for the radiologist to sign out the case without compromising accuracy and quality.
Even better, AI screenings reduced doctors’ workload in interpreting mammography images by nearly 50%, the news release states. Such an improvement would also be a boon to busy pathology practices were this technology to become available for tissue biopsy screenings as well.
“The greatest potential of AI right now is that it could allow radiologists to be less burdened by the excessive amount of reading,” said breast radiologist Kristina Lång, MD, PhD, Associate Professor in Diagnostic Radiology at Lund University. Pathologists working with clinical laboratories in cancer diagnosis could benefit from similar AI advancements. (Photo copyright: Lund University.)
Can AI Save Time and Improve Diagnoses?
One motivation for conducting this study is that Sweden, like other nations, has a shortage of radiologists. Given ongoing advances in machine learning and AI, researchers launched the study to assess the accuracy of AI in diagnosing images, as well as its ability to make radiologists more productive.
The MASAI trial was the first to demonstrate the effectiveness of AI-supported screening, the Lund news release noted.
“We found that using AI results in the detection of 20% (41) more cancers compared with standard screening, without affecting false positives. A false positive in screening occurs when a woman is recalled but cleared of suspicion of cancer after workup,” said breast radiologist Kristina Lång, MD, PhD, clinical researcher and associate professor in diagnostic radiology at Lund University, and consultant at Skåne University Hospital, in the news release.
Not only did the researchers explore the accuracy of AI-supported mammography compared with radiologists’ standard screen reading, they also looked into AI’s effect on radiologists’ screen-reading workload, the Lancet paper states.
Impetus for the research was the shortage of radiologists in Sweden and other countries. A Lancet news release noted that “there is a shortage of breast radiologists in many countries, including a shortfall of around 41 (8%) in the UK in 2020 and about 50 in Sweden, and it takes over a decade to train a radiologist capable of interpreting mammograms.”
More Breast Cancer Identified with Lower Radiologist Workload When Using AI Screening
Here are study findings, according to the Lancet paper:
AI-supported screening resulted in 244 cancers of 861 women recalled.
Standard screening found 203 screen-detected cancers among 817 women who were recalled.
The false positive rate of 1.5% was the same in both groups.
41 (20%) more cancers were detected in the AI-enabled screening group.
Screen readings by radiologists in the AI-supported group totaled 46,345, as compared to 83,231 in the standard screening group.
Workload dropped by 44% for physicians using screen-reading with AI.
“We need to see whether these promising results hold up under other conditions—with other radiologists or other algorithms,” Lang said in the Lund news release.
“The results from our first analysis show that AI-supported screening is safe since the cancer detection rate did not decline despite a reduction in the screen-reading workload,” she added.
Is AI a Threat to Radiologists?
The use of AI in the Swedish study is an early indication that the technology is advancing in ways that may contribute to increased diagnostic accuracy for radiologists. But could AI replace human radiologists’ readings. Not anytime soon.
“These promising interim safety results should be used to inform new trials and program-based evaluations to address the pronounced radiologist shortage in many countries. But they are not enough on their own to confirm that AI is ready to be implemented in mammography screening,” Lång cautioned. “We still need to understand the implications on patients’ outcomes, especially whether combining radiologists’ expertise with AI can help detect interval cancers that are often missed by traditional screening, as well as the cost-effectiveness of the technology.”
“These tools work best when paired with highly trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist,” she added.
Whether a simple tool or an industry-changing breakthrough, pathology groups and clinical laboratories that work with oncologists can safely assume that AI advances will lead to more cancer research and diagnostic tools that enable earlier and more accurate diagnoses from tissue biopsies and better guidance on therapies for patients.
Technology could enable patients to monitor their own oxygen levels and transmit that data to healthcare providers, including clinical laboratories
Clinical laboratories may soon have a new data point to add to their laboratory information system (LIS) for doctors to review. Researchers have determined that smartphones can read blood-oxygen levels as accurately as purpose-built pulse oximeters.
Conducted by researchers at the University of Washington (UW) and University of California San Diego (UC San Diego), the proof-of-concept study found that an unmodified smartphone camera and flash along with an app is “capable of detecting blood oxygen saturation levels down to 70%. This is the lowest value that pulse oximeters should be able to measure, as recommended by the US Food and Drug Administration,” according to Digital Health News.
This could mean that patients at risk of hypoxemia, or who are suffering a respiratory illness such as COVID-19, could eventually add accurate blood-oxygen saturation (SpO2) readings to their lab test results at any time and from any location.
“In an ideal world, this information could be seamlessly transmitted to a doctor’s office. This would be really beneficial for telemedicine appointments or for triage nurses to be able to quickly determine whether patients need to go to the emergency department or if they can continue to rest at home and make an appointment with their primary care provider later,” Matthew Thompson, DPhil, Professor of Global Health and Family Medicine at University of Washington, told Digital Health News. Clinical laboratories may soon have a new data point for their laboratory information systems. (Photo copyright. University of Washington.)
UW/UC San Diego Study Details
The researchers studied three men and three women, ages 20-34. All were Caucasian except for one African American, Digital Health News reported. To conduct the study, a standard pulse oximeter was placed on a finger and, on the same hand, another of the participant’s fingers was placed over a smartphone camera.
“We performed the first clinical development validation on a smartphone camera-based SpO2 sensing system using a varied fraction of inspired oxygen (FiO2) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG [photoplethysmography] methods on a wider range of SpO2 values (70–100%) than prior studies (85–100%). We built a deep learning model using this data to demonstrate an overall MAE [Mean Absolute Error] = 5.00% SpO2 while identifying positive cases of low SpO2 < 90% with 81% sensitivity and 79% specificity,” the researchers wrote in NPJ Digital Medicine.
When the smartphone camera’s flash passes light through the finger, “a deep-learning algorithm deciphers the blood oxygen levels.” Participants were also breathing in “a controlled mixture of oxygen and nitrogen to slowly reduce oxygen levels,” Digital Health News reported.
“The camera is recording a video: Every time your heart beats, fresh blood flows through the part illuminated by the flash,” Edward Wang, PhD, Assistant Professor of Electrical and Computer Engineering at UC San Diego and senior author of the project, told Digital Health News. Wang started this project as a UW doctoral student studying electrical and computer engineering and now directs the UC San Diego DigiHealth Lab.
“The camera records how much that blood absorbs the light from the flash in each of the three color channels it measures: red, green, and blue. Then we can feed those intensity measurements into our deep-learning model,” he added.
The deep learning algorithm “pulled out the blood oxygen levels. The remainder of the data was used to validate the method and then test it to see how well it performed on new subjects,” Digital Health News reported.
“Smartphone light can get scattered by all these other components in your finger, which means there’s a lot of noise in the data that we’re looking at,” Varun Viswanath, co-lead author in the study, told Digital Health News. Viswanath is a UW alumnus who is now a doctoral student being advised by Wang at UC San Diego.
“Deep learning is a really helpful technique here because it can see these really complex and nuanced features and helps you find patterns that you wouldn’t otherwise be able to see,” he added.
Each round of testing took approximately 15 minutes. In total the researchers gathered more than 10,000 blood oxygen readings. Levels ranged from 61% to 100%.
“The smartphone correctly predicted whether the subject had low blood oxygen levels 80% of the time,” Digital Health News reported.
Smartphones Accurately Collecting Data
The UW/UC San Diego study is the first to show such precise results using a smartphone.
“Other smartphone apps that do this were developed by asking people to hold their breath. But people get very uncomfortable and have to breathe after a minute or so, and that’s before their blood-oxygen levels have gone down far enough to represent the full range of clinically relevant data,” said Jason Hoffman, a PhD student researcher at UW’s UbiComp Lab and co-lead author of the study.
The ability to track a full 15 minutes of data is a prime example of improvement. “Our data shows that smartphones could work well right in the critical threshold range,” Hoffman added.
“Smartphone-based SpO2 monitors, especially those that rely only on built-in hardware with no modifications, present an opportunity to detect and monitor respiratory conditions in contexts where pulse oximeters are less available,” the researchers wrote.
“This way you could have multiple measurements with your own device at either no cost or low cost,” Matthew Thompson, DPhil, Professor of Global Health and Family Medicine at University of Washington, told Digital Health News. Thompson is a professor of both family medicine and global health and an adjunct professor of pediatrics at the UW School of Medicine.
What Comes Next
The UW/UC San Diego research team plans to continue its research and gather more diversity among subjects.
“It’s so important to do a study like this,” Wang said. “Traditional medical devices go through rigorous testing. But computer science research is still just starting to dig its teeth into using machine learning for biomedical device development and we’re all still learning. By forcing ourselves to be rigorous, we’re forcing ourselves to learn how to do things right.”
Though no current clinical laboratory application is pending, smartphone use to capture biometrics for testing is increasing. Soon, labs may need a way to input all that data into their laboratory information systems. It’s something to consider.
Australian government rules lab employee’s rogue actions jeopardized patient care
In an example of “if something can go wrong in the lab, it will,” a senior histology laboratory worker at Royal North Shore Hospital in Sydney, Australia, has been banned for life from providing health services for allegedly swapping patient tissue samples in an attempt to harm a lab co-worker, according to The Sydney Morning Herald.
Dianne Reader, 61, was a “a senior technical officer at the Anatomical Pathology Laboratory with more than 40 years’ experience,” the Herald noted, adding that Reader “had swapped 20 patient tissue samples, leading to the misdiagnosis of at least one patient.”
Her motivation, the Herald reported, was to “target and discredit her colleague.”
“Ms. Reader repeatedly engaged in conduct that demonstrated a flagrant disregard for patient health and safety” that may have “serious adverse consequences for the patients involved,” Tony Kofkin at Australia’s Health Care Complaints Commission told The Sydney Morning Herald. This is a lesson that clinical laboratory managers can never be too diligent because something unexpected can happen at any moment—and these events have the potential to cause serious patient harm. (Photo copyright: LinkedIn.)
Lab Staff Suspicions Raised
The sample mixups began in 2020, when the targeted employee (employee A) was working specimen “cut-up” duty. After two incidents of sample mixups being found in her work, she was removed from the duty for three weeks. The Herald reported that the employee told a co-worker she believed she was being “framed.” When she returned to cut-up duty, she took photographs of her work as a precautionary measure.
The employee’s photos served as evidence when that day’s work again showed errors, now the third incident of sample mixups. Upon further research, a total of four occasions of swapping samples were discovered between March and June of 2020.
Laboratory records showed that Reader was responsible for unpacking the tissue processor on each of those occasions, the Herald noted.
Lab workers noted a strained working relationship between Reader and the targeted employee. “One co-worker, a hospital scientist, told the [Health Care Complaints Commission] the working relationship between Reader and ‘Employee A’ could be ‘frosty,’” the Herald reported.
Lab staff apparently grew suspicious when a co-worker discovered that Reader “was only looking up gall bladder and appendices samples on the mornings Employee A had been ‘cutting up’ (dissecting and describing samples before placing them into cassettes for processing).” Lab staff also confirmed to the Health Care Complaints Commission that Reader had improperly accessed 43 patient records, adding that “there was no reason for her to have accessed the records when she did,” The Sydney Morning Herald reported.
Reader, according to the Herald, “denied she had ever interchanged specimens or improperly accessed patient files in two recorded interviews in July 2020, and maintains her innocence.”
Nevertheless, Tony Kofkin, the Commission’s complaint operations Executive Director, found that Reader “posed a risk to the health and safety of the public because she was prepared to risk patient safety in order to discredit her colleague.
“Ms. Reader repeatedly engaged in conduct that demonstrated a flagrant disregard for patient health and safety,” he wrote in the Commission’s findings, adding that Reader “had shown no remorse or insight into her conduct ‘despite the overwhelming evidence’ and as such posed a permanent risk to the health and safety of the public,” the Herald reported.
The Health Care Complaints Commission determined that Reader’s actions were “motivated by a desire to target and discredit her colleague.” The Commission’s decision prevents Reader from forever providing healthcare services, including medical, hospital, pharmaceutical, forensic pathology, or health education services, according to the Herald.
Who Was Harmed by the Swapped Samples?
Reader’s alleged actions had significant consequences. One patient’s swapped sample nearly led her to having a hysteroscopy for a glandular polyp, when in fact she was suffering with endometrial hyperplasia. Thankfully, the histology laboratory staff discovered the mistake and quickly contacted the patient’s doctor to ensure the proper surgery was performed, the Herald noted.
Things could have gone much worse for that patient and for others. Clinical laboratory managers should look upon this as a cautionary tale and consider how to ensure similar—and very rare—occurrences do not happen in their own laboratories.
Incident serves as a reminder that all clinical laboratories can be just one mistake away from reporting erroneous results to a number of doctors and patients
In May, more than 400 patients who agreed to take the Galleri multi-cancer early detection (MCED) blood test from GRAIL—a California-based biotechnology company that is owned by genetic technology developer Illumina—received letters falsely suggesting they had cancer, according to the Financial Times which broke the news.
The Times reported that a software error had caused GRAIL’s telemedicine provider PWNHealth, which is owned by Everly Health Solutions, to send an erroneous letter to 408 patients misinforming them that “they had a signal in their blood suggesting they could have cancer.”
In a statement, GRAIL said the letters were “in no way related to or caused by an incorrect Galleri laboratory test result” and that “the letters were inadvertently triggered by a PWNHealth software configuration issue, which had now been disabled,” Financial Times reported.
GRAIL, which stated that more than half of the people who received the letters hadn’t even had blood drawn for the test, also added that “no patient health information has been disclosed or breached due to this issue, and no patient harm or adverse events have been reported,” the Financial Times noted.
Nevertheless, it’s not hard to imagine the effect the letters had on those people. No clinical laboratory wants national headlines as a consequence of an error that causes incorrect test results to be reported to doctors and patients. How to prevent such occurrences is a challenge to all clinical laboratory managers.
According to GRAIL, its Galleri multicancer early detection test “can detect a signal shared by more than 50 cancer types and predict the tissue type or organ associated with the signal. At least 45 of these cancers lack recommended screening tests in the US today.” Clinical laboratories that draw the blood sample for the genetic test ship the collection kit directly to GRAIL’s laboratory for processing. (Photo copyright: GRAIL.)
What Went Wrong
PWNHealth said in a statement that the letters were sent due to “a misconfiguration of our patient engagement platform used to send templated communications to individuals,” CBS News reported.
Financial Times reported that the letters were issued from May 10-18, and on May 19 PWNHealth informed GRAIL of the problem. “We addressed the underlying problem within an hour of becoming aware of it and have implemented additional processes to ensure it does not happen again,” PWNHealth said. “In partnership with GRAIL, we started contacting impacted individuals within 36 hours.”
The software configuration fault was deactivated by PWNHealth, and GRAIL notified affected individuals via phone, email, and regular mail until all had been informed of the error, GRAIL said.
Though GRAIL reacted quickly, there has been fallout caused by the letters. Insurer confidence may have been damaged.
According to Financial Times, customers of life insurance company MassMutual and another unnamed insurer had “been affected” by the erroneous letters. As a result, MassMutual had suspended a pilot program and the unnamed insurer was “reviewing its relationship” with GRAIL.
About GRAIL and the Galleri Liquid Biopsy Test
GRAIL was founded in 2015 in San Francisco, California, with the goal of detecting early-stage cancer. They developed the Galleri liquid biopsy test which requires only one blood sample and can “detect a signal shared by over 50 types of cancer with 99.5% specificity and predict the cancer signal origin with high accuracy to help guide next steps,” according to the company’s website.
The $949 test can only be obtained by a doctor’s prescription. At this time it is not covered by insurance, Healthnews reported.
According to a GRAIL Galleri fact sheet, “All cells—cancer and healthy ones—shed DNA, which is called cell-free DNA (cfDNA), into the bloodstream. … After a blood sample is taken at a healthcare provider’s office or at a GRAIL partner laboratory, the Galleri test uses the power of next-generation sequencing and machine-learning algorithms to analyze cfDNA methylation patterns.
“The test uses these methylation patterns to determine if a cancer signal is present and, if so, predict the tissue type or organ where the cancer signal originated.
“If a cancer signal is detected, a healthcare provider will determine next steps for diagnostic evaluation, which may include personal and family health history, physical examination, and guideline directed evaluation(s) including lab work and imaging.”
Flashback to Another Notable Lab Error
This is not the first time inaccurate genetic test results have been sent out to patients.
In 2017, Dark Daily’s sister publication, The Dark Report, covered how genetic test developer Invitae Corporation had reported inaccurate genetic test results for up to 50,000 patients over a period of 11 months from September 2016 to July 2017.
In a statement, Invitae said the error occurred “because of the unique characteristics of how we we’re testing for the MSH2 Boland inversion, our quality control checks did not catch omission of the components of the assay. … As soon as the omission was recognized and relevant components returned to the assay, it once again performed properly. We have added two separate quality controls to ensure this issue will not reoccur.”
Negative Online Reviews Hurt Businesses including Clinical Laboratories
In its article, Status Labs references a 2021 PEW Research survey which found that “More than eight-in-10 US adults (86%) say they get news from a smartphone, computer, or tablet ‘often’ or ‘sometimes,’ including 60% who say they do so often. This is higher than the portion who get news from television, though 68% get news from TV at least sometimes and 40% do so often. Americans turn to radio and print publications for news far less frequently, with half saying they turn to radio at least sometimes (16% do so often) and about a third (32%) saying the same of print (10% get news from print publications often).”
Status Labs also cited studies showing the impact of negative press online. One study by Trustpilot showed that 90% of consumers said they will not frequent a business that has a bad reputation.
Another study by the University of Pennsylvania found that “negative reviews, messages, or rumors hurt product evaluations and reduce purchase likelihood and sales.”
Vigilance Is the Key
Clinical laboratory leaders are keenly aware that a lab’s reputation can make or break its business. This incident involving GRAIL and its telemedicine provider PWNHealth is a reminder that vendors providing services to medical laboratories can be a source of problems ranging from breaches of protected health information (PHI) to misstatements or misreporting of clinical laboratory test results.
Thus, it behooves lab managers to constantly monitor information leaving the lab, and to ensure all test results sent to patients and doctors are valid and accurate.
Study may also result in new clinical laboratory tools for determining antimicrobial resistance and efficacy of existing antibiotics
Researchers find it increasingly difficult to develop antibiotics that are effective against strains of bacteria that display antibiotic resistance—a subset of antimicrobial resistance (AMR). However, a new study provides a glimmer of hope and may spur clinical laboratories to look at this research in novel ways.
Conducted at the University of California Santa Barbara, the study looked at more than 500 antibiotic-bacteria combinations. The researchers discovered that several widely used, FDA-approved, antibiotics may be more useful than previously thought against a large range of bacterial infections, said infectious disease specialist Judy Stone, MD, in an article she penned for Forbes titled, “Why Antibiotics Fail—and How We Can Do Better.”
The researchers also discovered a common culture medium that enables a better assessment of the properties of various strains of bacteria to resist different antibiotics.
Clinical laboratories and microbiologists are tasked with plating and growing bugs to identify a specific bug, what strain of bug, and whether that strain has resistance to specific antibiotics. Thus, this research touches on what they do daily. It is something that may provide microbiologists with new approaches to detect AMR more accurately.
“We know there are a variety of reasons why antibiotics don’t work as predicted, from wrongly prescribed doses to infrequent administration, but another less noticeable reason is that lab testing can show a bacteria is susceptible to antibiotics when it’s actually not. You know, the whole in vitro (culture plate) versus in vivo (life) balance,” wrote Judy Stone, MD, infectious disease expert, in her Forbes article. Clinical laboratories may soon have a better way of identifying antibiotic resistance in deadly bacteria. (Photo: LinkedIn profile.)
UCSB Antimicrobial Study Details
Antibiotic-resistant infections are responsible for more than 32,000 deaths in the US and 1.27 million globally every year, Forbes reported. A study like this can have a far-reaching impact.
To conduct their study, Michael Mahan, PhD, Professor of Molecular, Cellular, and Developmental Biology at UCSB, and his team at the Mahan Lab on the UCSB campus, used Fisher Scientific’s Gibco Dulbecco’s Modified Eagle Medium (DMEM), a basal medium for supporting the growth of many different mammalian cells.
The DMEM predicted antibiotic effectiveness better than Mueller Hinton Broth (MHB), another growth medium from Thermo Fisher Scientific that has been used in clinical laboratories by World Health Organization (WHO) decree since 1968, Forbes reported.
Assays were run against 13 isolates from nine species of bacteria to determine the efficacy of 15 different antibiotics. Using DMEM, the team found different sensitivities in 15% of the bacterial isolates tested in vitro compared to MHB.
In Mahan’s follow-up tests, which looked at mice infected with different bacteria, MHB was accurate in 54% of test predictions while DMEM was accurate 77% of the time. Part of the reason, Mahan believes, is because DMEM is more physiologic and closer in conditions to people (in vivo), Forbes reported.
“People are not Petri plates—that is why antibiotics fail. Testing under conditions that mimic the body improves the accuracy by which lab tests predict drug potency,” said Mahan in a UCSB press release.
“I think it has merit. I think this study has been very well-designed … and showed that this makes clinical sense … If it bears out in humans, it will be clinically very significant,” pulmonologist Ken Yomer Yoneda, MD, Professor Emeritus, Department of Internal Medicine at UC Davis Health, told Forbes.
Though the major limitation of the study is that it was conducted on mice and not humans, Yoneda said it gives an indication of potential success with humans. “If it bears out in humans it will be clinically very significant,” he told Stone for her Forbes article.
Rodney Rohde, PhD, Professor and Chair of Clinical Lab Science Program at Texas State University also shared enthusiasm on the findings. According to Stone, “[Rohde] was ‘intrigued’ by the finding that using a physiologic media predicted ‘a change in susceptibility’ thresholds used to categorize patient isolates as susceptible or resistant.
“He was also ‘excited about the results of increasing diagnostic accuracy’ with especially difficult-to-treat organisms,” she noted.
“Rohde added that the issue of these clinical breakpoints—setting the level at which an organism is defined as ‘sensitive’ or ‘resistant’ to an antibiotic is a hot topic, undergoing considerable discussion in lab circles. Multiple agencies need to reach agreement for the standards that are used globally, both in the US and Europe,” Stone wrote.
Old Drug, New Tricks
According to the UCSB press release, “Physicians are aware of the flaws in the gold-standard test [MHB]. When recommended antibiotics do not work, they must rely on their experience to decide on the appropriate antibiotic(s) for their patients. This study provides a potential solution to address the disparity between antibiotics indicated by standard testing and actual patient outcomes.”
Infectious disease physician Lynn Fitzgibbons, MD, remarked in the UCSB press release, “Re-evaluation of FDA-approved antibiotics may be of far greater benefit than the time and cost of developing new drugs to combat antimicrobial resistance, potentially leading to significant life-savings and cost-savings.”
In her Forbes article, Stone wrote, “Pharmaceutical companies are abandoning the acute infectious disease market and few new antibiotics are in sight. Pharma is profit driven and antibiotics are simply not as lucrative as life-style drugs (like Viagra/Cialis or Rogaine for hair loss) or those for chronic diseases. So, Mahan et al.’s findings are welcome news indeed.”
Once further studies validate the UCSB study findings and allow their use in clinical settings for patient care, clinical laboratories and microbiologists may have new tools for accurately determining a bacterium’s ability to resist existing antibiotics or its susceptibility to antibiotics not currently used to treat certain infections.
Level 3 bio labs handle Ebola, smallpox and other deadly diseases, and may play a role in research into the human genome
Because of the COVID-19 pandemic, there is a concerted effort to improve public health laboratories and increase the growth of bioresearch. Clinical laboratories across the country are required by law to send specimens of certain infectious diseases to public health labs for testing and analysis. The results of those tests are then reported to the federal Centers for Disease Control and Prevention (CDC), which is working to foster robust connections and relationships between clinical labs and public health labs.
A land transaction for a 1.6-acre purchase between Dallas County and TXRE Properties closed in April. The development of the lab is expected to cost $52 million and should be completed by late 2025 with occupancy as early as January 2026.
The graphic above is an artist rendering of what the new Dallas County Health and Human Services Public Health Laboratory may look like. For some time now, Dallas County has been working to create a hub centered around infrastructure and buildings to be used for bio development and research, public health labs, and even clinical laboratories. (Graphic copyright: 5G Studio Collaborative.)
Continuing Support for HHS
“The large-scale response required for COVID-19 demonstrated the need for the acquisition that will permit the continued support of the HHS efforts in response to the ongoing safety, containment, incident response to emerging and high consequence diseases that could operate at the peak of a crisis without hindering or being hindered by other county operations,” states a Dallas County Commissioners Court Order, D Magazine reported.
“The county currently utilizes owned facilities to provide laboratory services, testing services, and other initiatives,” according to the court order. “These facilities have performance and design shortcomings and have required significant capital expenditure for their ongoing use.
“To avoid leasing space and avoid additional capital investment into deferred and ongoing maintenance, the county has been searching for a suitable location/acquisition to collocate uses/departments into a centralized, efficient, and suitable laboratory,” the court order continued.
Lab Will Conduct Research into Potentially Fatal Diseases
The facility will pursue becoming a Biological Safety Level-3 laboratory. BSL-3 labs typically conduct research or work on microbes that can cause serious and potentially fatal disease through inhalation. These labs are required to be easily decontaminated. They must also have additional safety measures, including interlocked doors, sealed windows, floors, and walls, and filtered ventilation systems.
“The core diagnostic functions are—along with safety—related to identification, containment, security, and incident response to emerging and high consequence diseases,” the court order notes.
A Georgetown University article published last year concluded there are 148 institutions with BSL-3 laboratories in the US. This number was established by identifying and totaling the number of BSL-3 facilities that published research between 2006 and 2021 using PubMed Central, a full-text archive of biomedical and life sciences journal literature at the US National Institutes of Health’s National Library of Medicine (NIH/NLM).
The creation of this new biosafety lab in Dallas is consistent with the trend of investment dollars being poured into research into the human genome. This type of research, along with the creation of new facilities, can directly lead to new biomarkers that can be utilized in clinical laboratory testing and disease prevention.
