News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

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News, Analysis, Trends, Management Innovations for
Clinical Laboratories and Pathology Groups

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FDA Grants Marketing Authorization to First Ever AI-Powered SaMD Diagnostic Tool for Sepsis That Shares Patient’s Risk within 24 Hours and Works with EHRs

Infection control teams and clinical laboratory managers may want to look at this new product designed to improve the diagnosis and treatment of sepsis

Accurate and fast diagnosis of sepsis for patients arriving in emergency departments is the goal of a new product that was just cleared by the federal Food and Drug Administration (FDA). It is also the newest example of how artificial intelligence (AI) continues to find its way into pathology and clinical laboratory medicine.

Sepsis is one of the deadliest killers in US hospitals. That is why there is interest in the recent action by the FDA to grant marketing authorization for an AI-powered sepsis detection software through the agency’s De Novo Classification Request. The DNCR “provides a marketing pathway to classify novel medical devices for which general controls alone, or general and special controls, provide reasonable assurance of safety and effectiveness for the intended use, but for which there is no legally marketed predicate device,” the FDA’s website states.

Developed by Chicago-based Prenosis, the Sepsis ImmunoScore is an AI and machine learning (ML) Software as a Medical Device (SaMD) used to “guide rapid diagnosis and prediction of sepsis” within 24 hours of the patient’s presentation in an emergency department or hospital, according to a company news release.

In a separate statement, Prenosis announced a commercial distribution deal with Roche, Basel, Switzerland, as well as the SaMD’s availability on Roche’s navify Algorithm Suite (a digital library of medical algorithms).

Unlike a single analyte assay that is run in a clinical laboratory, Prenosis’ AI/ML software uses 22 diagnostic and predictive parameters, along with ML algorithms, to analyze data and produce a clinically actionable answer on sepsis.

It is important for clinical laboratory managers and pathologists to recognize that this diagnostic approach to sepsis brings together a number of data points commonly found in a patient’s electronic health record (EHR), some of which the lab generated and others the lab did not generate.

“Sepsis is a serious and sometimes deadly complication. Technologies developed to help prevent this condition have the potential to provide a significant benefit to patients,” said Jeff Shuren, MD, JD, Director of the FDA’s Center for Devices and Radiological Health, in a statement. “The FDA’s authorization of the Prenosis Sepsis ImmunoScore software establishes specific premarket and post-market requirements for this device type.” Clinical laboratory EHRs contain some of the data points Prenosis’ diagnostic software uses. (Photo copyright: US Food and Drug Administration.)  

How it Works

To assist doctors diagnose sepsis, the ImmunoScore software is first integrated into the patient’s hospital EHR. From there, it leverages 22 parameters including:

Instead of requiring a doctor or nurse to look at each parameter separately, the SaMD tool uses AI “to evaluate all those markers at once”, CNBC noted. It then produces a risk score and four discrete risk stratification categories (low, medium, high, and very high) which correlate to “a patient’s risk of deterioration” represented by:

  • Hospital length of stay.
  • In-hospital mortality.
  • Intensive care unit transfer within 24 hours.
  • Vasopressor use within 24 hours.
  • Need for mechanical ventilation within 24 hours.

By sharing these details—a number from one to 100 for each of the 22 diagnostic and predictive parameters—Sepsis ImmunoScore helps doctors determine which will likely contribute most to the patient’s risk for developing sepsis, MedTech Dive reported.

“A lot of clinicians don’t trust AI products for multiple reasons. We are trying very hard to counter that skepticism by making a tool that was validated by the FDA first, and then the second piece is we’re not trying to replace the clinician,” Bobby Reddy Jr., PhD, Prenosis co-founder and CEO, told MedTech Dive.

Big Biobank and Blood Sample Data

Prenosis, which says its goal is the “enabling [of] precision medicine in acute care” developed Sepsis ImmunoScore using the company’s own biobank and a dataset of more than 100,000 blood samples from more than 25,000 patients.

AI algorithms drew on this biological/clinical dataset—the largest in the world for acute care patients suspected of having serious infections, according to Prenosis—to “elucidate patterns in rapid immune response.”

Carle Foundation Hospital, Urbana, Ill., is one of three Illinois hospitals that helped build the biobank and dataset used by Prenosis, according to a Carle news release.

“It does not work without data, and the data started at Carle,” said critical care specialist Karen White, MD, PhD, Carle Foundation Hospital, St. Louis, MO, in the news release.  “The project involved a large number of physicians, research staff, and internal medicine residents at Carle who helped recruit patients, collect data, and samples,” she said.

Opportunity for Clinical Laboratories

Sepsis is a life-threatening condition based on an “extreme response to an infection” that affects nearly 1.7 million adults in the US each year and is responsible for 350,000 deaths, according to US Centers for Disease Control and Prevention (CDC) data. 

A non-invasive diagnostic tool like Sepsis ImmunoScore will be a boon to emergency physicians and the patients they treat. Now that the FDA has authorized the SaMD diagnostic tool to go to market, it may not be long before physicians can use the information it produces to save lives.

Clinical laboratory managers inspired by the development of Sepsis ImmunoScore may want to look for similar ways they can take certain lab test results and combine them with other data in an EHR to create intelligence that physicians can use to better treat their patients. The way forward in laboratory medicine will be combining lab test results with other relevant sets of data to create clinically actionable intelligence for physicians, patients, and payers.

—Donna Marie Pocius

Related Information:

Prenosis Announces FDA De Novo Marketing Authorization of the Sepsis ImmunoScore  

Prenosis Announces Commercial Distribution Collaboration with Roche for Sepsis ImmunoScore

FDA Authorizes Prenosis Software as First AI Tool That Can Diagnose Sepsis

FDA Round-Up April 5, 2024

FDA Grants De Novo Clearance to AI Tool for Detecting Sepsis

New AI Tool for Sepsis Diagnosis Gets its Start to Research at Carle

An AI Tool to Stop Sepsis

New FDA Regulations of Clinical Decision-Support/Digital Health Applications and Medical Software Has Consequences for Medical Laboratories

Softened FDA regulation of both clinical-decision-support and patient-decision-support software applications could present opportunities for clinical laboratory developers of such tools

Late 2017, the Food and Drug Administration (FDA) released guidelines on how the agency intends to regulate—or not regulate—digital health, clinical-decision-support (CDS), and patient-decision-support (PDS) software applications. The increased/decreased oversight of the development of these physicians’ tools could have important implications for anatomic pathology groups and clinical laboratories.

Physician decision-support software utilizes medical laboratory test data as a significant part of a full dataset used to guide caregivers. Thus, if the FDA makes it easier for developers to get regulatory clearance for these types of products, that could positively impact medical labs’ ability to service their client physicians.

Additionally, clinical pathologists have unique training in diagnosing diseases and understanding the capabilities and limitations of medical laboratory tests in supporting how physicians diagnose disease and make treatment decisions. Thus, actions by the FDA to make it easier for developers of software algorithms that can incorporate clinical laboratory data and anatomic pathology images with the goal of improving diagnoses, decisions to treat, and monitoring of patients have the potential to bring great benefit to the nation’s medical laboratories.

FDA Clarifies Role in Regulating CDS/PDS Applications

The new guidelines clarified items specified in the 21st Century Cures Act, which was enacted by Congress in December of 2016. This Act authorized $6.3 billion in funding for the discovery, development, and delivery of advanced, state-of-the art medical cures.

“Today, we’re announcing three new guidances—two draft and one final—that address, in part, important provisions of the 21st Century Cures Act, that offer additional clarity about where the FDA sees its role in digital health, and importantly, where we don’t see a need for FDA involvement,” FDA commissioner Scott Gottlieb, MD, Commissioner of Food and Drugs, noted in a statement. “We’ve taken the instructions Congress gave us under the Cures Act and [we] are building on these provisions to make sure that we’re adopting the full spirit of the goals we were entrusted with by Congress.”

Helping Doctors’ Decision-Making

The first guideline concerns clinical decision support systems that are designed to help doctors make data-driven decisions about patient care. The new guidelines make it easier for software developers to get regulatory clearance, which, the FDA hopes, will spark innovation and makes regulation more efficient.

“CDS has many uses, including helping providers, and ultimately patients, identify the most appropriate treatment plan for their disease or condition,” Gottlieb said in the FDA’s statement. “For example, such software can include programs that compare patient-specific signs, symptoms, or results with available clinical guidelines to recommend diagnostic tests, investigations or therapy.

“This type of technology has the potential to enable providers and patients to fully leverage digital tools to improve decision making,” Gottlieb continued. “We want to encourage developers to create, adapt, and expand the functionalities of their software to aid providers in diagnosing and treating old and new medical maladies.”

Identifying Digital Health Applications That Receive/Don’t Receive FDA Oversight

The second guideline discusses and delineates which digital health applications are considered low risk and, thus, will not fall under FDA regulations.

Products that are not intended to be used for the diagnosis, cure, mitigation, prevention, or treatment of a condition will not be regulated by the FDA. These technologies are not considered medical devices and may include gadgets such as weight management and mindfulness tools. They can provide value to consumers and the healthcare industry while posing a low risk to patients.

“Similarly, the CDS draft guidance also proposes to not enforce regulatory requirements for lower-risk decision support software that’s intended to be used by patients or caregivers—known as patient-decision-support software (PDS)—when such software allows a patient or a caregiver to independently review the basis of the treatment recommendation,” Gottlieb noted in the statement.

 

Scott Gottlieb

Scott Gottlieb, MD (above), FDA Commissioner of Food and Drugs, noted in a statement, “We believe our proposals for regulating CDS and PDS not only fulfill the provisions of the Cures Act, but also strike the right balance between ensuring patient safety and promoting innovation. Clinical laboratories may find opportunities to work with CDS/PDS developers and support their client physicians. (Photo copyright: FDA.)

However, products that are intended to be used for the diagnosis, cure, mitigation, prevention, or treatment of a condition are considered medical devices and will fall under FDA regulations.

“The FDA will continue to enforce oversight of software programs that are intended to process or analyze medical images, signals from in vitro diagnostic devices, or patterns acquired from a processor like an electrocardiogram that use analytical functionalities to make treatment recommendations, as these remain medical devices under the Cures Act,” noted Gottlieb.

Items such as mobile apps that are utilized to maintain and encourage a healthy lifestyle are not deemed to be medical devices and will fall outside FDA regulations. The guidelines also defined that Office of the National Coordinator for Health Information Technology (ONC)-certified electronic health record (EHR) systems are not medical devices and, thus, will not be regulated by the FDA.

Software-as-a-Medical Device Gets FDA Oversight

The third guidance document deals with the assessment of the safety, performance, and effectiveness of Software as a Medical Device (SaMD).

“This final guidance provides globally recognized principles for analyzing and assessing SaMD, based on the overall risk of the product. The agency’s adoption of these principles provides us with an initial framework when further developing our own specific regulatory approaches and expectations for regulatory oversight and is another important piece in our overarching policy framework for digital health,” Gottlieb noted in the statement.

SaMD is defined by the International Medical Device Regulators Forum (IMDRF) as “software intended to be used for one or more medical purposes that perform these purposes without being part of a hardware medical device.”

Gottlieb noted that the three important guidance documents being issued would continue to expand the FDA’s efforts to encourage innovation in the ever-changing field of digital health. “Our aim is to provide more clarity on, and innovative changes to, our risk-based approach to digital health products, so that innovators know where they stand relative to the FDA’s regulatory framework. Our interpretation of the Cures Act is creating a bright line to define those areas where we do not require premarket review,” he concluded.

What remains to be seen is how the new FDA regulations will impact clinical laboratories and anatomic pathology groups. With the expanding interest in artificial intelligence (AI) and self-learning software systems, healthcare futurists are predicting a rosy future for informatics products that incorporate these technologies. Hopefully, with these new guidelines in place, innovative clinical laboratories will have the opportunity to develop new digital products for their clients.

—JP Schlingman

Related Information:

FDA Softens Stance on Clinical-decision Support Software

Clinical and Patient Decision Support Software

FDA Issues New Guidance for Clinical and Patient Decision Support Software

Statement from FDA Commissioner Scott Gottlieb, M.D., on Advancing New Digital Health Policies to Encourage Innovation, Bring Efficiency and Modernization to Regulation

FDA Issues Three Guidances, Including Long-awaited CDS Guidelines

The Feds Just Cleared a Major Roadblock for Digital Health

FDA Unveils Clinical Decision Support, Medical Device Guidance

 

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