Genetic engineers at the lab used the new tool to generate a catalog of 71 million possible missense variants, classifying 89% as either benign or pathogenic
Genetic engineers continue to use artificial intelligence (AI) and deep learning to develop research tools that have implications for clinical laboratories. The latest development involves Google’s DeepMind artificial intelligence lab which has created an AI tool that, they say, can predict whether a single-letter substitution in DNA—known as a missense variant (aka, missense mutation)—is likely to cause disease.
The Google engineers used their new model—dubbed AlphaMissense—to generate a catalog of 71 million possible missense variants. They were able to classify 89% as likely to be either benign or pathogenic mutations. That compares with just 0.1% that have been classified using conventional methods, according to the DeepMind engineers.
This is yet another example of how Google is investing to develop solutions for healthcare and medical care. In this case, DeepMind might find genetic sequences that are associated with disease or health conditions. In turn, these genetic sequences could eventually become biomarkers that clinical laboratories could use to help physicians make earlier, more accurate diagnoses and allow faster interventions that improve patient care.
“AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics,” wrote Google DeepMind engineers Jun Cheng, PhD (left), and Žiga Avsec, PhD (right), in a blog post describing the new tool. Clinical laboratories benefit from the diagnostic biomarkers generated by this type of research. (Photo copyrights: LinkedIn.)
AI’s Effect on Genetic Research
Genetic experiments to identify which mutations cause disease are both costly and time-consuming, Google DeepMind engineers Jun Cheng, PhD, and Žiga Avsec, PhD, wrote in a blog post. However, artificial intelligence sped up that process considerably.
“By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritize resources and accelerate more complex studies,” they noted.
Of all possible 71 million variants, approximately 6%, or four million, have already been seen in humans, they wrote, noting that the average person carries more than 9,000. Most are benign, “but others are pathogenic and can severely disrupt protein function,” causing diseases such as cystic fibrosis, sickle-cell anemia, and cancer.
“A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein,” Cheng and Avsec wrote in the blog post. “If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein.”
In the Google DeepMind study, AlphaMissense predicted that 57% of the 71 million variants are “likely benign,” 32% are “likely pathogenic,” and 11% are “uncertain.”
The AlphaMissense model is adapted from an earlier model called AlphaFold which uses amino acid genetic sequences to predict the structure of proteins.
“AlphaMissense was fed data on DNA from humans and closely related primates to learn which missense mutations are common, and therefore probably benign, and which are rare and potentially harmful,” The Guardian reported. “At the same time, the program familiarized itself with the ‘language’ of proteins by studying millions of protein sequences and learning what a ‘healthy’ protein looks like.”
The model assigned each variant a score between 0 and 1 to rate the likelihood of pathogenicity [the potential for a pathogen to cause disease]. “The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements,” Avsec and Cheng wrote in their blog post.
However, they also acknowledged that it doesn’t indicate exactly how the variation causes disease.
The engineers cautioned that the predictions in the catalog are not intended for clinical use. Instead, they “should be interpreted with other sources of evidence.” However, “this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes,” they noted.
Genomics England Sees a Helpful Tool
BBC noted that AlphaMissense has been tested by Genomics England, which works with the UK’s National Health Service. “The new tool is really bringing a new perspective to the data,” Ellen Thomas, PhD, Genomics England’s Deputy Chief Medical Officer, told the BBC. “It will help clinical scientists make sense of genetic data so that it is useful for patients and for their clinical teams.”
AlphaMissense is “a big step forward,” Ewan Birney, PhD, Deputy Director General of the European Molecular Biology Laboratory (EMBL) told the BBC. “It will help clinical researchers prioritize where to look to find areas that could cause disease.”
Other experts, however, who spoke with MIT Technology Review were less enthusiastic.
Heidi Rehm, PhD, co-director of the Program in Medical and Population Genetics at the Broad Institute, suggested that the DeepMind engineers overstated the certainty of the model’s predictions. She told the publication that she was “disappointed” that they labeled the variants as benign or pathogenic.
“The models are improving, but none are perfect, and they still don’t get you to pathogenic or not,” she said.
“Typically, experts don’t declare a mutation pathogenic until they have real-world data from patients, evidence of inheritance patterns in families, and lab tests—information that’s shared through public websites of variants such as ClinVar,” the MIT article noted.
Is AlphaMissense a Biosecurity Risk?
Although DeepMind has released its catalog of variations, MIT Technology Review notes that the lab isn’t releasing the entire AI model due to what it describes as a “biosecurity risk.”
The concern is that “bad actors” could try using it on non-human species, DeepMind said. But one anonymous expert described the restrictions “as a transparent effort to stop others from quickly deploying the model for their own uses,” the MIT article noted.
And so, genetics research takes a huge step forward thanks to Google DeepMind, artificial intelligence, and deep learning. Clinical laboratories and pathologists may soon have useful new tools that help healthcare provider diagnose diseases. Time will tell. But the developments are certain worth watching.
Studying gut bacteria continues to intrigue investors, but can the results produce viable diagnostic data for healthcare providers?
Even as microbiologists and clinical pathologists closely watch research into the human microbiome and anticipate study findings that could lead to new medical laboratory tests based on microbiome testing, there are entrepreneurs ready to tout the benefits of microbiome testing to consumers. That’s the impetus behind an announced deal between a microbiome testing company and a national pharmacy chain.
That deal involves health startup Viome Life Sciences, which recently closed a $86.5 million Series C funding round to support research and development of its consumer health at-home test kits, and CVS, which will sell Viome’s Gut Intelligence Test at 200 of the pharmacy company’s retail locations nationwide, according to an August press release.
“Founded seven years ago by serial entrepreneur Naveen Jain, Viome sells at-home kits that analyze the microbial composition of stool samples and provide food recommendations, as well as supplements and probiotics. Viome says it is the first company to sell gut tests at CVS, both online and in-store. The tests will sell for $179,” GeekWire reported.
Investors appear to be intrigued by these types of opportunities. To date, Viome has raised a total of $175 million.
“In a world where healthcare has often been reactive, treating symptoms and targeting diseases only after they manifest, Viome is pioneering a transformative shift by harnessing the innate power of food and nutrition,” stated Naveen Jain (above), Founder and CEO of Viome, in a press release. “Our mission is not just to prolong life but to enrich it, enabling everyone to thrive in health and vitality.” But some microbiologists and clinical laboratory scientists would consider that the current state of knowledge about the human microbiome is not well-developed enough to justify offering direct-to-consumer microbiology tests that encourage consumers to purchase nutritional products. (Photo copyright: Viome Life Sciences.)
Empowering People to Make Informed Decisions about Their Health
Established in 2016, Bellevue, Washington-based Viome produces and sells, among other tests, its Gut Intelligence at-home test kit, which analyzes the microbial composition of stool samples. This kit relies on RNA sequencing to detect bacteria and other elements present in the gut, such as yeasts and viruses.
The genetic data is then entered into an artificial intelligence (AI) algorithm to provide individuals with information regarding their personal gut health. Viome partnered with Los Alamos National Laboratory to create their AI platform. The company has collected more than 600,000 test samples to date.
“We are the only company that looks at the gene expression and what these microbes are doing,” said Naveen Jain, Founder and CEO of Viome in the press release.
Viome uses technology combined with science to determine the optimal outcomes for each individual consumer based on his or her unique human and microbial gene expression. The data derived from the microbiome is also utilized to offer nutritional recommendations and supplement advice to test takers.
“At Viome, we’re empowering our customers with an individualized nutrition strategy, cutting through the noise of temporary trends and one-size-fits-all advice,” Jain added. “We’re on a journey to redefine aging itself, and we’re invigorated by the support of our investors and customers. Together, we’re building pathways to wellness that hold the potential to enhance the lives of billions of fellow humans across the globe.”
Manipulating Microbiome through Diet
Some scientists, however, are not sold on the idea of microbiome test kits and the data they offer to healthcare providers for treating illnesses.
“The best thing anybody can do for their microbiome is to eat a healthy diet. That’s the best way of manipulating your microbiome,” David Suskind, MD, a gastroenterologist at Seattle Children’s Hospital and Professor of Pediatrics at the University of Washington, told GeekWire.
Verdu, GeekWire reported, added that “there needs to be standardization of protocols and better understanding of microbiome function in health and disease.”
“Recommendations for such commercial kits would have to be based on evidence-based guidelines, which currently do not exist,” she told GeekWire.
Nevertheless, Jain remains positive about the value of microbiome testing. “The future of medicine will be delivered at home, not at the hospital. And the medicines of the future are going to come from a farm, not a pharmacy,” he told GeekWire.
Other Viome At-home Tests
According to a paper published in the journal Therapeutic Advances in Gastroenterology titled, “Role of the Gut Microbiota in Health and Chronic Gastrointestinal Disease: Understanding a Hidden Metabolic Organ,” the human gut contains trillions of microbes, and no two people share the exact same microbiome composition. This complex community of microbial cells influences human physiology, metabolism, nutrition and immune function, and performs a critical role in overall health.
CVS currently sells Viome’s “Gut Intelligence Health Insights Plus Personalized Nutrition Plan” on its website for $149.99. Prices may vary from online to in-store. The test is intended for individuals who want to monitor and address gut imbalances or health symptoms, such as:
Constipation
Diarrhea
Stomach pain
Bloating
Heartburn
Itchy skin
Trouble maintaining a healthy weight
Viome sells the Gut Intelligence Test for $179 on its own website, as well as the following health tests:
Viome also sell precision probiotics and prebiotics, as well as supplements and oral health lozenges.
Gut microbiome testing kits, such as the one from Viome, typically require the collection of a stool sample. Healthcare consumers have in the past been reluctant to perform such testing, but as more information regarding gut health is published, that reluctance may diminish.
Clinical laboratories also have a stake in the game. Dynamic direct to consumer at-home testing has the potential to generate revenue for clinical laboratories, while helping consumers who want to monitor different aspects of their health. But this would be an adjunct to the primary mission of medical laboratories to provide testing services to local physicians and their patients.
Pathologists and clinical laboratory managers will want to stay alert to the concerns voiced by tech experts about the need to exercise caution when using generative AI to assist medical diagnoses
GPTs are an integral part of the framework of a generative artificial intelligence that creates text, images, and other media using generative models. These neural network models can learn the patterns and structure of inputted information and then develop new data that contains similar characteristics.
Through their proposal, the AMA has developed principles and recommendations surrounding the benefits and potentially harmful consequences of relying on AI-generated medical advice and content to advance diagnoses.
“We’re trying to look around the corner for our patients to understand the promise and limitations of AI,” said Alexander Ding, MD (above), AMA Trustee and Associate Vice President for Physician Strategy and Medical Affairs at Humana, in a press release. “There is a lot of uncertainty about the direction and regulatory framework for this use of AI that has found its way into the day-to-day practice of medicine.” Clinical laboratory professionals following advances in AI may want to remain informed on the use of generative AI solutions in healthcare. (Photo copyright: American Medical Association.)
Preventing Spread of Mis/Disinformation
GPTs are “a family of neural network models that uses the transformer architecture and is a key advancement in artificial intelligence (AI) powering generative AI applications such as ChatGPT,” according to Amazon Web Services.
In addition to creating human-like text and content, GPTs have the ability to answer questions in a conversational manner. They can analyze language queries and then predict high-quality responses based on their understanding of the language. GPTs can perform this task after being trained with billions of parameters on massive language datasets and then generate long responses, not just the next word in a sequence.
“AI holds the promise of transforming medicine,” said diagnostic and interventional radiologist Alexander Ding, MD, AMA Trustee and Associate Vice President for Physician Strategy and Medical Affairs at Humana, in an AMA press release.
“We don’t want to be chasing technology. Rather, as scientists, we want to use our expertise to structure guidelines, and guardrails to prevent unintended consequences, such as baking in bias and widening disparities, dissemination of incorrect medical advice, or spread of misinformation or disinformation,” he added.
The AMA plans to work with the federal government and other appropriate organizations to advise policymakers on the optimal ways to use AI in healthcare to protect patients from misleading AI-generated data that may or may not be validated, accurate, or relevant.
Advantages and Risks of AI in Medicine
The AMA’s proposal was prompted by AMA-affiliated organizations that stressed concerns about the lack of regulatory oversight for GPTs. They are encouraging healthcare professionals to educate patients about the advantages and risks of AI in medicine.
“AI took a huge leap with large language model tool and generative models, so all of the work that has been done up to this point in terms of regulatory and governance frameworks will have to be treated or at least reviewed with this new lens,” Sha Edathumparampil, Corporate Vice President, Digital and Data, Baptist Health South Florida, told Healthcare Brew.
According to the AMA press release, “the current limitations create potential risks for physicians and patients and should be used with appropriate caution at this time. AI-generated fabrications, errors, or inaccuracies can harm patients, and physicians need to be acutely aware of these risks and added liability before they rely on unregulated machine-learning algorithms and tools.”
According to the AMA press release, the organization will propose state and federal regulations for AI tools at next year’s annual meeting in Chicago.
In a July AMA podcast, AMA’s President, Jesse Ehrenfeld, MD, stressed that more must be done through regulation and development to bolster trust in these new technologies.
“There’s a lot of discomfort around the use of these tools among Americans with the idea of AI being used in their own healthcare,” Ehrenfeld said. “There was a 2023 Pew Research Center poll [that said] 60% of Americans would feel uncomfortable if their own healthcare provider relied on AI to do things like diagnose disease or recommend a treatment.”
WHO Issues Cautions about Use of AI in Healthcare
In May, the World Health Organization (WHO) issued a statement advocating for caution when implementing AI-generated large language GPT models into healthcare.
A current example of such a GPT is ChatGPT, a large language-based model (LLM) that enables users to refine and lead conversations towards a desired length, format, style, level of detail and language. Organizations across industries are now utilizing GPT models for Question and Answer bots for customers, text summarization, and content generation and search features.
“Precipitous adoption of untested systems could lead to errors by healthcare workers, cause harm to patients, erode trust in AI, and thereby undermine (or delay) the potential long-term benefits and uses of such technologies around the world,” commented WHO in the statement.
WHO’s concerns regarding the need for prudence and oversight in the use of AI technologies include:
Data used to train AI may be biased, which could pose risks to health, equity, and inclusiveness.
LLMs generate responses that can appear authoritative and plausible, but which may be completely incorrect or contain serious errors.
LLMs may be trained on data for which consent may not have been given.
LLMs may not be able to protect sensitive data that is provided to an application to generate a response.
LLMs can be misused to generate and disseminate highly convincing disinformation in the form of text, audio, or video that may be difficult for people to differentiate from reliable health content.
Tech Experts Recommended Caution
Generative AI will continue to evolve. Therefore, clinical laboratory professionals may want to keep a keen eye on advances in AI technology and GPTs in healthcare diagnosis.
“While generative AI holds tremendous potential to transform various industries, it also presents significant challenges and risks that should not be ignored,” wrote Edathumparampil in an article he penned for CXOTECH Magazine. “With the right strategy and approach, generative AI can be a powerful tool for innovation and differentiation, helping businesses to stay ahead of the competition and better serve their customers.”
GPT’s may eventually be a boon to healthcare providers, including clinical laboratories, and pathology groups. But for the moment, caution is recommended.
Findings could lead to deeper understanding of why we age, and to medical laboratory tests and treatments to slow or even reverse aging
Can humans control aging by keeping their genes long and balanced? Researchers at Northwestern University in Evanston, Illinois, believe it may be possible. They have unveiled a “previously unknown mechanism” behind aging that could lead to medical interventions to slow or even reverse aging, according to a Northwestern news release.
Should additional studies validate these early findings, this line of testing may become a new service clinical laboratories could offer to referring physicians and patients. It would expand the test menu with assays that deliver value in diagnosing the aging state of a patient, and which identify the parts of the transcriptome that are undergoing the most alterations that reduce lifespan.
It may also provide insights into how treatments and therapies could be implemented by physicians to address aging.
“I find it very elegant that a single, relatively concise principle seems to account for nearly all of the changes in activity of genes that happen in animals as they change,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN. Clinical laboratories involved in omics research may soon have new anti-aging diagnostic tests to perform. (Photo copyright: Amaral Lab.)
Possible ‘New Instrument’ for Biological Testing
Researchers found clues to aging in the length of genes. A gene transcript length reveals “molecular-level changes” during aging: longer genes relate to longer lifespans and shorter genes suggest shorter lives, GEN summarized.
The phenomenon the researchers uncovered—which they dubbed transcriptome imbalance—was “near universal” in the tissues they analyzed (blood, muscle, bone, and organs) from both humans and animals, Northwestern said.
According to the National Human Genome Research Institute fact sheet, a transcriptome is “a collection of all the gene readouts (aka, transcript) present in a cell” shedding light on gene activity or expression.
The Northwestern study suggests “systems-level” changes are responsible for aging—a different view than traditional biology’s approach to analyzing the effects of single genes.
“We have been primarily focusing on a small number of genes, thinking that a few genes would explain disease,” said Luis Amaral, PhD, Senior Author of the Study and Professor of Chemical and Biological Engineering at Northwestern, in the news release.
“So, maybe we were not focused on the right thing before. Now that we have this new understanding, it’s like having a new instrument. It’s like Galileo with a telescope, looking at space. Looking at gene activity through this new lens will enable us to see biological phenomena differently,” Amaral added.
In their Nature Aging paper, Amaral and his colleagues wrote, “We hypothesize that aging is associated with a phenomenon that affects the transcriptome in a subtle but global manner that goes unnoticed when focusing on the changes in expression of individual genes.
“We show that transcript length alone explains most transcriptional changes observed with aging in mice and humans,” they continued.
In tissues studied, older animals’ long transcripts were not as “abundant” as short transcripts, creating “imbalance.”
“Imbalance” likely prohibited the researchers’ discovery of a “specific set of genes” changing.
As animals aged, shorter genes “appeared to become more active” than longer genes.
In humans, the top 5% of genes with the shortest transcripts “included many linked to shorter life spans such as those involved in maintaining the length of telomeres.”
Conversely, the researchers’ review of the leading 5% of genes in humans with the longest transcripts found an association with long lives.
Antiaging drugs—rapamycin (aka, sirolimus) and resveratrol—were linked to an increase in long-gene transcripts.
“The changes in the activity of genes are very, very small, and these small changes involve thousands of genes. We found this change was consistent across different tissues and in different animals. We found it almost everywhere,” Thomas Stoeger, PhD, postdoctoral scholar in the Amaral Lab who led the study, told GEN.
In their paper, the Northwestern scientists noted implications for creation of healthcare interventions.
“We believe that understanding the direction of causality between other age-dependent cellular and transcriptomic changes and length-associated transcriptome imbalance could open novel research directions for antiaging interventions,” they wrote.
While more research is needed to validate its findings, the Northwestern study is compelling as it addresses a new area of transcriptome knowledge. This is another example of researchers cracking open human and animal genomes and gaining new insights into the processes supporting life.
For clinical laboratories and pathologists, diagnostic testing to reverse aging and guide the effectiveness of therapies may one day be possible—kind of like science’s take on the mythical Fountain of Youth.
From ‘new-school’ rules of running a clinical laboratory to pharmacy partnerships to leveraging lab data for diagnostics, key industry executives discussed the new era of clinical laboratory and pathology operations
Opening keynotes at the 28th Annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management taking place in New Orleans this week covered three main forces that healthcare and medical laboratory administrators should be preparing to address: new consumer preferences, new care models, and new payment models.
“COVID-19 didn’t change a whole lot of things in one sense, but it accelerated a lot of trends that were already happening in healthcare,” said Robert L. Michel, Editor-in-Chief of Dark Daily and its sister publication The Dark Report, and Founder of the Executive War College, during his opening keynote address to a packed ballroom of conference attendees. “Healthcare is transforming, and the transformation is far more pervasive than most consumers appreciate.
“Disintermediation, for example, is taking traditional service providers and disrupting them in substantial ways, and if you think about the end of fee-for-service, be looking forward because your labs can be paid for the value you originate that makes a difference in patient care,” Michel added.
Another opportunity for clinical laboratories, according to Michel, is serving Medicare Advantage plans which have soared in enrollment. “Lab leaders should be studying Medicare Advantage for how to integrate Medicare Advantage incentives into their lab strategies,” he said, highlighting the new influence of risk adjustment models which use diagnostic data to predict health condition expenditures.
Opening sessions at this week’s annual Executive War College on Diagnostics, Clinical Laboratory, and Pathology Management, presented by Robert L. Michel (above), Editor-in-Chief of Dark Daily and its sister publication The Dark Report, discussed demand for delivering healthcare services—including medical laboratory testing—as consumer preferences evolve, new care models are designed, and as payers seek value over volume. While these three forces may be challenging at the outset, they also create opportunities for clinical laboratories and pathology groups—a focal point of the Executive War College each year. (Photo copyright: The Dark Intelligence Group.)
Medical Laboratories Must Adapt to ‘New-School’ Rules
During his keynote address, Stan Schofield, Vice President and Managing Principal at The Compass Group, noted that while the basic “old-school” rules of successfully running a clinical laboratory have not changed—e.g., adding clients, keeping clients, creating revenue opportunities, getting paid, and reducing expenses—the interpretation of each rule has changed. The Compass Group is a trade federation based in South Carolina that serves not-for-profit healthcare integrated delivery networks (IDNs), including 32 health systems and 600 hospitals.
Schofield advised that when it comes to adding new clients under the “new-school” rules of lab management, clinical laboratory directors must be aware of and adapt to hospital integrations of core labs, clinical integrations across health systems, seamless services, direct contracting with employers in insurance relationships, and direct-to-consumer testing. Keeping clients, Schofield said, involves five elements:
Strong customer service.
A tailored metrics program for quality services based on what is important to a lab’s clients.
Balanced scorecards that look at the business opportunity and value proposition with each client.
Monitoring patients’ experiences and continuous improvement.
Participation in all payer agreements.
As to the problem of commoditization of laboratory goods and services, Schofield said, “Right now, we’re facing the monetization of the laboratory. We’re going to swiftly move from commoditization to monetization to commercialization.”
Pharmacies Enter the Clinical Laboratory Market
In another forward looking keynote address, David Pope, PharmD, CDE, Chief Pharmacy Officer at OmniSYS, XiFin Pharmacy Solutions, discussed the “test to treat” trend which could bring clinical laboratories and pharmacies together in new partnerships.
Diagnostics and pharmacy now intersect, according to Pope. “Pharmacists are on the move, and they are true contender as a new provider for you,” he said. “An area of pharmacy that is dependent upon labs is specialty medications.”
Specialty medicines now account for 55% of prescription spending, up from 28% in 2011, driven by growth in auto-immune and oncology, Pope noted. Other examples include companion diagnostics required for targeted treatments pertaining to all major cancers, and new areas like thalassemia (inherited blood disorders), obesity, next-generation sequencing, and pharmacogenomics, in addition to routine testing such as liver function and complete blood count (CBC).
Federal legislation may soon recognize pharmacists as healthcare providers who will be trained to perform specific clinical services, Pope said. Some states already recognize pharmacists as providers, he noted, explaining that pharmacies need lab data for three primary reasons:
Service—Pharmacies can act as a referral source to clinical laboratories. When referring, pharmacies may need to communicate lab test results to patients or providers to coordinate care.
Value-based care—Pharmacies would draw on data to counsel, prescribe, and coordinate care for chronic disease management, among other services.
Diagnostics and pharmacogenetics—Specialty medication workflows require documented test results within a specific timeframe prior to dispensing.
Another point Pope made: Large pharmacies are seeking lab partners. Labs that can provide rapid turnaround time and good pricing on complex tests provide pharmacies with partnership opportunities.
Using AI to Create Patients’ ‘Digital Twins’ That Help Identify Disease and Improve Care
High-tech healthcare technology underlies many opportunities in the clinical laboratory and pathology market, as evidenced throughout the Executive War College’s 2023 curriculum. An ongoing challenge for labs, however, is how to produce the valuable datasets that all labs have the potential to generate.
“It feels like we’ve come so far,” explained Brad Bostic, CEO of hc1 during his keynote address. “We’ve got the internet. We’ve got the cloud. All of this is amazing, but in reality, we have this massive proliferation of data everywhere and it’s very difficult to know how to actually put that into use. And nobody’s generating more data than clinical laboratories.
“Every single interaction with a patient that generates data gives you this opportunity to create the idea of a ‘digital twin.’ That means that labs are creating a mathematical description of what a person’s state is and using that information to look at how providers can optimally diagnose and treat that person. Ultimately, it is bigger than just one person. It’s hundreds of millions of people that are generating all this data, and many of these people fall into similar cohorts.”
This digital twin opportunity is heavily fueled by medical laboratory testing, Bostic said, adding that labs need to be able to leverage artificial intelligence (AI) to:
“I recommend lab leaders sit down with their teams and any outside partners they trust and identify what are their lab’s goals,” Bostic stated. “Think about how this technology can advance a lab’s mission. Look at strategy holistically—everything from internal operations to how patient care is affected.”
