Balwani’s lawyers opted not to have their client testify in his own defense and called only two witnesses, while Holmes’ defense team offered jurors the opportunity to hear her testimony
Elizabeth Holmes and Ramesh “Sunny” Balwani dreamed of revolutionizing the clinical laboratory blood-testing industry with their now defunct Theranos Edison device, which they claimed could perform multiple tests with a single finger prick of blood. Instead, they became the rare Silicon Valley executives to be convicted of fraud.
On July 7, ex-COO/President Balwani was convicted on all 12 counts of wire fraud and conspiracy charges in his federal fraud trial. Holmes, Theranos’ founder/CEO and former romantic partner to Balwani, avoided convictions six months ago in January on seven of the 11 counts she faced for her role in exaggerating the accuracy and reliability of the company’s Edison blood-testing device and providing false financial claims to investors.
“Once again, a jury has determined that the fraud at Theranos reached the level of criminal conspiracy,” said FBI Special Agent in Charge Sean Ragan in a press release posted on Twitter following the verdict. “The FBI has spent years investigating this investment fraud scheme with our partners at USPIS and the FDA Office of Criminal Investigations. Lies, deceit, and criminal actions cannot replace innovation and success.”
Ramesh “Sunny” Balwani (above center), former COO/President of Theranos, is shown leaving the federal courthouse in San Jose, Calif., on July 7 after he was found guilty on all 12 counts of fraud, a verdict more severe than ex-CEO and Theranos founder Elizabeth Holmes received in January for similar charges. Clinical laboratory directors and medical laboratory scientists have been closely monitoring both trails. (Photo copyright: Jim Wilson/The New York Times.)
Balwani’s Age and Experience May Have Worked Against Him
Michael Weinstein, JD, a former Justice Department prosecutor who is the Chair of White-collar Litigation at Cole Schotz, told The New York Times that Balwani’s age and his trial date—three months after Holmes’ conviction—worked against him. Balwani, 57, could not present himself as a young and inexperienced tech executive easily manipulated by those around him, as Holmes, 38, had attempted to do.
“Holmes could come off as a bit naïve, and [her defense team] tried to sell that,” Weinstein said of the former Stanford University dropout who founded Theranos in 2003 when she was 19.
In Holmes’ case the verdict was mixed, with jurors acquitting her of the patient fraud counts but unable to reach a decision on some of the investor fraud counts, Bloomberg reported.
Mr. Balwani, however, “came off as more of an experienced technology executive,” Weinstein added.
Weinstein pointed out that because the government’s case against Balwani mirrored its case against Holmes, prosecutors had time to refine their strategy before making a second appearance inside US District Court Judge Edward Davila’s San Jose courtroom.
“The streamlined presentation, the streamlined evidence, the streamlined narrative—all was beneficial for the government in the end,” he said.
Ever since opening arguments in March, Balwani’s legal team portrayed him to the jurors as a loyal partner who believed in Theranos’ technology and “put his money where his mouth is,” the Guardian noted.
Prosecutors, however, made the case that Balwani had a hands-on role in running the lab and was the source of Theranos’ overinflated financial projections.
Balwani invested about $15 million in the startup between 2009 and 2011 and never cashed in when his stake grew to $500 million. That money evaporated when Theranos collapsed.
In all, 24 witnesses testified against Balwani. He was ultimately convicted of all 12 counts he faced:
Two counts of conspiring with Holmes,
Six counts of defrauding investors, and
Four counts of patient fraud.
Major Differences in Trial Testimony
The Balwani trial made headlines due to COVID-19 pandemic related delays, but otherwise did not produce the news-generating moments that punctuated Holmes’ nearly four-month-long court appearance. Thirty-two witnesses appeared at the Holmes trial, including Secretary of Defense James Mattis, according to CNN.
Another significant difference in the two trials was that Holmes testified in her own defense. Holmes spent nearly 24 hours on the stand, CNN Business noted at that time, during which she cast the blame for Theranos’ failings on those around her, including Balwani.
ABC NewsRebecca Jarvis, host and creator of the podcast “The Dropout,” believes Balwani’s decision not to testify worked against him.
“[The abuse claims] did not come up at his trial, but during [Holmes’] seven days of testimony, they were a big portion of what she talked about,” Jarvis said in an ABC News “Start Here” podcast. “The biggest difference is that he didn’t take the stand to say, ‘I didn’t do this,’ or … raise his own objections to the claims against him.
“You think about a jury who is supposed to know nothing about any of [the defendant’s] backstory, and they’re shown these things like … case pictures of [Holmes] so much younger than [Balwani], supposedly having to rely on him for his expertise,” Jarvis added.
“You can imagine where the jury may have found that presentation more sympathetic than Sunny Balwani who had experience,” she said.
Text May Have Been Balwani’s Undoing
Balwani’s defense team called only two witnesses:
A naturopathic physician who used Theranos’ blood-testing lab, and
A technical consultant who Balwani’s legal team hired to assess the accessibility of patient data in Theranos’ Laboratory Information System (LIS), which the defense argued could have provided evidence of the accuracy of Theranos’ test results.
“This verdict also signals the jurors did not buy Balwani’s highly speculative argument that the database Theranos lost in 2018 would have proven his innocence,” Park said.
“We are obviously disappointed with the verdicts,” he said. “We plan to study and consider all of Mr. Balwani’s options including an appeal.”
Following the verdicts, Judge Davila raised Balwani’s bail to $750,000 and set a Nov. 15 sentencing date. Holmes is scheduled to be sentenced Sept. 26.
Balwani’s own words may have been his final undoing. During closing arguments, prosecutors again showed jurors a text message Balwani sent to Holmes in 2015, The New York Times reported.
“I am responsible for everything at Theranos,” he wrote. “All have been my decisions too.”
Clinical laboratory directors and medical laboratory scientists will no doubt continue to monitor the fallout from these two extraordinary federal fraud trials. There’s still much to learn about CLIA-laboratory director responsibility and how the government plans to prevent future lab testing fraud from taking place.
Clinical laboratory managers and pathology group leaders may want to pay closer attention to shrinking hospital margins and whether this may put pressure on hospital laboratory budgets
Financial performance of the nation’s hospitals and health systems continues to disappoint hospital leaders. For the fourth consecutive month this year, hospital operating margins have remained in the red. This will, of course, affect the clinical laboratories and pathology departments at these institutions.
A recently released National Hospital Flash Report from healthcare management consulting firm Kaufman Hall indicates that 2022 has started off poorly for most healthcare organizations. The information in Kaufman’s report is based on data gathered from more than 900 hospitals and healthcare systems across the country.
The key takeaways outlined in the report for the month of April that are negatively affecting hospitals’ bottom lines include:
More patients are utilizing urgent care facilities, telemedicine options, and primary care providers instead of seeking care at hospital emergency departments.
Patients tend to be sicker, more expensive to treat, and require longer hospital stays compared to April of 2021.
Expenses remain high due to labor shortages, specialty supplies, supply chain issues, and costly pharmaceuticals.
“Labor shortages, high prices for supplies, and cost increases to treat sicker patients over longer stays are ballooning hospital expenses,” Erik Swanson (above), Senior Vice President of Data and Analytics for Kaufman Hall, told Fierce Healthcare. “With a bleak consensus outlook for the US economy, those factors and their effects could be here for a while.” Clinical laboratories have been grappling with supply and personnel shortages and rising costs for many years. (Photo copyright: Kaufman Hall.)
According to the report, the operating margins for the hospitals were down nearly 40% compared to March 2022 and declined 76% when compared to April 2021. The calculated median operating margin index was -3.09% throughout April 2022. In addition, operating earnings declined almost 27% from March to April of this year and 51.5% when contrasted with April of last year.
The report also found that patient volumes, average lengths of stays, and surgeries performed had declined overall during the month of April—but that hospital expenses rose during that period—thus decreasing profit margins. Total expenditures increased by 8.3% over April 2021, and 9.6% between March and April of this year.
Inflation, COVID-19 Key Factors in Hospitals’ First Quarter Losses
The report noted that the historic rise in inflation during the month of April is fueling negative revenues for healthcare systems and hospitals. Several for-profit and nonprofit hospital systems reported losses for the first quarter of 2022.
Kaufman’s report for the month of March was slightly more positive as the healthcare organizations surveyed reported an incremental rise in patient volumes and minor expense relief, resulting in gains in volumes and revenues. March also saw an increase in outpatient and surgery volumes and lower numbers of high-acuity patients. However, that slight upward trend did not last through April.
Another reason for the year-to-date unsatisfactory revenue margins for hospitals across the country was the surge of patients seeking care for the SARS-CoV-2 omicron variant of the COVID-19 infection earlier in the year.
“The first few months of this year were decimated by the impact of the omicron wave, but as the omicron wave subsided, we had a bit of a rebound in those volumes, and that’s what you saw in March,” Erik Swanson, Senior Vice President of Data and Analytics for Kaufman Hall told HealthLeaders. “However, it wasn’t a rebound to the full historical volumes, and that is again because of that wave.”
Healthcare Organizations are Advised to Look at Expenses
The National Hospital Flash Report is published monthly by Kaufman Hall and provides vital analyses and observations on the fiscal performance of hospitals and healthcare systems. The information contained in the report includes data on margins, volumes, revenues, and expenses.
“The revenue side is a bit more challenging for organizations to control. Many are looking at their internal revenue cycle, understanding where there can be improvements in their own process, improving just the performance of the revenue cycle that improves the collections rates,” Swanson said. “Many are also trying to renegotiate with payers and negotiate perhaps as aggressively as possible to get the best rates. But I think where you see much of the levers that organizations can pull is on the expense side.”
Fluctuations in revenue mean that organizations—including clinical laboratories—will have to establish new strategies to diminish their financial shortfalls.
“Finally, because a lot of these challenges are due to these ebbs and flows in volumes, many organizations are also looking to see how they can embrace more data-driven predictive type models to look at volumes and think about how they can optimize their workforce to better handle these ebbs and flows of volume,” Swanson added. “This very often includes thinking about the appropriate size of float pools, the number of times that you need to pay overtime versus hiring new individuals, so many organizations are taking those approaches to bend the cost curve. There are quite a few levers that organizations are pulling to bend this cost curve down to ultimately improve their margins overall.”
The most recent report concluded that the first four months of 2022 have been extremely challenging for hospitals and health systems with extended negative margins taking their toll. The report also projected that the overall picture does not look favorable for these organizations for the remainder of the year and that many healthcare facilities may finish out 2022 with substantially depressed margins.
Clinical laboratory managers and pathology group leaders serving hospital and integrated delivery networks (IDNs) may want to consider how these depressed hospital margins will affect their own laboratories. It may be timely to anticipate how this fall’s budget-planning cycle might require their labs to specify how costs can be cut in the coming budget year.
Should their research result in new ways to identify and diagnose disease, doctors and clinical laboratories would do confirmatory testing and then initiate a precision medicine plan.
Dan Roden, MD, Senior Vice President for Personalized Medicine at VUMC and Senior Author of the Circulation study, said in a VUMC news release that the findings support the growing use of genetic information in clinical care.
“The questions we asked were: How many people who had no previous indication for cardiac genetic testing had pathogenic or likely pathogenic variants, and how many of those people actually had a phenotype in the electronic health records?” he explained.
Arrhythmia More Common than Previously Thought
The VUMC researchers drew data for their reports from the eMERGE Phase III study, which investigated the feasibility of population genomic screening by sequencing 109 genes across the spectrum of Mendelian diseases—genetic diseases that are caused by a mutation in a single gene—in more than 20,000 individuals. The scientists returned variant results to the participants and used EHR and follow-up clinical data to ascertain patient phenotypes, according to a Northwestern University Feinberg School of Medicine news release.
The research team looked specifically at the 120 consortium participants that had disease-associated pathogenic or likely pathogenic (P/LP) variants in the arrhythmia-associated genes. An analysis of the EHR data showed that 0.6% of the studied population had a variant that increases risk for potentially life-threatening arrhythmia, and that there was overrepresentation of arrhythmia phenotypes among patients, the VUMC news release noted.
The research team returned results to 54 participants and, with clinical follow-up, made 19 diagnoses (primarily long-QT syndrome) of inherited arrhythmia syndromes. Twelve of those 19 diagnoses were made only after variant results were returned, the study’s authors wrote.
Carlos G. Vanoye, PhD, Research Associate Professor of Pharmacology at Northwestern University (NU), said the study suggests arrhythmia genes may be more common than previously thought.
“A person can carry a disease-causing gene variant but exhibit no obvious signs or symptoms of the disease,” he said in the NU news release. “Because the genes we studied are associated with sudden death, which may have no warning signs, discovery of a potentially life-threatening arrhythmia gene variant can prompt additional clinical work-up to determine risks and guide preventive therapies.”
“The take-home message is that 3% of people will carry a pathogenic or likely pathogenic variant in a disease-causing gene and many others will carry variants of uncertain significance,” said Dan Roden, MD (above), Senior Vice President for Personalized Medicine at VUMC and Senior Author of the Circulation study in the VUMC news release. “We can use genetic testing, electronic health record phenotypes, and in vitro technologies to evaluate and find people who have unrecognized genetic disease and save lives by making earlier diagnoses.” Clinical laboratories will play a key role in making those early diagnoses and in managing personalized medical treatment plans. (Photo copyright: Vanderbilt University.)
Variants of Uncertain Significance
According to the NU news release, the scientists determined the functional consequences of the variants of uncertain significance they found and used that data to refine the assessment of pathogenicity. In the end, they reclassified 11 of the variants: three that were likely benign and eight that were likely pathogenic.
In the JAMA Oncology study, the VUMC scientists and other researchers conducted a phenome-wide association study to find EHR phenotypes associated with variants in 23 hereditary cancer genes. According to the VUMC news release, they identified 19 new associations:
The VUMC study findings could improve disease diagnosis and management for cancer patients and help identify high-risk individuals, the researchers noted in their published report.
In an editorial published in Circulation, titled, “First Steps of Population Genomic Medicine in the Arrhythmia World: Pros and Cons,” the professors noted that using genomic information in the case of potentially lethal inherited arrhythmia syndromes could be “lifesaving,” but questioned the benefits of reporting such secondary findings when patients are undergoing genome sequencing for other indications such as cancer.
“The likelihood that these ‘genetic diagnoses’ are translated into clinical diagnoses have not been completely evaluated,” they wrote. “In addition to the challenge of accurately identifying disease-causing genetic variants, defining the penetrance of such variants is critical to this process, i.e., what proportion of individuals in the general population with apparently pathogenic variants will develop the associated phenotype? If penetrance is low for particular gene/phenotype combinations, the costs associated with clinical screening and the psychological effects on individuals informed that they have potentially life-threatening variants may outweigh the benefits of the few new clinical diagnoses.”
These latest studies provide further evidence of the value of big data in healthcare and offer another lesson to clinical laboratories and pathologist about the future role data streaming from clinical laboratories and pathology assays may have in the growth of personalized medicine.
Ultima Genomics says it is emerging from “stealth mode” with millions in fresh capital and technology capable of sequencing whole human genomes for a fraction of the cost
Investors seem to be optimistic that an emerging genetics company has the proprietary solution to sequence a whole human genome for just $100. If true, this is a development that would be of interest to clinical laboratory managers and pathologists.
The company, Ultima Genomics of Newark, Calif., recently announced that it had raised $600 million from the investment community. In a press release last month, the company announced it has “emerged from stealth mode with a new high-throughput, low-cost sequencing platform that delivers the $100 genome.”
The press release goes on to state that Ultima will unleash a new era in genomics-driven discoveries by developing a “fundamentally new sequencing architecture designed to scale beyond conventional approaches, including completely different approaches to flow cell engineering, sequencing chemistry, and machine learning.”
Are we at the cusp of a revolution in genomics? Ultima Genomics’ founder and CEO, Gilad Almogy, PhD, believes so.
“Our architecture is intended for radical scaling, and the $100 genome is merely the first example of what it can deliver,” he said in the press release. “We are committed to continuously drive down the cost of genomic information until it is routinely used in every part of the healthcare system.”
From an Estimated Cost of $3 Billion to $450 in Just 30 Years!
Whole genome sequencing (WGS) has decreased dramatically in cost since research into the technology required got started in the early 1990s with the publicly-funded Human Genome Project. At that time, the cost to sequence the entire human genome was estimated at around $3 billion. Then, in 1998, John Craig Venter created Celera Genomics (now a subsidiary of Quest Diagnostics) and was the first to sequence the whole human genome (his own) and at a significantly lower cost of around $300 million.
The cost continued to drop as technology improved. In 2001, the cost to sequence the whole human genome hovered around $100 million. Twenty years later that cost had dropped to about $450/sequence, according to data compiled by the National Human Genome Research Institute (NHGRI), a division of the National Institutes of Health (NIH).
When DNA sequencer Illumina announced in 2014 the arrival of the $1,000 genome, the news was expected to put whole genome sequencing on the road to becoming routine, Forbes reported. But that prediction didn’t pan out.
Ultima Genomics’ $100 price point, however, could be game changing. It would make the cost of decoding a human genome affordable for nearly everyone and accelerate the growth of personalized medicine in clinical laboratory diagnostics.
Applied Physics versus Biological Sciences
According to GEN, Almogy brings a tech background to Ultima—his PhD is in applied physics, not the biological sciences. He founded Ultima in 2016 after serving as founder, president, and CEO at Fulfil Solutions, a manufacturer of custom automation robotics systems. At Ultima, his goal is to “unleash the same relentless scaling in sequencing” that was used to drive down the cost of computing power and transform modern life.
“Ultima is the real deal, with good technology,” Raymond McCauley, cofounder and Chief Architect at BioCurious, and Chair of Digital Biology at Singularity Group, told Singularity Hub. “They’ve been working on an Illumina killer for years.”
“We designed our new sequencing architecture to scale beyond conventional technologies, and are excited to soon make the UG 100, our first instrument using this architecture, commercially available to more customers,” said Gilad Almogy, PhD (above), Ultima Genomics’ founder and CEO, in a press release. “In the future, we aim to continuously improve our technology, further drive down costs, and increase the scale of genomic information to improve patient outcomes.” At $100/sequence, whole genome sequencing may well become commonly available to improve precision medicine diagnostics and clinical laboratory testing. (Photo copyright: Ultima Genomics.)
TechCrunch reported that Ultima’s UG100 sequencing machine and software platform can perform a complete sequencing of a human genome in about 20 hours, with precision comparable to existing options, but does so at a far lower cost per gigabase (Gb), equal to one billion base pairs.
According to the Ultima Genomics website, its breakthroughs include:
An open substrate that creates a massive, low-cost reaction surface that delivers many billions of reads while avoiding costly flow cells and complicated fluidics.
Novel scalable chemistry that combines the speed, efficiency, and read lengths of natural nucleotides with the accuracy and scalability of endpoint detection.
A revolutionary sequencing hardware that uses spinning circular wafers that enable efficient reagent use, zero crosstalk, and ultra-high-speed scanning of large surfaces.
“We may be on the brink of the next revolution in sequencing,” Beth Shapiro, DPhil, an evolutionary molecular biologist at the University of California, Santa Cruz (UCSC), told Science. Shapiro is a professor of ecology and evolutionary biology and an HHMI Investigator at UCSC and Director of Evolutionary Genomics at the UCSC Genomics Institute.
Ultima Genomics maintained a low profile since its founding six years ago. But that changed in May when it announced it had raised $600 million from multiple investors, including:
Affordable Genomics Will Lead to ‘Millions of Tests per Year’
Exact Sciences’ Chairman and CEO Kevin Conroy—whose Wisconsin-based molecular diagnostics company recently entered into a long-term supply agreement for Ultima Genomic’s NGS technologies—believes low-cost genomic sequencing will improve cancer screening and disease monitoring.
“Exact Sciences believes access to differentiated and affordable genomics technologies is critical to providing patients better information before diagnosis and across all stages of cancer treatment,” Conroy said in a press release. “Ultima’s mission to drive down the cost of sequencing and increase the use of genomic information supports our goal to provide accurate and affordable testing options across the cancer continuum. This is particularly important for applications like cancer screening, minimal residual disease, and recurrence monitoring, which could lead to millions of tests per year.”
GEN pointed out that Ultima’s 20-hour turnaround time is fast and its quality on par with its competitors, but that it is Ultima’s $1/Gb price (noted in the preprint) that will set it apart. That cost would be a fraction of Illumina’s NextSeq ($20/Gb) and Element Biosciences’ AVITI ($5/Gb).
Almogy told TechCrunch that Ultima is working with early access partners to publish more proof-of-concept studies showing the capabilities of the sequencing technique, with broader commercial deployment of the technology in 2023. Final pricing is yet to be determined, he said.
If the $100 genome accelerates the pace of medical discoveries and personalized medicine, clinical laboratory scientists and pathologists will be in ideal positions to capitalize on what the executives and investors at Ultima Genomics hope may become a revolution in whole human genome sequencing and genomics.
Two studies show the accuracy of perception-based systems in detecting disease biomarkers without needing molecular recognition elements, such as antibodies
Researchers from multiple academic and research institutions have collaborated to develop a non-conventional machine learning-based technology for identifying and measuring biomarkers to detect ovarian cancer without the need for molecular identification elements, such as antibodies.
Traditional clinical laboratory methods for detecting biomarkers of specific diseases require a “molecular recognition molecule,” such as an antibody, to match with each disease’s biomarker. However, according to a Lehigh University news release, for ovarian cancer “there’s not a single biomarker—or analyte—that indicates the presence of cancer.
“When multiple analytes need to be measured in a given sample, which can increase the accuracy of a test, more antibodies are required, which increases the cost of the test and the turnaround time,” the news release noted.
Unveiled in two sequential studies, the new method for detecting ovarian cancer uses machine learning to examine spectral signatures of carbon nanotubes to detect and recognize the disease biomarkers in a very non-conventional fashion.
“Carbon nanotubes have interesting electronic properties,” said Daniel Heller, PhD (above), in the Lehigh University news release. “If you shoot light at them, they emit a different color of light, and that light’s color and intensity can change based on what’s sticking to the nanotube. We were able to harness the complexity of so many potential binding interactions by using a range of nanotubes with various wrappings. And that gave us a range of different sensors that could all detect slightly different things, and it turned out they responded differently to different proteins.” This method differs greatly from traditional clinical laboratory methods for identifying disease biomarkers. (Photo copyright: Memorial Sloan-Kettering Cancer Center.)
Perception-based Nanosensor Array for Detecting Disease
In the Science Advances paper, the researchers described their development of “a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids.
“Perception-based machine learning (ML) platforms, modeled after the complex olfactory system, can isolate individual signals through an array of relatively nonspecific receptors. Each receptor captures certain features, and the overall ensemble response is analyzed by the neural network in our brain, resulting in perception,” the researchers wrote.
“This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements,” the researchers concluded.
In the Nature Biomedical Engineering paper, the researchers described a fined-tuned toolset that could accurately differentiate ovarian cancer biomarkers from biomarkers in individuals who are cancer-free.
“Here we show that a ‘disease fingerprint’—acquired via machine learning from the spectra of near-infrared fluorescence emissions of an array of carbon nanotubes functionalized with quantum defects—detects high-grade serous ovarian carcinoma in serum samples from symptomatic individuals with 87% sensitivity at 98% specificity (compared with 84% sensitivity at 98% specificity for the current best [clinical laboratory] screening test, which uses measurements of cancer antigen 125 and transvaginal ultrasonography,” the researchers wrote.
“We demonstrated that a perception-based nanosensor platform could detect ovarian cancer biomarkers using machine learning,” said Yoona Yang, PhD, a postdoctoral research associate in Lehigh’s Department of Chemical and Biomolecular Engineering and co-first author of the Science Advances article, in the news release.
How Perception-based Machine Learning Platforms Work
According to Yang, perception-based sensing functions like the human brain.
“The system consists of a sensing array that captures a certain feature of the analytes in a specific way, and then the ensemble response from the array is analyzed by the computational perceptive model. It can detect various analytes at once, which makes it much more efficient,” Yang said.
“SWCNTs have unique optical properties and sensitivity that make them valuable as sensor materials. SWCNTS emit near-infrared photoluminescence with distinct narrow emission bands that are exquisitely sensitive to the local environment,” the researchers wrote in Science Advances.
“Carbon nanotubes have interesting electronic properties,” said Daniel Heller, PhD, Head of the Cancer Nanotechnology Laboratory at Memorial Sloan Kettering Cancer Center and Associate Professor in the Department of Pharmacology at Weill Cornell Medicine of Cornell University, in the Lehigh University news release.
“If you shoot light at them, they emit a different color of light, and that light’s color and intensity can change based on what’s sticking to the nanotube. We were able to harness the complexity of so many potential binding interactions by using a range of nanotubes with various wrappings. And that gave us a range of different sensors that could all detect slightly different things, and it turned out they responded differently to different proteins,” he added.
The researchers put their technology to practical test in the second study. The wanted to learn if it could differentiate symptomatic patients with high-grade ovarian cancer from cancer-free individuals.
The research team used 269 serum samples. This time, nanotubes were bound with a specific molecule providing “an extra signal in terms of data and richer data from every nanotube-DNA combination,” said Anand Jagota PhD, Professor, Bioengineering and Chemical and Biomolecular Engineering, Lehigh University, in the news release.
This year, 19,880 women will be diagnosed with ovarian cancer and 12,810 will die from the disease, according to American Cancer Society data. While more research and clinical trials are needed, the above studies are compelling and suggest the possibility that one day clinical laboratories may detect ovarian cancer faster and more accurately than with current methods.
