Abbott’s HCV genotype test approved
The FDA approved Abbott’s hepatitis C virus genotyping test for use in the United States. The RealTime HCV Genotype II test differentiates genotypes 1, 1a, 1b, 2, 3, 4, and 5 and is run on the automated m2000 platform.
Gavin Cloherty, PhD, Abbott Molecular’s director of scientific affairs, told CAP TODAY the test has a 99.5 percent accuracy relative to sequencing and a greater than 99 percent discrimination of HCV genotype 1 subtype 1a versus 1b. Time to result for 22 samples and two controls, he said, is 5.25 hours, with 30 minutes hands-on time.
Treatment eligibility decisions are based on genotype, not HCV subtype, and thus the clinical utility of the latter is controversial. Subtype determination of genotype 1 is useful because “it provides clinicians with insights into the risk of developing resistance to first-line direct-acting antiviral regimens,” Dr. Cloherty said, noting that genotype 1a has a lower barrier to resistance than 1b. “How physicians use this information is at their discretion,” he added.
Rebecca Shinol, MT (ASCP)M, et al., of the Infectious Diseases Laboratory in the Medical Service of the VA Medical Center in Washington, DC, evaluated the Abbott RealTime HCV Genotype II RUO assay using the m2000 system. “Concordance was 98% (81/83 samples) with samples previously typed by the Versant HCV Genotype 2.0 RUO system with manual extraction,” they wrote (J Clin Microbiol. 2012;50[9]:3099–3101). Total assay time dropped from 10.5 to six hours, the authors reported, and hands-on time went from 13 to four minutes per patient sample.
UPMC’s ‘big data’ work takes shape
Eight months into its $100 million, five-year enterprise analytics effort, UPMC and its research partners at the University of Pittsburgh are starting to see its potential to speed scientific discoveries and advance personalized medicine.
With the foundational architecture of UPMC’s new enterprise data warehouse in place, Pitt researchers recently were able to electronically integrate for the first time clinical and genomic information on 140 patients previously treated for breast cancer.
“One of the first questions we asked was, ‘Is there a difference, a unique difference, between premenopausal and postmenopausal breast cancer?’” Adrian V. Lee, PhD, director of the Women’s Cancer Research Center at the University of Pittsburgh Cancer Institute and Magee-Womens Research Institute, said in a statement. The researchers found molecular differences in the makeup of premenopausal versus postmenopausal breast cancer. While understanding those differences will require more research, the findings eventually could provide a roadmap for developing targeted therapies, Dr. Lee added.
This initial cancer question is just the start of UPMC’s and Pitt’s effort to mine clinical, genomic, proteomic, imaging, financial, and other data. Traditionally, these data resided in separate information systems. “The integration of data, which is the goal of the enterprise data warehouse, allows us to ask questions that we just simply couldn’t ask before,” Dr. Lee said in the statement.
While the data warehouse started with only two types of breast cancer “omic” data—gene expression and copy number variant data, measuring changes in the amount of DNA—many more will be added.
The breast cancer research was chosen as a test of the enterprise data warehouse because of the genomics data available on these 140 patients. Their de-identified information previously had been submitted as part of the federally funded project The Cancer Genome Atlas.
UPMC last fall announced it was working with Oracle, IBM, Informatica, and dbMotion to create an enterprise data warehouse that would foster personalized medicine. With the help of these companies, UPMC is installing the hardware and software needed to bring together data from more than 200 sources of information across UPMC, UPMC Health Plan, and outside entities, including labs and pharmacies. When the first phase of the multiyear project is completed in spring 2014, researchers, clinicians, and administrators will have secure, real-time access to data and analytic tools that fit their interests and needs.
FDA clears BioFire’s blood culture ID panel
BioFire Diagnostics received FDA clearance for its FilmArray Blood Culture Identification panel, which can identify more than 100 blood pathogens known to cause sepsis.
The 27-target panel provides results for gram-positive bacteria, gram-negative bacteria, and yeast that cause bloodstream infections.
The panel includes the first FDA cleared diagnostic test for the blaKPC gene, which is linked to carbapenem resistance in Klebsiella pneumoniae, Acinetobacter spp., and carbapenem-resistant Enterobacteriaceae. The BCID panel also tests for common antimicrobial resistance genes associated with methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci.
At Methodist in Houston, a germ killer moves in
The Methodist Hospital in Houston will put a 5-foot-5 robot to work killing influenza, norovirus, C. difficile, MRSA, and other pathogens in patient rooms, ICUs, and surgery suites. Its weapon: ultraviolet light.
The Total Room Ultraviolet Disinfector SmartUVC robot, called TRU-D and made by Lumalier, uses technology that measures reflected UVC emissions and automatically calculates pathogen-lethal UV doses. The company says more than 100 such devices are used in hospitals and medical facilities in the U.S. and Canada.
After a hospital staff member cleans a room using traditional methods, the TRU-D device is placed in the center of the room to finish the job by scanning and flooding the space with germicidal energy from its UVC lamps.
“Although ultraviolet germicidal irradiation is an old technology, advancements in delivery and application have made it a very effective tool in combating the transmission of common hospital pathogens,” says Mario Soares, Methodist’s director of environmental health and infection prevention and control.
Leica unveils Aperio AT2
Leica Biosystems launched on July 1 its Aperio AT2 image capture device.
The technology built into the Aperio AT2 reduces overhead and technician hours spent in front of the image capture device, “proven by the tissue finding accuracy, focusing, automated magnification selection, and less than two percent rescan rate, all aimed to achieve a very high-sustained throughput,” Leica chief medical officer Jared Schwartz, MD, PhD, said in a statement.