Gilead Sciences reported positive data from the Phase III Discover trial and the efficacy data demonstrated non-inferiority of Descovy to Truvada for HIV pre-exposure prophylaxis, Piper Jaffray analyst Tyler Van Buren tells investors in a research note. The analyst, however, believes the numerical improvements appear small and wonders if a year will be enough time to convert the majority of a $2.6B Truvada U.S. sales franchise prior to generic entry in 2021 In order for this conversion to be “exceedingly” successful, the safety advantage needs to be “dramatic” given the anticipated low price of generic Truvada, says Van Buren. He’s still uncertain as to how well it will go and keeps a Neutral rating on Gilead with a $75 price target.
Thursday, March 7, 2019
CareDx remains a top small cap idea at Piper Jaffray
Piper Jaffray analyst William Quirk says CareDx’s Q4 results were driven by strong AlloSure performance and enrollment expansion in the K-OAR study. The analyst views the company’s 2019 revenue guidance as conservative and believes its competitive moat in transplant medicine continues to widen. The stock remains his top small cap idea and Quirk reiterates an Overweight rating on CareDx with a $42 price target.
Illumina, Chinese Firm Partner on NGS System for Genetic Disease Dx
Illumina and China firm Boai NKY Medical Holdings have partnered to develop next-generation sequencing-based hereditary disease tests in China.
Under the agreement announced on Tuesday, NKY and Illumina will develop an NGS system based on Illumina’s MiniSeq system and NKY’s library prep kits and analysis software to develop in vitro diagnostics for hereditary kidney disease. The goal is to develop a platform that will meet regulatory criteria of China’s National Medical Products Administration.
NKY is Tianjin-based manufacturer of polyvinylpyrrolidone, a water-soluble polymer that is used in a range of pharmaceutical, industrial, and cosmetic applications. But recently, it has also formed a precision medicine business arm.
“The molecular diagnosis of hereditary diseases has three major applications,” Huasheng Fang, chairman of NKY, said in a statement. First, “it could be a good auxiliary diagnosis for certain diseases; second, it could be used as a screening method for high-risk populations with a family history of hereditary diseases.” Lastly, it could provide guidance to families, who have given birth to a child with congenital disease, on their reproductive health, he said.
CRISPR Researchers Find Some Editors Generate Substantial Off-Target Effects
In a study published in Science late last week, researchers from the US, China, and Germany reported a new method they’ve developed to detect off-target mutations created from editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or one of two base editing technologies.
This method — named GOTI (Genome-wide Off-target analysis by Two-cell embryo Injection) — found that off-target single nucleotide variants (SNVs) were rare in embryos edited by CRISPR-Cas9 or the adenine base editor 7.10 (ABE7.10), which both caused off-target effects with a frequency close to the spontaneous mutation rate. However, the researchers also found that the cytosine base editor 3 (BE3) induced SNVs with frequencies more than 20-fold higher than the spontaneous mutation rate.
The team began by injecting CRISPR-Cas9, BE3, or ABE7.10, along with Cre mRNA, into one blastomere of two-cell embryos derived from mice engineered to express the tdTomato fluorescent protein. The progeny cells of the edited and non-edited blastomeres were then sorted on tdTomato expression in the gene-edited cells at embryonic day 14.5, and the researchers performed whole-genome sequencing separately on the tdTomato-positive and tdTomato-negative cells. SNVs and indels were called by three algorithms in the tdTomato-positive sample, using the tdTomato-negative sample from the same embryo as the reference.
They validated the on-target efficiency of their approach in embryos at the eight-cell and embryonic day-14.5 stages by Sanger sequencing, and then performed WGS at an average depth of 47x on 46 samples from 23 embryonic day-14.5 embryos in order to further explore the on-target efficiency and potential genome-wide off-target effects.
“The SNVs detected in the Cre- or Cas9-treated samples were likely caused by spontaneous mutations during genome replication during development, since the number of variants was within the range of simulated spontaneous mutations and no sequence similarity was observed between the adjacent sequences of the identified SNVs and the target sites,” the authors wrote. “Surprisingly, we found on average 283 SNVs/embryo in BE3-treated embryos, a level at least 20 times higher than that observed in Cre- or Cas9-treated embryos. By contrast, ABE7.10 generated on average 10 SNVs/embryo, with a frequency close to the spontaneous mutation rate.”
The researchers further found that SNVs induced by BE3 were significantly enriched in transcribed regions, especially in genes with high expression, and that none of the off-target sites were shared by any of the BE3-treated embryos or overlapped with predicted off-target mutations.
“Besides, no similarity was observed between the off-target and on-target sequences,” they added, “whereas the top predicted off-target sites showed high sequence similarity with BE3 on-target loci. Thus, the BE3 off-target SNVs were sgRNA-independent and likely caused by overexpression of APOBEC1.”
The team also noted that numerous de novo SNVs induced by BE3 turned up in this analysis which had not been reported in previous studies. The investigators speculated that this could be because GOTI examines the cell population derived from a single gene-edited blastomere, whereas previous studies have used large pools of cells where editing is variable, resulting in loss of signal for random off-target effects. They concluded that off-target effects of base editors may be reduced by decreasing the DNA binding ability of APOBEC1 or using different versions of cytidine deaminase, and that GOTI could be useful in examining the off-target effects of various gene editing tools.
In a different study published today in Nature Biotechnology, researchers from South Korea showed that Cas9, BE3, and ABE7.10 often recognize different off-target sites. They also used a targeted sequencing method along with preassembled adenine base editor ribonucleoproteins, modified guide RNAs, and Sniper/Cas9 to reduce adenine base editor off-target activity in human cells.
In a previous study, these researchers used a modified Digenome-seq protocol to detect off-target effects from cytosine base editors in the human genome. For this study, they sought to profile the off-target activity of adenine base editors using the same protocol.
They began by analyzing whether the off-target activities of ABE7.10, BE3, and CRISPR-Cas9 were different from each other by testing a series of mismatched sgRNAs targeted to endogenous genomic loci, and found that base editors and Cas9 nucleases tolerated most of the single or double mismatches in the sgRNAs but were poorly active when combined with most of the sgRNAs having triple or quadruple mismatches.
They also noted that the tolerance of Cas9, ABE7.10, and BE3 for mismatched sgRNAs was often different from each other, suggesting that ABE7.10, BE3, and Cas9 could recognize separate sets of off-target sites in the human genome. The researchers concluded that a method was needed to determine the genome-wide specificity of adenine base editors in an unbiased manner.
After various analyses suggested that Digenome-seq could be used to comprehensively map genome-wide on-target and off-target sites of adenine base editing, the researchers moved on to determine ABE7.10 off-target sites in the human genome. They assigned a DNA cleavage score to each base pair position across the entire genome, allowing direct comparisons between adenine and cytosine base editors and Cas9, and found that adenine base editors in general are more specific than Cas9 but can recognize different sets of off-target sites.
They also unexpectedly found that ABE7.10 activities were correlated more strongly with Cas9 activities than with BE3 activities. Among six sites edited at relatively high frequencies with ABE7.10 but poorly with BE3, two sites had no cytosine within the BE3 editing window of several nucleotides.
In a subsequent experiment to minimize or avoid off-target effects from adenine base editing, the researchers tested three different methods that have proven to reduce off-target effects from Cas9 and BE3 editing: sgRNA modification, delivery of RNPs in lieu of plasmids, and use of an engineered Cas9 variant called Sniper-Cas9. They found that extended sgRNAs reduced off-target activity at almost every site without sacrificing on-target activity, while truncated sgRNAs reduced both on-target and off-target activity at most sites and exacerbated off-target effects at sites with mismatches at or near the 5′ terminus.
Further, the use of Sniper ABE7.10 or delivery of ABE7.10 RNPs rather than plasmids improved the specificity of base editing, and combining Sniper ABE7.10 with modified sgRNAs further reduced off-target activity at many validated off-target sites.
Amazon-led healthcare venture has a name and a website
Forget ABC or ABJ or even #berkmorgazon as some in the industry had dubbed the mystery partnership between Amazon, JPMorgan and Berkshire Hathaway. The group released new details about its plans on Wednesday, including its new name: Haven.
The new company also unveiled its website.
“We want to change the way people experience healthcare so that it is simpler, better and lower cost,” said Haven CEO Atul Gawande, M.D., in a statement. “We’ll start small, learn from the experience of patients and continue to expand to meet their needs.”
As the group describes their work, Haven will focus on the 1.2 million employees and families affiliated with Amazon, Berkshire and JPMorgan across the U.S. with a plan to “share what it learns to help others.”
“The good news is the best results are not the most complicated or expensive. The right care in the right place is often more effective and less costly than what we get today,” Gawande said in the statement.
The three major companies announced in January 2018 that they were teaming up to create a venture that could leverage their combined resources to create health solutions to benefit their U.S. workforces and eventually, all Americans. The announcement caused shockwaves across the industry.
According to Haven’s new website, they are looking to simplify healthcare and said their work may take “many forms.”
“We believe it is possible to deliver simplified, high-quality and transparent healthcare at a reasonable cost,” the website said. “We are focused on leveraging the power of data and technology to drive better incentives, a better patient experience and a better system.
Other members of the leadership team include Jack Stoddard as chief operating officer, Serkan Kutan as chief technology officer and Dana Safran as head of measurement.
Unsealed testimony from Optum’s challenge against the hiring of a former executive at the insurer who took a role at Haven, revealed new details that touched on the theme of addressing insurance complexity.
“It’s very difficult for the employees when we talk to them to be able to understand what’s covered, to afford their coverage,” Stoddard said during testimony. “These are fulfillment center workers. These are call center workers.” He said as the team studies how these employees are using their health plans, the company is likely to significantly overhaul benefit design.
The organization is headquartered in Boston with an office in New York, and officials said they are looking to recruit a range of talent, including software engineers, data scientists and clinicians.
Glenmark Pharmaceuticals gets FDA nod for hypertension drug
Glenmark Pharmaceuticals Tuesday said it has received final approval from the US health regulator for Telmisartan and Hydrochlorothiazide tablets, used to treat high blood pressure (hypertension).
The approved products is a generic version of Boehringer Ingelheim Pharmaceuticals Inc`s Micardis HCT tablets.
Glenmark Pharmaceuticals Inc, USA has been granted final approval by the United States Food & Drug Administration (USFDA) for Telmisartan and Hydrochlorothiazide Tablets USP in the strengths of 40 mg/12.5 mg, 80 mg/12.5 mg, and 80 mg/25 mg, the company said in a BSE filing.
Quoting IQVIA sales data for the 12 month period ending January 2019, Glenmark said the Micardis HCT tablets market achieved annual sales of approximately USD 40.6 million.
The company`s current portfolio consists of 150 products authorised for distribution at the US marketplace and 52 Abbreviated New Drug Applications (ANDAs) pending approval with the USFDA.
Roche Study Shows AI Can Detect Severity of Diabetic Macular Edema
A new study conducted by researchers from Genentech and Roche shows first-time proof that artificial intelligence can detect the severity of diabetic macular edema, which is a leading cause of blindness.
On Monday, researchers from Genentech and its parent company Roche published the study, Deep Learning Predicts OCT Measures of Diabetic Macular Thickening From Color Fundus Photographs” in the journal, Investigative Ophthalmology & Visual Science. The study showed that artificial intelligence can be used to provide widespread, cost-effective eye screenings via telemedicine to assist ophthalmologists in improving vision outcomes for millions of people with diabetes who may not be getting regular eye exams. The article is the first to be published that is part of a Roche/Genentech’s Ophthalmology Personalized Healthcare initiative. The initiative, Roche said in a statement, aims to combine meaningful large-scale data and AI technology to predict and prevent ocular conditions and preserve vision.
The study, Roche said, adds to the growing amount of scholarly information about the use of artificial intelligence in ophthalmology. The study sheds light on how a company such as Roche and its Genentech subsidiary can use its clinical trial database to develop AI algorithms to predict the presence of disease, risk of disease progression, and response to treatment; all of which could be supplied to ophthalmologists to deliver higher quality personalized healthcare.
Diabetic macular edema (DME) is a condition in which the retina develops diabetic microangiopathy with subsequent accumulation of fluid in the macula. It is a leading cause of vision impairment in people with diabetes, compromising their function and quality of life. According to the article, in 2017, approximately 425 million people worldwide had diabetes, and this number is estimated to grow to 629 million by 2045. Adults with diabetes and DME also have a substantially higher risk of cardiovascular morbidity, mortality, and amputation risk than those without, creating a further public health hazard.
According to the American Academy of Ophthalmology, having a dilated eye exam yearly or as recommended by an ophthalmologist can prevent 95 percent of diabetes-related vision loss. Roche though, said that many diabetic patients do not receive these kinds of examinations annually. Because of that, diagnoses of DME, or the severity of the disease, go unknown in many individuals. Because of that, many people with DME may be under-diagnosed or treated late and are at risk for irreversible vision loss or blindness, Roche said.
Roche and Genentech said that the study was the first time that researchers were able to demonstrate that artificial intelligence, specifically deep learning technology, is able to detect swelling in the macula, which is the part of the eye responsible for central vision and allows for people to see color and details. Also, the study showed that DLT can detect the severity of the swelling in people with diabetes. This swelling in the macula is known as diabetic macular edema (DME), a sight-stealing condition that impacts approximately 10 percent of the 425 million people around the world living with diabetes,” Roche said.
The primary way of diagnosing diabetic macular edema is through the use of optical coherence tomography (OCT), which takes three-dimensional, cross-sectional images of the macula. However, in its announcement, Roche said OCT is not often used in screening programs or telemedicine. OCT uses two-dimensional color photos called color fundus photos. Roche said one of the issues of these types of images is the two-dimensional nature of CFPs actually makes detecting the severity of DME difficult. In order to address this limitation, the Roche/Genentech research assessed how deep learning can automatically view CFPs to accurately detect DME and determine its severity.
Roche said its researchers used approximately 18,000 CFPs and associated OCT images during Genentech’s previous Phase III DME studies to develop and assess the performance of deep learning algorithms. The researchers said the results of the study showed that “the best deep learning algorithm was up to 97 percent accurate in detecting DME severity using CFP images alone.”
“Such results underscore the promising potential of AI in increasing screening capacity via telemedicine with appropriate triage to assist ophthalmologists in improving vision outcomes for a large population of patients who may not be getting comprehensive eye exams,” Roche said in its announcement.
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