|Bid||6,270.00 x 0|
|Ask||6,500.00 x 0|
|Day's range||6,359.00 - 6,454.00|
|52-week range||5,312.00 - 6,634.00|
|Beta (3Y monthly)||1.10|
|PE ratio (TTM)||33.63|
|Earnings date||25 Jul 2019|
|Forward dividend & yield||2.15 (3.36%)|
|1y target est||78.83|
(Bloomberg) -- Machine-learning technology has beaten humans at games of chess and Go to worldwide fanfare. A demonstration of its eerily lifelike prowess in making phone calls to unsuspecting people went viral.But a less-noticed win for DeepMind, the artificial-intelligence arm of Google’s parent Alphabet Inc., at a biennial biology conference could upend how drugmakers find and develop new medicines. It could also dial up pressure on the world’s largest pharmaceutical companies to prepare for a technological arms race. Already, a new breed of upstarts are jumping into the fray.In December, at the CASP13 meeting in Riviera Maya, Mexico, DeepMind beat seasoned biologists at predicting the shapes of proteins, the basic building blocks of disease. The seemingly esoteric pursuit has serious implications: A tool that can accurately model protein structures could speed up the development of new drugs. “Absolutely stunning,” tweeted one scientist after the raw results were posted online. “It was a total surprise,” said conference founder John Moult, a University of Maryland computational biologist. “Compared to the history of what we had been able to do, it was pretty spectacular.” Sorting out the structure of proteins in order to find ways for medicines to attack disease is an enormously complex problem. Researchers still don’t fully understand the rules for how proteins are built. And then there’s the math: There are more possible protein shapes than there are atoms in the universe, making prediction a herculean undertaking of computation. For a quarter century, computational biologists have labored to devise software equal to the task.Enter DeepMind. With limited experience in protein folding — the physical process by which a protein acquires its three-dimensional shape — but armed with the latest neural-network algorithms, DeepMind did more than what 50 top labs from around the world could accomplish. Excitement rippled around the Mayan-themed resort where the meeting was held. Two DeepMind presenters were peppered with questions from scientists about how they had done it. Within hours, the British newspaper The Guardian said DeepMind’s AI could “usher in new era of medical progress.” In a blog post, the company bragged that its protein models were “far more accurate than any that have come before,” opening up “new potential within drug discovery.”In an email, DeepMind said its scientists were “fully focused on their research” and not available for interviews. DeepMind’s simulation doesn’t yet produce the kind of atomic-level resolution that is important for drug discovery. And though many companies are looking for ways to use computers to identify new medications, few machine-learning-based drugs have progressed to the point of being tested in humans. It will be years before anyone knows whether such software can regularly spot promising therapies that researchers might otherwise have missed.Artificial intelligence is a chic catchphrase in health care, often trotted out as a cure-all for whatever ails the industry. It has been held up as a potential solution to fix cumbersome electronic medical records, speed up diagnosis and make surgery more precise. DeepMind’s victory points to a possible practical application for the technology in one of the most expensive and failure-prone parts of the pharmaceutical business. Some observers said that the fact that a team of outsiders could make such significant progress in untangling one of the most vexing problems of biology is a black eye for researchers in the field. It could also be a portent for the drug industry, which spends billions on research and development, but was beaten to the punch. Mohammed AlQuraishi, a Harvard computational biology researcher who attended the conference, wrote in a blog post that giant pharmaceutical companies haven’t put a serious effort into protein folding, essentially ceding the ground to tech companies. While drug companies dithered, “Alphabet swoops in and sets up camp right in their backyard,” he wrote.Finding new drugs and bringing them to market is notoriously difficult. According to some estimates, big drugmakers spend more than $2.5 billion to get a new medicine to patients. Just one of every 10 therapies that enters human clinical trials makes it to the pharmacy. And science moves slowly: In the nearly 20 years since the human genome was sequenced, researchers have found treatments for a tiny fraction of the approximately 7,000 known rare diseases.Further, there are approximately 20,000 genes that can malfunction in at least 100,000 ways, and millions of possible interactions between the resultant proteins. It’s impossible for drug hunters to probe all of those combinations by hand.“If we want to understand the other 97 percent of human biology, we will have to acknowledge it is too complex for humans,” said Chris Gibson, the co-founder and Chief Executive Officer of Recursion Pharmaceuticals, a Salt Lake City-based startup that uses machine learning to hunt for new therapies.Companies like Recursion are rapidly luring investors. Venture capitalists poured $1.08 billion into AI and machine-learning startups focused on drug discovery last year, according to data provider PitchBook, up from just $237 million in 2016, and have already put in $699 million more so far this year. Recursion raised $121 million in its latest financing round, the company said on Monday, from investors including Intermountain Ventures and the Regents of the University of Minnesota. It has a valuation of $646 million, according to PitchBook. “It is a very ambitious company. They are thinking in terms of radically changing the industry,” said Marina Record, an investment manager at Baillie Gifford & Co. in Scotland, which led the funding round.Established drugmakers are racing to ally with companies doing similar work.In April, Gilead Sciences Inc. agreed to a deal with Insitro, a startup led by the former Stanford University machine-learning expert Daphne Koller, to find ways to treat liver disease NASH. AstraZeneca Plc the same month linked up with U.K.-based BenevolentAI to identify treatments for kidney disease and lung fibrosis. In June, GlaxoSmithKline Plc partnered with gene-editing pioneers at the University of California in a $67 million target-hunting collaboration that will use AI.“Where else would you accept a 1-in-10 success rate?” said GlaxoSmithKline senior vice president Tony Wood, who heads medicinal science and technology for the British pharmaceutical giant. “If we could double that to 20% it would be phenomenal.” Machine-learning methods “are going to be critical” to drug discovery, said Juan Alvarez, an associate vice president for computational chemistry at Merck & Co. The giant drugmaker is developing AI tools to help its chemists accelerate the laborious process of crafting chemicals to block aberrant proteins. Early machine-learning efforts have already contributed to drugs in human testing, while the first drugs based on more advanced neural-network methods could hit trials in several years, Alvarez said.Artificial intelligence could be used to scan millions of high-resolution cellular images—more than humans could ever process on their own—to identify therapies that could make diseased cells healthier in unexpected ways.At Recursion, one of the earliest startups to use such methods, each week robots apply thousands of potential drugs to various types of diseased cells, in 400,000 to 500,000 miniature experiments that generate 5 to 10 million cellular images. Machine-learning algorithms then scan the images, searching for compounds that disrupt disease without harming healthy cells. The initial algorithms were coded by hand to interpret basic cellular features, but Recursion is increasingly using neural-network methods that directly interpret the images and may spot patterns human programmers wouldn't have looked for. Computer scientists work in tandem with biologists in the laboratory to refine the leads. The company, which has agreed to rare-disease deals with Takeda Pharmaceutical Co. Ltd. and Sanofi, generated more than 2.5 petabytes of data in the past few years, a total that exceeds roughly the bandwidth of all Hollywood feature films. What the company is doing “just wasn't feasible six, or seven, or eight years ago,” said Gibson, its founder. Gibson first turned to machine learning as a graduate student at the University of Utah searching for treatments for cerebral cavernous malformation, which causes abnormal clumps of leaky blood vessels in the brain. The disorder affects about 1 in 500 people, according to the Angioma Alliance, and while often silent, can lead to seizures, speech or vision difficulties, and devastating brain hemorrhages. About a quarter of patients have a genetic form of the illness that is more likely to cause multiple malformations. Even though the three genes that cause it are known, there are no pharmaceutical treatments. One drug Gibson tested at the University of Utah based on the prevailing understanding of the disease made its symptoms worse in animals.Frustrated, Gibson and his colleagues used open-source machine-learning software for scanning cellular images to probe the effects of 2,100 compounds, searching for ones that improved the appearance and function of blood vessel cells that carried the bad genes. The algorithms pointed to an unexpected chemical that reduced leaky blood vessels in animal tests by 50 percent. That drug, set to enter second-stage human trials next year, led to the founding of Recursion.Other parts of Alphabet, as well as the AI research unit of social-media giant Facebook Inc., which quietly released a paper using deep learning to analyze 250 million protein sequences in April, are creeping into pharmaceutical-company turf. This spring, AI researchers at Google unveiled a neural network that can predict the function of a protein from its sequence of amino acids, which can help biologists understand what a newly discovered protein does. AI proponents say that nobody is talking about taking human researchers out of the equation. The goal is “augmenting and enhancing the decision-making capacity of scientists,” said Jackie Hunter, a former GlaxoSmithKline research executive who now leads clinical programs at BenevolentAI. In the short run, it’s more likely that AI-based simulations will be used to game out whether prospective drugs will be effective before going to a full-on clinical trial.An aerospace company “won’t build and fly a plane without building it on the computer first and simulating it under many conditions,” said Colin Hill of GNS Healthcare, a startup using AI to model disease, whose investors include Amgen Inc. In the future, drugmakers won’t begin clinical trials without a virtual dry run, Hill said.Still, the surprise that unfolded in Mexico has increased the tempo. DeepMind “basically beat everyone by a sizeable margin” said AlQuraishi, the Harvard researcher. If drugmakers don’t take the threat seriously, he said, they could be left in the dust. To contact the author of this story: Robert Langreth in New York at email@example.comTo contact the editor responsible for this story: Drew Armstrong at firstname.lastname@example.org, Timothy AnnettFor more articles like this, please visit us at bloomberg.com©2019 Bloomberg L.P.
GlaxoSmithKline Plc's cancer treatment Zejula met the main goal of helping patients with ovarian cancer live longer without their disease worsening in a late-stage study, the company said on Monday. The company bought the drug when it acquired U.S. cancer specialist Tesaro for $5.1 billion in December and Zejula is already approved for certain ovarian cancer patients. For GSK, the success of Zejula would help it access a wider population group and give it an edge over rival PARP inhibitors such as AstraZeneca and Merck & Co's Lynparza and Clovis Oncology's Rubraca.
These two FTSE 100 (INDEXFTSE:UKX) stocks could deliver improving income returns in my opinion.
Ruud Dobber, AstraZeneca’s biopharmaceuticals president, weighs in on the Trump administration walking back one change it had been seeking in the drug space.
London's FTSE 100 saw its seventh day in the red on Friday, its longest losing streak since 2015, led lower by losses in pharmaceuticals after the U.S. White House scrapped a rebate rule, while the midcap bourse jumped on prospects of lower interest rates. The UK's blue-chip index edged 0.1% lower after trading in positive territory for most of the session as its more internationally-exposed constituents such as miners climbed on hopes of an interest rate cut by the U.S Federal Reserve. The mid-cap FTSE 250, however, saw a 0.6% rise as a Bank of England official said that the BoE might need to cut interest rates almost to zero after a no-deal Brexit.
* European stocks fall after pharma stocks slide * STOXX 600 closes down 0.1%, healthcare stocks weigh: Siemens Healthineers -6% * Autos drag Germany's DAX 0.3% lower * UK housebuilders rise on upbeat survey * Indivior soars after lifting profit guidance, Reckitt rises after U.S. settlement Welcome to the home for real-time coverage of European equity markets brought to you by Reuters stocks reporters and anchored today by Thyagaraju Adinarayan. Reach him on Messenger to share your thoughts on market moves: email@example.com CLOSING SNAPSHOT: EUROPE CLOSES AT 2-WEEK LOW (1601 GMT) Profit taking in pharma stocks has derailed the Powell-induced gains, pushing the STOXX 600 into the red in late afternoon trade and to its lowest close since June 28.
* European stocks fall after pharma stocks slide * STOXX 600 down 0.2%, healthcare stocks weigh: Siemens Healthineers -7% * Autos drag Germany's DAX 0.3% lower * UK housebuilders rise on upbeat survey * Indivior soars after lifting profit guidance, Reckitt rises after U.S. settlement Welcome to the home for real-time coverage of European equity markets brought to you by Reuters stocks reporters and anchored today by Thyagaraju Adinarayan. Reach him on Messenger to share your thoughts on market moves: firstname.lastname@example.org HEALTH CHECK FOR PHARMA AS U.S. SHIFTS FOCUS TO HIGH DRUG PRICES (1527 GMT) European pharma stocks are taking a hit this afternoon on worries that U.S. Congress will now look at doing something about high drug prices.
A federal district court judge on Monday stopped the Trump administration from requiring drug makers to disclose drug wholesale prices in TV ads. But consumers can still find drug prices.
European shares closed at a two-week low on Thursday weighed down by pharma stocks on worries that U.S. government may intervene on high drug prices, while optimism from the Federal Reserve's dovish stance faded away. The pan-European stocks benchmark rallied earlier in the day on remarks from Fed Chair Jerome Powell but reversed course in late afternoon trading to close 0.1% lower. The White House announced that it was ditching its push for changes to the pharma rebate structure, providing some relief to health insurance companies but hurting drugmakers, including those in Europe.
London's main index skidded for the sixth straight session on Thursday as investors sold off healthcare stocks after Washington withdrew a rebate rule aimed at lowering drug prices, and a Fed-fuelled rally fizzled out. The FTSE 100 shed 0.3%, while the mid-cap FTSE 250 capitalised on a rise in sterling to add 0.1%.
Britain's main index rallied to a 10-month high on Wednesday as sterling fell after weak economic data, which aided exporter firms, reinforced bets that the Bank of England would cut interest rates and drove investors to high-dividend stocks. The FTSE 100 rose 0.7%, scaling its highest level since Aug. 29, boosted by shares of companies that book a major chunk of their revenue overseas. The FTSE 250 added 0.6%.
Pascal Soriot has been the CEO of AstraZeneca PLC (LON:AZN) since 2012. This report will, first, examine the CEO...
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Trial showed statistically-significant and clinically meaningful benefit in patients with the most aggressive type of lung cancer
London's main index edged up on Monday as gains in defensive stocks such as healthcare were balanced by pressure on Asia-focussed banks, with Sino-U.S. trade talks once again set to take centre stage at this week's G20 summit. The FTSE 100 eked out a 0.1% gain, outperforming the broader European index, which fell on poor German economic data, and as a profit warning from Mercedes-Benz owner Daimler triggered a sell-off in the region's carmakers.
London's FTSE 100 rebounded on growing hopes of more central bank stimulus after the Bank of England cut its growth forecast and the U.S. Federal Reserve flagged interest rate cuts, though cruise operator Carnival slid after lowering its profit target. The FTSE 100 index rose 0.3% with BP and Shell both up more than 1% as Middle East tensions drove oil prices higher.
On March 28, AstraZeneca (AZN) issued a press release announcing its collaboration with Daiichi Sankyo for the development and commercialization of trastuzumab deruxtecan, an investigational therapy currently being evaluated for multiple HER2-expressing cancers.
In the first quarter, Lynparza garnered revenue of $237 million for AstraZeneca (AZN), a YoY (year-over-year) rise of more than 105% driven mainly by its ongoing launch as a second-line maintenance therapy for ovarian cancer and as a therapy for germline BRCA-mutated metastatic breast cancer in the US and Japan.
London's main stock index recorded its best one-day gain in more than four months on Tuesday as a promise of more stimulus if required from European Central Bank (ECB) chief Mario Draghi lifted UK shares across sectors. The FTSE 100 index ended 1.2% higher, after having earlier touched levels not seen in two months, and the FTSE 250 midcap index added 0.8% after Draghi said the central bank would need to ease policy again if inflation did not head back to its target. The ECB's comments came in the midst of a two-day meeting of the U.S. Federal Reserve that money market pricing shows should clear the way to a cut in interest rates by the central bank next month.
London's FTSE 100 edged higher on Tuesday with tool hire firm Ashtead gaining after an upbeat earnings report and miners boosted by a rise in copper prices driven by expectations of a global shortfall in production. The miner-heavy main index was up 0.1% while the FTSE 250 midcap index lost 0.2% by 0708 GMT. Ashtead rose nearly 3%, topping the FTSE 100 leader-board, while miners were up 1% as a key mine in Chile halved output due to a strike.
Lynparza, being jointly developed by AstraZeneca along with U.S. drugmaker Merck & Co , can now be used in patients who are in response following chemotherapy for advanced BRCA-mutated ovarian cancer in Europe, AstraZeneca said. BRCA genes are responsible for producing proteins which repair damaged DNA, and if the genes are mutated, they can cause cancer growth.