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Live Conference Coverage @Medcitynews Converge 2018 @Philadelphia: Promising Drugs and Breaking Down Silos

Reporter: Stephen J. Williams, PhD

Promising Drugs, Pricing and Access

The drug pricing debate rages on. What are the solutions to continuing to foster research and innovation, while ensuring access and affordability for patients? Can biosimilars and generics be able to expand market access in the U.S.?

Moderator: Bunny Ellerin, Director, Healthcare and Pharmaceutical Management Program, Columbia Business School
Speakers:
Patrick Davish, AVP, Global & US Pricing/Market Access, Merck
Robert Dubois M.D., Chief Science Officer and Executive Vice President, National Pharmaceutical Council
Gary Kurzman, M.D., Senior Vice President and Managing Director, Healthcare, Safeguard Scientifics
Steven Lucio, Associate Vice President, Pharmacy Services, Vizient

What is working and what needs to change in pricing models?

Robert:  He sees so many players in the onStevencology space discovering new drugs and other drugs are going generic (that is what is working).  However are we spending too much on cancer care relative to other diseases (their initiative Going Beyond the Surface)

Steven:  the advent of biosimilars is good for the industry

Patrick:  large effort in oncology, maybe too much (750 trials on Keytruda) and he says pharma is spending on R&D (however clinical trials take large chunk of this money)

Robert: cancer has gotten a free ride but cost per year relative to benefit looks different than other diseases.  Are we overinvesting in cancer or is that a societal decision

Gary:  maybe as we become more specific with precision medicines high prices may be a result of our success in specifically targeting a mutation.  We need to understand the targeted drugs and outcomes.

Patrick: “Cancer is the last big frontier” but he says prices will come down in most cases.  He gives the example of Hep C treatment… the previous only therapeutic option was a very toxic yearlong treatment but the newer drugs may be more cost effective and safer

Steven: Our blockbuster drugs could diffuse the expense but now with precision we can’t diffuse the expense over a large number of patients

President’s Cancer Panel Recommendation

Six recommendations

  1. promoting value based pricing
  2. enabling communications of cost
  3. financial toxicity
  4. stimulate competition biosimilars
  5. value based care
  6. invest in biomedical research

Patrick: the government pricing regime is hurting.  Alot of practical barriers but Merck has over 200 studies on cost basis

Robert:  many concerns/impetus started in Europe on pricing as they are a set price model (EU won’t pay more than x for a drug). US is moving more to outcomes pricing. For every one health outcome study three studies did not show a benefit.  With cancer it is tricky to establish specific health outcomes.  Also Medicare gets best price status so needs to be a safe harbor for payers and biggest constraint is regulatory issues.

Steven: They all want value based pricing but we don’t have that yet and there is a challenge to understand the nuances of new therapies.  Hard to align all the stakeholders together so until some legislation starts to change the reimbursement-clinic-patient-pharma obstacles.  Possibly the big data efforts discussed here may help align each stakeholders goals.

Gary: What is the data necessary to understand what is happening to patients and until we have that information it still will be complicated to determine where investors in health care stand at in this discussion

Robert: on an ICER methods advisory board: 1) great concern of costs how do we determine fair value of drug 2) ICER is only game in town, other orgs only give recommendations 3) ICER evaluates long term value (cost per quality year of life), budget impact (will people go bankrupt)

4) ICER getting traction in the public eye and advocates 5) the problem is ICER not ready for prime time as evidence keeps changing or are they keeping the societal factors in mind and they don’t have total transparancy in their methodology

Steven: We need more transparency into all the costs associated with the drug and therapy and value-based outcome.  Right now price is more of a black box.

Moderator: pointed to a recent study which showed that outpatient costs are going down while hospital based care cost is going rapidly up (cost of site of care) so we need to figure out how to get people into lower cost setting

Breaking Down Silos in Research

“Silo” is healthcare’s four-letter word. How are researchers, life science companies and others sharing information that can benefit patients more quickly? Hear from experts at institutions that are striving to tear down the walls that prevent data from flowing.

Moderator: Vini Jolly, Executive Director, Woodside Capital Partners
Speakers:
Ardy Arianpour, CEO & Co-Founder, Seqster @seqster
Lauren Becnel, Ph.D., Real World Data Lead for Oncology, Pfizer
Rakesh Mathew, Innovation, Research, & Development Lead, HealthShareExchange
David Nace M.D., Chief Medical Officer, Innovaccer

Seqster: Seqster is a secure platform that helps you and your family manage medical records, DNA, fitness, and nutrition data—all in one place. Founder has a genomic sequencing background but realized sequence  information needs to be linked with medical records.

HealthShareExchange.org :

HealthShare Exchange envisions a trusted community of healthcare stakeholders collaborating to deliver better care to consumers in the greater Philadelphia region. HealthShare Exchange will provide secure access to health information to enable preventive and cost-effective care; improve quality of patient care; and facilitate care transitions. They have partnered with multiple players in healthcare field and have data on over 7 million patients.

Innovacer

Data can be overwhelming, but it doesn’t have to be this way. To drive healthcare efficiency, we designed a modular suite of products for a smooth transition into a data-driven world within 4 weeks. Why does it take so much money to move data around and so slowly?

What is interoperatibility?

Ardy: We knew in genomics field how to build algorithms to analyze big data but how do we expand this from a consumer standpoint and see and share your data.

Lauren: how can we use the data between patients, doctors, researchers?  On the research side genomics represent only 2% of data.  Silos are one issue but figuring out the standards for data (collection, curation, analysis) is not set. Still need to improve semantic interoperability. For example Flatiron had good annotated data on male metastatic breast cancer.

David: Technical interopatabliltiy (platform), semantic interopatability (meaning or word usage), format (syntactic) interopatibility (data structure).  There is technical interoperatiblity between health system but some semantic but formats are all different (pharmacies use different systems and write different prescriptions using different suppliers).  In any value based contract this problem is a big issue now (we are going to pay you based on the quality of your performance then there is big need to coordinate across platforms).  We can solve it by bringing data in real time in one place and use mapping to integrate the format (need quality control) then need to make the data democratized among players.

Rakesh:  Patients data should follow the patient. Of Philadelphia’s 12 health systems we had a challenge to make data interoperatable among them so tdhey said to providers don’t use portals and made sure hospitals were sending standardized data. Health care data is complex.

David: 80% of clinical data is noise. For example most eMedical Records are text. Another problem is defining a patient identifier which US does not believe in.

 

 

 

 

Please follow on Twitter using the following #hash tags and @pharma_BI

#MCConverge

#cancertreatment

#healthIT

#innovation

#precisionmedicine

#healthcaremodels

#personalizedmedicine

#healthcaredata

And at the following handles:

@pharma_BI

@medcitynews

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Live Conference Coverage Medcity Converge 2018 Philadelphia: Clinical Trials and Mega Health Mergers

Reporter: Stephen J. Williams, PhD

1:30 – 2:15 PM Clinical Trials 2.0

The randomized, controlled clinical trial is the gold standard, but it may be time for a new model. How can patient networks and new technology be leveraged to boost clinical trial recruitment and manage clinical trials more efficiently?

Moderator: John Reites, Chief Product Officer, Thread @johnreites
Speakers:
Andrew Chapman M.D., Chief of Cancer Services , Sidney Kimmel Cancer Center, Thomas Jefferson University Hospital
Michelle Longmire, M.D., Founder, Medable @LongmireMD
Sameek Roychowdhury MD, PhD, Medical Oncologist and Researcher, Ohio State University Comprehensive Cancer Center @OSUCCC_James

 

Michele: Medable is creating a digital surrogate biomarker for short term end result for cardiology clinical trials as well as creating a virtual site clinical trial design (independent of geography)

Sameek:  OSU is developing RNASeq tests for oncogenic fusions that are actionable

John: ability to use various technologies to conduct telehealth and tele-trials.  So why are we talking about Clinical Trials 2.0?

Andrew: We are not meeting many patients needs.  The provider also have a workload that prevents from the efficient running of a clinical trial.

Michele:  Personalized medicine: what is the framework how we conduct clinical trials in this new paradigm?

Sameek: How do we find those rare patients outside of a health network?  A fragmented health system is hurting patient recruitment efforts.

Wout: The Christmas Tree paradigm: collecting data points based on previous studies may lead to unnecessary criteria for patient recruitment

Sameek:  OSU has a cancer network (Orion) that has 95% success rate of recruitment.  Over Orion network sequencing performed at $10,000 per patient, cost reimbursed through network.  Network helps pharma companies find patients and patients to find drugs

Wout: reaching out to different stakeholders

John: what he sees in 2.0 is use of tech.  They took 12 clinic business but they integrated these sites and was able to benefit patient experience… this helped in recruitment into trials.  Now after a patient is recruited, how 2.0 model works?

Sameek:  since we work with pharma companies, what if we bring in patients from all over the US.  how do we continue to take care of them?

Andrew: utilizing a technology is critically important for tele-health to work and for tele-clinical trials to work

Michele:  the utilization of tele-health by patients is rather low.

Wout:  We are looking for insights into the data.  So we are concentrated on collecting the data and not decision trees.

John: What is a barrier to driving Clinical Trial 2.0?

Andrew: The complexity is a barrier to the patient.  Need to show the simplicity of this.  Need to match trials within a system.

Saleem: Data sharing incentives might not be there or the value not recognized by all players.  And it is hard to figure out how to share the data in the most efficient way.

Wout: Key issue when think locally and act globally but healthcare is the inverse of this as there are so many stakeholders but that adoption by all stakeholders take time

Michele: accessibility of healthcare data by patients is revolutionary.  The medical training in US does not train doctors in communicating a value of a trial

John: we are in a value-driven economy.  You have to give alot to get something in this economy. Final comments?

Saleem: we need fundamental research on the validity of clinical trials 2.0.

Wout:  Use tools to mine manually but don’t do everything manually, not underlying tasks

Andrew: Show value to patient

2:20-3:00 PM CONVERGEnce on Steroids: Why Comcast and Independence Blue Cross?

This year has seen a great deal of convergence in health care.  One of the most innovative collaborations announced was that of Cable and Media giant Comcast Corporation and health plan Independence Blue Cross.  This fireside chat will explore what the joint venture is all about, the backstory of how this unlikely partnership came to be, and what it might mean for our industry.

sponsored by Independence Blue Cross @IBX 

Moderator: Tom Olenzak, Managing Director Strategic Innovation Portfolio, Independence Blue Cross @IBX
Speakers:
Marc Siry, VP, Strategic Development, Comcast
Michael Vennera, SVP, Chief Information Officer, Independence Blue Cross

Comcast and Independence Blue Cross Blue Shield are teaming together to form an independent health firm to bring various players in healthcare onto a platform to give people a clear path to manage their healthcare.  Its not just about a payer and information system but an ecosystem within Philadelphia and over the nation.

Michael:  About 2015 at a health innovation conference they came together to produce a demo on how they envision the future of healthcare.

Marc: When we think of a customer we think of the household. So we thought about aggregating services to people in health.  How do people interact with their healthcare system?

What are the risks for bringing this vision to reality?

Michael: Key to experience is how to connect consumer to caregiver.

How do we aggregate the data, and present it in a way to consumer where it is actionable?

How do we help the patient to know where to go next?

Marc: Concept of ubiquity, not just the app, nor asking the provider to ask patient to download the app and use it but use our platform to expand it over all forms of media. They did a study with an insurer with metabolic syndrome and people’s viewing habits.  So when you can combine the expertise of IBX and the scale of a Comcast platform you can provide great amount of usable data.

Michael: Analytics will be a prime importance of the venture.

Tom:  We look at lots of companies that try to pitch technologies but they dont understand healthcare is a human problem not a tech problem.  What have you learned?

Marc: Adoption rate of new tech by doctors is very low as they are very busy.  Understanding the clinicians workflow is important and how to not disrupt their workflow was humbling for us.

Michael:  The speed at which big tech companies can integrate and innovate new technologies is very rapid, something we did not understand.  We want to get this off the ground locally but want to take this solution national and globally.

Marc:  We are not in competition with local startups but we are looking to work with them to build scale and operability so startups need to show how they can scale up.  This joint venture is designed to look at these ideas.  However this will take a while before we open up the ecosystem until we can see how they would add value. There are also challenges with small companies working with large organizations.

 

Please follow on Twitter using the following #hashtags and @pharma_BI

#MCConverge

#cancertreatment

#healthIT

#innovation

#precisionmedicine

#healthcaremodels

#personalizedmedicine

#healthcaredata

And at the following handles:

@pharma_BI

@medcitynews

 

Please see related articles on Live Coverage of Previous Meetings on this Open Access Journal

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT

Real Time Coverage and eProceedings of Presentations on 11/16 – 11/17, 2016, The 12th Annual Personalized Medicine Conference, HARVARD MEDICAL SCHOOL, Joseph B. Martin Conference Center, 77 Avenue Louis Pasteur, Boston

Tweets Impression Analytics, Re-Tweets, Tweets and Likes by @AVIVA1950 and @pharma_BI for 2018 BioIT, Boston, 5/15 – 5/17, 2018

BIO 2018! June 4-7, 2018 at Boston Convention & Exhibition Center

https://pharmaceuticalintelligence.com/press-coverage/

 

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Reporter: Stephen J. Williams, PhD

10:00-10:45 AM The Davids vs. the Cancer Goliath Part 1

Startups from diagnostics, biopharma, medtech, digital health and emerging tech will have 8 minutes to articulate their visions on how they aim to tame the beast.

Start Time End Time Company
10:00 10:08 Belong.Life
10:09 10:17 Care+Wear
10:18 10:26 OncoPower
10:27 10:35 PolyAurum LLC
10:36 10:44 Seeker Health

Speakers:
Karthik Koduru, MD, Co-Founder and Chief Oncologist, OncoPower
Eliran Malki, Co-Founder and CEO, Belong.Life
Chaitenya Razdan, Co-founder and CEO, Care+Wear @_crazdan
Debra Shipley Travers, President & CEO, PolyAurum LLC @polyaurum
Sandra Shpilberg, Founder and CEO, Seeker Health @sandrashpilberg

Belong Life

  • 10,000 cancer patients a month helping patients navigate cancer care with Belong App
  • Belong Eco system includes all their practitioners and using a trigger based content delivery (posts, articles etc)
  • most important taking unstructured health data (images, social activity, patient compilance) and converting to structured data

Care+Wear

personally design picc line cover for oncology patients

partners include NBA Major league baseball, Oscar de la Renta,

designs easy access pic line gowns and shirts

OncoPower :Digital Health in a Blockchain Ecosystem

problems associated with patient adherence and developed a product to address this

  1. OncoPower Blockchain: HIPAA compliant using the coin Oncopower security token to incentiavize patients and oncologists to consult with each other or oncologists with tumor boards; this is not an initial coin offering

PolyArum

  • spinout from UPENN; developing a nanoparticle based radiation therapy; glioblastoma muse model showed great response with gold based nanoparticle and radiation
  • they see enhanced tumor penetration, and retention of the gold nanoparticles
  • however most nanoparticles need to be a large size greater than 5 nm to see effect so they used a polymer based particle; see good uptake but excretion past a week so need to re-dose with Au nanoparticles
  • they are looking for capital and expect to start trials in 2020

Seeker Health

  • tying to improve the efficiency of clinical trial enrollment
  • using social networks to find the patients to enroll in clinical trials
  • steps they use 1) find patients on Facebook, Google, Twitter 2) engage patient screen 3) screening at clinical sites
  • Seeker Portal is a patient management system: patients referred to a clinical site now can be tracked

11:00- 11:45 AM Breakout: How to Scale Precision Medicine

The potential for precision medicine is real, but is limited by access to patient datasets. How are government entities, hospitals and startups bringing the promise of precision medicine to the masses of oncology patients

Moderator: Sandeep Burugupalli, Senior Manager, Real World Data Innovation, Pfizer @sandeepburug
Speakers:
Ingo ​Chakravarty, President and CEO, Navican @IngoChakravarty
Eugean Jiwanmall, Senior Research Analyst for Medical Policy & Technology Evaluation , Independence Blue Cross @IBX
Andrew Norden, M.D., Chief Medical Officer, Cota @ANordenMD
Ankur Parikh M.D, Medical Director of Precision Medicine, Cancer Treatment Centers of America @CancerCenter

Ingo: data is not ordered, only half of patients are tracked in some database, reimbursement a challenge

Eugean: identifying mutations as patients getting more comprehensive genomic coverage, clinical trials are expanding more rapidly as seen in 2018 ASCO

Ingo: general principals related to health outcomes or policy or reimbursement.. human studies are paramount but payers may not allowing for general principals (i.e. an Alk mutation in lung cancer and crizotanib treatment may be covered but maybe not for glioblastoma or another cancer containing similar ALK mutation; payers still depend on clinical trial results)

Andrew: using gene panels and NGS but only want to look for actionable targets; they establish an expert panel which reviews these NGS sequence results to determine actionable mutations

Ankur:  they have molecular tumor boards but still if want to prescribe off label and can’t find a clinical trial there is no reimbursement

Andrew: going beyond actionable mutations, although many are doing WES (whole exome sequencing) can we use machine learning to see if there are actionable data from a WES

Ingo: we forget in datasets is that patients have needs today and we need those payment systems and structures today

Eugean: problem is the start from cost (where the cost starts at and was it truly medically necessary)

Norden: there are not enough data sharing to make a decision; an enormous amount of effort to get businesses and technical limitations in data sharing; possibly there are policies needed to be put in place to assimilate datasets and promote collaborations

Ingo: need to take out the middle men between sequencing of patient tumor and treatment decision; middle men are taking out value out of the ‘supply chain’;

Andrew: PATIENTS DON’T OWN their DATA but MOST clinicians agree THEY SHOULD

Ankur: patients are willing to share data but the HIPAA compliance is a barrier

 

11:50- 12:30 AM Fireside Chat with Michael Pellini, M.D.

Building a Precision Medicine Business from the Ground Up: An Operating and Venture Perspective

Dr. Pellini has spent more than 20 years working on the operating side of four companies, each of which has pushed the boundaries of the standard of care. He will describe his most recent experience at Foundation Medicine, at the forefront of precision medicine, and how that experience can be leveraged on the venture side, where he now evaluates new healthcare technologies.

Speaker:
Michael Pellini, M.D., Managing Partner, Section 32 and Chairman, Foundation Medicine @MichaelPellini

Roche just bought Foundation Medicine for $2.5 billion.  They negotiated over 7 months but aside from critics they felt it was a great deal because it gives them, as a diagnostic venture, the international reach and biotech expertise.  Foundation Medicine offered Roche expertise on the diagnostic space including ability to navigate payers and regulatory aspects of the diagnostic business.  He feels it benefits all aspects of patient care and the work they do with other companies.

Moderatore: Roche is doing multiple deals to ‘own’ a disease state.

Dr. Pellini:  Roche is closing a deal with Flatiron just like how Merck closed deals with genomics companies.  He feels best to build the best company on a stand alone basis and provide for patients, then good things will happen.  However the problem of achieving scale for Precision Medicine is reimbursement by payers.  They still have to keep collecting data and evolving services to suit pharma.  They didn’t know if there model would work but when he met with FDA in 2011 they worked with Precision Medicine, said collect the data and we will keep working with you,

However the payers aren’t contributing to the effort.  They need to assist some of the young companies that can’t raise the billion dollars needed for all the evidence that payers require.  Precision Medicine still have problems, even though they have collected tremendous amounts of data and raised significant money.  From the private payer perspective there is no clear roadmap for success.

They recognized that the payers would be difficult but they had a plan but won’t invest in companies that don’t have a plan for getting reimbursement from payers.

Moderator: What is section 32?

Pellini:  Their investment arm invests in the spectrum of precision healtcare companies including tech companies.  They started with a digital path imaging system that went from looking through a scope and now looking at a monitor with software integrated with medical records. Section 32 has $130 million under management and may go to $400 Million but they want to stay small.

Pellini: we get 4-5 AI pitches a week.

Moderator: Are you interested in companion diagnostics?

Pellini:  There may be 24 expected 2018 drug approvals and 35% of them have a companion diagnostic (CDX) with them.  however going out ten years 70% may have a CDX associated with them.  Payers need to work with companies to figure out how to pay with these CDXs.

 

 

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Turing Institute Engaging the Science of Big Data

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Alan Turing Institute Will Lead Research in Data Science

12/08/2015 –   Duncan Roweth, Cray

Cray is partnering with the Alan Turing Institute, the new U.K. data science research organization in London, to help the U.K. as it increases research in data science to benefit research and industry.

Earlier this month Fiona Burgess, U.K. senior account manager, and I attended the launch of the institute. At the event, U.K. Minister for Science and Universities Jo Johnson paid tribute to Turing and his work. Institute director Professor Andrew Blake told the audience that the Turing Institute is about much more than just big data — it is about data science, analyzing that data and gaining a new understanding that leads to decisions and actions.

Alan Turing was a pioneering British computer scientist. He has become a household name in the U.K. following publicity surrounding his role in breaking the Enigma machine ciphers during the Second World War. This was a closely guarded secret until a few years ago, but has recently become the subject of numerous books and several films. Turing was highly influential in the development of computer science, providing a formalization of the concepts of algorithm and computation with the Turing machine. After the war, he worked at the National Physical Laboratory, where he designed ACE, one of the first stored-program computers.

The Alan Turing Institute is a joint venture between the universities of Cambridge, Edinburgh, Oxford, Warwick, University College London, and the U.K. Engineering and Physical Science Research Council (EPSRC). The Institute received initial funding in excess of £75 million ($110 million) from the U.K. government, the university partners and other business organizations, including the Lloyd’s Register Foundation.

The Turing Institute will, among other topics, research how knowledge and predictions can be extracted from large-scale and diverse digital data. It will bring together people, organizations and technologies in data science for the development of theory, methodologies and algorithms. The U.K. government is looking to this new Institute to enable the science community, commerce and industry to realize the value of big data for the U.K. economy.

Cray will be working with the Turing Institute and EPSRC to provide data analytics capability to the U.K.’s data sciences community.  EPSRC’s ARCHER supercomputer, a Cray XC30 system based at the University of Edinburgh, has been chosen for this work. Much as we worked with NERSC to port Docker to Cray systems, we will be working with ATI to port analytics software to ARCHER and then XC systems generally.

ARCHER is currently the largest supercomputer for scientific research in the U.K. — with its recent upgrade ARCHER’s 118,080 cores can access in excess of 300 TB of memory. What sort of problem might need that amount of processing power?  Genomics England is collecting around 200 GB of DNA sequence data from each of 100,000 people. Finding patterns in all this information will be a mammoth task!

ATI have put together a wide ranging programme of workshops and data science summits, details of which can be found on their Web site.

Duncan Roweth is a principal engineer in the Cray CTO Office in Bristol, U.K.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Best Big Data?

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

What’s The Big Data?

Google’s RankBrain Outranks the Best Brains in the Industry

Bloomberg recently broke the news that Google is “turning its lucrative Web search over to AI machines.” Google revealed to the reporter that for the past few months, a very large fraction of the millions of search queries Google responds to every second have been “interpreted by an artificial intelligence system, nicknamed RankBrain.”

The company that has tried hard to automate its mission to organize the world’s information was happy to report that its machines have again triumphed over humans. When Google search engineers “were asked to eyeball some pages and guess which they thought Google’s search engine technology would rank on top,” RankBrain had an 80% success rate compared to “the humans [who] guessed correctly 70 percent of the time.”

There you have it. Google’s AI machine RankBrain, after only a few months on the job, already outranks the best brains in the industry, the elite engineers that Google typically hires.

Or maybe not. Is RankBrain really “smarter than your average engineer” and already “living up to its AI hype,” as the Bloomberg article informs us, or is this all just, well, hype?

Desperate to find out how far our future machine overlords are already ahead of the best and the brightest (certainly not “average”), I asked Google to shed more light on the test, e.g., how do they determine the “success rate”?

“That test was fairly informal, but it was some of our top search engineers looking at search queries and potential search results and guessing which would be favored by users. (We don’t have more detail to share on how that’s determined; our evaluations are a pretty complex process).”

I guess both RankBrain and Google search engineers were given possible search results to a given query and RankBrain outperformed humans in guessing which are the “better” results, according to some undisclosed criteria.

I don’t know about you, but my TinyBrain is still confused. Wouldn’t Google search engine, with or without RankBrain, outperform any human being, including the smartest people on earth, in terms of “guessing” which search results “would be favored by users”? Haven’t they been mining the entire corpus of human knowledge for more than fifteen years and, by definition, have produced a search engine that “understands” relevance more than any individual human being?

The key to the competition, I guess, is that the “search queries” used in it were not just any search queries but complex queries containing words that have different meaning in different context. It’s the kind of queries that will stump most human beings and it’s quite surprising that Google engineers scored 70% on search queries that presumably require deep domain knowledge in all human endeavors, in addition to search expertise.

The only example of a complex query given in the Bloomberg article is “What’s the title of the consumer at the highest level of a food chain?” The word “consumer” in this context is a scientific term for something that consumes food and the label (the “title”) at highest level of the food chain is “predator.”

This explanation comes from search guru Danny Sullivan who has come to the rescue of perplexed humans like me, providing a detailed RankBrain FAQ, up to the limits imposed by Google’s legitimate reluctance to fully share its secrets. Sullivan: “From emailing with Google, I gather RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for.”

Sullivan points out that a lot of work done by humans is behind Google’s outstanding search results (e.g., creating a synonym list or a database with connections between “entities”—places, people, ideas, objects, etc.). But Google needs now to respond to some 450 million new queries per day, queries that have never been entered before into its search engine.

RankBrain “can see patterns between seemingly unconnected complex searches to understand how they’re actually similar to each other,” writes Sullivan. In addition, “RankBrain might be able to better summarize what a page is about than Google’s existing systems have done.”

Finding out the “unknown unknowns,” discovering previously unknown (to humans) links between words and concepts is the marriage of search technology with the hottest trend in big data analysis—deep learning. The real news about RankBrain is that it is the first time Google applied deep learning, the latest incarnation of “neural networks” and a specific type of machine learning, to its most prized asset—its search engine.

Google has been doing machine learning since its inception. The first published paper listed in the AI and  machine learning section of its research page is from 2001, and, to use just one example, Gmail is so good at detecting spam because of machine learning). But Goggle hasn’t applied machine learning to search. That there has been internal opposition to doing so we learn from a summary of a 2008 conversation between Anand Rajaraman and Peter Norvig, co-author of the most popular AI textbook and leader of Google search R&D since 2001. Here’s the most relevant excerpt:

The big surprise is that Google still uses the manually-crafted formula for its search results. They haven’t cut over to the machine learned model yet. Peter suggests two reasons for this. The first is hubris: the human experts who created the algorithm believe they can do better than a machine-learned model. The second reason is more interesting. Google’s search team worries that machine-learned models may be susceptible to catastrophic errors on searches that look very different from the training data. They believe the manually crafted model is less susceptible to such catastrophic errors on unforeseen query types.

This was written three years after Microsoft has applied machine learning to its search technology. But now, Google got over its hubris. 450 million unforeseen query types per day are probably too much for “manually crafted models” and google has decided that a “deep learning” system such as RankBrain provides good enough protection against “catastrophic errors.”

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Better bioinformatics

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Big data in biomedicine: 4 big questions

Eric Bender  Nature Nov 2015; S19, 527.     http://dx.doi.org:/10.1038/527S19a

http://www.nature.com/nature/journal/v527/n7576_supp/full/527S19a.html

Gathering and understanding the deluge of biomedical research and health data poses huge challenges. But this work is rapidly changing the face of medicine.

 

http://www.nature.com/nature/journal/v527/n7576_supp/images/527S19a-g1.jpg

 

1. How can long-term access to biomedical data that are vital for research be improved?

Why it matters
Data storage may be getting cheaper, particularly in cloud computing, but the total costs of maintaining biomedical data are too high and climbing rapidly. Current models for handling these tasks are only stopgaps.

Next steps
Researchers, funders and others need to analyse data usage and look at alternative models, such as ‘data commons’, for providing access to curated data in the long term. Funders also need to incorporate resources for doing this.

Quote
“Our mission is to use data science to foster an open digital ecosystem that will accelerate efficient, cost-effective biomedical research to enhance health, lengthen life and reduce illness and disability.” Philip Bourne, US National Institutes of Health.

 

2. How can the barriers to using clinical trial results and patients’ health records for research be lowered?

Why it matters
‘De-identified’ data from clinical trials and patients’ medical records offer opportunities for research, but the legal and technical obstacles are immense. Clinical study data are rarely shared, and medical records are walled off by privacy and security regulations and by legal concerns.

Next steps
Patient advocates are lobbying for access to their own health data, including genomic information. The European Medicines Agency is publishing clinical reports submitted as part of drug applications. And initiatives such as CancerLinQ are gathering de-identified patient data.

Quote
“There’s a lot of genetic information that no one understands yet, so is it okay or safe or right to put that in the hands of a patient? The flip side is: it’s my information — if I want it, I should get it.”Megan O’Boyle, Phelan-McDermid Syndrome Foundation.

 

3. How can knowledge from big data be brought into point-of-care health-care delivery?

Why it matters
Delivering precision medicine will immensely broaden the scope of electronic health records. This massive shift in health care will be complicated by the introduction of new therapies, requiring ongoing education for clinicians who need detailed information to make clinical decisions.

Next steps
Health systems are trying to bring up-to-date treatments to clinics and build ‘health-care learning systems’ that integrate with electronic health records. For instance, the CancerLinQ project provides recommendations for patients with cancer whose treatment is hard to optimize.

Quote
“Developing a standard interface for innovators to access the information in electronic health records will connect the point of care to big data and the full power of the web, spawning an ‘app store’ for health.” Kenneth Mandl, Harvard Medical School.

 

4. Can academia create better career tracks for bioinformaticians?

Why it matters
The lack of attractive career paths in bioinformatics has led to a shortage of scientists that have both strong statistical skills and biological understanding. The loss of data scientists to other fields is slowing the pace of medical advances.

Next steps
Research institutions will take steps, including setting up formal career tracks, to reward bioinformaticians who take on multidisciplinary collaborations. Funders will find ways to better evaluate contributions from bioinformaticians.

Quote
“Perhaps the most promising product of big data, that labs will be able to explore countless and unimagined hypotheses, will be stymied if we lack the bioinformaticians that can make this happen.” Jeffrey Chang, University of Texas.

 

Eric Bender is a freelance science writer based in Newton, Massachusetts.

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  • Oracle Industry Connect Presents Their 2015 Life Sciences and Healthcare Program

 

Reporter: Stephen J. Williams, Ph.D. and Aviva Lev-Ari, Ph.D., R.N.

oraclehealthcare

Copyright photo Oracle Inc. (TM)

 

Transforming Clinical Research and Clinical Care with Data-Driven Intelligence

March 25-26 Washington, DC

For more information click on the following LINK:

https://www.oracle.com/oracleindustryconnect/life-sciences-healthcare.html

oracle-healthcare-solutions-br-1526409

https://www.oracle.com/industries/health-sciences/index.html  

Oracle Health Sciences: Life Sciences & HealthCare — the Solutions for Big Data

Healthcare and life sciences organizations are facing unprecedented challenges to improve drug development and efficacy while driving toward more targeted and personalized drugs, devices, therapies, and care. Organizations are facing an urgent need to meet the unique demands of patients, regulators, and payers, necessitating a move toward a more patient-centric, value-driven, and personalized healthcare ecosystem.

Meeting these challenges requires redesigning clinical R&D processes, drug therapies, and care delivery through innovative software solutions, IT systems, data analysis, and bench-to-bedside knowledge. The core mission is to improve the health, well-being, and lives of people globally by:

  • Optimizing clinical research and development, speeding time to market, reducing costs, and mitigating risk
  • Accelerating efficiency by using business analytics, costing, and performance management technologies

 

  • Establishing a global infrastructure for collaborative clinical discovery and care delivery models
  • Scaling innovations with world-class, transformative technology solutions
  • Harnessing the power of big data to improve patient experience and outcomes

The Oracle Industry Connect health sciences program features 15 sessions showcasing innovation and transformation of clinical R&D, value-based healthcare, and personalized medicine.

The health sciences program is an invitation-only event for senior-level life sciences and healthcare business and IT executives.

Complete your registration and book your hotel reservation prior to February 27, 2015 in order to secure the Oracle discounted hotel rate.

Learn more about Oracle Healthcare.

General Welcome and Joint Program Agenda

Wednesday, March 25

10:30 a.m.–12:00 p.m.

Oracle Industry Connect Opening Keynote

Mark Hurd, Chief Executive Officer, Oracle

Bob Weiler, Executive Vice President, Global Business Units, Oracle

Warren Berger, Author of “A More Beautiful Question: The Power of Inquiry to Spark Breakthrough Ideas.”

12:00 p.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:45 p.m.

Oracle Industry Connect Keynote

Bob Weiler, Executive Vice President, Global Business Units, Oracle

2:45 p.m.–3:45 p.m.

Networking Break

3:45 p.m.–5:45 p.m.

Life Sciences and Healthcare General Session

Robert Robbins, President, Chief Executive Officer, Texas Medical Center

Steve Rosenberg, Senior Vice President and General Manager Health Sciences Global Business Unit, Oracle

7:00 p.m.–10:00 p.m.

Life Sciences and Healthcare Networking Reception

National Museum of American History
14th Street and Constitution Avenue, NW
Washington DC 20001

Life Sciences Agenda

Thursday, March 26

7:00 a.m.–8:00 a.m.

Networking Breakfast

8:00 a.m.–9:15 a.m.

Digital Trials and Research Models of the Future 

Markus Christen, Senior Vice President and Head of Global Development, Proteus

Praveen Raja, Senior Director of Medical Affairs, Proteus Digital Health

Michael Stapleton, Vice President and Chief Information Officer, R&D IT, Merck

9:15 a.m.–10:30 a.m.

Driving Patient Engagement and the Internet of Things 

Howard Golub, Vice President of Clinical Research, Walgreens

Jean-Remy Behaeghel, Senior Director, Client Account Management, Product Development Solutions, Vertex Pharmaceuticals

10:30 a.m.–10:45 a.m.

Break

10:45 a.m.–12:00 p.m.

Leveraging Data and Advanced Analytics to Enable True Pharmacovigilance and Risk Management 

Leonard Reyno, Senior Vice President, Chief Medical Officer, Agensys

 

Accelerating Therapeutic Development Through New Technologies 

Andrew Rut, Chief Executive Officer, Co-Founder and Director, MyMeds&Me

12:45 a.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:30 p.m.

Oracle Industry Connect Keynote

2:30 p.m.–2:45 p.m.

Break

2:45 p.m.–3:15 p.m.

Harnessing Big Data to Increase R&D Innovation, Efficiency, and Collaboration 

Sandy Tremps, Executive Director, Global Clinical Development IT, Merck

3:15 p.m.–3:30 p.m.

Break

3:30 p.m.–4:45 p.m.

Transforming Clinical Research from Planning to Postmarketing 

Kenneth Getz, Director of Sponsored Research Programs and Research Associate Professor, Tufts University

Jason Raines, Head, Global Data Operations, Alcon Laboratories

4:45 p.m.–6:00 p.m.

Increasing Efficiency and Pipeline Performance Through Sponsor/CRO Data Transparency and Cloud Collaboration 

Thomas Grundstrom, Vice President, ICONIK, Cross Functional IT Strategies and Innovation, ICON

Margaret Keegan, Senior Vice President, Global Head Data Sciences and Strategy, Quintiles

6:00 p.m.–9:00 p.m.

Oracle Customer Networking Event

Healthcare Agenda

Thursday, March 26

7:00 a.m.–8:15 a.m.

Networking Breakfast

8:30 a.m.–9:15 a.m.

Population Health: A Core Competency for Providers in a Post Fee-for-Service Model 

Margaret Anderson, Executive Director, FasterCures

Balaji Apparsamy, Director, Business Intellegence, Baycare

Leslie Kelly Hall, Senior Vice President, Policy, Healthwise

Peter Pronovost, Senior Vice President, Patient Safety & Quality, Johns Hopkins

Sanjay Udoshi, Healthcare Product Strategy, Oracle

9:15 a.m.–9:30 a.m.

Break

9:30 a.m.–10:15 a.m.

Population Health: A Core Competency for Providers in a Post Fee-for-Service Model (Continued)

10:15 a.m.–10:45 a.m.

Networking Break

10:45 a.m.–11:30 a.m.

Managing Cost of Care in the Era of Healthcare Reform 

Chris Bruerton, Director, Budgeting, Intermountain Healthcare

Tony Byram, Vice President Business Integration, Ascension

Kerri-Lynn Morris, Executive Director, Finance Operations and Strategic Projects, Kaiser Permanente

Kavita Patel, Managing Director, Clinical Transformation, Brookings Institute

Christine Santos, Chief of Strategic Business Analytics, Providence Health & Services

Prashanth Kini, Senior Director, Healthcare Product Strategy, Oracle

11:30 a.m.–11:45 a.m.

Break

11:45 a.m.–12:45 p.m.

Managing Cost of Care in the Era of Healthcare Reform (Continued)

12:45 p.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:30 p.m.

Oracle Industry Connect Keynote

2:30 p.m.–2:45 p.m.

Break

2:45 p.m.–3:30 p.m.

Precision Medicine 

Annerose Berndt, Vice President, Analytics and Information, UPMC

James Buntrock, Vice Chair, Information Management and Analytics, Mayo Clinic

Dan Ford, Vice Dean for Clinical Investigation, Johns Hopkins Medicine

Jan Hazelzet, Chief Medical Information Officer, Erasmus MC

Stan Huff, Chief Medical Information Officer, Intermountain Healthcare

Vineesh Khanna, Director, Biomedical Informatics, SIDRA

Brian Wells, Vice President, Health Technology, Penn Medicine

Wanmei Ou, Senior Product Strategist, Healthcare, Oracle

3:30 p.m.–3:45 p.m.

Networking Break

3:45 p.m.–4:30 p.m.

Precision Medicine (Continued)

4:30 p.m.–4:45 p.m.

Break

6:00 p.m.–9:00 p.m.

Oracle Customer Networking Event

Additional Links to Oracle Pharma, Life Sciences and HealthCare

 
Life Sciences | Industry | Oracle <http://www.oracle.com/us/industries/life-sciences/overview/>

http://www.oracle.com/us/industries/life-sciences/overview/

 
Oracle Corporation

 
Oracle Applications for Life Sciences deliver a powerful combination of technology and preintegrated applications.

  • Clinical

<http://www.oracle.com/us/industries/life-sciences/clinical/overview/index.html>

  • Medical Devices

<http://www.oracle.com/us/industries/life-sciences/medical/overview/index.html>

  • Pharmaceuticals

<http://www.oracle.com/us/industries/life-sciences/pharmaceuticals/overview/index.html>

 
Life Sciences Solutions | Pharmaceuticals and … – Oracle <http://www.oracle.com/us/industries/life-sciences/solutions/index.html>

http://www.oracle.com  Industries  Life Sciences

 
Oracle Corporation

 
Life Sciences Pharmaceuticals and Biotechnology.

 
Oracle Life Sciences Data Hub – Overview | Oracle <http://www.oracle.com/us/products/applications/health-sciences/e-clinical/data-hub/index.html>

http://www.oracle.com  …  E-Clinical Solutions

 
Oracle Corporation

 
Oracle Life Sciences Data Hub. Better Insights, More Informed Decision-Making. Provides an integrated environment for clinical data, improving regulatory …

 
Pharmaceuticals and Biotechnology | Oracle Life Sciences <http://www.oracle.com/us/industries/life-sciences/pharmaceuticals/overview/index.html>

http://www.oracle.com/us/…/life-sciences/…/index.html

 
Oracle Corporation

 
Oracle Applications for Pharmaceuticals and Biotechnology deliver a powerful combination of technology and preintegrated applications.

 
Oracle Health Sciences – Healthcare and Life Sciences … <https://www.oracle.com/industries/health-sciences/>

https://www.oracle.com/industries/health-sciences/

 
Oracle Corporation

 
Oracle Health Sciences leverages industry-shaping technologies that optimize clinical R&D, mitigate risk, advance healthcare, and improve patient outcomes.

 
Clinical | Oracle Life Sciences | Oracle <http://www.oracle.com/us/industries/life-sciences/clinical/overview/index.html>

http://www.oracle.com  Industries  Life Sciences  Clinical

 
Oracle Corporation

 
Oracle for Clinical Applications provides an integrated remote data collection facility for site-based entry.

 
Oracle Life Sciences | Knowledge Zone | Oracle … <http://www.oracle.com/partners/en/products/industries/life-sciences/get-started/index.html>

http://www.oracle.com/partners/…/life-sciences/…/index.ht&#8230;

 
Oracle Corporation

 
This Knowledge Zone was specifically developed for partners interested in reselling or specializing in Oracle Life Sciences solutions. To become a specialized …

 
[PDF]Brochure: Oracle Health Sciences Suite of Life Sciences … <http://www.oracle.com/us/industries/life-sciences/oracle-life-sciences-solutions-br-414127.pdf>

http://www.oracle.com/…/life-sciences/oracle-life-sciences-s&#8230;

 
Oracle Corporation

 
Oracle Health Sciences Suite of. Life Sciences Solutions. Integrated Solutions for Global Clinical Trials. Oracle Health Sciences provides the world’s broadest set …

 

 

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