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Archive for the ‘Intellectual Property, Innovations, Commercialization, Investment in technological breakthrough’ Category


MIT Technology Review announced list of “Innovators Under 35, 2020”

Reporter: Aviva Lev-Ari, PhD, RN

 

Innovators Under 35, 2020

In chaotic times it can be reassuring to see so many people working toward a better world. That’s true for medical professionals fighting a pandemic and for ordinary citizens fighting for social justice. And it’s true for those among us striving to employ technology to address those problems and many others.

The 35 young innovators in these pages aren’t all working to fight a pandemic, though some are: see Omar Abudayyeh and Andreas Puschnik. And they’re not all looking to remedy social injustices though some are: see Inioluwa Deborah Raji and Mohamed Dhaouafi. But even those who aren’t tackling those specific problems are seeking ways to use technology to help people. They’re trying to solve our climate crisis, find a cure for Parkinson’s, or make drinking water available to those who are desperate for it.

We’ve been presenting our list of innovators under 35 for the past 20 years. We do it to highlight the things young innovators are working on, to show at least some of the possible directions that technology will take in the coming decade. This contest generates more than 500 nominations each year. The editors then face the task of picking 100 semifinalists to put in front of our 25 judges, who have expertise in artificial intelligence, biotechnology, software, energy, materials, and so on. With the invaluable help of these rankings, the editors pick the final list of 35.

Inventors

Their innovations point toward a future with new types of batteries, solar panels, and microchips.
  • Omar Abudayyeh

    He’s working to use CRISPR as a covid-19 test that you could take at home.

    Omar Abudayyeh
  • Christina Boville

    She modifies enzymes to enable production of new compounds for industry.

    Christina Boville
  • Manuel Le Gallo

    He uses novel computer designs to make AI less power hungry.

    Manuel Le Gallo
  • Nadya Peek

    She builds novel modular machines that can do just about anything you can imagine.

    Nadia Peek
  • Leila Pirhaji

    She developed an AI-based system that can identify more small molecules in a patient’s body, faster than ever before.

    Leila Pirhaji
  • Randall Jeffrey Platt

    His recording tool provides a video of genes turning on or off.

    Randall Jeffrey Platt
  • Rebecca Saive

    She found a way to make solar panels cheaper and more efficient.

    Rebecca Saive
  • Venkat Viswanathan

    His work on a new type of battery could make EVs much cheaper.

    Venkat Viswanathan
  • Anastasia Volkova

    Her platform uses remote sensing and other techniques to monitor crop health—helping farmers focus their efforts where they’re most needed.

    Anastasia Volkova
  • Sihong Wang

    His stretchable microchips promise to make all sorts of new devices possible.

    Sihong Wang

Entrepreneurs

Their technological innovations bust up the status quo and lead to new ways of doing business.
  • Jiwei Li

    In the last few months, Google and Facebook have both released new chatbots. Jiwei Li’s techniques are at the heart of both.

    Jiwei Li
  • Atima Lui

    She’s using technology to correct the cosmetics industry’s bias toward light skin.

    Atima Lui
  • Tony Pan

    His company revamps an old device to allow you to generate electricity in your own home.

    Tony Pan

Visionaries

Their innovations are leading to breakthroughs in AI, quantum computing, and medical implants.
  • Leilani Battle

    Her program sifts through data faster so scientists can focus more on science.

    Leilani Battle
  • Morgan Beller

    She was a key player behind the idea of a Facebook cryptocurrency.

  • Eimear Dolan

    Medical implants are often thwarted as the body grows tissue to defend itself. She may have found a drug-free fix for the problem.

    Eimear Dolan
  • Rose Faghih

    Her sensor-laden wristwatch would monitor your brain states.

    Rose Fagih
  • Bo Li

    By devising new ways to fool AI, she is making it safer.

    Bo Li
  • Zlatko Minev

    His discovery could reduce errors in quantum computing.

    Zlatko Minev
  • Miguel Modestino

    He is reducing the chemical industry’s carbon footprint by using AI to optimize reactions with electricity instead of heat.

    Miguel Modestino
  • Inioluwa Deborah Raji

    Her research on racial bias in data used to train facial recognition systems is forcing companies to change their ways.

    Inioluwa Deborah Raji
  • Adriana Schulz

    Her tools let anyone design products without having to understand materials science or engineering.

    Adriana Schulz
  • Dongjin Seo

    He is designing computer chips to seamlessly connect human brains and machines.

Humanitarians

They’re using technology to cure diseases and make water, housing, and prosthetics available to all.
  • Mohamed Dhaouafi

    His company’s artificial limbs are not only high-functioning but cheap enough for people in low-income countries.

    Mohamed Dhaouafi
  • Alex Le Roux

    A massive 3D-printing project in Mexico could point the way to the future of affordable housing.

    Alex Le Roux
  • Katharina Volz

    A loved one’s diagnosis led her to employ machine learning in the search for a Parkinson’s cure.

    Katharina Volz
  • David Warsinger

    His system could alleviate the drawbacks of existing desalination plants.

    David Warsinger

Pioneers

Their innovations lead the way to biodegradable plastics, textiles that keep you cool, and cars that “see.”
  • Ghena Alhanaee

    Heavy dependence on infrastructure like oil rigs, nuclear reactors, and desalination plants can be catastrophic in a crisis. Her data-driven framework could help nations prepare.

    Ghena Alhanaee
  • Avinash Manjula Basavanna

    His biodegradable plastic protects against extreme chemicals, but heals itself using water.

  • Lili Cai

    She created energy-efficient textiles to break our air-conditioning habit.

    Lili Cai
  • Gregory Ekchian

    He invented a way to make radiation therapy for cancer safer and more effective.

    Gregory Ekchian
  • Jennifer Glick

    If quantum computers work, what can we use them for? She’s working to figure that out.

  • Andrej Karpathy

    He’s employing neural networks to allow automated cars to “see.”

    Karpathy
  • Siddharth Krishnan

    A tiny, powerful sensor for making disease diagnosis cheaper, faster, and easier.

    Siddharth Krishnan
  • Andreas Puschnik

    Seeking a universal treatment for viral diseases, he might leave us much better prepared for the next pandemic.

    Andreas Puschnik

SOURCE

https://www.technologyreview.com/innovators-under-35/2020/?truid=edf020ada5f25f6d6c4b0b32ac4a1ee9&utm_source=weekend_reads&utm_medium=email&utm_campaign=weekend_reads.unpaid.engagement&utm_term=non-subs&utm_content=06-20-2020

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Predicting the Protein Structure of Coronavirus: Inhibition of Nsp15 can slow viral replication and Cryo-EM – Spike protein structure (experimentally verified) vs AI-predicted protein structures (not experimentally verified) of DeepMind (Parent: Google) aka AlphaFold

 

Curators: Stephen J. Williams, PhD and Aviva Lev-Ari, PhD, RN

This illustration, created at the Centers for Disease Control and Prevention (CDC), reveals ultrastructural morphology exhibited by coronaviruses. Note the spikes that adorn the outer surface of the virus, which impart the look of a corona surrounding the virion, when viewed electron microscopically. A novel coronavirus virus was identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China in 2019.

Image and Caption Credit: Alissa Eckert, MS; Dan Higgins, MAM available at https://phil.cdc.gov/Details.aspx?pid=23311

 

UPDATED on 3/11/2020

Coronaviruses

According to the World Health Organization, coronaviruses make up a large family of viruses named for the crown-like spikes found on their surface (Figure 1). They carry their genetic material in single strands of RNA and cause respiratory problems and fever. Like HIV, coronaviruses can be transmitted between animals and humans.  Coronaviruses have been responsible for the Severe Acute Respiratory Syndrome (SARS) pandemic in the early 2000s and the Middle East Respiratory Syndrome (MERS) outbreak in South Korea in 2015. While the most recent coronavirus, COVID-19, has caused international concern, accessible and inexpensive sequencing is helping us understand COVID-19 and respond to the outbreak quickly.

Figure 1. Coronaviruses with the characteristic spikes as seen under a microscope.

First studies that explore genetic susceptibility to COVID-19 are now being published. The first results indicate that COVID-19 infects cells using the ACE2 cell-surface receptor. Genetic variants in the ACE2 receptor gene are thus likely to influence how effectively COVID-19 can enter the cells in our bodies. Researchers hope to discover genetic variants that confer resistance to a COVID-19 infection, similar to how some variants in the CCR5 receptor gene make people immune to HIV. At Nebula Genomics, we are monitoring the latest COVID-19 research and will add any relevant discoveries to the Nebula Research Library in a timely manner.

The Role of Genomics in Responding to COVID-19

Scientists in China sequenced COVID-19’s genome just a few weeks after the first case was reported in Wuhan. This stands in contrast to SARS, which was discovered in late 2002 but was not sequenced until April of 2003. It is through inexpensive genome-sequencing that many scientists across the globe are learning and sharing information about COVID-19, allowing us to track the evolution of COVID-19 in real-time. Ultimately, sequencing can help remove the fear of the unknown and allow scientists and health professionals to prepare to combat the spread of COVID-19.

Next-generation DNA sequencing technology has enabled us to understand COVID-19 is ~30,000 bases long. Moreover, researchers in China determined that COVID-19 is also almost identical to a coronavirus found in bats and is very similar to SARS. These insights have been critical in aiding in the development of diagnostics and vaccines. For example, the Centers for Disease Control and Prevention developed a diagnostic test to detect COVID-19 RNA from nose or mouth swabs.

Moreover, a number of different government agencies and pharmaceutical companies are in the process of developing COVID-19 vaccines to stop the COVID-19 from infecting more people. To protect humans from infection inactivated virus particles or parts of the virus (e.g. viral proteins) can be injected into humans. The immune system will recognize the inactivated virus as foreign, priming the body to build immunity against possible future infection. Of note, Moderna Inc., the National Institute of Allergy and Infectious Diseases, and Coalition for Epidemic Preparedness Innovations identified a COVID-19 vaccine candidate in a record 42 days. This vaccine will be tested in human clinical trials starting in April.

For more information about COVID-19, please refer to the World Health Organization website.

SOURCE

https://blog.nebula.org/role-of-genomics-coronavirus-covid-19/?utm_source=Nebula%20Genomics&utm_medium=email&utm_campaign=COVID-19

Aviva Lev-Ari
13.3K Tweets

Aviva Lev-Ari
@AVIVA1950

My BIO lnkd.in/eEyn69r MediaPharma ex-SRI ex-MITRE ex-McGraw-Hill Followed by

Aviva Lev-Ari
@AVIVA1950

Predicting the #ProteinStructure of #Coronavirus: #Inhibition of #Nsp15 #Cryo-EM – #spike #protein structure (#experimentally verified) vs #AI-predicted protein structures (not verified) of

(

) #AlphaFold

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Eric Topol
@EricTopol
·
The problem w/ visionaries is that we don’t recognize them in a timely manner (too late) Ralph Baric @UNCpublichealth and Vineet Menachery deserve recognition for being 5 yrs ahead of #COVID19 nature.com/articles/nm.39 @NatureMedicine pnas.org/content/113/11 @PNASNews via @hoondy

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Senior, A.W., Evans, R., Jumper, J. et al. Improved protein structure prediction using potentials from deep learningNature 577, 706–710 (2020)https://doi.org/10.1038/s41586-019-1923-7

Abstract

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)—a blind assessment of the state of the field—AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined7. https://doi.org/10.1038/s41586-019-1923-7

[ALA added bold face]

COVID-19 outbreak

The scientific community has galvanised in response to the recent COVID-19 outbreak, building on decades of basic research characterising this virus family. Labs at the forefront of the outbreak response shared genomes of the virus in open access databases, which enabled researchers to rapidly develop tests for this novel pathogen. Other labs have shared experimentally-determined and computationally-predicted structures of some of the viral proteins, and still others have shared epidemiological data. We hope to contribute to the scientific effort using the latest version of our AlphaFold system by releasing structure predictions of several under-studied proteins associated with SARS-CoV-2, the virus that causes COVID-19. We emphasise that these structure predictions have not been experimentally verified, but hope they may contribute to the scientific community’s interrogation of how the virus functions, and serve as a hypothesis generation platform for future experimental work in developing therapeutics. We’re indebted to the work of many other labs: this work wouldn’t be possible without the efforts of researchers across the globe who have responded to the COVID-19 outbreak with incredible agility.

Knowing a protein’s structure provides an important resource for understanding how it functions, but experiments to determine the structure can take months or longer, and some prove to be intractable. For this reason, researchers have been developing computational methods to predict protein structure from the amino acid sequence.  In cases where the structure of a similar protein has already been experimentally determined, algorithms based on “template modelling” are able to provide accurate predictions of the protein structure. AlphaFold, our recently published deep learning system, focuses on predicting protein structure accurately when no structures of similar proteins are available, called “free modelling”.  We’ve continued to improve these methods since that publication and want to provide the most useful predictions, so we’re sharing predicted structures for some of the proteins in SARS-CoV-2 generated using our newly-developed methods.

It’s important to note that our structure prediction system is still in development and we can’t be certain of the accuracy of the structures we are providing, although we are confident that the system is more accurate than our earlier CASP13 system. We confirmed that our system provided an accurate prediction for the experimentally determined SARS-CoV-2 spike protein structure shared in the Protein Data Bank, and this gave us confidence that our model predictions on other proteins may be useful. We recently shared our results with several colleagues at the Francis Crick Institute in the UK, including structural biologists and virologists, who encouraged us to release our structures to the general scientific community now. Our models include per-residue confidence scores to help indicate which parts of the structure are more likely to be correct. We have only provided predictions for proteins which lack suitable templates or are otherwise difficult for template modeling.  While these understudied proteins are not the main focus of current therapeutic efforts, they may add to researchers’ understanding of SARS-CoV-2.

Normally we’d wait to publish this work until it had been peer-reviewed for an academic journal. However, given the potential seriousness and time-sensitivity of the situation, we’re releasing the predicted structures as we have them now, under an open license so that anyone can make use of them.

Interested researchers can download the structures here, and can read more technical details about these predictions in a document included with the data. The protein structure predictions we’re releasing are for SARS-CoV-2 membrane protein, protein 3a, Nsp2, Nsp4, Nsp6, and Papain-like proteinase (C terminal domain). To emphasise, these are predicted structures which have not been experimentally verified. Work on the system continues for us, and we hope to share more about it in due course.

Citation:  John Jumper, Kathryn Tunyasuvunakool, Pushmeet Kohli, Demis Hassabis, and the AlphaFold Team, “Computational predictions of protein structures associated with COVID-19”, DeepMind website, 5 March 2020, https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19

SARS-COV-2 MEMBRANE PROTEIN: A RENDERING OF ONE OF OUR PROTEIN STRUCTURE PREDICTIONS

SOURCES

Computational predictions of protein structures associated with COVID-19

https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19

AlphaFold: Using AI for scientific discovery 

https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery

 

DeepMind has shared its results with researchers at the Francis Crick Institute, a biomedical research lab in the UK, as well as offering it for download from its website.

“Normally we’d wait to publish this work until it had been peer-reviewed for an academic journal. However, given the potential seriousness and time-sensitivity of the situation, we’re releasing the predicted structures as we have them now, under an open license so that anyone can make use of them,” it said. [ALA added bold face]

There are 93,090 cases of COVID-19, and 3,198 deaths, spread across 76 countries, according to the latest report from the World Health Organization at time of writing. ®

SOURCE

https://www.theregister.co.uk/2020/03/06/deepmind_covid19_outbreak/

 

  • MHC content – The spike protein is thought to be the key to binding to cells via the angiotensin II receptor, the major mechanism the immune system uses to distinguish self from non-self

Preliminary Identification of Potential Vaccine Targets for the COVID-19 Coronavirus (SARS-CoV-2) Based on SARS-CoV Immunological Studies

Syed Faraz Ahmed 1,† , Ahmed A. Quadeer 1, *,† and Matthew R. McKay 1,2, *

1 Department of Electronic and Computer Engineering, The Hong Kong University of Science and

Technology, Hong Kong, China; sfahmed@connect.ust.hk

2 Department of Chemical and Biological Engineering, The Hong Kong University of Science and

Technology, Hong Kong, China

* Correspondence: eeaaquadeer@ust.hk.com (A.A.Q.); m.mckay@ust.hk (M.R.M.)

These authors contributed equally to this work.

Received: 9 February 2020; Accepted: 24 February 2020; Published: 25 February 2020

Abstract:

The beginning of 2020 has seen the emergence of COVID-19 outbreak caused by a novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). There is an imminent need to better understand this new virus and to develop ways to control its spread. In this study, we sought to gain insights for vaccine design against SARS-CoV-2 by considering the high genetic similarity between SARS-CoV-2 and SARS-CoV, which caused the outbreak in 2003, and leveraging existing immunological studies of SARS-CoV. By screening the experimentally determined SARS-CoV-derived B cell and T cell epitopes in the immunogenic structural proteins of SARS-CoV, we identified a set of B cell and T cell epitopes derived from the spike (S) and nucleocapsid (N) proteins that map identically to SARS-CoV-2 proteins. As no mutation has been observed in these identified epitopes among the 120 available SARS-CoV-2 sequences (as of 21 February 2020), immune targeting of these epitopes may potentially offer protection against this novel virus. For the T cell epitopes, we performed a population coverage analysis of the associated MHC alleles and proposed a set of epitopes that is estimated to provide broad coverage globally, as well as in China. Our findings provide a screened set of epitopes that can help guide experimental efforts towards the development of vaccines against SARS-CoV-2.

Keywords: Coronavirus; 2019-nCoV; 2019 novel coronavirus; SARS-CoV-2; COVID-19; SARS-CoV; MERS-CoV; T cell epitopes; B cell epitopes; vaccine [ALA added bold face]

SOURCE

https://www.mdpi.com/1999-4915/12/3/254/pdf

 

Selected Online COMMENTS to

https://forums.theregister.co.uk/forum/all/2020/03/06/deepmind_covid19_outbreak/

MuscleguySilver badge

Re: Protein structure prediction has been done for ages…

Not quite, Natural Selection does not measure methods, it measures outputs, usually at the organism level.

Sure correct folding is necessary for much protein function and we have prions and chaperone proteins to get it wrong and right.

The only way NS measures methods and mechanisms is if they are very energetically wasteful. But there are some very wasteful ones out there. Beta-Catenin at the end of point of Wnt signalling comes particularly to mind.

Chemist

Re: Does not matter at all

“Determining the structure of the virus proteins might also help in developing a molecule that disrupts the operation of just those proteins, and not anything else in the human body.”

Well it might, but predicting whether a ‘drug’ will NOT interact with any other of the 20000+ protein in complex organisms is well beyond current science. If we could do that we could predict/avoid toxicity and other non-mechanism related side-effects & mostly we can’t.

rob miller

Title

There are 480 structures on PDBe resulting from a search on ‘coronavirus,’ the top hits from MERS and SARS. PR stunt or not, they did win the most recent CASP ‘competition’, so arguably it’s probably our best shot right now – and I am certainly not satisfied that they have been sufficiently open in explaining their algorithms though I have not checked in the last few months. No one is betting anyone’s health on this, and it is not like making one wrong turn in a series of car directions. Latest prediction algorithms incorporate contact map predictions, so it’s not like a wrong dihedral angle sends the chain off in the wrong direction. A decent model would give something to run docking algorithms against with a series of already approved drugs, then we take that shortlist into the lab. A confirmed hit could be an instantly available treatment, no two year wait as currently estimated. [ALA added bold face]

jelabarre59Silver badge

Re: these structure predictions have not been experimentally verified

Naaaah. Can’t possibly be a stupid marketing stunt.

Well yes, a good possibility. But it can also be trying to build on the open-source model of putting it out there for others to build and improve upon. Essentially opening that “peer review” to a larger audience quicker. [ALA added bold face]

We shall see.

Anonymous Coward

Anonymous CowardWhat bothers me, besides the obvious PR stunt, is that they say this prediction is licensed. How can a prediction from software be protected by, I presume, patents? And if this can be protected without even verifying which predictions actually work, what’s to stop someone spitting out millions of random, untested predictions just in case they can claim ownership later when one of them is proven to work? [ALA added bold face]

 

 

SOURCES

 

  • AI-predicted protein structures could unlock vaccine for Wuhan coronavirus… if correct… after clinical trials It’s not quite DeepMind’s ‘Come with me if you want to live’ moment, but it’s close, maybe

Experimentally derived by a group of scientists at the University of Texas at Austin and the National Institute of Allergy and Infectious Diseases, an agency under the US National Institute of Health. They both feature a “Spike protein structure.”

  • Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation

See all authors and affiliations

Science  19 Feb 2020:
eabb2507
DOI: 10.1126/science.abb2507

 

  • Israeli scientists: We have developed a coronavirus vaccine

https://www.fromthegrapevine.com/health/coronavirus-vaccine-israel-migal-research-institute-david-zigdon

Other related articles published in this Open Access Online Scientific Journal include the following:

 

  • Group of Researchers @ University of California, Riverside, the University of Chicago, the U.S. Department of Energy’s Argonne National Laboratory, and Northwestern University solve COVID-19 Structure and Map Potential Therapeutics

Reporters: Stephen J Williams, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/03/06/group-of-researchers-solve-covid-19-structure-and-map-potential-therapeutic/

 

  • Is It Time for the Virtual Scientific Conference?: Coronavirus, Travel Restrictions, Conferences Cancelled Curator:

Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2020/03/06/is-it-time-for-the-virtual-scientific-conference-coronavirus-travel-restrictions-conferences-cancelled/

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Old Industrial Revolution Paradigm of Education Needs to End: How Scientific Curation Can Transform Education

Curator: Stephen J. Williams, PhD.

Dr. Cathy N. Davidson from Duke University gives a talk entitled: Now You See It.  Why the Future of Learning Demands a Paradigm Shift

In this talk, shown below, Dr. Davidson shows how our current education system has been designed for educating students for the industrial age type careers and skills needed for success in the Industrial Age and how this educational paradigm is failing to prepare students for the challenges they will face in their future careers.

Or as Dr. Davidson summarizes

Designing education not for your past but for their future

As the video is almost an hour I will summarize some of the main points below

PLEASE WATCH VIDEO

Summary of talk

Dr. Davidson starts the talk with a thesis: that Institutions tend to preserve the problems they were created to solve.

All the current work, teaching paradigms that we use today were created for the last information age (19th century)

Our job to to remake the institutions of education work for the future not the one we inherited

Four information ages or technologies that radically changed communication

  1. advent of writing: B.C. in ancient Mesopotamia allowed us to record and transfer knowledge and ideas
  2. movable type – first seen in 10th century China
  3. steam powered press – allowed books to be mass produced and available to the middle class.  First time middle class was able to have unlimited access to literature
  4. internet- ability to publish and share ideas worldwide

Interestingly, in the early phases of each of these information ages, the same four complaints about the new technology/methodology of disseminating information was heard

  • ruins memory
  • creates a distraction
  • ruins interpersonal dialogue and authority
  • reduces complexity of thought

She gives an example of Socrates who hated writing and frequently stated that writing ruins memory, creates a distraction, and worst commits ideas to what one writes down which could not be changed or altered and so destroys ‘free thinking’.

She discusses how our educational institutions are designed for the industrial age.

The need for collaborative (group) learning AND teaching

Designing education not for your past but for the future

In other words preparing students for THEIR future not your past and the future careers that do not exist today.

In the West we were all taught to answer silently and alone.  However in Japan, education is arranged in the han or group think utilizing the best talents of each member in the group.  In Japan you are arranged in such groups at an early age.  The concept is that each member of the group contributes their unique talent and skill for the betterment of the whole group.  The goal is to demonstrate that the group worked well together.

see https://educationinjapan.wordpress.com/education-system-in-japan-general/the-han-at-work-community-spirit-begins-in-elementary-school/ for a description of “in the han”

In the 19th century in institutions had to solve a problem: how to get people out of the farm and into the factory and/or out of the shop and into the firm

Takes a lot of regulation and institutionalization to convince people that independent thought is not the best way in the corporation

keywords for an industrial age

  • timeliness
  • attention to task
  • standards, standardization
  • hierarchy
  • specialization, expertise
  • metrics (measures, management)
  • two cultures: separating curriculum into STEM versus artistic tracts or dividing the world of science and world of art

This effort led to a concept used in scientific labor management derived from this old paradigm in education, an educational system controlled and success measured using

  • grades (A,B,C,D)
  • multiple choice tests

keywords for our age

  • workflow
  • multitasking attention
  • interactive process (Prototype, Feedback)
  • data mining
  • collaboration by difference

Can using a methodology such as scientific curation affect higher education to achieve this goal of teaching students to collaborate in an interactive process using data mining to create a new workflow for any given problem?  Can a methodology of scientific curation be able to affect such changes needed in academic departments to achieve the above goal?

This will be the subject of future curations tested using real-world in class examples.

However, it is important to first discern that scientific content curation takes material from Peer reviewed sources and other expert-vetted sources.  This is unique from other types of content curation in which take from varied sources, some of which are not expert-reviewed, vetted, or possibly ‘fake news’ or highly edited materials such as altered video and audio.  In this respect, the expert acts not only as curator but as referee.  In addition, collaboration is necessary and even compulsory for the methodology of scientific content curation, portending the curator not as the sole expert but revealing the CONTENT from experts as the main focus for learning and edification.

Other article of note on this subject in this Open Access Online Scientific Journal include:

The above articles will give a good background on this NEW Conceived Methodology of Scientific Curation and its Applicability in various areas such as Medical Publishing, and as discussed below Medical Education.

To understand the new paradigm in medical communication and the impact curative networks have or will play in this arena please read the following:

Scientific Curation Fostering Expert Networks and Open Innovation: Lessons from Clive Thompson and others

This article discusses a history of medical communication and how science and medical communication initially moved from discussions from select individuals to the current open accessible and cooperative structure using Web 2.0 as a platform.

 

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The Digital Age Gave Rise to New Definitions – New Benchmarks were born on the World Wide Web for the Intangible Asset of Firm’s Reputation: Pay a Premium for buying e-Reputation

Curator: Aviva Lev–Ari, PhD, RN

 

Direct reputation, feedback reputation and signaling effects are present; and shows that better sellers are always more likely to brand stretch. The comparative statics with respect to the initial reputation level, however, are not obvious. … a higher reputation firm can earn a higher direct reputation effect premium. But a higher reputation firm also has more to lose. The trade-off between using one’s reputation and protecting it can go both ways.

Luıs M B Cabral, New York University and CEPR, 2005

 

 

Part 1:   A Digital Business Defined and the Intangible Asset of Firm’s Reputation

  1.  Claiming Distinction
  2.  Recognition Bestowed
  3.  The Technology
  4.  The Sphere of Influence
  5.  The Industrial Benefactors in Potential
  6.  The Actors at Play – Experts, Authors, Writers – Life Sciences & Medicine as it applies to HEALTH CARE
  7.  1st Level Connection on LinkedIn = +7,100 and Endorsements = +1,500
  8.  The DIGITAL REPUTATION of our Venture – Twitter for the Professional and for Institutions
  9.  Growth in Twitter Followers and in Global Reach: Who are the NEW Followers? they are OUR COMPETITION   and   other Media Establishments – that is the definition of Trend Setter, Opinion Leader and Source for Emulation
  10.  Business Aspects of the Brick & Mortar World render OBSOLETE

Part 2:   Business Perspectives on Reputation

Part 3:   Economics Perspectives on Reputation

 

 

Part 1:   A Digital Business Defined and the Intangible Asset of Firm’s Reputation

This curation attempts to teach-by-example the new reality of the Intangible Asset of Firm’s Reputation when the business is 100% in the cloud, 100% electronic in nature (paperless), the customers are the Global Universe and the organization is 100% Global and 100% virtual.

 

A Case in Point: Intellectual Property Production Process of Health Care Digital Content using electronic Media Channels

 

Optimal Testimonial of e-Product Quality and Reputation for an Open Access Online Scientific Journal pharmaceuticalintelligence.com 

 

 1.   Claiming Distinction

Executive Summary

WHAT ARE LPBI Group’s NEEDS in June 2019: Aviva’s BOLD VISION on June 11, 2019

 

2.   Recognition Bestowed 

Our Books are here

  • On 8/17/2018, Dr. Lev-Ari, PhD, RN was contacted by the President elect of the Massachusetts Academy of Sciences (MAS), Prof. Katya Ravid of Boston University, School of Medicine, to join MAS in the role of Liaison to the Biotechnology and eScientific Publishing industries for the term of August 2018-July 2021. In the MAS, Dr. Lev-Ari serve as Board member, Fellow, and Advisor to the Governing Board.

http://www.maacadsci.org

MAS FELLOWS 

GOVERNING BOARD

ACTIVITIES

BUNDLED BY AMAZON.COM INTO A SIX-VOLUME SERIES FOR $515

https://lnkd.in/e6WkMgF

Sixteen Volumes ARE ON AMAZON.COM, average book length – 2,400 pages

https://lnkd.in/ekWGNqA

3.   The Technology

Curation Methodology – Digital Communication Technology to mitigate Published Information Explosion and Obsolescence in Medicine and Life Sciences

Detailed Technology Description

LPBI’s Pipeline Map: A Positioning Perspectives – An Outlook to the Future from the Present

 

4.   The Sphere of Influence 

LPBI Group’s Social Media Presence

JOURNAL Statistics on 2/24/2019

  • LPBI Platform is been used by GLOBAL Communities of Scientists for interactive dialogue of SCIENCE – Four case studies are presented in the link, below

Electronic Scientific AGORA: Comment Exchanges by Global Scientists on Articles published in the Open Access Journal @pharmaceuticalintelligence.com – Four Case Studies

Curator and Editor-in-Chief: Journal and BioMed e-Series, Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/04/10/electronic-scientific-agora-comment-exchanges-by-global-scientists-on-articles-published-in-the-open-access-journal-pharmaceuticalintelligence-com-four-case-studies/

 

5.   The Industrial Benefactors in Potential

Opportunities Map in the Acquisition Arena

Dynamic Contents for LPBI Group’s PowerPoint Presentation

Potential Use of LPBI IP as Value Price Driver by Potential Acquirer: Assumptions per Asset Class 

 

6.   The Actors at Play – Experts, Authors, Writers – Life Sciences & Medicine as it applies to HEALTH CARE

Founder’s Role in the Development of Venture’s Factors of Content Production – Biographical Notes by Aviva Lev-Ari, PhD, RN, LPBI Group

Top Authors by Number of eReaders Views

Top Articles by Number of e-Readers for All Days ending 2019-02-17

FIT Members Contribute to Opportunities Map

FINAL IMPROVEMENT TEAM (FIT): Definition of Active, Lapsing of Active Status, COMPs Formulas

FIT members – Who works on WHAT?

Summer 2019 Plan – Research Associates Tasks

 

7.   1st Level Connection on LinkedIn = +7,100 and Endorsements = +1,500

Connections First Level on LinkedIn: 500 CEOs, 200 Big Pharma Professionals, 7,000 in Total: LPBI Group Founder – Aviva Lev-Ari, PhD, RN

 

8.   The DIGITAL REPUTATION of our Venture – Twitter for the Professional and for Institutions

Mostly HONORED to be followed by [from an Excerpt of 117 Followers of the Twitter Account @AVIVA1950 from the List of 359 Followers] by the Number of their Followers on 2/24/2019

LPBI Group is mostly HONORED to be followed by [from an Excerpt of 136 Followers of the Twitter Account @pharma_BI from the List of 505 Followers] by the Number of their Followers on 3/20/2019

Excerpt of 136 Followers of @pharma_BI (from the List of 505 Followers) by the Number of their Followers on 3/20/2019

Excerpt of 117 Followers of @AVIVA1950 (from the List of 359 Followers) by the Number of their Followers

REACH – Two Handles on Twitter.com @AVIVA1950 @pharma_BI

9.   Growth in Twitter Followers and in Global Reach: Who are the NEW Followers: OUR COMPETITION and other Media Establishments – that is the definition of Trend Setter, Opinion Leader and Source for Emulation

@4openjournalFollows you

Follow

4open is a multi- & inter-disciplinary, online, peer-reviewed, open access journal publishing across a broad range of subjects in the STEM domain.

@roll_clausFollows you

Follow

Publishing Editor at 

@EDPSciences

@PubtextoPFollows you

Following

Pubtexto is an International online publishing organization that publishes Scientific literature through its different open access Journals.

@alexanderlabrieFollows you

Following

CEO 

@sphereinc

@BjoernBruecherFollows you

Following

THEODOR-BILLROTH-ACADEMY® 

(link: http://linkedin.com/in/bruecher)

linkedin.com/in/bruecher // 

(link: http://4open-sciences.org)

4open-sciences.org – Editor-in-Chief // Science Profile – 

(link: http://researchgate.net/profile/Bjoern)

researchgate.net/profile/Bjoern

@MPDexpertFollows you

Follow

translate research into life-changing Global manufactured Medical Products – drugs, devices, biotech, combination; anything requiring FDA approval#MedProdDev

@P_A_MORGONFollows you

Following

Life science expert & investor_travel, wine & golf amateur_Proud father of 2 girls_My Tweets are only mine 

@INmuneBioFollows you

Follow

INmune Bio, Inc. is developing therapies that harness patient’s #immunesystem to treat #cancer. Our focus is on #NKcells and #myeloid derived suppressor cells.

@sallyeavesFollows you

Following

Innovating #tech #education #business CEO CTO Advisor & Prof. #blockchain #AI 

@OxfordSBS

@Forbes

 #FinTech #speaker #SDGs #STEM #techforgood #sustainability

@sciencetracker2Follows you

You will hear more recent and cool scientific news here. Besides, some health and tech news. Follow us in

(link: http://facebook.com/sciencetracker2)

facebook.com/sciencetracker2

13.8K Following

24.6K Followers

Followed by Stanford Tweets, Biotech Week Boston, and 23 others you follow

@sgruenwaldFollows you

Following

MD, PhD, scientist, futurist, entrepreneur, managing director of 

(link: http://www.genautica.com)

genautica.com, co-founder 

(link: http://www.diagnomics.com)

diagnomics.com

(link: http://www.scoop.it/t/amazing-science)

scoop.it/t/amazing-scie…user

 

10.  Business Aspects of the Brick & Mortar World render OBSOLETE

Financial Valuation of Three Health Care Intellectual Property (IP) Content Asset Classes

Global Market Penetration Forecast for each Volume in the 16 Volume BioMed e-Series

2013-2019, On the Medical & Scientific Bookshelf in Kindle Store: eReader Behaviors: Browsing, Page Downloads and Buying e-Books – LPBI Group’s BioMed e-Series, Royalties Payment Analysis 

 

Part 2: BUSINESS PERSPECTIVES on Reputation

 

Warren Buffett on reputation: the economic value of values, integrity and corporate culture

Warren Buffett understands that reputation and integrity have economic value. Research that shows that a good reputation is worth real money — in fact, some research indicates that a good reputation might replace a line of credit at the bank. In his book Berkshire Beyond Buffett: The Enduring Value of Values, Lawrence Cunningham argues that one of Berkshire Hathaway’s greatest assets is reputation.

https://www.finn.agency/fr/warren-buffett-reputation-berkshire-hathaway

 

The Value of Reputation

Thomas Pfeiffer1,2,4,*, Lily Tran5, Coco Krumme5 and David G Rand1,3,* 1 Program for Evolutionary Dynamics, FAS, 2 School of Applied Sciences and Engineering, and 3 Department of Psychology, Harvard University, Cambridge MA 02138, USA 4 New Zealand Institute for Advanced Study, Massey University, Auckland 0745, New Zealand 5 MIT Media Laboratory, Cambridge MA 02139, USA

 

Reputation plays a central role in human societies.

Empirical and theoretical work indicates that a good reputation is valuable in that it increases one’s expected payoff in the future. Here, we explore a game that couples a repeated Prisoner’s Dilemma (PD), in which participants can earn and can benefit from a good reputation, with a market in which reputation can be bought and sold. This game allows us to investigate how the trading of reputation affects cooperation in the PD, and how participants assess the value of having a good reputation. We find that depending on how the game is set up, trading can have a positive or a negative effect on the overall frequency of cooperation. Moreover, we show that the more valuable a good reputation is in the PD, the higher the price at which it is traded in the market. Our findings have important implications for the use of reputation systems in practice.

Keywords: evolution of cooperation; reciprocal altruism; indirect reciprocity; reputation

http://decisionlab.harvard.edu/_content/research/papers/Krumme_Pfieffer_Tran_and_Rand_Value_of_Reputation.pdf

 

The Impact of Reputation on Market Value by Simon Cole

One of the most familiar, but least understood, intangible assets is a firm’s reputation.

Simon Cole is the founding partner of the corporate reputation and branding consultancy Reputation Dividend (www. reputationdividend.com).

http://www.reputationdividend.com/files/4713/4822/1479/Reputation_Dividend_WEC_133_Cole.pdf

 

Part 3:   ECONOMICS PERSPECTIVES on Reputation

 

The Economics of Trust and Reputation: A Primer

Luıs M B Cabral New York University and CEPR, June 2005, lecture series at the University of Zurich

lcabral@stern.nyu.edu

https://pdfs.semanticscholar.org/24e5/2f3bd22d4bfa86902e5ae07d57039480004f.pdf

 

Notes on the literature

Important note: The notes in this section are essentially limited to the ideas discussed in the present version of these lectures notes. They cannot therefore be considered a survey of the literature. There are dozens of articles on the economics of reputation which I do not include here. In a future version of the text, I hope to provide a more complete set of notes on the literature. The notes below follow the order with which topics are presented.

Bootstrap models. The bootstrap mechanism for trust is based on a general result known as the folk theorem (known as such because of its uncertain origins). For a fairly general statement of the theorem (and its proof) see Fudenberg and Makin (1986). One of the main areas of application of the folk theorem has been the problem of (tacit or explicit) collusion in oligopoly. This is a typical problem of trust (or lack thereof): all firms would prefer prices to be high and output to be low; but each firm, individually, has an incentive to drop price and increase output. Friedman (1971) presents one of the earliest formal applications of the folk theorem to oligopoly collusion. He considers the case when firms set prices and history is perfectly observable. Both of the extensions presented in Section 2.2 were first developed with oligopoly collusion applications in mind. The case of trust with noisy signals (2.2.1) was first developed by Green and Porter (1984). A long series of papers have been written on this topic, including the influential work by Abreu, Pearce and Stacchetti (1990). Rotemberg and Saloner (1986) proposed a model of oligopoly collusion with fluctuating market demand. In this case, the intuition presented in Section 2.2.2 implies that firms collude on a lower price during periods of higher demand. This suggests that prices are counter-cyclical in markets where firms collude. Rotemberg and Saloner (1986) present supporting evidence from the cement industry. A number of papers have built on Rotemberg and Saloner’s analysis. Kandori (1992) shows that the i.i.d. assumption simplifies the analysis but is not crucial. Harrington (19??) considers a richer demand model and looks at how prices vary along the business cycle. The basic idea of repetition as a form of ensuring seller trustworthiness is developed in Klein and Leffler (1981). See also Telser (1980) and Shapiro (1983). When considering the problem of free entry, Klein and Leffler (1981) propose advertising as a solution, whereas Shapiro (1983) suggests low intro25 ductory prices. Section ?? is based on my own research notes. The general analysis of selfreinforcing agreements when there is an outside option of the kind considered here may be found in Ray (2002). Watson (1999, 2002) also considers models where the level of trust stars at a low level and gradually increases.

Bayesian models. The seminal contributions to the study of Bayesian models of reputation are Kreps and Wilson (1982) and Milgrom and Roberts (1982). The model in Section 3.2.1 includes elements from these papers as well as from Diamond (1989). H¨olmstrom (1982/1999) makes the point that separation leads to reduced incentives to invest in reputation. The issue of reputation with separation and changing types is treated in detail in the forthcoming book by Mailath and Samuelson (2006). In Section 3.3, I presented a series of models that deal with name as carriers of reputations. The part on changing names (Section 3.3.1) reflects elements from a variety of models, though, to the best of my knowledge, no study exists that models the process of secret, costless name changes in an infinite period adverse selection context. The study of markets for names follows the work by Tadelis (1999) and Mailath and Samuelson (2001). All of these papers are based on the Bayesian updating paradigm. Kreps (1990) presents an argument for trading reputations in a bootstrap type of model. The analysis of brand stretching (Section 3.3.3) is adapted from Cabral (2000). The paper considers a more general framework where the direct reputation, feedback reputation and signalling effects are present; and shows that better sellers are always more likely to brand stretch. The comparative statics with respect to the initial reputation level, however, are not obvious. As we saw above, a higher reputation firm can earn a higher direct reputation effect premium. But a higher reputation firm also has more to lose. The trade-off between using one’s reputation and protecting it can go both ways. For other papers on brand stretching and umbrella branding see Choi (1998), Anderson (2002).

Bibliography

Abreu, Dilip, David Pearce and Ennio Stacchetti (1990), “Toward a Theory of Discounted Repeated Games with Imperfect Monitoring,” Econometrica 58, 1041–1064. Andersson, Fredrik (2002), “Pooling reputations,” International Journal of Industrial Organization 20, 715–730. Bernhein, B. Douglas and Michael D. Whinston (1990), “Multimarket Contact and Collusive Behavior,” Rand Journal of Economics 21, 1–26. Cabral, Lu´ıs M B (2000), “Stretching Firm and Brand Reputation,” Rand Journal of Economics 31, 658-673. Choi, J.P. (1998), “Brand Extension and Informational Leverage,” Review of Economic Studies 65, 655–69. Diamond, Douglas W (1989), “Reputation Acquisition in Debt Markets,” Journal of Political Economy 97, 828–862. Ely, Jeffrey C., and Juuso Valim ¨ aki ¨ (2003), “Bad Reputation,” The Quarterly Journal of Economics 118, 785–814. Fishman, A., and R. Rob (2005), “Is Bigger Better? Customer Base Expansion through Word of Mouth Reputation,” forthcoming in Journal of Political Economy. Friedman, James (1971), “A Noncooperative Equilibrium for Supergames,” Review of Economic Studies 28, 1–12. Fudenberg, Drew and Eric Maskin (1986), “The Folk Theorem in Repeated Games with Discounting or with Imperfect Public Information,” Econometrica 54, 533–556. Green, Ed and Robert Porter (1984), “Noncooperative Collusion Under Imperfect Price Information,” Econometrica 52, 87–100. Holmstrom, Bengt ¨ (1999), “Managerial Incentive Problems: A Dynamic Perspective,” Review of Economic Studies 66, 169–182. (Originally (1982) in Essays in Honor of Professor Lars Wahlback.) Kandori, Michihiro (1992), “Repeated Games Played by Overlapping Generations of Players,” Review of Economic Studies 59, 81–92. Klein, B, and K Leffler (1981), “The Role of Market Forces in Assuring Contractual Performance,” Journal of Political Economy 89, 615–641. 27 Kreps, David (1990), “Corporate Culture and Economic Theory,” in J Alt and K Shepsle (Eds), Perspectives on Positive Political Economy, Cambridge: Cambridge University Press, 90–143. Kreps, David M., Paul Milgrom, John Roberts and Robert Wilson (1982), “Rational Cooperation in the Finitely Repeated Prisoners’ Dilemma,” Journal of Economic Theory 27, 245–252. Kreps, David M., and Robert Wilson (1982), “Reputation and Imperfect Information,” Journal of Economic Theory 27, 253–279. Mailath, George J, and Larry Samuelson (2001), “Who Wants a Good Reputation?,” Review of Economic Studies 68, 415–441. Mailath, George J, and Larry Samuelson (1998), “Your Reputation Is Who You’re Not, Not Who You’d Like To Be,” University of Pennsylvania and University of Wisconsin. Mailath, George J, and Larry Samuelson (2006), Repeated Games and Reputations: Long-Run Relationships, Oxford: Oxford University Press. Milgrom, Paul, and John Roberts (1982), “Predation, Reputation, and Entry Deterrence,” Journal of Economic Theory 27, 280–312. Phelan, Christopher (2001), “Public Trust and Government Betrayal,” forthcoming in Journal of Economic Theory. Ray, Debraj (2002), “The Time Structure of Self-Enforcing Agreements,” Econometrica 70, 547–582. Rotemberg, Julio, and Garth Saloner (1986), “A Supergame-Theoretic Model of Price Wars During Booms,” American Economic Review 76, 390–407. Shapiro, Carl (1983), “Premiums for High Quality Products as Rents to Reputation,” Quarterly Journal of Economics 98, 659–680. Tadelis, S. (1999), “What’s in a Name? Reputation as a Tradeable Asset,” American Economic Review 89, 548–563. Tadelis, Steven (2002), “The Market for Reputations as an Incentive Mechanism,” Journal of Political Economy 92, 854–882. Telser, L G (1980), “A Theory of Self-enforcing Agreements,” Journal of Business 53, 27–44. Tirole, Jean (1996), “A Theory of Collective Reputations (with applications to the persistence of corruption and to firm quality),” Review of Economic Studies 63, 1–22. 28 Watson, Joel (1999), “Starting Small and Renegotiation,” Journal of Economic Theory 85, 52–90. Watson, Joel (2002), “Starting Small and Commitment,” Games and Economic Behavior 38, 176–199. Wernerfelt, Birger (1988), “Umbrella Branding as a Signal of New Product Quality: An Example of Signalling by Posting a Bond,” Rand Journal of Economics 19, 458–466.

https://pdfs.semanticscholar.org/24e5/2f3bd22d4bfa86902e5ae07d57039480004f.pdf

 

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Selection Process for Chief Innovation and Entrepreneurship Officer (CIEO) @Berkeley: Ecosystem Evangelist, Professor Richard Lyons, Berkeley’s ex-Dean of the Haas School of Business

 

Reporter: Aviva Lev-Ari, PhD, RN, Berkeley PhD’83

 

for @Berkeley Alumna Ecosystem Evangelist see

https://pharmaceuticalintelligence.com/2019-vista/executive-summary/

The University of California at Berkeley appointed professor Richard Lyons as the university’s first-ever chief innovation and entrepreneurship officer (CIEO).

The Selection Process

Professor Richard Lyons was selected for the CIEO position through a rigorous recruitment and selection process that attracted several hundred top-notch applications from all over the world. Throughout the process, Lyons stood out as a true visionary, a strategic leader and an ecosystem evangelist who could understand and activate the untapped potential of Berkeley’s innovation and entrepreneurship landscape.

 

“If together we can improve the transformation of Berkeley’s prodigious intellectual product, across the whole campus, into greater societal benefit, then we will have achieved a great deal,” said Lyons, in a statement.

Image Source: Courtesy of University of California, Berkeley, Doe Library Building with the  Campanile Tower in the background

Professor Richard Lyons,  Accomplishments as Berkeley’s ex-Dean of the Haas School of Business

  • He helped launch the Management, Entrepreneurship, & Technology (M.E.T.) dual-degree program in partnership with the College of Engineering.
  • He also initiated the Biology + Business dual degree program with Molecular & Cell Biology and
  • He revitalized the Berkeley-Haas Entrepreneurship Program (BHEP).
  • He helped the campus to launch the Berkeley SkyDeck startup accelerator in 2012 and served on its Governing Board, did that in collaboration with leadership in the Office of Research and College of Engineering.

 

SOURCE

https://venturebeat-com.cdn.ampproject.org/c/s/venturebeat.com/2019/07/10/richard-lyons-will-be-uc-berkeleys-first-ever-chief-innovation-and-entrepreneurship-officer/amp/

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Real Time @BIOConvention #BIO2019:#Bitcoin Your Data! From Trusted Pharma Silos to Trustless Community-Owned Blockchain-Based Precision Medicine Data Trials

Reporter: Stephen J Williams, PhD @StephenJWillia2
Speakers

As care for lifestyle-driven chronic diseases expands in scope, prevention and recovery are becoming the new areas of focus. Building a precision medicine foundation that will promote ownership of individuals’ health data and allow for sharing and trading of this data could prove a great blockchain.

At its core, blockchain may offer the potential of a shared platform that decentralizes healthcare interactions ensuring access control, authenticity and integrity, while presenting the industry with radical possibilities for value-based care and reimbursement models. Panelists will explore these new discoveries as well as look to answer lingering questions, such as: are we off to a “trustless” information model underpinned by Bitcoin cryptocurrency, where no central authority validates the transactions in the ledger, and anyone whose computers can do the required math can join to mine and add blocks to your data? Would smart contracts begin to incentivize “rational” behaviors where consumers respond in a manner that makes their data interesting?

Moderator:  Cybersecurity is extremely important in the minds of healthcare CEOs.  CEO of Kaiser Permenente has listed this as one of main concerns for his company.

Sanjeey of Singularity: There are Very few companies in this space.  Singularity have collected thousands of patient data.  They wanted to do predictive health care, where a patient will know beforehand what health problems and issues to expect.  Created a program called Virtual Assistant. As data is dynamic, the goal was to provide Virtual Assistant to everyone.

Benefits of blockchain: secure, simple to update, decentralized data; patient can control their own data, who sees it and monetize it.

Nebular Genetics: Company was founded by Dr. George Church, who had pioneered the next generation sequencing (NGS) methodology.  The company goal is to make genomics available to all but this currently is not the case as NGS is not being used as frequently.

The problem is a data problem:

  • data not organized
  • data too parsed
  • data not accessible

Blockchain may be able to alleviate the accessibiltiy problem.  Pharma is very interested in the data but expensive to collect.  In addition many companies just do large scale but low depth sequencing.  For example 23andme (which had recently made a big deal with Lilly for data) only sequences about 1% of genome.

There are two types of genome sequencing companies

  1.  large scale and low depth – like 23andme
  2. smaller scale but higher depth – like DECODE and some of the EU EXOME sequencing efforts like the 1000 Project

Simply Vital Health: Harnesses blockchain to combat ineffeciencies in hospital records. They tackle the costs after acute care so increase the value based care.  Most of healthcare is concentrated on the top earners and little is concentrated on the majority less affluent and poor.  On addressing HIPAA compliance issues: they decided to work with HIPAA and comply but will wait for this industry to catch up so the industry as a whole can lobby to affect policy change required for blockchain technology to work efficiently in this arena.  They will only work with known vendors: VERY Important to know where the data is kept and who are controlling the servers you are using.  With other blockchain like Etherium or Bitcoin, the servers are anonymous.

Encrypgen: generates new blockchain for genomic data and NGS companies.

 

Please follow LIVE on TWITTER using the following @ handles and # hashtags:

@Handles

@pharma_BI

@AVIVA1950

@BIOConvention

# Hashtags

#BIO2019 (official meeting hashtag)

#blockchain
#bitcoin
#clinicaltrials

 

 

 

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At California Central District Court Juno Therapeutics, Inc. et al v. Kite Pharma, Inc. – Multi-party Patent Infringement

Curator and Reporter: Aviva Lev-Ari, PhD, RN

 

Infringement of Patent: US7446190B2 – which is exclusively licensed to Juno Therapeutics, Inc.

United States

Inventor
Michel Sadelain
Renier Brentjens
John Maher
Current Assignee
Sloan-Kettering Institute for Cancer Research

Worldwide applications
2003  US

Application US10/448,256 events
2002-05-28
Priority to US38387202P
2008-11-04
Application granted
Application status is Active
Adjusted expiration
Show all events

 

SUMMARY OF INVENTION

The present invention provides chimeric TCR’s, nucleic acid polymer encoding the chimeric TCR’s and methods of using the chimeric TCR’s to facilitate T cell response to a specific target. The chimeric TCR’s of the invention combine, in a single chimeric species, the intracellular domain of CD3 ζ-chain (“zeta chain portion”), a signaling region from a costimulatory protein such as CD28 and a binding element that specifically interacts with a selected target. Thus, in accordance with a first aspect of the invention, there is provided a nucleic acid encoding a chimeric T cell receptor, said chimeric T cell receptor comprising a zeta chain, a CD28 signaling region and a binding element that specifically interacts with a selected target. In accordance with a second aspect of the invention, there is provided a chimeric T cell receptor comprising a zeta chain portion, a CD28 signaling region and a binding element.

In accordance with the method of the invention a chimeric TCR is provided which comprises a zeta chain portion, a co-stimulatory signaling element and a binding element which specifically interacts with a cellular marker associated with target cells. T-lymphocytes from the individual to be treated, for example a human individual, are transduced with the chimeric TCR. This transduction may occur ex vivo, after which the transduced cells are reintroduced into the individual. As a result, T cell immune response is stimulated in the individual to the target cells.

SOURCE

https://patents.google.com/patent/US7446190B2/en

  • Prior Art Search results: (cells) (nucleic acid) (acid polymer) (cell) (cd28) before:priority:2002-05-28

Assignees Inventors include:

C12P21
C12P21/00
C12P
C12P21/02
C07K14/52
C07K14/715
C07K14/54
C07K14/521
C07K14/47
C07K14/46
C12N9/6432
C12Y304/21006
C07K14/47
C07K14/46
C07K14/475
C07K14/435
A01K2217
A01K2217/00
A01K
A01K2217/075
C12N2533/00
C12N2533/14
C12N2533/18
C12N2533/30
G01N33/502
G01N33/5041
Y10S435/973
G01N33/5008
B01J2219/00648
B01J2219/00306
B82Y15/00
B01J2219/00646
C07K14/70532
C07K14/70503
C07K16/2827
A61K2039/5158
A61K38/1774
A61K31/33
A61K45
A61K45/06
C07K14/70532
C12N2795
C12N2795/00
C12N2795/00011
C07K14/47
C07K14/46
A61K48/00
C07K14/435
C12N2510/00
C12N2502/99
C12N2501/515
C12N2501/51
C07K14/70503
A61K38/00
A61K
C07K14/705
G01N33/6878
G01N33/68
C07K1/047
C07K1/04
C07K14/70503
A01K2217/05
C07K14/705
A01K2217
Y02A50/38
A61K2039/6068
A61K2039/6025
C07K2319/21
C07K14/47
C07K14/46
A61K48/00
C07K14/435
C07K14/4747
C07K14/70575
A61K45/06
A61K45

SOURCE

https://patents.google.com/?q=cells&q=nucleic+acid&q=acid+polymer&q=cell&q=cd28&before=priority:20020528&scholar

 

IRELL & MANELLA LLP Morgan Chu (SBN 70446) Alan J. Heinrich (SBN 212782) Elizabeth C. Tuan (SBN 295020) 1800 Avenue of the Stars, Suite 900 Los Angeles, California 90067-4276 Telephone: (310) 277-1010 Facsimile: (310) 203-7199 Attorneys for

Plaintiffs JUNO THERAPEUTICS, INC., MEMORIAL SLOAN KETTERING CANCER CENTER, and SLOAN KETTERING INSTITUTE FOR CANCER RESEARCH UNITED STATES DISTRICT COURT CENTRAL DISTRICT OF CALIFORNIA Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, and Sloan Kettering Institute for Cancer Research,,

Plaintiffs, v. Kite Pharma, Inc., Defendant. ) ) ) ) ) ) ) ) ) ) ) )

CASE NO.: 2:17-CV-07639

COMPLAINT FOR PATENT INFRINGEMENT

DEMAND FOR JURY TRIAL

Case 2:17-cv-07639 Document 1 Filed 10/18/17 Page 1 of 14 Page ID #:1

Knowing that it infringes the ’190 Patent, Kite challenged the validity of all claims of the ’190 Patent in an inter partes review (“IPR”) in the United States Patent and Trademark Office (“PTO” or “Office”) before the Patent Trial and Appeal Board (“PTAB” or “Board”). The PTAB instituted the IPR and then upheld all claims of the ’190 Patent in a Final Written Decision issued December 16, 2016. The PTAB concluded that Kite did not even show “by a preponderance of the evidence”—the lower standard applicable to validity challenges in an IPR—that any claim of the ’190 Patent was unpatentable.

Kite recently received marketing approval from the Food and Drug Administration (“FDA”) for its Yescarta™ product (axicabtagene ciloleucel) (“axicel” or “Yescarta,” also known as “KTE-C19”) on October 18, 2017. Plaintiffs accordingly bring suit against Kite for infringement based on Kite’s making, using, offering to sell, and selling of its chimeric antigen receptor products that comprise the claimed nucleic acid polymers of the ’190 Patent. 35 U.S.C. § 271(a). Plaintiffs hereby allege for their Complaint against Defendant Kite, on personal knowledge as to their own actions and on information and belief as to the actions of others,

26. Indeed, the DNA sequence of Kite’s retroviral vector demonstrates that Kite’s anti-CD19 chimeric TCR falls within the scope of the ’190 Patent claims. In a document Kite filed with the Recombinant DNA Advisory Committee (“RAC”), a federal committee that reviews clinical trial protocols that are either directly funded by the National Institutes of Health (“NIH”) or conducted at institutions that receive NIH funding, Kite provided the DNA sequence of KTE-C19’s anti-CD19 chimeric TCR vector. Exhibit 10 (KTE-C19 DNA Sequence). The RAC filing described the retroviral vector used as

encoding a chimeric antigen receptor directed against the B cell antigen, CD19 . . . The retroviral vector utilizes the MSGV1 (murine stem cell virus-based splice-gag vector 1) retroviral vector backbone and consists of 7026 bps including the 5’ long terminal repeat (LTR) from the murine stem cell virus (promoter), packaging signal including the splicing donor (SD) and splicing acceptor sites, FMC63- based (anti-CD19 FMC63-28) CAR protein containing a signal peptide (human GM-CSF receptor), FMC63 light chain variable region (FMC63 VL), linker peptide, FMC63 heavy chain variable region (FMC63 VH), CD28 (hinge, transmembrane and cytoplasmic region), and TCR-zeta (cytoplasmic region), followed by the murine stem cell virus 3’LTR. This particular vector was provided by Dr. Steven A. Rosenberg from the Surgery Branch/NCI and is the same vector used in an ongoing RAC-approved clinical trial of which Dr. Stephen A. Rosenberg is the Principal Investigator (OBA/RAC submission 0809-940). . . . [T]he complete nucleotide sequence as determined by the standard nucleotide sequencing protocol is shown in Appendix 2 of this application.

27. During the IPR Kite initiated against the ’190 Patent, Sloan Kettering’s expert, Prof. Thomas Brocker, the Director of the Institute for Immunology at the Ludwig-Maximilians University in Munich, Germany, compared the chimeric TCR used by Kite’s scientific collaborators to the claims of the ’190 Patent, demonstrating that Kite’s collaborators’ chimeric TCR construct, and thus, Kite’s own KTE-C19 product, falls within the scope of at least claims 1-3 and 5 of the ’190 Patent. Exhibit 12 (Brocker Declaration), ¶ 224. The NCI chimeric TCR analyzed by Prof. Brocker contains the same nucleotide sequence as KTE-C19’s chimeric TCR. See Exhibit 11 (RAC Filing).

28. On October 18, 2017, Kite received approval for the FDA to market and sell Yescarta (axicabtagene ciloleucel) in the United States.

COUNT 1:

INFRINGEMENT OF THE ’190 PATENT UNDER 35 U.S.C. § 271(a)

29. Plaintiffs re-allege and incorporate by reference the allegations contained in paragraphs 1-28 above.

30. to 40. are Plaintiffs’ description of Defendant Infringement on claims of the Patent

MAIN SOURCE for Filings by Plaintiffs

http://litigationtools.maxval-ip.com/UnifiedPatentViewDocument/home/index?caseid=128416

 

 

Plaintiffs:

  • Juno Therapeutics, Inc.,
  • Memorial Sloan Kettering Cancer Center,
  • Sloan Kettering Institute for Cancer Research

Defendant and Counterclaimant

  • Kite Pharma, Inc.

 

Effective April 17, 2018, Magistrate Judge Rozella A. Oliver will be located at the Edward R. Roybal Federal Building and U.S. Courthouse, COURTROOM 590 on the 5th floor, located at 255 East Temple Street, Los Angeles, California 90012. All Court appearances shall be made in Courtroom 590 of the Roybal Federal Building,

100

Oct 9, 2018

MINUTE IN CHAMBERS CLAIM CONSTRUCTION ORDER by Judge S. James Otero: The Court finds that a POSITA encountering the 190 Patent prior to the CoC would have understood SEQ ID NO:6 to begin with nucleotide 336 of the CD28 protein. The Court construes the disputed claim terms as follows: 1. The amino acid sequence encoded by SEQ ID NO:6 before the Certificate of Correction means Amino Acids 113-220 of CD28 (starting with lysine (K)) and after the Certificate of Correction means Amino Acids 114-220 of CD28 (starting with isoleucine (I)). 2. nucleic acid polymer encoding… a binding element that specifically interacts with a selected target is given its plain and ordinary meaning. (shb) (Entered: 10/10/2018)

 

Main Doc

 

Juno Therapeutics, Inc. et al v. Kite Pharma, Inc. (2:17-cv-07639), California Central District Court

California Central District Court
Judge: S James Otero
Referred: Jacqueline Chooljian
Case #: 2:17-cv-07639
Nature of Suit 830 Property Rights – Patent
Cause 35:271 Patent Infringement
Case Filed: Oct 18, 2017
Docket last updated: 03/08/2019 11:59 PM PST 

Thursday, March 07, 2019
150 order For Order Thu 12:50 PM 
ORDER GRANTING DEFENDANT KITE PHARMA, INC.S EX PARTE APPLICATION FOR AN EXTENSION OF TIME FOR THE MAGISTRATE JUDGE TO HEAR MOTIONS TO COMPEL PRODUCTION OF DOCUMENTS AND WITNESSES144 by Judge S. James Otero: 1. Time is extended until April 17, 2019, for the Magistrate Judge to hear (a) any motions to compel Plaintiffs to produce documents that Kite has already identified as deficient in Plaintiffs production and Plaintiffs have not yet produced, and (b) a motion to compel Bristol-Myers Squibb Company to produce documents in response to Kites subpoena; and 2. Time is extended until May 10, 2019, for the Magistrate Judge to hear a motion to compel deposition testimony regarding the documents described in paragraph 1 above. (lc) Modified on 3/7/2019 (lc)
Wednesday, March 06, 2019
149 transcript -Transcript Order Form (G-120) Wed 2:56 PM 
TRANSCRIPT ORDER as to Defendant Kite Pharma, Inc. for Court Smart (CS). Court will contact Adam R. Lawton at adam.lawton@mto.com with further instructions regarding this order. Transcript preparation will not begin until payment has been satisfied with the transcription company. (Lawton, Adam)
Tuesday, March 05, 2019
147 respm Reply (Motion related) Tue 5:31 PM 
REPLY in support of EX PARTE APPLICATION for Order for Extension of Time for the Magistrate Judge to Hear Motions to Compel Production of Documents and Witnesses 144 filed by Defendant Kite Pharma, Inc..(Lawton, Adam)
Att: 1 Reply Declaration of Adam R. Lawton
146 respm Objection/Opposition (Motion related) Tue 12:26 PM 
OPPOSITION Ex Parte Application re: EX PARTE APPLICATION for Order for Extension of Time for the Magistrate Judge to Hear Motions to Compel Production of Documents and Witnesses 144Opposition filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research.(Wells, Crawford)
Att: 1 Declaration,
Att: 2 Exhibit 1
Monday, March 04, 2019
148 minutes Telephone Conference For Order re Discovery Matter Wed 9:27 AM 
MINUTES OF CONTINUED PRE-MOTION TELEPHONIC DISCOVERY CONFERENCE settling139 Motion re: Informal Discovery Dispute held before Magistrate Judge Karen L. Stevenson. Should Judge Otero grant Kite’s Ex Parte Application, Kite may file a motion to compel. In the interim, at the request of counsel for non-party BMS, who does not receive the CM/ECF notifications in this case, the Court ORDERS Defendant Kite, to provide copies to BMS counsel of the following: (1) Minutes of Pre-Motion Telephonic Discovery Conference held on February 26, 2019, (Dkt. No. 138) (see document for further details). Court Recorder: XTR 03-04-19. (hr)
145 respm Declaration (Motion related) Mon 12:52 PM 
DECLARATION of Adam R. Lawton (Corrected) in support of EX PARTE APPLICATION for Order for Extension of Time for the Magistrate Judge to Hear Motions to Compel Production of Documents and Witnesses 144 filed by Defendant Kite Pharma, Inc.. (Lawton, Adam)
144 17 pgs motion Order Mon 11:50 AM 
EX PARTE APPLICATION for Order for Extension of Time for the Magistrate Judge to Hear Motions to Compel Production of Documents and Witnesses filed by Defendant Kite Pharma, Inc.. (Lawton, Adam)
Att: 1 Proposed Order,
Att: 2 Declaration of Adam R. Lawton,
Att: 3 Exhibit 1,
Att: 4 Exhibit 2,
Att: 5 Exhibit 3,
Att: 6 Exhibit 4,
Att: 7 Exhibit 5,
Att: 8 Exhibit 6,
Att: 9 Exhibit 7,
Att: 10 Exhibit 8,
Att: 11 Exhibit 9,
Att: 12 Exhibit 10,
Att: 13 Exhibit 11,
Att: 14 Exhibit 12,
Att: 15 Exhibit 13,
Att: 16 Exhibit 14,
Att: 17 Exhibit 15,
Att: 18 Exhibit 16
Thursday, February 28, 2019
143 order Leave to File Excess Pages Thu 10:50 AM 
ORDER GRANTING-IN-PART DEFENDANT KITE PHARMA, INC.’S APPLICATION FOR LEAVE TO FILE A 10-PAGE REPLY BRIEF IN SUPPORT OF MOTION FOR SUMMARY JUDGMENT OF NONINFRINGEMENT140 by Judge S. James Otero. It is hereby ordered that Defendant Kite Pharma, Inc. may file a reply brief of no more than 10 pages in support of its motion for summary judgment of noninfringement. Plaintiffs are permitted to file a sur-reply, not to exceed 7 pages, addressing the admissibility of the expert declarations submitted in support of its opposition to Defendant’s motion for summary judgment of noninfringement. The sur-reply shall be filed no later than 5 days from Defendant’s reply. IT IS SO ORDERED. (lom)

Juno Therapeutics, Inc. v. Kite Pharma, Inc. (2:17-cv-07639)

District Court, C.D. California

 

 

 

 

 

 

 

Recorded here ONLY if PDF is Downloadable

Oct 18, 2017

COMPLAINT Receipt No: 0973-20685642 – Fee: $400, filed by Plaintiffs Juno Therapeutics, Inc., Sloan Kettering Institute for Cancer Research, Memorial Sloan Kettering Cancer Center. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10, # 11 Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit 14) (Attorney Morgan Chu added to party Juno Therapeutics, Inc.(pty:pla), Attorney Morgan Chu added to party Memorial Sloan Kettering Cancer Center(pty:pla), Attorney Morgan Chu added to party Sloan Kettering Institute for Cancer Research(pty:pla))(Chu, Morgan) (Entered: 10/18/2017)

Main Doc

3

Oct 18, 2017

Request for Clerk to Issue Summons on Complaint (Attorney Civil Case Opening),, 1 filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research. (Chu, Morgan) (Entered: 10/18/2017)

SKIPPED

46

Jan 29, 2018

JOINT REPORT Rule 26(f) Discovery Plan ; estimated length of trial 5-12 days, filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research.. (Attachments: # 1 Appendix 2)(Chu, Morgan) (Entered: 01/29/2018)

SKIPPED

66

Mar 29, 2018

AMENDED ANSWER and AMENDED COUNTERCLAIM to Complaint (Attorney Civil Case Opening),, 1 filed by Defendant and Counterclaimant Kite Pharma, Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6 Exhibit F, # 7 Exhibit G, # 8 Exhibit H, # 9 Exhibit I, # 10 Exhibit J, # 11 Exhibit K, # 12 Exhibit L, # 13 Exhibit M, # 14 Appendix (redline version of amended pleading))(Lawton, Adam) (Entered: 03/29/2018)

SKIPPED

74

May 11, 2018

STIPULATION for Protective Order filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research. (Attachments: # 1 Proposed Order)(Tuan, Elizabeth) (Entered: 05/11/2018)

75

May 14, 2018

ORDER GRANTING PROTECTIVE ORDER by Magistrate Judge Rozella A. Oliver re Stipulation for Protective Order 74 (dml) (Entered: 05/14/2018)

Protective Order

SKIPPED

85

Aug 13, 2018

DECLARATION of Alan J. Heinrich re Brief (non-motion non-appeal), 84 ISO Juno’s Claim Construction Brief filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research, Counter Defendants Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research. (Attachments: # 1 Exhibit Exhibit 1, # 2 Exhibit Exhibit 2, # 3 Exhibit Exhibit 3, # 4 Exhibit Exhibit 4, # 5 Exhibit Exhibit 5, # 6 Exhibit Exhibit 6, # 7 Exhibit Exhibit 7, # 8 Exhibit Exhibit 8, # 9 Exhibit Exhibit 9, # 10 Exhibit Exhibit 10, # 11 Exhibit Exhibit 11)(Heinrich, Alan) (Entered: 08/13/2018)

Main Doc

Declaration

115

Dec 3, 2018

SEALED DECLARATION IN SUPPORT OF APPLICATION to file document (Reply in Support of Motion to Dismiss and Exhibits J-M) under seal 114 filed by Defendant Kite Pharma, Inc.. (Attachments: # 1 Unredacted Document Reply in Support of Motion to Dismiss, # 2 Unredacted Document Exhibit J, # 3 Unredacted Document Exhibit K, # 4 Unredacted Document Exhibit L, # 5 Unredacted Document Exhibit M)(Lawton, Adam) (Entered: 12/03/2018)

Main Doc

117

Jan 4, 2019

STIPULATION to AMEND Protective Order 75 filed by Defendant Kite Pharma, Inc.. (Attachments: # 1 Amended Protective Order, # 2 Proposed Order)(Lawton, Adam) (Entered: 01/04/2019)

118

Jan 7, 2019

ORDER GRANTING AMENDED PROTECTIVE ORDER by Magistrate Judge Rozella A. Oliver, re Stipulation to Amend Protective Order 117 (dml) (Entered: 01/07/2019)

119

Jan 7, 2019

AMENDED PROTECTIVE ORDER by Magistrate Judge Rozella A. Oliver, re Order Granting 118 (dml) (Entered: 01/07/2019)

122

Jan 24, 2019

Joint STIPULATION to Extend Discovery Cut-Off Date to March 29, 2019 filed by Plaintiffs Juno Therapeutics, Inc., Memorial Sloan Kettering Cancer Center, Sloan Kettering Institute for Cancer Research. (Attachments: # 1 Proposed Order)(Heinrich, Alan) (Entered: 01/24/2019)

Main Doc

SOURCE

https://www.courtlistener.com/docket/6175992/juno-therapeutics-inc-v-kite-pharma-inc/

Other related sources

35 U.S.C. 271 – Infringement of patent

Other related articles published in this Online Open Access Scientific Journal, include the following:

Economic Potential of a Drug Invention (Prof. Zelig Eshhar, Weitzman Institute, registered the patent) versus a Cancer Drug in Clinical Trials: CAR-T as a Case in Point, developed by Kite Pharma, under Arie Belldegrun, CEO, acquired by Gilead for $11.9 billion, 8/2017.

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/10/04/economic-potential-of-a-drug-invention-prof-zelig-eshhar-weitzman-institute-registered-the-patent-versus-a-cancer-drug-in-clinical-trials-car-t-as-a-case-in-point-developed-by-kite-pharma-unde/

 

Read Full Post »


Patent on Methods and compositions for RNA-directed target DNA modification and for RNA-directed modulation of transcription was awarded to UC, Berkeley on October 30, 2018

  •  site-specific modification of a target DNA and/or a polypeptide associated with the target DNA, a DNA-targeting RNA
  •  genetically modified cells that produce Cas9; and Cas9 transgenic non-human multicellular organisms.

Reporter: Aviva Lev-Ari, PhD, RN

 

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United States Patent 10,113,167
Doudna ,   et al. October 30, 2018

Methods and compositions for RNA-directed target DNA modification and for RNA-directed modulation of transcription 

AbstractThe present disclosure provides a DNA-targeting RNA that comprises a targeting sequence and, together with a modifying polypeptide, provides for site-specific modification of a target DNA and/or a polypeptide associated with the target DNA. The present disclosure further provides site-specific modifying polypeptides. The present disclosure further provides methods of site-specific modification of a target DNA and/or a polypeptide associated with the target DNA The present disclosure provides methods of modulating transcription of a target nucleic acid in a target cell, generally involving contacting the target nucleic acid with an enzymatically inactive Cas9 polypeptide and a DNA-targeting RNA. Kits and compositions for carrying out the methods are also provided. The present disclosure provides genetically modified cells that produce Cas9; and Cas9 transgenic non-human multicellular organisms.


Inventors: Doudna; Jennifer A. (Berkeley, CA), Jinek; Martin (Berkeley, CA), Chylinski; Krzysztof (Vienna, AT), Charpentier; Emmanuelle (Braunschweig, DE)
Applicant:
Name City State Country Type

The Regents of the University of California
University of Vienna
Charpentier; Emmanuelle
Oakland
Vienna
Braunschweig
CA
N/A
N/A
US
AT
DE
Assignee: The Regents of the University of California (Oakland, CA)
University of Vienna (Vienna, AT)
Charpentier; Emmanuelle (Braunschweig, DE)
Family ID: 1000003617643
Appl. No.: 15/138,604
Filed: April 26, 2016

SOURCE

http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=10113167.PN.&OS=PN/10113167&RS=PN/10113167

SAVE

UC Berkeley team awarded second CRISPR-Cas9 patent

 

“Today’s news … represents yet another validation of the historic and field-changing breakthrough invented by scientists Jennifer Doudna, Emmanuelle Charpentier, and their team… The patent announced today specifically highlights the CRISPR-Cas9 invention’s ability to edit DNA in any setting, including within animal and human cells. It also highlights its utility in several formats across both dual-RNA and single-RNA configurations, useful for therapy for genetic diseases and for improving food security.”
— Edward Penhoet, special adviser to the UC Berkeley chancellor, tells Axios

The details: According to the patent, the compositions can be used in animal or human cells, and can work as either 2 separate pieces of RNA or a single piece of RNA.

  • Penhoet says the new patent covers 2 RNA components that together form the “DNA-targeting-RNA,” with one that targets the particular sequence of DNA needed to be edited and the other that binds with the Cas9 protein.
  • This follows another patent given to UC Berkeley in June on methods to use CRISPR-cas9.
  • The patents cover the composites used by CRISPR-Cas9 within human, plant, animal and bacteria cells.
  • Both allow the use of strands of RNA “that can be shorter than naturally-occurring RNA components. This allows them to be more easily used and, therefore, is a form often preferred,” Penhoet says.

Go deeper:

SOURCE

https://www.axios.com/uc-berkeley-awarded-crispr-cas9-gene-edit-patent-5a533f22-929d-4e7d-83fe-0a73ebeb4538.html

Read Full Post »


 

HUBweek 2018, October 8-14, 2018, Greater Boston – “We The Future” – coming together, of breaking down barriers, of convening across disciplinary lines to shape our future

Reporter: Aviva Lev-Ari, PhD, RN

 

HUBweek 2018

Hi Aviva,

 

At HUBweek and in this community, we believe a brighter future is built together. In these times of division, particularly when many are feeling excluded from the benefits brought forth by rapid technological development, there is critical importance in the act of coming together, of breaking down barriers, of convening across disciplinary lines to shape our future.

That’s why this year’s theme for HUBweek is We the Future. It is a call to action and an invitation. Throughout the week, we’ll bring together innovators, artists, and curious minds to explore the ways in which we can shape a more inclusive and equitable future for all.

Today, HUBweek kicks off with dozens of events taking place across the city–from public art tours, a drone zoo, and discussions on nuclear weapons and the impact of emerging technologies on people with disabilities, to a policy hackathon hosted by MIT and the first ever Change Maker Conference.

There are 225+ more experiences to take part in throughout HUBweek–a three-day Forum and a documentary film festival; open dialogues with leading thinkers; a robot block party; and collaborative and participatory art. And we’ve got a little fun in store for you, too–make sure you sign up and stop by The HUB later this week to check it all out.

At its core, HUBweek is a collaboration. If not for our partners and the unwavering support of this community, this would not be a reality. A big thank you to our presenting partners Blue Cross Blue Shield of Massachusetts, Liberty Mutual Insurance, and Merck KGaA, to our sponsors, and to the hundreds of collaborating organizations, speakers, artists, and creative minds that are behind this year’s festival.

On behalf of the HUBweek team and our founders The Boston Globe, Harvard University, Mass. General Hospital, and MIT, we’re thrilled to invite you to join us at HUBweek 2018.

 

Linda Pizzuti Henry

SOURCE

 

From: Linda Pizzuti Henry <hello@hubweek.org>

Reply-To: <hello@hubweek.org>

Date: Monday, October 8, 2018 at 9:38 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: Welcome to HUBweek

Read Full Post »


NIH SBIR Funding Early Ventures: September 26, 2018 sponsored by Pennovation

Stephen J. Williams PhD, Reporter

Penn Center for Innovation (Pennovation) sponsored a “Meet with NCI SBIR” program directors at University of Pennsylvania Medicine Smilow Center for Translational Research with a presentation on advice on preparing a successful SBIR/STTR application to the NCI as well as discussion of NCI SBIR current funding opportunities.   Time was allotted in the afternoon for one-on-one discussions with NCI SBIR program directors.

To find similar presentations and one-on-one discussions with NCI/SBIR program directors in an area nearest to you please go to their page at:

https://sbir.cancer.gov/newsevents/events

For more complete information on the NCI SBIR and STTR programs please go to their web page at: https://sbir.cancer.gov/about

A few notes from the meeting are given below:

  • In 2016 the SBIR/STTR 2016 funded $2.5 billion (US) of early stage companies; this is compared to the $6.6 billion invested in early  stage ventures by venture capital firms so the NCI program is very competitive with alternate sources of funding
  • It was stressed that the SBIR programs are flexible as far as ownership of a company; SBIR allows now that >50% of the sponsoring company can be owned by other ventures;  In addition they are looking more favorably on using outside contractors and giving leeway on budgetary constraints so AS THEY SUGGEST ALWAYS talk to the program director about any questions you may have well before (at least 1 month) you submit. More on eligibility criteria is found at: https://sbir.cancer.gov/about/eligibilitycriteria
  • STTR should have strong preliminary data since more competitive; if don’t have enough go for  an R21 emerging technologies grant which usually does not require preliminary data
  • For entities outside the US need a STRONG reason for needing to do work outside the US

Budget levels were discussed as well as  the waiver program, which allows for additional funds to be requested based on criteria set by NCI (usually for work that is deemed high priority or of a specialized nature which could not be covered sufficiently under the standard funding limits) as below:

Phase I: 150K standard but you can get waivers for certain work up to 300K

Phase II: 1M with waiver up to 2M

Phase IIB waiver up to 4M

You don’t need to apply for the waiver but grant offices may suggest citing a statement requesting a waiver as review panels will ask for this information

Fast Track was not discussed in the presentation but for more information of the Fast Track program please visit the website  

NCI is working hard to cut review times to 7 months between initial review to funding however at beginning of the year they set pay lines and hope to fund 50% of the well scored grants

NCI SBIR is a Centralized system with center director and then program director with specific areas of expertise: Reach out to them

IMAT Program and Low-Resource Setting new programs more suitable for initial studies and also can have non US entities

Phase IIB Bridge funding to cross “valley of death” providing up to 4M for 2-3 years: most were for drug/biological but good amount for device and diagnostics

 

Also they have announced administrative supplements for promoting diversity within a project: can add to the budget

FY18 Contracts Areas

3 on biotherapies

2 imaging related

2 on health IT

4 on radiation therapy related: NOTE They spent alot of time discussing the contracts centered on radiation therapy and seems to be an area of emphasis of the NCI SBIR program this year

4 other varied topics

 

Breakdown of funding

>70% of NCI SBIR budget went to grants (for instance Omnibus grants); about 20-30% for contracts; 16% for phase I and 34 % for phase II ;

ALSO the success rate considerably higher for companies that talk to the program director BEFORE applying than not talking to them; also contracts more successful than Omnibus applications

Take Advantage of these useful Assistance Programs through the NIH SBIR Program (Available to all SBIR grantees)

NICHE ASSESSMENT Program

From the NCI SBIR website:

The Niche Assessment Program is designed to help small businesses “jump start” their commercialization efforts. All active HHS (NIH, CDC, FDA) SBIR/STTR Phase I awardees and Phase I Fast-Track awardees (by grant or contract) are eligible to apply. Registration is on a first-come, first-serve basis!

The Niche Assessment Program provides market insight and data that can be used to help small businesses strategically position their technology in the marketplace. The results of this program can help small businesses develop their commercialization plans for their Phase II application, and be exposed to potential partners. Services are provided by Foresight Science & Technology of Providence, RI.

Technology Niche Analyses® (TNA®) are provided by Foresight, for one hundred and seventy-five (175), HHS SBIR/STTR Phase I awardees. These analyses assess potential applications for a technology and then for one viable application, it provides an assessment of the:

  1. Needs and concerns of end-users;
  2. Competing technologies and competing products;
  3. Competitive advantage of the SBIR/STTR-developed technology;
  4. Market size and potential market share (may include national and/or global markets);
  5. Barriers to market entry (may include but is not limited to pricing, competition, government regulations, manufacturing challenges, capital requirements, etc.);
  6. Market drivers;
  7. Status of market and industry trends;
  8. Potential customers, licensees, investors, or other commercialization partners; and,
  9. The price customers are likely to pay.

Commercialization Acceleration Program  (CAP)

From the NIH SBIR website:

NIH CAP is a 9-month program that is well-regarded for its combination of deep domain expertise and access to industry connections, which have resulted in measurable gains and accomplishments by participating companies. Offered since 2004 to address the commercialization objectives of companies across the spectrum of experience and stage, 1000+ companies have participated in the CAP. It is open only to HHS/NIH SBIR/STTR Phase II awardees, and 80 slots are available each year. The program enables participants to establish market and customer relevance, build commercial relationships, and focus on revenue opportunities available to them.

I-Corps Program

The I-Corps program provides funding, mentoring, and networking opportunities to help commercialize your promising biomedical technology. During this 8-week, hands-on program, you’ll learn how to focus your business plan and get the tools to bring your treatment to the patients who need it most.

Program benefits include:

  • Funding up to $50,000 to cover direct program costs
  • Training from biotech sector experts
  • Expanding your professional network
  • Building the confidence and skills to create a comprehensive business model
  • Gaining years of entrepreneurial skills in only weeks.

 

ICORPS is an Entrepreneurial Program (8 week course) to go out talk to customers, get assistance with business models, useful resource which can guide the new company where they should focus on for the commercialization aspect

THE NCI Applicant Assistance Program (AAP)

The SBIR/STTR Applicant Assistance Program (AAP) is aimed at helping eligible small R&D businesses and individuals successfully apply for Phase I SBIR/STTR funding from the National Cancer Institute (NCI), National Institute for Neurological Disorders and Stroke (NINDS), National Heart, Lung and Blood Institute (NHLBI). Participation in the AAP will be funded by the NCI, NINDS, and NHLBI with NO COST TO PARTICIPANTS. The program will include the following services:

  • Needs Assessment/Small Business Mentoring
  • Phase I Application Preparation Support
  • Application Review
  • Team/Facilities Development
  • Market Research
  • Intellectual Property Consultation

For more details about the program, please refer to NIH Notice NOT-CA-18-072.

 

These programs are free for first time grant applicants and must not have been awarded previous SBIR

Peer Learning Webinar Series goal to improve peer learning .Also they are starting to provide Regulatory Assistance (see below)

NIH also provides Mentoring programs for CEOS and C level

Application tips

  1. Start early: and obtain letters of collaboration
  2. Build a great team: PI multi PI, consider other partners to fill gaps (academic, consultants, seasoned entrepreneurs (don’t need to be paid)
  3. They will pre review 1 month before due date, use NIH Project Reporter to view previous funded grants
  4. Specify study section in SF to specify areas of expertise for review
  5. Specific aims are very important; some of the 20 reviewers focus on this page (describes goals and milestones as well; spend as much time on this page as the rest of the application
  6. Letters of support from KOLs are important to have; necessary from consultants and collaborators; helpful from clinicians
  7. Have a phase II commercialization plan
  8. Note for non US clinical trials:  They will not fund nonUS clinical trials; the company must have a FWA
  9. SBIR budgets defined by direct costs; can request a 7% fee as an indirect cost; and they have a 5,000 $ technical assistance program like regulatory consultants but if requested can’t participate in NIH technical assistance programs so most people don’t apply for TAP

 

  • They are trying to change the definition of innovation as also using innovative methods (previously reviewers liked tried and true methodology)

10.  before you submit solicit independent readers

NCI SBIR can be found on Twitter @NCIsbir ‏

Discussion with Monique Pond, Ph.D. on Establishment of a Regulatory Assistance Program for NCI SBIR

I was able to sit down with Dr. Monique Pond,  AAAS Science & Technology Policy Fellow, Health Scientist within the NCI SBIR Development Center to discuss the new assistance program in regulatory affairs she is developing for the NCI SBIR program.  Dr Pond had received her PhD in chemistry from the Pennsylvania State University, completed a postdoctoral fellow at NIST and then spent many years as a regulatory writer and consultant in the private sector.  She applied through the AAAS for this fellowship and will bring her experience and expertise in regulatory affairs from the private sector to the SBIR program. Dr. Pond discussed the difficulties that new ventures have in formulating regulatory procedures for their companies, the difficulties in getting face time with FDA regulators and helping young companies start thinking about regulatory issues such as pharmacovigilence, oversight, compliance, and navigating the complex regulatory landscape.

In addition Dr. Pond discussed the AAAS fellowship program and alternative career paths for PhD scientists.

 

A formal interview will follow on this same post.

 

Other articles on this OPEN ACCESS JOURNAL on Funding for Startups and Early Ventures are given below:

 

Mapping Medical Device Startups Across The Globe per Funding Criteria

Funding Oncorus’s Immunotherapy Platform: Next-generation Oncolytic Herpes Simplex Virus (oHSV) for Brain Cancer, Glioblastoma Multiforme (GBM)

 

Funding Opportunities for Cancer Research

 

Team Profile: DrugDiscovery @LPBI Group – A BioTech Start Up submitted for Funding Competition to MassChallenge Boston 2016 Accelerator

 

A Message from Faculty Director Lee Fleming on Latest Issue of Crowdfunding; From the Fung Institute at Berkeley

 

PROTOCOL for Drug Screening of 3rd Party Intellectual Property Presented for Funding Representation

 

Foundations as a Funding Source

 

The Bioscience Crowdfunding Environment: The Bigger Better VC?

 

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