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Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Posted in Artificial Intelligence Applications in Health Care, BioIT: BioInformatics, Blockchain Transactions System, Curation, Curation methodology, De novo synthesis, Discovery process, Historical relevance, IP Development by LPBI Group Team, IP Development by LPBI Group Team & Other Organizations, Key Opinion Leaders in eScientific Publishing - Interviews with, LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management, Open Access Journals, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific Publishing, tagged #science2_0, #science3_0, communication of scientific findings, Curation of Scientific Content, Curation of Scientific Findings, LinkedIn, NFT, science communication, Twitter, web 2.0, web 3.0 on April 1, 2022| 2 Comments »

Will Web 3.0 Do Away With Science 2.0? Is Science Falling Behind?

Curator: Stephen J. Williams, Ph.D.

UPDATED 4/06/2022

A while back (actually many moons ago) I had put on two posts on this site:

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

Twitter is Becoming a Powerful Tool in Science and Medicine

Each of these posts were on the importance of scientific curation of findings within the realm of social media and the Web 2.0; a sub-environment known throughout the scientific communities as Science 2.0, in which expert networks collaborated together to produce massive new corpus of knowledge by sharing their views, insights on peer reviewed scientific findings. And through this new media, this process of curation would, in itself generate new ideas and new directions for research and discovery.

The platform sort of looked like the image below:

 

This system lied above a platform of the original Science 1.0, made up of all the scientific journals, books, and traditional literature:

Previous image source: PeerJ.com

To index the massive and voluminous research and papers beyond the old Dewey Decimal system, a process of curation was mandatory. The dissemination of this was a natural for the new social media however the cost had to be spread out among numerous players. Journals, faced with the high costs of subscriptions and their only way to access this new media as an outlet was to become Open Access, a movement first sparked by journals like PLOS and PeerJ but then begrudingly adopted throughout the landscape. But with any movement or new adoption one gets the Good the Bad and the Ugly (as described in my cited, above, Clive Thompson article). The bad side of Open Access Journals were

1. costs are still assumed by the individual researcher not by the journals
2. the arise of the numerous Predatory Journals

 

Even PeerJ, in their column celebrating an anniversary of a year’s worth of Open Access success stories, lamented the key issues still facing Open Access in practice

• which included the cost and the rise of predatory journals.

In essence, Open Access and Science 2.0 sprung full force BEFORE anyone thought of a way to defray the costs

 

Can Web 3.0 Finally Offer a Way to Right the Issues Facing High Costs of Scientific Publishing?

What is Web 3.0?

From Wikipedia: https://en.wikipedia.org/wiki/Web3

Web 1.0 and Web 2.0 refer to eras in the history of the Internet as it evolved through various technologies and formats. Web 1.0 refers roughly to the period from 1991 to 2004, where most websites were static webpages, and the vast majority of users were consumers, not producers, of content.^[6][7] Web 2.0 is based around the idea of “the web as platform”,^[8] and centers on user-created content uploaded to social-networking services, blogs, and wikis, among other services.^[9] Web 2.0 is generally considered to have begun around 2004, and continues to the current day.^[8][10][4]

Terminology[edit]

The term “Web3”, specifically “Web 3.0”, was coined by Ethereum co-founder Gavin Wood in 2014.^[1] In 2020 and 2021, the idea of Web3 gained popularity^{[citation needed]}. Particular interest spiked towards the end of 2021, largely due to interest from cryptocurrency enthusiasts and investments from high-profile technologists and companies.^[4][5] Executives from venture capital firm Andreessen Horowitz travelled to Washington, D.C. in October 2021 to lobby for the idea as a potential solution to questions about Internet regulation with which policymakers have been grappling.^[11]

Web3 is distinct from Tim Berners-Lee‘s 1999 concept for a semantic web, which has also been called “Web 3.0”.^[12] Some writers referring to the decentralized concept usually known as “Web3” have used the terminology “Web 3.0”, leading to some confusion between the two concepts.^[2][3] Furthermore, some visions of Web3 also incorporate ideas relating to the semantic web.^[13][14]

Concept[edit]

Web3 revolves around the idea of decentralization, which proponents often contrast with Web 2.0, wherein large amounts of the web’s data and content are centralized in the fairly small group of companies often referred to as Big Tech.^[4]

Specific visions for Web3 differ, but all are heavily based in blockchain technologies, such as various cryptocurrencies and non-fungible tokens (NFTs).^[4] Bloomberg described Web3 as an idea that “would build financial assets, in the form of tokens, into the inner workings of almost anything you do online”.^[15] Some visions are based around the concepts of decentralized autonomous organizations (DAOs).^[16] Decentralized finance (DeFi) is another key concept; in it, users exchange currency without bank or government involvement.^[4] Self-sovereign identity allows users to identify themselves without relying on an authentication system such as OAuth, in which a trusted party has to be reached in order to assess identity.^[17]

Reception[edit]

Technologists and journalists have described Web3 as a possible solution to concerns about the over-centralization of the web in a few “Big Tech” companies.^[4][11] Some have expressed the notion that Web3 could improve data security, scalability, and privacy beyond what is currently possible with Web 2.0 platforms.^[14] Bloomberg states that sceptics say the idea “is a long way from proving its use beyond niche applications, many of them tools aimed at crypto traders”.^[15] The New York Times reported that several investors are betting $27 billion that Web3 “is the future of the internet”.^[18][19]

Some companies, including Reddit and Discord, have explored incorporating Web3 technologies into their platforms in late 2021.^[4][20] After heavy user backlash, Discord later announced they had no plans to integrate such technologies.^[21] The company’s CEO, Jason Citron, tweeted a screenshot suggesting it might be exploring integrating Web3 into their platform. This led some to cancel their paid subscriptions over their distaste for NFTs, and others expressed concerns that such a change might increase the amount of scams and spam they had already experienced on crypto-related Discord servers.^[20] Two days later, Citron tweeted that the company had no plans to integrate Web3 technologies into their platform, and said that it was an internal-only concept that had been developed in a company-wide hackathon.^[21]

Some legal scholars quoted by The Conversation have expressed concerns over the difficulty of regulating a decentralized web, which they reported might make it more difficult to prevent cybercrime, online harassment, hate speech, and the dissemination of child abuse images.^[13] But, the news website also states that, “[decentralized web] represents the cyber-libertarian views and hopes of the past that the internet can empower ordinary people by breaking down existing power structures.” Some other critics of Web3 see the concept as a part of a cryptocurrency bubble, or as an extension of blockchain-based trends that they see as overhyped or harmful, particularly NFTs.^[20] Some critics have raised concerns about the environmental impact of cryptocurrencies and NFTs. Others have expressed beliefs that Web3 and the associated technologies are a pyramid scheme.^[5]

Kevin Werbach, author of The Blockchain and the New Architecture of Trust,^[22] said that “many so-called ‘web3’ solutions are not as decentralized as they seem, while others have yet to show they are scalable, secure and accessible enough for the mass market”, adding that this “may change, but it’s not a given that all these limitations will be overcome”.^[23]

David Gerard, author of Attack of the 50 Foot Blockchain,^[24] told The Register that “web3 is a marketing buzzword with no technical meaning. It’s a melange of cryptocurrencies, smart contracts with nigh-magical abilities, and NFTs just because they think they can sell some monkeys to morons”.^[25]

Below is an article from MarketWatch.com Distributed Ledger series about the different forms and cryptocurrencies involved

From Marketwatch: https://www.marketwatch.com/story/bitcoin-is-so-2021-heres-why-some-institutions-are-set-to-bypass-the-no-1-crypto-and-invest-in-ethereum-other-blockchains-next-year-11639690654?mod=home-page

by Frances Yue, Editor of Distributed Ledger, Marketwatch.com

Clayton Gardner, co-CEO of crypto investment management firm Titan, told Distributed Ledger that as crypto embraces broader adoption, he expects more institutions to bypass bitcoin and invest in other blockchains, such as Ethereum, Avalanche, and Terra in 2022. which all boast smart-contract features.

Bitcoin traditionally did not support complex smart contracts, which are computer programs stored on blockchains, though a major upgrade in November might have unlocked more potential.

“Bitcoin was originally seen as a macro speculative asset by many funds and for many it still is,” Gardner said. “If anything solidifies its use case, it’s a store of value. It’s not really used as originally intended, perhaps from a medium of exchange perspective.”

For institutions that are looking for blockchains that can “produce utility and some intrinsic value over time,” they might consider some other smart contract blockchains that have been driving the growth of decentralized finance and web 3.0, the third generation of the Internet, according to Gardner. 

“Bitcoin is still one of the most secure blockchains, but I think layer-one, layer-two blockchains beyond Bitcoin, will handle the majority of transactions and activities from NFT (nonfungible tokens) to DeFi,“ Gardner said. “So I think institutions see that and insofar as they want to put capital to work in the coming months, I think that could be where they just pump the capital.”

Decentralized social media？ 

The price of Decentralized Social, or DeSo, a cryptocurrency powering a blockchain that supports decentralized social media applications, surged roughly 74% to about $164 from $94, after Deso was listed at Coinbase Pro on Monday, before it fell to about $95, according to CoinGecko.

In the eyes of Nader Al-Naji, head of the DeSo foundation, decentralized social media has the potential to be “a lot bigger” than decentralized finance.

“Today there are only a few companies that control most of what we see online,” Al-Naji told Distributed Ledger in an interview. But DeSo is “creating a lot of new ways for creators to make money,” Al-Naji said.

“If you find a creator when they’re small, or an influencer, you can invest in that, and then if they become bigger and more popular, you make money and they make and they get capital early on to produce their creative work,” according to AI-Naji.

BitClout, the first application that was created by AI-Naji and his team on the DeSo blockchain, had initially drawn controversy, as some found that they had profiles on the platform without their consent, while the application’s users were buying and selling tokens representing their identities. Such tokens are called “creator coins.”

AI-Naji responded to the controversy saying that DeSo now supports more than 200 social-media applications including Bitclout. “I think that if you don’t like those features, you now have the freedom to use any app you want. Some apps don’t have that functionality at all.”

 

But Before I get to the “selling monkeys to morons” quote,

I want to talk about

THE GOOD, THE BAD, AND THE UGLY

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

THE GOOD

My foray into Science 2.0 and then pondering what the movement into a Science 3.0 led me to an article by Dr. Vladimir Teif, who studies gene regulation and the nucleosome, as well as creating a worldwide group of scientists who discuss matters on chromatin and gene regulation in a journal club type format.

For more information on this Fragile Nucleosome journal club see https://generegulation.org/fragile-nucleosome/.

Fragile Nucleosome is an international community of scientists interested in chromatin and gene regulation. Fragile Nucleosome is active in several spaces: one is the Discord server where several hundred scientists chat informally on scientific matters. You can join the Fragile Nucleosome Discord server. Another activity of the group is the organization of weekly virtual seminars on Zoom. Our webinars are usually conducted on Wednesdays 9am Pacific time (5pm UK, 6pm Central Europe). Most previous seminars have been recorded and can be viewed at our YouTube channel. The schedule of upcoming webinars is shown below. Our third activity is the organization of weekly journal clubs detailed at a separate page (Fragile Nucleosome Journal Club).

 

His lab site is at https://generegulation.org/ but had published a paper describing what he felt what the #science2_0 to #science3_0 transition would look like (see his blog page on this at https://generegulation.org/open-science/).

This concept of science 3.0 he had coined back in 2009.  As Dr Teif had mentioned

So essentially I first introduced this word Science 3.0 in 2009, and since then we did a lot to implement this in practice. The Twitter account @generegulation is also one of examples

 

This is curious as we still have an ill defined concept of what #science3_0 would look like but it is a good read nonetheless.

His paper,  entitled “Science 3.0: Corrections to the Science 2.0 paradigm” is on the Cornell preprint server at https://arxiv.org/abs/1301.2522 

 

Abstract

Science 3.0: Corrections to the Science 2.0 paradigm

Vladimir B. Teif

The concept of Science 2.0 was introduced almost a decade ago to describe the new generation of online-based tools for researchers allowing easier data sharing, collaboration and publishing. Although technically sound, the concept still does not work as expected. Here we provide a systematic line of arguments to modify the concept of Science 2.0, making it more consistent with the spirit and traditions of science and Internet. Our first correction to the Science 2.0 paradigm concerns the open-access publication models charging fees to the authors. As discussed elsewhere, we show that the monopoly of such publishing models increases biases and inequalities in the representation of scientific ideas based on the author’s income. Our second correction concerns post-publication comments online, which are all essentially non-anonymous in the current Science 2.0 paradigm. We conclude that scientific post-publication discussions require special anonymization systems. We further analyze the reasons of the failure of the current post-publication peer-review models and suggest what needs to be changed in Science 3.0 to convert Internet into a large journal club. [bold face added]

In this paper it is important to note the transition of a science 1.0, which involved hard copy journal publications usually only accessible in libraries to a more digital 2.0 format where data, papers, and ideas could be easily shared among networks of scientists.

As Dr. Teif states, the term “Science 2.0” had been coined back in 2009, and several influential journals including Science, Nature and Scientific American endorsed this term and suggested scientists to move online and their discussions online.  However, even at present there are thousands on this science 2.0 platform, Dr Teif notes the number of scientists subscribed to many Science 2.0 networking groups such as on LinkedIn and ResearchGate have seemingly saturated over the years, with little new members in recent times. 

The consensus is that science 2.0 networking is:

1. good because it multiplies the efforts of many scientists, including experts and adds to the scientific discourse unavailable on a 1.0 format
2. that online data sharing is good because it assists in the process of discovery (can see this evident with preprint servers, bio-curated databases, Github projects)
3. open-access publishing is beneficial because free access to professional articles and open-access will be the only publishing format in the future (although this is highly debatable as many journals are holding on to a type of “hybrid open access format” which is not truly open access
4. only sharing of unfinished works and critiques or opinions is good because it creates visibility for scientists where they can receive credit for their expert commentary

There are a few concerns on Science 3.0 Dr. Teif articulates:

A.  Science 3.0 Still Needs Peer Review

Peer review of scientific findings will always be an imperative in the dissemination of well-done, properly controlled scientific discovery.  As Science 2.0 relies on an army of scientific volunteers, the peer review process also involves an army of scientific experts who give their time to safeguard the credibility of science, by ensuring that findings are reliable and data is presented fairly and properly.  It has been very evident, in this time of pandemic and the rapid increase of volumes of preprint server papers on Sars-COV2, that peer review is critical.  Many of these papers on such preprint servers were later either retracted or failed a stringent peer review process.

Now many journals of the 1.0 format do not generally reward their peer reviewers other than the self credit that researchers use on their curriculum vitaes.  Some journals, like the MDPI journal family, do issues peer reviewer credits which can be used to defray the high publication costs of open access (one area that many scientists lament about the open access movement; where the burden of publication cost lies on the individual researcher).

An issue which is highlighted is the potential for INFORMATION NOISE regarding the ability to self publish on Science 2.0 platforms.

 

The NEW BREED was born in 4/2012

An ongoing effort on this platform, https://pharmaceuticalintelligence.com/, is to establish a scientific methodology for curating scientific findings where one the goals is to assist to quell the information noise that can result from the massive amounts of new informatics and data occurring in the biomedical literature. 

B.  Open Access Publishing Model leads to biases and inequalities in the idea selection

The open access publishing model has been compared to the model applied by the advertising industry years ago and publishers then considered the journal articles as “advertisements”.  However NOTHING could be further from the truth.  In advertising the publishers claim the companies not the consumer pays for the ads.  However in scientific open access publishing, although the consumer (libraries) do not pay for access the burden of BOTH the cost of doing the research and publishing the findings is now put on the individual researcher.  Some of these publishing costs can be as high as $4000 USD per article, which is very high for most researchers.  However many universities try to refund the publishers if they do open access publishing so it still costs the consumer and the individual researcher, limiting the cost savings to either.  

However, this sets up a situation in which young researchers, who in general are not well funded, are struggling with the publication costs, and this sets up a bias or inequitable system which rewards the well funded older researchers and bigger academic labs.

C. Post publication comments and discussion require online hubs and anonymization systems

Many recent publications stress the importance of a post-publication review process or system yet, although many big journals like Nature and Science have their own blogs and commentary systems, these are rarely used.  In fact they show that there are just 1 comment per 100 views of a journal article on these systems.  In the traditional journals editors are the referees of comments and have the ability to censure comments or discourse.  The article laments that comments should be easy to do on journals, like how easy it is to make comments on other social sites, however scientists are not offering their comments or opinions on the matter. 

In a personal experience, 

a well written commentary goes through editors which usually reject a comment like they were rejecting an original research article.  Thus many scientists, I believe, after fashioning a well researched and referenced reply, do not get the light of day if not in the editor’s interests.  

Therefore the need for anonymity is greatly needed and the lack of this may be the hindrance why scientific discourse is so limited on these types of Science 2.0 platforms.  Platforms that have success in this arena include anonymous platforms like Wikipedia or certain closed LinkedIn professional platforms but more open platforms like Google Knowledge has been a failure.

A great example on this platform was a very spirited conversation on LinkedIn on genomics, tumor heterogeneity and personalized medicine which we curated from the LinkedIn discussion (unfortunately LinkedIn has closed many groups) seen here:

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

 

 

Issues in Personalized Medicine: Discussions of Intratumor Heterogeneity from the Oncology Pharma forum on LinkedIn

 

In this discussion, it was surprising that over a weekend so many scientists from all over the world contributed to a great discussion on the topic of tumor heterogeneity.

But many feel such discussions would be safer if they were anonymized.  However then researchers do not get any credit for their opinions or commentaries.

A Major problem is how to take the intangible and make them into tangible assets which would both promote the discourse as well as reward those who take their time to improve scientific discussion.

This is where something like NFTs or a decentralized network may become important!

See

https://pharmaceuticalintelligence.com/portfolio-of-ip-assets/

 

UPDATED 5/09/2022

Below is an online @TwitterSpace Discussion we had with some young scientists who are just starting out and gave their thoughts on what SCIENCE 3.0 and the future of dissemination of science might look like, in light of this new Meta Verse.  However we have to define each of these terms in light of Science and not just the Internet as merely a decentralized marketplace for commonly held goods.

This online discussion was tweeted out and got a fair amount of impressions (60) as well as interactors (50).

Set a reminder for my upcoming Space! https://t.co/7mOpScZfGN @Pharma_BI @PSMTempleU #science3_0 @science2_0

— Stephen J Williams (@StephenJWillia2) April 28, 2022

 For the recording on both Twitter as well as on an audio format please see below

<blockquote class=”twitter-tweet”><p lang=”en” dir=”ltr”>Set a reminder for my upcoming Space! <a href=”https://t.co/7mOpScZfGN”>https://t.co/7mOpScZfGN</a&gt; <a href=”https://twitter.com/Pharma_BI?ref_src=twsrc%5Etfw”>@Pharma_BI</a&gt; <a href=”https://twitter.com/PSMTempleU?ref_src=twsrc%5Etfw”>@PSMTempleU</a&gt; <a href=”https://twitter.com/hashtag/science3_0?src=hash&amp;ref_src=twsrc%5Etfw”>#science3_0</a&gt; <a href=”https://twitter.com/science2_0?ref_src=twsrc%5Etfw”>@science2_0</a></p>&mdash; Stephen J Williams (@StephenJWillia2) <a href=”https://twitter.com/StephenJWillia2/status/1519776668176502792?ref_src=twsrc%5Etfw”>April 28, 2022</a></blockquote> <script async src=”https://platform.twitter.com/widgets.js&#8221; charset=”utf-8″></script>

 

 

To introduce this discussion first a few startoff material which will fram this discourse

 

The Intenet and the Web is rapidly adopting a new “Web 3.0” format, with decentralized networks, enhanced virtual experiences, and greater interconnection between people. Here we start the discussion what will the move from Science 2.0, where dissemination of scientific findings was revolutionized and piggybacking on Web 2.0 or social media, to a Science 3.0 format. And what will it involve or what paradigms will be turned upside down?

Old Science 1.0 is still the backbone of all scientific discourse, built on the massive amount of experimental and review literature. However this literature was in analog format, and we moved to a more accesible digital open access format for both publications as well as raw data. However as there was a structure for 1.0, like the Dewey decimal system and indexing, 2.0 made science more accesible and easier to search due to the newer digital formats. Yet both needed an organizing structure; for 1.0 that was the scientific method of data and literature organization with libraries as the indexers. In 2.0 this relied on an army mostly of volunteers who did not have much in the way of incentivization to co-curate and organize the findings and massive literature.

Each version of Science has their caveats: their benefits as well as deficiencies. This curation and the ongoing discussion is meant to solidy the basis for the new format, along with definitions and determination of structure.

We had high hopes for Science 2.0, in particular the smashing of data and knowledge silos. However the digital age along with 2.0 platforms seemed to excaccerbate this somehow. We still are critically short on analysis!

 

We really need people and organizations to get on top of this new Web 3.0 or metaverse so the similar issues do not get in the way: namely we need to create an organizing structure (maybe as knowledgebases), we need INCENTIVIZED co-curators, and we need ANALYSIS… lots of it!!

Are these new technologies the cure or is it just another headache?

 

There were a few overarching themes whether one was talking about AI, NLP, Virtual Reality, or other new technologies with respect to this new meta verse and a concensus of Decentralized, Incentivized, and Integrated was commonly expressed among the attendees

The Following are some slides from representative Presentations

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Other article of note on this topic on this Open Access Scientific Journal Include:

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

eScientific Publishing a Case in Point: Evolution of Platform Architecture Methodologies and of Intellectual Property Development (Content Creation by Curation) Business Model 

e-Scientific Publishing: The Competitive Advantage of a Powerhouse for Curation of Scientific Findings and Methodology Development for e-Scientific Publishing – LPBI Group, A Case in Point

@PharmaceuticalIntelligence.com –  A Case Study on the LEADER in Curation of Scientific Findings

Real Time Coverage @BIOConvention #BIO2019: Falling in Love with Science: Championing Science for Everyone, Everywhere

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

 

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

Posted in Conference Coverage with Social Media, LPBI Group Founder - Aviva Lev-Ari, LPBI Group, e-Scientific Media, DFP, R&D-M3DP, R&D-Drug Discovery, US Patents: SOPs and Team Management, MassBio, REAL TIME Conference Coverage Twitter's Hashtags and Handles per Presentation/session, Scientific & Biotech Conferences: Press Coverage, Scientific Publishing, tagged #openscience, #science2_0, @MozillaScience, @science 2_0, Conference Coverage with Social Media, https://twitter.com/#!/pharma_BI, Open access journal, Open Access Online Scientific Journal, open science, real time conference coverage, scientific curation, Twitter on March 6, 2020| Leave a Comment »

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

Curator: Stephen J. Williams, PhD.

UPDATED 3/12/2020

To many of us scientists, presenting and attending scientific meetings, especially international scientific conferences, are a crucial tool for disseminating and learning new trends and cutting edge findings occurring in our respective fields.  Large international meetings, like cancer focused meetings like AACR (held in the spring time), AAAS and ASCO not only highlight the past years great discoveries but are usually the first place where breakthroughs are made known to the scientific/medical community as well as the public.  In addition these conferences allow for scientists to learn some of the newest technologies crucial for their work in vendor exhibitions.

During the coronavirus pandemic, multiple cancellations of business travel, conferences, and even university based study abroad programs are being cancelled and these cancellations are now hitting the 2020 Spring and potentially summer scientific/medical conferences.  Indeed one such conference hosted by Amgen in Massachusetts was determined as an event where some attendees tested positive for the virus, and as such, now other attendees are being asked to self quarantine.

Today I received two emails on conference cancellations, one from Experimental Biology in California and another from The Cancer Letter, highlighting other conferences, including National Cancer Coalition Network (NCCN) meetings which had been canceled.

 

Dear Stephen,

After thoughtful deliberations, the leaders of the Experimental Biology host societies have made the difficult but necessary decision to cancel Experimental Biology (EB) 2020 set to take place April 4–7 in San Diego, California. We know how much EB means to everyone, and we did not make this decision in haste. The health and safety of our members, attendees, their students, our staff, partners and our communities are our top priority.

As we have previously communicated via email, on experimentalbiology.org and elsewhere, EB leadership has been closely monitoring the spread of COVID-19 (coronavirus disease). Based on the latest guidance from public health officials, the travel bans implemented by different institutions and the state of emergency declared in California less than 48 hours ago, it became clear to us that canceling was the right course of action.

We thank you and the entire EB community for understanding the extreme difficulty of this decision and for your commitment to the success of this conference – from the thousands of attendees to the presenters, exhibitors and sponsors who shared their time, expertise, collaboration and leadership. We deeply appreciate your contributions to this community.

What Happens Next?

Everyone who has registered to attend the meeting will receive a full registration refund within the next 45 days. Once your registration cancellation is processed, you will receive confirmation in a separate email. You do not need to contact anyone at EB or your host society to initiate the process. Despite the cancellation of the meeting, we are pleased to tell you that we will publish abstracts in the April 2020 issue of The FASEB Journal as originally planned. Please remember to cancel any personal arrangements you’ve made, such as travel and housing reservations. 

We ask for patience as we evaluate our next steps, and we will alert you as additional information becomes available please see our FAQs for details.

And in The Cancer Letter

Coronavirus vs. oncology: Meeting cancellations, travel restrictions, fears about drug supply chain

By Alexandria Carolan

NOTE: An earlier version of this story was published March 4 on the web and was updated March 6 to include information about restricted travel for employees of cancer centers, meeting cancellations, potential disruptions to the drug supply chain, and funds allocated by U.S. Congress for combating the coronavirus.

Further updates will be posted as the story develops.

Forecasts of the inevitable spread of coronavirus can be difficult to ignore, especially at a time when many of us are making travel plans for this spring’s big cancer meetings.

The decision was made all the more difficult earlier this week, as cancer centers and at least one biotechnology company—Amgen—implemented travel bans that are expected to last through the end of March and beyond. The Cancer Letter was able to confirm such travel bans at Fred Hutchinson Cancer Research Center, MD Anderson Cancer Center, and Dana-Farber Cancer Institute.

Meetings are getting cancelled in all fields, including oncology:

The National Comprehensive Cancer Network March 5 postponed its 2020 annual conference of about 1,500 attendees March 19-22 in Orlando, citing precautions against coronavirus.

“The health and safety of our attendees and the patients they take care of is our number one concern,” said Robert W. Carlson, chief executive officer of NCCN. “This was an incredibly difficult and disappointing decision to have to make. However, our conference attendees work to save the lives of immunocompromised people every day. Some of them are cancer survivors themselves, particularly at our patient advocacy pavilion. It’s our responsibility, in an abundance of caution, to safeguard them from any potential exposure to COVID-19.”

UPDATED 3/12/2020

And today the AACR canceled its yearly 2020 Meeting (https://www.aacr.org/meeting/aacr-annual-meeting-2020/coronavirus-information/)

The American Association for Cancer Research (AACR) Board of Directors has made the difficult decision, after careful consideration and comprehensive evaluation of currently available information related to the novel coronavirus (COVID-19) outbreak, to terminate the AACR Annual Meeting 2020, originally scheduled for April 24-29 in San Diego, California. A rescheduled meeting is being planned for later this year.

The AACR has been closely monitoring the rapidly increasing domestic and worldwide developments during the last several weeks related to COVID-19. This evidence-based decision was made after a thorough review and discussion of all factors impacting the Annual Meeting, including the U.S. government’s enforcement of restrictions on international travelers to enter the U.S.; the imposition of travel restrictions issued by U.S. government agencies, cancer centers, academic institutions, and pharmaceutical and biotech companies; and the counsel of infectious disease experts. It is clear that all of these elements significantly affect the ability of delegates, speakers, presenters of proffered papers, and exhibitors to participate fully in the Annual Meeting.

The health, safety, and security of all Annual Meeting attendees and the patients and communities they serve are the AACR’s highest priorities. While we believe that the decision to postpone the meeting is absolutely the correct one to safeguard our meeting participants from further potential exposure to the coronavirus, we also understand that this is a disappointing one for our stakeholders. There had been a great deal of excitement about the meeting, which was expected to be the largest ever AACR Annual Meeting, with more than 7,400 proffered papers, a projected total of 24,000 delegates from 80 countries and more than 500 exhibitors. We recognize that the presentation of new data, exchange of information, and opportunities for collaboration offered by the AACR Annual Meeting are highly valued by the entire cancer research community, and we are investigating options for rescheduling the Annual Meeting in the near future.

We thank all of our stakeholders for their patience and support at this time. Additional information regarding hotel reservation cancellations, registration refunds, and meeting logistics is available on the FAQ page on the AACR website. We will announce the dates and location of the rescheduled AACR Annual Meeting 2020 as soon as they are confirmed. Our heartfelt sympathies go out to everyone impacted by this global health crisis.

However,  according to both Dr. Fauci and Dr. Scott Gottlieb (former FDA director)  the outbreak may revisit the US and the world in the fall (see https://www.cnbc.com/2020/03/04/were-losing-valuable-time-ex-fda-chief-says-of-coronavirus-spread.html)  therefore these meetings may be cancelled for the whole year.

Is It Time For the Virtual (Real-Time) Conference?

Readers of this Online Access Journal are familiar with our ongoing commitment to open science and believe that forming networks of scientific experts in various fields using a social strategy is pertinent to enhancing the speed, reproducibility and novelty of important future scientific/medical discoveries.  Some of these ideas are highlighted in the following articles found on this site:

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

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

Twitter is Becoming a Powerful Tool in Science and Medicine

e-Scientific Publishing: The Competitive Advantage of a Powerhouse for Curation of Scientific Findings and Methodology Development for e-Scientific Publishing – LPBI Group, A Case in Point

Reconstructed Science Communication for Open Access Online Scientific Curation

In addition, we understand the importance of communicating the latest scientific/medical discoveries in an open and rapid format, accessible over the social media platforms.  To this effect we have developed a methodology for real time conference coverage

see  Press and Conference Coverage

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

AND

The Process of Real Time Coverage using Social Media

at https://pharmaceuticalintelligence.com/press-coverage/part-one-the-process-of-real-time-coverage-using-social-media/

Using these strategies we are able to communicate, in real time, analysis of conference coverage for a multitude of conferences.

Has technology and social media platforms now have enabled our ability to rapidly communicate, in a more open access platform, seminal discoveries and are scientists today amenable to virtual type of meetings including displaying abstracts using a real-time online platform?

Some of the Twitter analytics we have curated from such meetings show that conference attendees are rapidly adopting such social platforms to communicate with their peers and colleagues meeting notes.

Statistical Analysis of Tweet Feeds from the 14th ANNUAL BIOTECH IN EUROPE FORUM For Global Partnering & Investment 9/30 – 10/1/2014 • Congress Center Basel – SACHS Associates, London

Word Associations of Twitter Discussions for 10th Annual Personalized Medicine Conference at the Harvard Medical School, November 12-13, 2014

Comparative Analysis of the Level of Engagement for Four Twitter Accounts: @KDNuggets (Big Data) @GilPress @Forbes @pharma_BI @AVIVA1950

Twitter Analytics on the Inside 3DPrinting Conference #I3DPConf

 

Other Twitter analyses of Conferences Covered by LPBI in Real Time have produced a similar conclusion: That conference attendees are very engaged over social media networks to discuss, share, and gain new insights into material presented at these conferences, especially international conferences.

And although attracting international conferences is lucrative to many cities, the loss in revenue to organizations, as well as the loss of intellectual capital is indeed equally as great.  

Maybe there is room for such type of conferences in the future, and attending by a vast more audience than currently capable. And perhaps the #openscience movement like @MozillaScience can collaborate with hackathons to produce the platforms for such an online movement of scientific conferences as a Plan B.

Other articles on Real Time Conference Coverage in the Online Open Access Journal Include:

Innovations in electronic Scientific Publishing (eSP): Case Studies in Marketing eContent, Curation Methodology, Categories of Research Functions, Interdisciplinary conceptual innovations by Cross Section of Categories, Exposure to Frontiers of Science by Real Time Press coverage of Scientific Conferences

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

Tweets by @pharma_BI and by @AVIVA1950: Real Time Coverage and eProceedings of The 11th Annual Personalized Medicine Conference, November 18-19, 2015, Harvard Medical School

REAL TIME Cancer Conference Coverage: A Novel Methodology for Authentic Reporting on Presentations and Discussions launched via Twitter.com @ The 2nd ANNUAL Sachs Cancer Bio Partnering & Investment Forum in Drug Development, 19th March 2014 • New York Academy of Sciences • USA

Search Results for ‘Real Time Conference’

REAL TIME Cancer Conference Coverage: A Novel Methodology for Authentic Reporting on Presentations and Discussions launched via Twitter.com @ The 2nd ANNUAL Sachs Cancer Bio Partnering & Investment Forum in Drug Development, 19th March 2014 • New York Academy of Sciences • USA

2020 State of Possible Conference, MassBio’s Annual Meeting, March 25-26, 2020, Sonesta Hotel, Cambridge, MA

eProceedings 15th Annual Personalized Medicine Conference at Harvard Medical School – THE PARADIGM EVOLVES, November 13 – 14, 2019 • Harvard Medical School, Boston, MA

eProceedings for BIO 2019 International Convention, June 3-6, 2019 Philadelphia Convention Center; Philadelphia PA, Real Time Coverage by Stephen J. Williams, PhD @StephenJWillia2

 

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How Will FDA’s new precisionFDA Science2.0 Collaboration Platform Protect Data

Posted in Clinical & Translational, Clinical Diagnostics, Clinical Genomics, Computational Biology/Systems and Bioinformatics, Curation, Curation methodology, FDA, FDA Regulatory Affairs, tagged #science2_0, @science 2_0, biocuration, clinical genomics, Curation, NGS, Open access, scientific networks, Social media, Social network, Social science on December 16, 2015| Leave a Comment »

How Will FDA’s new precisionFDA Science 2.0 Collaboration Platform Protect Data?

Reporter: Stephen J. Williams, Ph.D.

As reported in MassDevice.com

FDA launches precisionFDA to harness the power of scientific collaboration

December 16, 2015 By MassDevice Leave a Comment

By: Taha A. Kass-Hout, M.D., M.S. and Elaine Johanson

Imagine a world where doctors have at their fingertips the information that allows them to individualize a diagnosis, treatment or even a cure for a person based on their genes. That’s what President Obama envisioned when he announced his Precision Medicine Initiative earlier this year. Today, with the launch of FDA’s precisionFDA web platform, we’re a step closer to achieving that vision.

PrecisionFDA is an online, cloud-based, portal that will allow scientists from industry, academia, government and other partners to come together to foster innovation and develop the science behind a method of “reading” DNA known as next-generation sequencing (or NGS). Next Generation Sequencing allows scientists to compile a vast amount of data on a person’s exact order or sequence of DNA. Recognizing that each person’s DNA is slightly different, scientists can look for meaningful differences in DNA that can be used to suggest a person’s risk of disease, possible response to treatment and assess their current state of health. Ultimately, what we learn about these differences could be used to design a treatment tailored to a specific individual.

The precisionFDA platform is a part of this larger effort and through its use we want to help scientists work toward the most accurate and meaningful discoveries. precisionFDA users will have access to a number of important tools to help them do this. These tools include reference genomes, such as “Genome in the Bottle,” a reference sample of DNA for validating human genome sequences developed by the National Institute of Standards and Technology. Users will also be able to compare their results to previously validated reference results as well as share their results with other users, track changes and obtain feedback.

Over the coming months we will engage users in improving the usability, openness and transparency of precisionFDA. One way we’ll achieve that is by placing the code for the precisionFDA portal on the world’s largest open source software repository, GitHub, so the community can further enhance precisionFDA’s features.Through such collaboration we hope to improve the quality and accuracy of genomic tests – work that will ultimately benefit patients.

precisionFDA leverages our experience establishing openFDA, an online community that provides easy access to our public datasets. Since its launch in 2014, openFDA has already resulted in many novel ways to use, integrate and analyze FDA safety information. We’re confident that employing such a collaborative approach to DNA data will yield important advances in our understanding of this fast-growing scientific field, information that will ultimately be used to develop new diagnostics, treatments and even cures for patients.

Taha A. Kass-Hout, M.D., M.S., is FDA’s Chief Health Informatics Officer and Director of FDA’s Office of Health Informatics. Elaine Johanson is the precisionFDA Project Manager.

 

The opinions expressed in this blog post are the author’s only and do not necessarily reflect those of MassDevice.com or its employees.

So What Are the Other Successes With Such Open Science 2.0 Collaborative Networks?

In the following post there are highlighted examples of these Open Scientific Networks and, as long as

• transparancy
• equal contributions (lack of heirarchy)

exists these networks can flourish and add interesting discourse.  Scientists are already relying on these networks to collaborate and share however resistance by certain members of an “elite” can still exist.  Social media platforms are now democratizing this new science2.0 effort.  In addition the efforts of multiple biocurators (who mainly work for love of science) have organized the plethora of data (both genomic, proteomic, and literature) in order to provide ease of access and analysis.

Science and Curation: The New Practice of Web 2.0

Curation: an Essential Practice to Manage “Open Science”

The web 2.0 gave birth to new practices motivated by the will to have broader and faster cooperation in a more free and transparent environment. We have entered the era of an “open” movement: “open data”, “open software”, etc. In science, expressions like “open access” (to scientific publications and research results) and “open science” are used more and more often.

Curation and Scientific and Technical Culture: Creating Hybrid Networks

Another area, where there are most likely fewer barriers, is scientific and technical culture. This broad term involves different actors such as associations, companies, universities’ communication departments, CCSTI (French centers for scientific, technical and industrial culture), journalists, etc. A number of these actors do not limit their work to popularizing the scientific data; they also consider they have an authentic mission of “culturing” science. The curation practice thus offers a better organization and visibility to the information. The sought-after benefits will be different from one actor to the next.

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

• Using Curation and Science 2.0 to build Trusted, Expert Networks of Scientists and Clinicians

Given the aforementioned problems of:

        I.            the complex and rapid deluge of scientific information

      II.            the need for a collaborative, open environment to produce transformative innovation

    III.            need for alternative ways to disseminate scientific findings

CURATION MAY OFFER SOLUTIONS

        I.            Curation exists beyond the review: curation decreases time for assessment of current trends adding multiple insights, analyses WITH an underlying METHODOLOGY (discussed below) while NOT acting as mere reiteration, regurgitation

 

      II.            Curation providing insights from WHOLE scientific community on multiple WEB 2.0 platforms

 

    III.            Curation makes use of new computational and Web-based tools to provide interoperability of data, reporting of findings (shown in Examples below)

 

Therefore a discussion is given on methodologies, definitions of best practices, and tools developed to assist the content curation community in this endeavor

which has created a need for more context-driven scientific search and discourse.

However another issue would be Individual Bias if these networks are closed and protocols need to be devised to reduce bias from individual investigators, clinicians.  This is where CONSENSUS built from OPEN ACCESS DISCOURSE would be beneficial as discussed in the following post:

Risk of Bias in Translational Science

As per the article

Risk of bias in translational medicine may take one of three forms:

1. a systematic error of methodology as it pertains to measurement or sampling (e.g., selection bias),
2. a systematic defect of design that leads to estimates of experimental and control groups, and of effect sizes that substantially deviate from true values (e.g., information bias), and
3. a systematic distortion of the analytical process, which results in a misrepresentation of the data with consequential errors of inference (e.g., inferential bias).

This post highlights many important points related to bias but in summarry there can be methodologies and protocols devised to eliminate such bias.  Risk of bias can seriously adulterate the internal and the external validity of a clinical study, and, unless it is identified and systematically evaluated, can seriously hamper the process of comparative effectiveness and efficacy research and analysis for practice. The Cochrane Group and the Agency for Healthcare Research and Quality have independently developed instruments for assessing the meta-construct of risk of bias. The present article begins to discuss this dialectic.

• Information dissemination to all stakeholders is key to increase their health literacy in order to ensure their full participation
• threats to internal and external validity  represent specific aspects of systematic errors (i.e., bias)in design, methodology and analysis

So what about the safety and privacy of Data?

A while back I did a post and some interviews on how doctors in developing countries are using social networks to communicate with patients, either over established networks like Facebook or more private in-house networks.  In addition, these doctor-patient relationships in developing countries are remote, using the smartphone to communicate with rural patients who don’t have ready access to their physicians.

Located in the post Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.

I discuss some of these problems in the following paragraph and associated posts below:

Mobile Health Applications on Rise in Developing World: Worldwide Opportunity

According to International Telecommunication Union (ITU) statistics, world-wide mobile phone use has expanded tremendously in the past 5 years, reaching almost 6 billion subscriptions. By the end of this year it is estimated that over 95% of the world’s population will have access to mobile phones/devices, including smartphones.

This presents a tremendous and cost-effective opportunity in developing countries, and especially rural areas, for physicians to reach patients using mHealth platforms.

How Social Media, Mobile Are Playing a Bigger Part in Healthcare

E-Medical Records Get A Mobile, Open-Sourced Overhaul By White House Health Design Challenge Winners

In Summary, although there are restrictions here in the US governing what information can be disseminated over social media networks, developing countries appear to have either defined the regulations as they are more dependent on these types of social networks given the difficulties in patient-physician access.

Therefore the question will be Who Will Protect The Data?

For some interesting discourse please see the following post

Atul Butte Talks on Big Data, Open Data and Clinical Trials

 

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Artificial Intelligence Versus the Scientist: Who Will Win?

Posted in Academic Publishing, Biological Networks, BioTechnology - Venture Creation, CANCER BIOLOGY & Innovations in Cancer Therapy, Computational Biology/Systems and Bioinformatics, Curation, Curation methodology, De novo synthesis, Discovery process, Disease Biology, Evolutionary cognition, Experimental validation, Explanatory, Gene Regulation and Evolution, Historical relevance, Interviews with Scientific Leaders, Open Access Journals, Small Molecules in Development of Therapeutic Drugs, Technology Advance Assessment of, Theoretic convergence, tagged #science2_0, @science 2_0, Artificial intelligence, Aviva Lev-Ari, biocuration, Cancer - General, Cell Biology, cognition systems, Computational Medical Science, Computer Model, Content Curation, curation communities, Curation methodology, DARPA, knowledge-based conceptualization, Larry H. Bernstein, learning algorithms, Machine Learning, oncogene, Open access, open innovation, Open source intelligence, Ras, Ras oncogene, research, science on March 2, 2015| Leave a Comment »

Artificial Intelligence Versus the Scientist: Who Will Win?

Will DARPA Replace the Human Scientist: Not So Fast, My Friend!

Writer, Curator: Stephen J. Williams, Ph.D.

Last month’s issue of Science article by Jia You “DARPA Sets Out to Automate Research”[1] gave a glimpse of how science could be conducted in the future: without scientists. The article focused on the U.S. Defense Advanced Research Projects Agency (DARPA) program called ‘Big Mechanism”, a $45 million effort to develop computer algorithms which read scientific journal papers with ultimate goal of extracting enough information to design hypotheses and the next set of experiments,

all without human input.

The head of the project, artificial intelligence expert Paul Cohen, says the overall goal is to help scientists cope with the complexity with massive amounts of information. As Paul Cohen stated for the article:

“‘

Just when we need to understand highly connected systems as systems,

our research methods force us to focus on little parts.

                                                                                                                                                                                                               ”

The Big Mechanisms project aims to design computer algorithms to critically read journal articles, much as scientists will, to determine what and how the information contributes to the knowledge base.

As a proof of concept DARPA is attempting to model Ras-mutation driven cancers using previously published literature in three main steps:

1. Natural Language Processing: Machines read literature on cancer pathways and convert information to computational semantics and meaning

One team is focused on extracting details on experimental procedures, using the mining of certain phraseology to determine the paper’s worth (for example using phrases like ‘we suggest’ or ‘suggests a role in’ might be considered weak versus ‘we prove’ or ‘provide evidence’ might be identified by the program as worthwhile articles to curate). Another team led by a computational linguistics expert will design systems to map the meanings of sentences.

2. Integrate each piece of knowledge into a computational model to represent the Ras pathway on oncogenesis.
3. Produce hypotheses and propose experiments based on knowledge base which can be experimentally verified in the laboratory.

The Human no Longer Needed?: Not So Fast, my Friend!

The problems the DARPA research teams are encountering namely:

• Need for data verification
• Text mining and curation strategies
• Incomplete knowledge base (past, current and future)
• Molecular biology not necessarily “requires casual inference” as other fields do

Verification

Notice this verification step (step 3) requires physical lab work as does all other ‘omics strategies and other computational biology projects. As with high-throughput microarray screens, a verification is needed usually in the form of conducting qPCR or interesting genes are validated in a phenotypical (expression) system. In addition, there has been an ongoing issue surrounding the validity and reproducibility of some research studies and data.

See Importance of Funding Replication Studies: NIH on Credibility of Basic Biomedical Studies

Therefore as DARPA attempts to recreate the Ras pathway from published literature and suggest new pathways/interactions, it will be necessary to experimentally validate certain points (protein interactions or modification events, signaling events) in order to validate their computer model.

Text-Mining and Curation Strategies

The Big Mechanism Project is starting very small; this reflects some of the challenges in scale of this project. Researchers were only given six paragraph long passages and a rudimentary model of the Ras pathway in cancer and then asked to automate a text mining strategy to extract as much useful information. Unfortunately this strategy could be fraught with issues frequently occurred in the biocuration community namely:

Manual or automated curation of scientific literature?

Biocurators, the scientists who painstakingly sort through the voluminous scientific journal to extract and then organize relevant data into accessible databases, have debated whether manual, automated, or a combination of both curation methods [2] achieves the highest accuracy for extracting the information needed to enter in a database. Abigail Cabunoc, a lead developer for Ontario Institute for Cancer Research’s WormBase (a database of nematode genetics and biology) and Lead Developer at Mozilla Science Lab, noted, on her blog, on the lively debate on biocuration methodology at the Seventh International Biocuration Conference (#ISB2014) that the massive amounts of information will require a Herculaneum effort regardless of the methodology.

Although I will have a future post on the advantages/disadvantages and tools/methodologies of manual vs. automated curation, there is a great article on researchinformation.info “Extracting More Information from Scientific Literature” and also see “The Methodology of Curation for Scientific Research Findings” and “Power of Analogy: Curation in Music, Music Critique as a Curation and Curation of Medical Research Findings – A Comparison” for manual curation methodologies and A MOD(ern) perspective on literature curation for a nice workflow paper on the International Society for Biocuration site.

The Big Mechanism team decided on a full automated approach to text-mine their limited literature set for relevant information however was able to extract only 40% of relevant information from these six paragraphs to the given model. Although the investigators were happy with this percentage most biocurators, whether using a manual or automated method to extract information, would consider 40% a low success rate. Biocurators, regardless of method, have reported ability to extract 70-90% of relevant information from the whole literature (for example for Comparative Toxicogenomics Database)[3-5].

Incomplete Knowledge Base

In an earlier posting (actually was a press release for our first e-book) I had discussed the problem with the “data deluge” we are experiencing in scientific literature as well as the plethora of ‘omics experimental data which needs to be curated.

Tackling the problem of scientific and medical information overload

Figure. The number of papers listed in PubMed (disregarding reviews) during ten year periods have steadily increased from 1970.

Analyzing and sharing the vast amounts of scientific knowledge has never been so crucial to innovation in the medical field. The publication rate has steadily increased from the 70’s, with a 50% increase in the number of original research articles published from the 1990’s to the previous decade. This massive amount of biomedical and scientific information has presented the unique problem of an information overload, and the critical need for methodology and expertise to organize, curate, and disseminate this diverse information for scientists and clinicians. Dr. Larry Bernstein, President of Triplex Consulting and previously chief of pathology at New York’s Methodist Hospital, concurs that “the academic pressures to publish, and the breakdown of knowledge into “silos”, has contributed to this knowledge explosion and although the literature is now online and edited, much of this information is out of reach to the very brightest clinicians.”

Traditionally, organization of biomedical information has been the realm of the literature review, but most reviews are performed years after discoveries are made and, given the rapid pace of new discoveries, this is appearing to be an outdated model. In addition, most medical searches are dependent on keywords, hence adding more complexity to the investigator in finding the material they require. Third, medical researchers and professionals are recognizing the need to converse with each other, in real-time, on the impact new discoveries may have on their research and clinical practice.

These issues require a people-based strategy, having expertise in a diverse and cross-integrative number of medical topics to provide the in-depth understanding of the current research and challenges in each field as well as providing a more conceptual-based search platform. To address this need, human intermediaries, known as scientific curators, are needed to narrow down the information and provide critical context and analysis of medical and scientific information in an interactive manner powered by web 2.0 with curators referred to as the “researcher 2.0”. This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Yaneer Bar-Yam of the New England Complex Systems Institute was not confident that using details from past knowledge could produce adequate roadmaps for future experimentation and noted for the article, “ “The expectation that the accumulation of details will tell us what we want to know is not well justified.”

In a recent post I had curated findings from four lung cancer omics studies and presented some graphic on bioinformatic analysis of the novel genetic mutations resulting from these studies (see link below)

Multiple Lung Cancer Genomic Projects Suggest New Targets, Research Directions for

Non-Small Cell Lung Cancer

which showed, that while multiple genetic mutations and related pathway ontologies were well documented in the lung cancer literature there existed many significant genetic mutations and pathways identified in the genomic studies but little literature attributed to these lung cancer-relevant mutations.

  This ‘literomics’ analysis reveals a large gap between our knowledge base and the data resulting from large translational ‘omic’ studies.

A ‘literomics’ approach focuses on what we don NOT know about genes, proteins, and their associated pathways while a text-mining machine learning algorithm focuses on building a knowledge base to determine the next line of research or what needs to be measured. Using each approach can give us different perspectives on ‘omics data.

Deriving Casual Inference

Ras is one of the best studied and characterized oncogenes and the mechanisms behind Ras-driven oncogenenis is highly understood.   This, according to computational biologist Larry Hunt of Smart Information Flow Technologies makes Ras a great starting point for the Big Mechanism project. As he states,” Molecular biology is a good place to try (developing a machine learning algorithm) because it’s an area in which common sense plays a minor role”.

Even though some may think the project wouldn’t be able to tackle on other mechanisms which involve epigenetic factors UCLA’s expert in causality Judea Pearl, Ph.D. (head of UCLA Cognitive Systems Lab) feels it is possible for machine learning to bridge this gap. As summarized from his lecture at Microsoft:

“The development of graphical models and the logic of counterfactuals have had a marked effect on the way scientists treat problems involving cause-effect relationships. Practical problems requiring causal information, which long were regarded as either metaphysical or unmanageable can now be solved using elementary mathematics. Moreover, problems that were thought to be purely statistical, are beginning to benefit from analyzing their causal roots.”

According to him first

1) articulate assumptions

2) define research question in counter-inference terms

Then it is possible to design an inference system using calculus that tells the investigator what they need to measure.

To watch a video of Dr. Judea Pearl’s April 2013 lecture at Microsoft Research Machine Learning Summit 2013 (“The Mathematics of Causal Inference: with Reflections on Machine Learning”), click here.

The key for the Big Mechansism Project may me be in correcting for the variables among studies, in essence building a models system which may not rely on fully controlled conditions. Dr. Peter Spirtes from Carnegie Mellon University in Pittsburgh, PA is developing a project called the TETRAD project with two goals: 1) to specify and prove under what conditions it is possible to reliably infer causal relationships from background knowledge and statistical data not obtained under fully controlled conditions 2) develop, analyze, implement, test and apply practical, provably correct computer programs for inferring causal structure under conditions where this is possible.

In summary such projects and algorithms will provide investigators the what, and possibly the how should be measured.

So for now it seems we are still needed.

References

1. You J: Artificial intelligence. DARPA sets out to automate research. Science 2015, 347(6221):465.
2. Biocuration 2014: Battle of the New Curation Methods [http://blog.abigailcabunoc.com/biocuration-2014-battle-of-the-new-curation-methods]
3. Davis AP, Johnson RJ, Lennon-Hopkins K, Sciaky D, Rosenstein MC, Wiegers TC, Mattingly CJ: Targeted journal curation as a method to improve data currency at the Comparative Toxicogenomics Database. Database : the journal of biological databases and curation 2012, 2012:bas051.
4. Wu CH, Arighi CN, Cohen KB, Hirschman L, Krallinger M, Lu Z, Mattingly C, Valencia A, Wiegers TC, John Wilbur W: BioCreative-2012 virtual issue. Database : the journal of biological databases and curation 2012, 2012:bas049.
5. Wiegers TC, Davis AP, Mattingly CJ: Collaborative biocuration–text-mining development task for document prioritization for curation. Database : the journal of biological databases and curation 2012, 2012:bas037.

Other posts on this site on include: Artificial Intelligence, Curation Methodology, Philosophy of Science

Inevitability of Curation: Scientific Publishing moves to embrace Open Data, Libraries and Researchers are trying to keep up

A Brief Curation of Proteomics, Metabolomics, and Metabolism

The Methodology of Curation for Scientific Research Findings

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

The growing importance of content curation

Data Curation is for Big Data what Data Integration is for Small Data

Cardiovascular Original Research: Cases in Methodology Design for Content Co-Curation The Art of Scientific & Medical Curation

Exploring the Impact of Content Curation on Business Goals in 2013

Power of Analogy: Curation in Music, Music Critique as a Curation and Curation of Medical Research Findings – A Comparison

conceived: NEW Definition for Co-Curation in Medical Research

Reconstructed Science Communication for Open Access Online Scientific Curation

Search Results for ‘artificial intelligence’

 The Simple Pictures Artificial Intelligence Still Can’t Recognize

Data Scientist on a Quest to Turn Computers Into Doctors

Vinod Khosla: “20% doctor included”: speculations & musings of a technology optimist or “Technology will replace 80% of what doctors do”

Where has reason gone?

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Twitter is Becoming a Powerful Tool in Science and Medicine

Posted in Academic Publishing, Clinical Diagnostics, Computational Biology/Systems and Bioinformatics, Conference Coverage with Social Media, Curation, Curation methodology, Digital HealthCare – biotech & internet joint ventures, Drug Toxicity, Evolutionary cognition, FDA, FDA Regulatory Affairs, Global Partnering & Biotech Investment, Health Economics and Outcomes Research, HealthCare IT, Interviews with Scientific Leaders, Investment in Technological Breakthrough, Personal Health Applications: Tech Innovations serves HealhCare, Pharmaceutical Analytics, Pharmaceutical Discovery, Pharmacologic toxicities, Regulated Clinical Trials: Design, Methods, Components and IRB related issues, Scientific & Biotech Conferences: Press Coverage, tagged #mobilehealth, #science2_0, @science 2_0, Adverse event, Aviva Lev-Ari, Cancer - General, cancer patient management, Clinical trial, Conditions and Diseases, Conference Coverage with Social Media, Content Curation, Curation methodology, Food and Drug Administration, health, https://twitter.com/#!/pharma_BI, medical devices and digital health, medicine, mobile applications, patient outcomes, patient-interaction, Pharmacovigilance, research, science, Social media, Social network, Twitter on November 6, 2014| 1 Comment »

Twitter is Becoming a Powerful Tool in Science and Medicine

 Curator: Stephen J. Williams, Ph.D.

Updated 4/2016

Twitter.com

A recent Science article (Who are the science stars of Twitter?; Sept. 19, 2014) reported the top 50 scientists followed on Twitter. However, the article tended to focus on the use of Twitter as a means to develop popularity, a sort of “Science Kardashian” as they coined it. So the writers at Science developed a “Kardashian Index (K-Index) to determine scientists following and popularity on Twitter.

Now as much buzz Kim Kardashian or a Perez Hilton get on social media, their purpose is solely for entertainment and publicity purposes, the Science sort of fell flat in that it focused mainly on the use of Twitter as a metric for either promotional or public outreach purposes. A notable scientist was mentioned in the article, using Twitter feed to gauge the receptiveness of his presentation. In addition, relying on Twitter for effective public discourse of science is problematic as:

• Twitter feeds are rapidly updated and older feeds quickly get buried within the “Twittersphere” = LIMITED EXPOSURE TIMEFRAME
• Short feeds may not provide the access to appropriate and understandable scientific information (The Science Communication Trap) which is explained in The Art of Communicating Science: traps, tips and tasks for the modern-day scientist. “The challenge of clearly communicating the intended scientific message to the public is not insurmountable but requires an understanding of what works and what does not work.” – from Heidi Roop, G.-Martinez-Mendez and K. Mills

However, as highlighted below, Twitter, and other social media platforms are being used in creative ways to enhance the research, medical, and bio investment collaborative, beyond a simple news-feed.  And the power of Twitter can be attributed to two simple features

1. Ability to organize – through use of the hashtag (#) and handle (@), Twitter assists in the very important task of organizing, indexing, and ANNOTATING content and conversations. A very great article on Why the Hashtag in Probably the Most Powerful Tool on Twitter by Vanessa Doctor explains how hashtags and # search may be as popular as standard web-based browser search. Thorough annotation is crucial for any curation process, which are usually in the form of database tags or keywords. The use of # and @ allows curators to quickly find, index and relate disparate databases to link annotated information together. The discipline of scientific curation requires annotation to assist in the digital preservation, organization, indexing, and access of data and scientific & medical literature. For a description of scientific curation methodologies please see the following links:

Please read the following articles on CURATION

The Methodology of Curation for Scientific Research Findings

Power of Analogy: Curation in Music, Music Critique as a Curation and Curation of Medical Research Findings – A Comparison

Science and Curation: The New Practice of Web 2.0

2. Information Analytics –

Multiple analytic software packages have been made available to analyze information surrounding Twitter feeds, including Twitter feeds from #chat channels one can set up to cover a meeting, product launch etc.. Some of these tools include:

Twitter Analytics – measures metrics surrounding Tweets including retweets, impressions, engagement, follow rate, …

Twitter Analytics – Hashtags.org – determine most impactful # for your Tweets For example, meeting coverage of bioinvestment conferences or startup presentations using #startup generates automatic retweeting by Startup tweetbot @StartupTweetSF.

 

3. Tweet Sentiment Analytics

Examples of Twitter Use

A. Scientific Meeting Coverage

• The 2013 Society of Teachers of Family Medicine Annual Spring Conference. integrated social media with meeting proceedings to enhance conference engagement

In a paper entitled Twitter Use at a Family Medicine Conference: Analyzing #STFM13 authors Ranit Mishori, MD, Frendan Levy, MD, and Benjamin Donvan analyzed the public tweets from the 2013 Society of Teachers of Family Medicine (STFM) conference bearing the meeting-specific hashtag #STFM13. Thirteen percent of conference attendees (181 users) used the #STFM13 to share their thoughts on the meeting (1,818 total tweets) showing a desire for social media interaction at conferences but suggesting growth potential in this area. As we have also seen, the heaviest volume of conference-tweets originated from a small number of Twitter users however most tweets were related to session content.

However, as the authors note, although it is easy to measure common metrics such as number of tweets and retweets, determining quality of engagement from tweets would be important for gauging the value of Twitter-based social-media coverage of medical conferences.

Thea authors compared their results with similar analytics generated by the HealthCare Hashtag Project, a project and database of medically-related hashtag use, coordinated and maintained by the company Symplur.  Symplur’s database includes medical and scientific conference Twitter coverage but also Twitter usuage related to patient care. In this case the database was used to compare meeting tweets and hashtag use with the 2012 STFM conference.

These are some of the published journal articles that have employed Symplur (www.symplur.com) data in their research of Twitter usage in medical conferences.

• The impact of social media on a major international emergency medicine conference.
  Neill, A., Cronin, J. J., Brannigan, D., O’Sullivan, R., & Cadogan, M. (2013). The impact of social media on a major international emergency medicine conference. Emergency Medicine Journal, emermed-2012. Chicago
• Social media in radiology: early trends in Twitter microblogging at radiology’s largest international meeting.
  Hawkins, C. M., Duszak, R., & Rawson, J. V. (2014). Social Media in Radiology: Early Trends in Twitter Microblogging at Radiology’s Largest International Meeting. Journal of the American College of Radiology, 11(4), 387-390.
• International Urology Journal Club via Twitter: 12-Month Experience.
  Thangasamy, I. A., Leveridge, M., Davies, B. J., Finelli, A., Stork, B., & Woo, H. H. (2014). International Urology Journal Club via Twitter: 12-Month Experience. European urology.
• Use of social media in urology: data from the American Urological Association (AUA).
  Loeb, S., Bayne, C. E., Frey, C., Davies, B. J., Averch, T. D., Woo, H. H., … & Eggener, S. E. (2014). Use of social media in urology: data from the American Urological Association (AUA). BJU international, 113(6), 993-998. Chicago.
• Social media: A tool to spread information: A case study analysis of Twitter conversation at the Cardiac Society of Australia & New Zealand 61st Annual Scientific Meeting 2013.
  Ferguson, C., Inglis, S. C., Newton, P. J., Cripps, P. J., Macdonald, P. S., & Davidson, P. M. (2014). Social media: A tool to spread information: A case study analysis of Twitter conversation at the Cardiac Society of Australia & New Zealand 61st Annual Scientific Meeting 2013. Collegian.

• Here, at Leaders in Pharmaceutical Business Intelligence (LBPI) we have integrated our web site, Twitter handle (@pharma_BI), and meeting specific hashtags, with a unique methodology, to monitor and measure meeting participant engagement for various international meetings (please see our Press Coverage section of our site for more information). These meetings included the 2nd Annual Sachs Associates Cancer BioInvestment & Partnering Forum and the 14^th Annual Sachs Associates Global Forum.

B. Twitter Usage for Patient Care and Engagement

Although the desire of patients to use and interact with their physicians over social media is increasing, along with increasing health-related social media platforms and applications, there are certain obstacles to patient-health provider social media interaction, including lack of regulatory framework as well as database and security issues. Some of the successes and issues of social media and healthcare are discussed in the post Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.

However there is also a concern if social media truly engages the patient and improves patient education. In a study of Twitter communications by breast cancer patients Tweeting about breast cancer, authors noticed Tweeting was a singular event. The majority of tweets did not promote any specific preventive behavior. The authors concluded “Twitter is being used mostly as a one-way communication tool.” (Using Twitter for breast cancer prevention: an analysis of breast cancer awareness month. Thackeray R¹, Burton SH, Giraud-Carrier C, Rollins S, Draper CR. BMC Cancer. 2013;13:508).

In addition a new poll by Harris Interactive and HealthDay shows one third of patients want some mobile interaction with their physicians.

Some papers cited in Symplur’s HealthCare Hashtag Project database on patient use of Twitter include:

• e-Patients in Twitter Hashtag Communities.
  Harmel M, Young K. e-Patients in twitter hashtag communities . J Participat Med. 2013 Jan 16; 5:e22
• Nurses and Twitter: The good, the bad, and the reluctant.
  Wilson, R., Ranse, J., Cashin, A., & McNamara, P. (2013). Nurses and Twitter: The good, the bad, and the reluctant. Collegian. Chicago.
• Using social media for continuous professional development.
  Moorley, C., & Chinn, T. (2014). Using social media for continuous professional development. Journal of advanced nursing.
• Networking opportunities for learning disability nurses.
  Abdulla, S., Marsden, D., Wilson, S., & Parker, M. (2013). Networking opportunities for learning disability nurses: Samuel Abdulla and colleagues explain why social media offer professionals new opportunities for information sharing, discussion and peer support. Learning Disability Practice, 16(5), 30-32.
• Using Twitter for professional knowledge.
  Kraft, M. A. (2013). Using Twitter for professional knowledge. Journal of the European Association for Health Information and Libraries, 9(4), 10.
• A Study on the Influence of Semantics on the Analysis of Micro-blog Tags in the Medical Domain.
  Vicient, C., & Moreno, A. (2013). A Study on the Influence of Semantics on the Analysis of Micro-blog Tags in the Medical Domain. In Availability, Reliability, and Security in Information Systems and HCI (pp. 446-459). Springer Berlin Heidelberg.
• Twitter for Public Health: An Open-source Data Solution.
  Nghiema, S., Mehtab, P., & Taoc, L. Twitter for Public Health: An Open-source Data Solution. Chicago.

C. Twitter Use in Pharmacovigilance to Monitor Adverse Events

Pharmacovigilance is the systematic detection, reporting, collecting, and monitoring of adverse events pre- and post-market of a therapeutic intervention (drug, device, modality e.g.). In a Cutting Edge Information Study, 56% of pharma companies databases are an adverse event channel and more companies are turning to social media to track adverse events (in Pharmacovigilance Teams Turn to Technology for Adverse Event Reporting Needs). In addition there have been many reports (see Digital Drug Safety Surveillance: Monitoring Pharmaceutical Products in Twitter) that show patients are frequently tweeting about their adverse events.

There have been concerns with using Twitter and social media to monitor for adverse events. For example FDA funded a study where a team of researchers from Harvard Medical School and other academic centers examined more than 60,000 tweets, of which 4,401 were manually categorized as resembling adverse events and compared with the FDA pharmacovigilance databases. Problems associated with such social media strategy were inability to obtain extra, needed information from patients and difficulty in separating the relevant Tweets from irrelevant chatter.  The UK has launched a similar program called WEB-RADR to determine if monitoring #drug_reaction could be useful for monitoring adverse events. Many researchers have found the adverse-event related tweets “noisy” due to varied language but had noticed many people do understand some principles of causation including when adverse event subsides after discontinuing the drug.

However Dr. Clark Freifeld, Ph.D., from Boston University and founder of the startup Epidemico, feels his company has the algorithms that can separate out the true adverse events from the junk. According to their web site, their algorithm has high accuracy when compared to the FDA database. Dr. Freifeld admits that Twitter use for pharmacovigilance purposes is probably a starting point for further follow-up, as each patient needs to fill out the four-page forms required for data entry into the FDA database.

D. Use of Twitter in Big Data Analytics

Published on Aug 28, 2012

http://blogs.ischool.berkeley.edu/i29…

Course: Information 290. Analyzing Big Data with Twitter
School of Information
UC Berkeley

Lecture 1: August 23, 2012

Course description:
How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered.

This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.

Other posts on this site on USE OF SOCIAL MEDIA AND TWITTER IN HEALTHCARE and Conference Coverage include:

Methodology for Conference Coverage using Social Media: 2014 MassBio Annual Meeting 4/3 – 4/4 2014, Royal Sonesta Hotel, Cambridge, MA

Strategy for Event Joint Promotion: 14th ANNUAL BIOTECH IN EUROPE FORUM For Global Partnering & Investment 9/30 – 10/1/2014 • Congress Center Basel – SACHS Associates, London

REAL TIME Cancer Conference Coverage: A Novel Methodology for Authentic Reporting on Presentations and Discussions launched via Twitter.com @ The 2nd ANNUAL Sachs Cancer Bio Partnering & Investment Forum in Drug Development, 19th March 2014 • New York Academy of Sciences • USA

PCCI’s 7th Annual Roundtable “Crowdfunding for Life Sciences: A Bridge Over Troubled Waters?” May 12 2014 Embassy Suites Hotel, Chesterbrook PA 6:00-9:30 PM

CRISPR-Cas9 Discovery and Development of Programmable Genome Engineering – Gabbay Award Lectures in Biotechnology and Medicine – Hosted by Rosenstiel Basic Medical Sciences Research Center, 10/27/14 3:30PM Brandeis University, Gerstenzang 121

Tweeting on 14th ANNUAL BIOTECH IN EUROPE FORUM For Global Partnering & Investment 9/30 – 10/1/2014 • Congress Center Basel – SACHS Associates, London

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

Statistical Analysis of Tweet Feeds from the 14th ANNUAL BIOTECH IN EUROPE FORUM For Global Partnering & Investment 9/30 – 10/1/2014 • Congress Center Basel – SACHS Associates, London

1st Pitch Life Science- Philadelphia- What VCs Really Think of your Pitch

What VCs Think about Your Pitch? Panel Summary of 1st Pitch Life Science Philly

How Social Media, Mobile Are Playing a Bigger Part in Healthcare

Can Mobile Health Apps Improve Oral-Chemotherapy Adherence? The Benefit of Gamification.

Medical Applications and FDA regulation of Sensor-enabled Mobile Devices: Apple and the Digital Health Devices Market

E-Medical Records Get A Mobile, Open-Sourced Overhaul By White House Health Design Challenge Winners

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