Archive for the ‘LPBI Management’ Category

Science Has A Systemic Problem, Not an Innovation Problem

Curator: Stephen J. Williams, Ph.D.

    A recent email, asking me to submit a survey, got me thinking about the malaise that scientists and industry professionals frequently bemoan: that innovation has been stymied for some reason and all sorts of convuluted processes must be altered to spur this mythical void of great new discoveries…..  and it got me thinking about our current state of science, and what is the perceived issue… and if this desert of innovation actually exists or is more a fundamental problem which we have created.

The email was from an NIH committee asking for opinions on recreating the grant review process …. now this on the same day someone complained to me about a shoddy and perplexing grant review they received.

The following email, which was sent out to multiple researchers, involved in either NIH grant review on both sides, as well as those who had been involved in previous questionnaires and studies on grant review and bias.  The email asked for researchers to fill out a survey on the grant review process, and how to best change it to increase innovation of ideas as well as inclusivity.  In recent years, there have been multiple survey requests on these matters, with multiple confusing procedural changes to grant format and content requirements, adding more administrative burden to scientists.

The email from Center for Scientific Review (one of the divisions a grant will go to before review {they set up review study sections and decide what section a grant should be  assigned to} was as follows:

Update on Simplifying Review Criteria: A Request for Information


NIH has issued a request for information (RFI) seeking feedback on revising and simplifying the peer review framework for research project grant applications. The goal of this effort is to facilitate the mission of scientific peer review – identification of the strongest, highest-impact research. The proposed changes will allow peer reviewers to focus on scientific merit by evaluating 1) the scientific impact, research rigor, and feasibility of the proposed research without the distraction of administrative questions and 2) whether or not appropriate expertise and resources are available to conduct the research, thus mitigating the undue influence of the reputation of the institution or investigator.

Currently, applications for research project grants (RPGs, such as R01s, R03s, R15s, R21s, R34s) are evaluated based on five scored criteria: Significance, Investigators, Innovation, Approach, and Environment (derived from NIH peer review regulations 42 C.F.R. Part 52h.8; see Definitions of Criteria and Considerations for Research Project Grant Critiques for more detail) and a number of additional review criteria such as Human Subject Protections.

NIH gathered input from the community to identify potential revisions to the review framework. Given longstanding and often-heard concerns from diverse groups, CSR decided to form two working groups to the CSR Advisory Council—one on non-clinical trials and one on clinical trials. To inform these groups, CSR published a Review Matters blog, which was cross-posted on the Office of Extramural Research blog, Open Mike. The blog received more than 9,000 views by unique individuals and over 400 comments. Interim recommendations were presented to the CSR Advisory Council in a public forum (March 2020 videoslides; March 2021 videoslides). Final recommendations from the CSRAC (report) were considered by the major extramural committees of the NIH that included leadership from across NIH institutes and centers. Additional background information can be found here. This process produced many modifications and the final proposal presented below. Discussions are underway to incorporate consideration of a Plan for Enhancing Diverse Perspectives (PEDP) and rigorous review of clinical trials RPGs (~10% of RPGs are clinical trials) within the proposed framework.

Simplified Review Criteria

NIH proposes to reorganize the five review criteria into three factors, with Factors 1 and 2 receiving a numerical score. Reviewers will be instructed to consider all three factors (Factors 1, 2 and 3) in arriving at their Overall Impact Score (scored 1-9), reflecting the overall scientific and technical merit of the application.

  • Factor 1: Importance of the Research (Significance, Innovation), numerical score (1-9)
  • Factor 2: Rigor and Feasibility (Approach), numerical score (1-9)
  • Factor 3: Expertise and Resources (Investigator, Environment), assessed and considered in the Overall Impact Score, but not individually scored

Within Factor 3 (Expertise and Resources), Investigator and Environment will be assessed in the context of the research proposed. Investigator(s) will be rated as “fully capable” or “additional expertise/capability needed”. Environment will be rated as “appropriate” or “additional resources needed.” If a need for additional expertise or resources is identified, written justification must be provided. Detailed descriptions of the three factors can be found here.

Now looking at some of the Comments were very illuminating:

I strongly support streamlining the five current main review criteria into three, and the present five additional criteria into two. This will bring clarity to applicants and reduce the workload on both applicants and reviewers. Blinding reviewers to the applicants’ identities and institutions would be a helpful next step, and would do much to reduce the “rich-getting-richer” / “good ole girls and good ole boys” / “big science” elitism that plagues the present review system, wherein pedigree and connections often outweigh substance and creativity.

I support the proposed changes. The shift away from “innovation” will help reduce the tendency to create hype around a proposed research direction. The shift away from Investigator and Environment assessments will help reduce bias toward already funded investigators in large well-known institutions.

As a reviewer for 5 years, I believe that the proposed changes are a step in the right direction, refocusing the review on whether the science SHOULD be done and whether it CAN BE DONE WELL, while eliminating burdensome and unhelpful sections of review that are better handled administratively. I particularly believe that the de-emphasis of innovation (which typically focuses on technical innovation) will improve evaluation of the overall science, and de-emphasis of review of minor technical details will, if implemented correctly, reduce the “downward pull” on scores for approach. The above comments reference blinded reviews, but I did not see this in the proposed recommendations. I do not believe this is a good idea for several reasons: 1) Blinding of the applicant and institution is not likely feasible for many of the reasons others have described (e.g., self-referencing of prior work), 2) Blinding would eliminate the potential to review investigators’ biosketches and budget justifications, which are critically important in review, 3) Making review blinded would make determination of conflicts of interest harder to identify and avoid, 4) Evaluation of “Investigator and Environment” would be nearly impossible.

Most of the Comments were in favor of the proposed changes, however many admitted that it adds additional confusion on top of many administrative changes to formats and content of grant sections.

Being a Stephen Covey devotee, and just have listened to  The Four Principles of Execution, it became more apparent that issues that hinder many great ideas coming into fruition, especially in science, is a result of these systemic or problems in the process, not at the level of individual researchers or small companies trying to get their innovations funded or noticed.  In summary, Dr. Covey states most issues related to the success of any initiative is NOT in the strategic planning, but in the failure to adhere to a few EXECUTION principles.  Primary to these failures of strategic plans is lack of accounting of what Dr. Covey calls the ‘whirlwind’, or those important but recurring tasks that take us away from achieving the wildly important goals.  In addition, lack of  determining lead and lag measures of success hinder such plans.

In this case a lag measure in INNOVATION.  It appears we have created such a whirlwind and focus on lag measures that we are incapable of translating great discoveries into INNOVATION.

In the following post, I will focus on issues relating to Open Access, publishing and dissemination of scientific discovery may be costing us TIME to INNOVATION.  And it appears that there are systemic reasons why we appear stuck in a rut, so to speak.

The first indication is from a paper published by Johan Chu and James Evans in 2021 in PNAS:


Slowed canonical progress in large fields of science

Chu JSG, Evans JA. Slowed canonical progress in large fields of science. Proc Natl Acad Sci U S A. 2021 Oct 12;118(41):e2021636118. doi: 10.1073/pnas.2021636118. PMID: 34607941; PMCID: PMC8522281



In many academic fields, the number of papers published each year has increased significantly over time. Policy measures aim to increase the quantity of scientists, research funding, and scientific output, which is measured by the number of papers produced. These quantitative metrics determine the career trajectories of scholars and evaluations of academic departments, institutions, and nations. Whether and how these increases in the numbers of scientists and papers translate into advances in knowledge is unclear, however. Here, we first lay out a theoretical argument for why too many papers published each year in a field can lead to stagnation rather than advance. The deluge of new papers may deprive reviewers and readers the cognitive slack required to fully recognize and understand novel ideas. Competition among many new ideas may prevent the gradual accumulation of focused attention on a promising new idea. Then, we show data supporting the predictions of this theory. When the number of papers published per year in a scientific field grows large, citations flow disproportionately to already well-cited papers; the list of most-cited papers ossifies; new papers are unlikely to ever become highly cited, and when they do, it is not through a gradual, cumulative process of attention gathering; and newly published papers become unlikely to disrupt existing work. These findings suggest that the progress of large scientific fields may be slowed, trapped in existing canon. Policy measures shifting how scientific work is produced, disseminated, consumed, and rewarded may be called for to push fields into new, more fertile areas of study.

So the Summary of this paper is

  • The authors examined 1.8 billion citations among 90 million papers over 241 subjects
  • found the corpus of papers do not lead to turnover of new ideas in a field, but rather the ossification or entrenchment of canonical (or older ideas)
  • this is mainly due to older paper cited more frequently than new papers with new ideas, potentially because authors are trying to get their own papers cited more frequently for funding and exposure purposes
  • The authors suggest that “fundamental progress may be stymied if quantitative growth of scientific endeavors is not balanced by structures fostering disruptive scholarship and focusing attention of novel ideas”

The authors note that, in most cases, science policy reinforces this “more is better” philosophy”,  where metrics of publication productivity are either number of publications or impact measured by citation rankings.  However, using an analysis of citation changes occurring in large versus smaller fields, it becomes apparent that this process is favoring the older, more established papers and a recirculating of older canonical ideas.

“Rather than resulting in faster turnover of field paradigms, the massive amounts of new publications entrenches the ideas of top-cited papers.”  New ideas are pushed down to the bottom of the citation list and potentially lost in the literature.  The authors suggest that this problem will intensify as the “annual mass” of new publications in each field grows, especially in large fields.  This issue is exacerbated by the deluge on new online ‘open access’ journals, in which authors would focus on citing the more highly cited literature. 

We maybe at a critical junction, where if many papers are published in a short time, new ideas will not be considered as carefully as the older ideas.  In addition,

with proliferation of journals and the blurring of journal hierarchies due to online articles-level access can exacerbate this problem

As a counterpoint, the authors do note that even though many molecular biology highly cited articles were done in 1976, there has been extremely much innovation since then however it may take a lot more in experiments and money to gain the level of citations that those papers produced, and hence a lower scientific productivity.

This issue is seen in the field of economics as well

Ellison, Glenn. “Is peer review in decline?” Economic Inquiry, vol. 49, no. 3, July 2011, pp. 635+. Gale Academic OneFile, link.gale.com/apps/doc/A261386330/AONE?u=temple_main&sid=bookmark-AONE&xid=f5891002. Accessed 12 Dec. 2022.


Over the past decade, there has been a decline in the fraction of papers in top economics journals written by economists from the highest-ranked economics departments. This paper documents this fact and uses additional data on publications and citations to assess various potential explanations. Several observations are consistent with the hypothesis that the Internet improves the ability of high-profile authors to disseminate their research without going through the traditional peer-review process. (JEL A14, 030)

The facts part of this paper documents two main facts:

1. Economists in top-ranked departments now publish very few papers in top field journals. There is a marked decline in such publications between the early 1990s and early 2000s.

2. Comparing the early 2000s with the early 1990s, there is a decline in both the absolute number of papers and the share of papers in the top general interest journals written by Harvard economics department faculty.

Although the second fact just concerns one department, I see it as potentially important to understanding what is happening because it comes at a time when Harvard is widely regarded (I believe correctly) as having ascended to the top position in the profession.

The “decline-of-peer-review” theory I allude to in the title is that the necessity of going through the peer-review process has lessened for high-status authors: in the old days peer-reviewed journals were by far the most effective means of reaching readers, whereas with the growth of the Internet high-status authors can now post papers online and exploit their reputation to attract readers.

Many alternate explanations are possible. I focus on four theories: the decline-in-peer-review theory and three alternatives.

1. The trends could be a consequence of top-school authors’ being crowded out of the top journals by other researchers. Several such stories have an optimistic message, for example, there is more talent entering the profession, old pro-elite biases are being broken down, more schools are encouraging faculty to do cutting-edge research, and the Internet is enabling more cutting-edge research by breaking down informational barriers that had hampered researchers outside the top schools. (2)

2. The trends could be a consequence of the growth of revisions at economics journals discussed in Ellison (2002a, 2002b). In this more pessimistic theory, highly productive researchers must abandon some projects and/or seek out faster outlets to conserve the time now required to publish their most important works.

3. The trends could simply reflect that field journals have declined in quality in some relative sense and become a less attractive place to publish. This theory is meant to encompass also the rise of new journals, which is not obviously desirable or undesirable.

The majority of this paper is devoted to examining various data sources that provide additional details about how economics publishing has changed over the past decade. These are intended both to sharpen understanding of the facts to be explained and to provide tests of auxiliary predictions of the theories. Two main sources of information are used: data on publications and data on citations. The publication data include department-level counts of publications in various additional journals, an individual-level dataset containing records of publications in a subset of journals for thousands of economists, and a very small dataset containing complete data on a few authors’ publication records. The citation data include citations at the paper level for 9,000 published papers and less well-matched data that is used to construct measures of citations to authors’ unpublished works, to departments as a whole, and to various journals.

Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship

Josh Angrist, Pierre Azoulay, Glenn Ellison, Ryan Hill, Susan Feng Lu. Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship.


VOL. 58, NO. 1, MARCH 2020

(pp. 3-52)

So if innovation is there but it may be buried under the massive amount of heavily cited older literature, do we see evidence of this in other fields like medicine?

Why Isn’t Innovation Helping Reduce Health Care Costs?


National health care expenditures (NHEs) in the United States continue to grow at rates outpacing the broader economy: Inflation- and population-adjusted NHEs have increased 1.6 percent faster than the gross domestic product (GDP) between 1990 and 2018. US national health expenditure growth as a share of GDP far outpaces comparable nations in the Organization for Economic Cooperation and Development (17.2 versus 8.9 percent).

Multiple recent analyses have proposed that growth in the prices and intensity of US health care services—rather than in utilization rates or demographic characteristics—is responsible for the disproportionate increases in NHEs relative to global counterparts. The consequences of ever-rising costs amid ubiquitous underinsurance in the US include price-induced deferral of care leading to excess morbidity relative to comparable nations.

These patterns exist despite a robust innovation ecosystem in US health care—implying that novel technologies, in isolation, are insufficient to bend the health care cost curve. Indeed, studies have documented that novel technologies directly increase expenditure growth.

Why is our prolific innovation ecosystem not helping reduce costs? The core issue relates to its apparent failure to enhance net productivity—the relative output generated per unit resource required. In this post, we decompose the concept of innovation to highlight situations in which inventions may not increase net productivity. We begin by describing how this issue has taken on increased urgency amid resource constraints magnified by the COVID-19 pandemic. In turn, we describe incentives for the pervasiveness of productivity-diminishing innovations. Finally, we provide recommendations to promote opportunities for low-cost innovation.



Net Productivity During The COVID-19 Pandemic

The issue of productivity-enhancing innovation is timely, as health care systems have been overwhelmed by COVID-19. Hospitals in Italy, New York City, and elsewhere have lacked adequate capital resources to care for patients with the disease, sufficient liquidity to invest in sorely needed resources, and enough staff to perform all of the necessary tasks.

The critical constraint in these settings is not technology: In fact, the most advanced technology required to routinely treat COVID-19—the mechanical ventilator—was invented nearly 100 years ago in response to polio (the so-called iron lung). Rather, the bottleneck relates to the total financial and human resources required to use the technology—the denominator of net productivity. The clinical implementation of ventilators has been illustrative: Health care workers are still required to operate ventilators on a nearly one-to-one basis, just like in the mid-twentieth century. 

High levels of resources required for implementation of health care technologies constrain the scalability of patient care—such as during respiratory disease outbreaks such as COVID-19. Thus, research to reduce health care costs is the same kind of research we urgently require to promote health care access for patients with COVID-19.

Types Of Innovation And Their Relationship To Expenditure Growth

The widespread use of novel medical technologies has been highlighted as a central driver of NHE growth in the US. We believe that the continued expansion of health care costs is largely the result of innovation that tends to have low productivity (exhibit 1). We argue that these archetypes—novel widgets tacked on to existing workflows to reinforce traditional care models—are exactly the wrong properties to reduce NHEs at the systemic level.

Exhibit 1: Relative productivity of innovation subtypes

Source: Authors’ analysis.

Content Versus Process Innovation

Content (also called technical) innovation refers to the creation of new widgets, such as biochemical agents, diagnostic tools, or therapeutic interventions. Contemporary examples of content innovation include specialty pharmaceuticalsmolecular diagnostics, and advanced interventions and imaging.

These may be contrasted with process innovations, which address the organized sequences of activities that implement content. Classically, these include clinical pathways and protocols. They can address the delivery of care for acute conditions, such as central line infections, sepsis, or natural disasters. Alternatively, they can target chronic conditions through initiatives such as team-based management of hypertension and hospital-at-home models for geriatric care. Other processes include hiring staffdelegating labor, and supply chain management.

Performance-Enhancing Versus Cost-Reducing Innovation

Performance-enhancing innovations frequently create incremental outcome gains in diagnostic characteristics, such as sensitivity or specificity, or in therapeutic characteristics, such as biomarkers for disease status. Their performance gains often lead to higher prices compared to existing alternatives.  

Performance-enhancing innovations can be compared to “non-inferior” innovations capable of achieving outcomes approximating those of existing alternatives, but at reduced cost. Industries outside of medicine, such as the computing industry, have relied heavily on the ability to reduce costs while retaining performance.

In health care though, this pattern of innovation is rare. Since passage of the 2010 “Biosimilars” Act aimed at stimulating non-inferior innovation and competition in therapeutics markets, only 17 agents have been approved, and only seven have made it to market. More than three-quarters of all drugs receiving new patents between 2005 and 2015 were “reissues,” meaning they had already been approved, and the new patent reflected changes to the previously approved formula. Meanwhile, the costs of approved drugs have increased over time, at rates between 4 percent and 7 percent annually.

Moreover, the preponderance of performance-enhancing diagnostic and therapeutic innovations tend to address narrow patient cohorts (such as rare diseases or cancer subtypes), with limited clear clinical utility in broader populations. For example, the recently approved eculizimab is a monoclonal antibody approved for paroxysmal nocturnal hemoglobinuria—which effects 1 in 10 million individuals. At the time of its launch, eculizimab was priced at more than $400,000 per year, making it the most expensive drug in modern history. For clinical populations with no available alternatives, drugs such as eculizimab may be cost-effective, pending society’s willingness to pay, and morally desirable, given a society’s values. But such drugs are certainly not cost-reducing.

Additive Versus Substitutive Innovation

Additive innovations are those that append to preexisting workflows, while substitutive innovations reconfigure preexisting workflows. In this way, additive innovations increase the use of precedent services, whereas substitutive innovations decrease precedent service use.

For example, previous analyses have found that novel imaging modalities are additive innovations, as they tend not to diminish use of preexisting modalities. Similarly, novel procedures tend to incompletely replace traditional procedures. In the case of therapeutics and devices, off-label uses in disease groups outside of the approved indication(s) can prompt innovation that is additive. This is especially true, given that off-label prescriptions classically occur after approved methods are exhausted.

Eculizimab once again provides an illustrative example. As of February 2019, the drug had been used for 39 indications (it had been approved for three of those, by that time), 69 percent of which lacked any form of evidence of real-world effectiveness. Meanwhile, the drug generated nearly $4 billion in sales in 2019. Again, these expenditures may be something for which society chooses to pay—but they are nonetheless additive, rather than substitutive.

Sustaining Versus Disruptive Innovation

Competitive market theory suggests that incumbents and disruptors innovate differently. Incumbents seek sustaining innovations capable of perpetuating their dominance, whereas disruptors pursue innovations capable of redefining traditional business models.

In health care, while disruptive innovations hold the potential to reduce overall health expenditures, often they run counter to the capabilities of market incumbents. For example, telemedicine can deliver care asynchronously, remotely, and virtually, but large-scale brick-and-mortar medical facilities invest enormous capital in the delivery of synchronous, in-house, in-person care (incentivized by facility fees).

The connection between incumbent business models and the innovation pipeline is particularly relevant given that 58 percent of total funding for biomedical research in the US is now derived from private entities, compared with 46 percent a decade prior. It follows that the growing influence of eminent private organizations may favor innovations supporting their market dominance—rather than innovations that are societally optimal.

Incentives And Repercussions Of High-Cost Innovation

Taken together, these observations suggest that innovation in health care is preferentially designed for revenue expansion rather than for cost reduction. While offering incremental improvements in patient outcomes, therefore creating theoretical value for society, these innovations rarely deliver incremental reductions in short- or long-term costs at the health system level.

For example, content-based, performance-enhancing, additive, sustaining innovations tend to add layers of complexity to the health care system—which in turn require additional administration to manage. The net result is employment growth in excess of outcome improvement, leading to productivity losses. This gap leads to continuously increasing overall expenditures in turn passed along to payers and consumers.

Nonetheless, high-cost innovations are incentivized across health care stakeholders (exhibit 2). From the supply side of innovation, for academic researchers, “breakthrough” and “groundbreaking” innovations constitute the basis for career advancement via funding and tenure. This is despite stakeholders’ frequent inability to generalize early successes to become cost-effective in the clinical setting. As previously discussed, the increasing influence of private entities in setting the medical research agenda is also likely to stimulate innovation benefitting single stakeholders rather than the system.

Exhibit 2: Incentives promoting low-value innovation

Source: Authors’ analysis adapted from Hofmann BM. Too much technology. BMJ. 2015 Feb 16.

From the demand side of innovation (providers and health systems), a combined allure (to provide “cutting-edge” patient care), imperative (to leave “no stone unturned” in patient care), and profit-motive (to amplify fee-for-service reimbursements) spur participation in a “technological arms-race.” The status quo thus remains as Clay Christensen has written: “Our major health care institutions…together overshoot the level of care actually needed or used by the vast majority of patients.”

Christensen’s observations have been validated during the COVID-19 epidemic, as treatment of the disease requires predominantly century-old technology. By continually adopting innovation that routinely overshoots the needs of most patients, layer by layer, health care institutions are accruing costs that quickly become the burden of society writ large.

Recommendations To Reduce The Costs Of Health Care Innovation

Henry Aaron wrote in 2002 that “…the forces that have driven up costs are, if anything, intensifying. The staggering fecundity of biomedical research is increasing…[and] always raises expenditures.” With NHEs spiraling ever-higher, urgency to “bend the cost curve” is mounting. Yet, since much biomedical innovation targets the “flat of the [productivity] curve,” alternative forms of innovation are necessary.

The shortcomings in net productivity revealed by the COVID-19 pandemic highlight the urgent need for redesign of health care delivery in this country, and reevaluation of the innovation needed to support it. Specifically, efforts supporting process redesign are critical to promote cost-reducing, substitutive innovations that can inaugurate new and disruptive business models.

Process redesign rarely involves novel gizmos, so much as rejiggering the wiring of, and connections between, existing gadgets. It targets operational changes capable of streamlining workflows, rather than technical advancements that complicate them. As described above, precisely these sorts of “frugal innovations” have led to productivity improvements yielding lower costs in other high-technology industries, such as the computing industry.

Shrank and colleagues recently estimated that nearly one-third of NHEs—almost $1 trillion—were due to preventable waste. Four of the six categories of waste enumerated by the authors—failure in care delivery, failure in care coordination, low-value care, and administrative complexity—represent ripe targets for process innovation, accounting for $610 billion in waste annually, according to Shrank.

Health systems adopting process redesign methods such as continuous improvement and value-based management have exhibited outcome enhancement and expense reduction simultaneously. Internal processes addressed have included supply chain reconfiguration, operational redesign, outlier reconciliation, and resource standardization.

Despite the potential of process innovation, focus on this area (often bundled into “health services” or “quality improvement” research) occupies only a minute fraction of wallet- or mind-share in the biomedical research landscape, accounting for 0.3 percent of research dollars in medicine. This may be due to a variety of barriers beyond minimal funding. One set of barriers is academic, relating to negative perceptions around rigor and a lack of outlets in which to publish quality improvement research. To achieve health care cost containment over the long term, this dimension of innovation must be destigmatized relative to more traditional manners of innovation by the funders and institutions determining the conditions of the research ecosystem.

Another set of barriers is financial: Innovations yielding cost reduction are less “reimbursable” than are innovations fashioned for revenue expansion. This is especially the case in a fee-for-service system where reimbursement is tethered to cost, which creates perverse incentives for health care institutions to overlook cost increases. However, institutions investing in low-cost innovation will be well-positioned in a rapidly approaching future of value-based care—in which the solvency of health care institutions will rely upon their ability to provide economically efficient care.

Innovating For Cost Control Necessitates Frugality Over Novelty

Restraining US NHEs represents a critical step toward health promotion. Innovation for innovation’s sake—that is content-based, incrementally effective, additive, and sustaining—is unlikely to constrain continually expanding NHEs.

In contrast, process innovation offers opportunities to reduce costs while maintaining high standards of patient care. As COVID-19 stress-tests health care systems across the world, the importance of cost control and productivity amplification for patient care has become apparent.

As such, frugality, rather than novelty, may hold the key to health care cost containment. Redesigning the innovation agenda to stem the tide of ever-rising NHEs is an essential strategy to promote widespread access to care—as well as high-value preventive care—in this country. In the words of investors across Silicon Valley: Cost-reducing innovation is no longer a “nice-to-have,” but a “need-to-have” for the future of health and overall well-being this country.

So Do We Need A New Way of Disseminating Scientific Information?  Can Curation Help?

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!

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.

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?

We have discussed this in other posts such as

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


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

For years the pharmaceutical industry has toyed with the idea of making innovation networks and innovation hubs

It has been the main focus of whole conferences

Tales from the Translational Frontier – Four Unique Approaches to Turning Novel Biology into Investable Innovations @BIOConvention #BIO2018

However it still seems these strategies have not worked

Is it because we did not have an Execution plan? Or we did not understand the lead measures for success?

Other Related Articles on this Open Access Scientific Journal Include:

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

Analysis of Utilizing LPBI Group’s Scientific Curation Platform as an Educational Tool: New Paradigm for Student Engagement

Global Alliance for Genomics and Health Issues Guidelines for Data Siloing and Sharing

Multiple Major Scientific Journals Will Fully Adopt Open Access Under Plan S

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

Read Full Post »

Relevance of Twitter.com forthcoming Payment System for Scientific Content Promotion and Monetization

Highlighted Text in BLUE, BLACK, GREEN, RED by Aviva Lev-Ari, PhD, RN


Gian M. Volpicelli


Gian M. Volpicelli is a senior writer at WIRED, where he covers cryptocurrency, decentralization, politics, and technology regulation. He received a master’s degree in journalism from City University of London after studying politics and international relations in Rome. He lives in London.





APR 5, 2022 7:00 AM

What Twitter Is Really Planning for Crypto

The duo behind Twitter Crypto say NFT profile pics and crypto tipping are just the beginning.


YOU MIGHT HAVE heard of crypto Twitter, the corner of the social network where accounts have Bored Apes as profile pictures, posts are rife with talk of tokens, blockchains, and buying the Bitcoin dip, and Elon Musk is venerated.

Then again, you might have heard of Twitter Crypto, the business unit devoted to developing the social network’s strategy for cryptocurrency, blockchains, and that grab-bag of decentralized technologies falling under the rubric of Web3. The team’s unveiling came in November 2021 via a tweet from the newly hired project lead, Tess Rinearson, a Berlin-based American computer scientist whose career includes stints at blockchain companies such as Tendermint and Interchain.

Rinearson joined Twitter at a crucial moment. Jack Dorsey, the vociferously pro-Bitcoin company CEO, would leave a few weeks later, to be replaced by CTO Parag Agrawal. Agrawal had played an instrumental role in Bluesky, a Twitter-backed project to create a protocol—possibly with blockchain components—to build decentralized social networks.

As crypto went mainstream globally and crypto Twitter burgeoned, the company tried to dominate the space. Under the stewardship of product manager Esther Crawford, in September 2021 Twitter introduced a “tipping” feature that helps creators on Twitter to receive Bitcoin contributions through Lightning—a network for fast Bitcoin payments. In January, Twitter allowed subscribers of Twitter’s premium service, Twitter Blue, to flaunt their NFTs as hexagonal profile pictures, through a partnership with NFT marketplace OpenSea.

Twitter Crypto is just getting started. While Rinearson works with people all across the company, her team is still under 10 people, although more hires are in the pipeline, judging from recent job postings. So it’s worth asking what is next. I caught up over a video call with Rinearson and Crawford to talk about where Twitter Crypto is headed. 

The conversation has been edited for clarity and brevity.

WIRED: Let’s start with the basics. Why does Twitter have a crypto unit?

Tess Rinearson: We really see crypto—and what we’re now calling Web3— as something that could be this incredibly powerful tool that would unlock a lot for our users. The whole crypto world is like an internet of money, an internet of value that our users can potentially tap into to create new ways of owning their content, monetizing their content, owning their own identity, and even relating to each other.

One of my goals is to build Twitter’s crypto unit in such a way that it caters to communities that go beyond just that core crypto community. I love the crypto Twitter space, obviously—I’m a very proud member of the crypto community. And at the same time, I recognize that people who are really deep in the crypto space may not relate to concepts, like for instance blockchain’s immutability, in the same way that someone who’s less intensely involved might feel about those things.

So a lot of what we try to think about is, what can we learn from this group of people who are super engaged and really, really, creative? And then, how can we translate some of that stuff into a format or a mechanism or a product that’s a little bit more accessible to people who don’t have that background?

How are you learning from crypto Twitter? Do you just follow a lot of accounts, do you actually talk to them? How does that learning experience play out?

Esther Crawford: It’s a combination. We have an amazing research team that sets up panel interviews and surveys. But we’re also embedded in the community itself and follow a bunch of accounts, sit on Twitter spaces, go to conferences and events, engage with customers in that way. That’s the way the research piece of it works. But we also encounter it as end users: Twitter is the discovery platform today for all things crypto.

One of the things we do differently at Twitter is we build out in the open. And so this means having dialog with customers in real time—designers will take something that is very early-stage and post it as a tweet and then get real-time feedback. They’ll hop into spaces with product managers and engineering managers, talk about it live with real customers, and then incorporate that feedback into the designs and what ultimately we end up launching.

Rinearson: One of the things I wanted to make sure of before I came to Twitter was to know that we would be able to build features in the open and solicit feedback and show rough drafts. And so this is something I asked Parag Agrawal, who’s now the CEO, and was the person who hired me. Pretty early in the job interview process, I said this was going to be really important, and he said, “If you think it’s important to the success of this work, great, do it—thumbs up.” He also shares that openness.

As you said, Tess, you come from crypto. When you were out there, what did you think Twitter was getting right? What did you think Twitter was getting wrong?

Rinearson: I had been a Twitter power user for a really long time. The thing that I saw was a lot of aesthetic alignment between how Twitter exists in the world and the way that crypto exists in the world. Twitter has decentralized user experiences in its DNA. And, this is a bit cheesy, but people use Twitter sometimes in ways that they use a public blockchain, as a public database where everything’s time stamped and people can agree on what happened.

And for most people it’s open, it is there for public conversation. And then obviously it was also the place—a place—where the crypto community really found its footing. I think it’s been a place where an enormous amount of discovery happens, and education and learning for the whole community. I joined when there were some murmurings about Twitter starting to do crypto stuff, mostly stuff Esther had led actually, and I was excited to see where it was going. And then Twitter’s investment in Bluesky also gave me a lot of confidence.

Let’s talk about the two main things you have delivered so far: The crypto tipping feature and NFT pictures. Can you give me just a potted history of how each came about and why?

Crawford: Those are our first set of early explorations, and the reason why we started there was we really wanted to make sure that what we built benefited creators, their audiences, and then all the conversations that are happening on Twitter. For creators in particular, we know that they rely on platforms like Twitter to monetize and earn a living, and not all people are able to use traditional currencies. Not everybody has a traditional banking account setup.

And so we wanted to provide an opportunity for a borderless payment solution, and that’s why we decided to go ahead and use Bitcoin Lightning as our first big integration. One of the reasons we chose Bitcoin Lightning was also because of the low transaction fees. And we have Bitcoin and Ethereum addresses that you can also put in there [on your Twitter “tipping jar”]. We noticed that people were actually adding information about their crypto wallet addresses in their profiles. And so we wanted to make a more seamless experience, so that people could just tip through the platform, so that it felt native.

With NFT profile pictures, the way that came about was, again, looking at user behavior. People were adding NFTs that they owned as avatars, but you didn’t really know whether they owned those NFTs or not. So we decided to go ahead and build out that feature so that one could actually prove ownership.

That’s similar to how other things developed on Twitter, right? The hashtag, or even even the retweet, were initially just things users invented—by adding the # sign, or by pasting other users’ tweets—and then Twitter made that a feature.

Crawford: Yeah, exactly. Many of the best ideas come from watching user behavior on the platform, and then we just productize that.

Rinearson: Sometimes I’ve heard people call that the “help wanted signs,” and like, keeping an eye out for the “help wanted signs” across the platform. The NFT profile picture was a clear example of that.

How do all these things—these two things and possibly other crypto features coming further down the line—really help Twitter’s bottom line?

Crawford: With creator monetization our goal was to help creators get paid, not Twitter. But Twitter takes a really small cut of earnings. For more successful creators, we take a larger percentage. The way we think about this is, it is part of our revenue diversification.

Twitter today is a wholly ad-based business. In the future we imagine Twitter making money from a variety of different product areas. So Twitter Blue is one of those products—you can pay $2.99 a month and you get additional features, such as the NFT profile pictures. We really think that revenue diversification sits across a variety of areas, and creator monetization is one really small component of that.

As you said, these are just early experiments. Where is Twitter Crypto going next? What’s your vision for crypto technology’s role within Twitter?

Rinearson: The real trick here is to find the right parts of Twitter to decentralize, and to not try to decentralize everything at once—or, you know, make every user suddenly responsible for taking care of some private keys or something like that.

We have to find the right ways to open up some access to a decentralized economic layer, or give people ways that they can take their identity with them, without relying on a single centralized service.

We’re really early in these explorations, and even looking at things like Bitcoin tipping or the NFT profile pictures—we view those features as experiments themselves in a lot of ways and learning experiences. We’re learning things about how our users relate to these concepts, what they understand about them, what they find confusing, and what’s most useful to them. We really want to try to use this technology to bring utility to people and you know, not just like, sprinkle a little blockchain on it for the sake of it. So creator monetization is an area that I’m really excited about because I think there’s a really clear path forward. But again, we’re looking beyond that: We’re also looking at using crypto technology in fields like [digital] identity and [digital] ownership space and also figuring out how we can better serve crypto communities on the platform.

Are you going to put Twitter verified users’ blue ticks on a blockchain, then?



[More laughter]

OK, moving on. How does the kind of work you do dovetail with Bluesky’s plan to create a protocol for a decentralized social media platform? Is there any synergy there?

Rinearson: I have known Jay [Graber], the Bluesky lead, for a long time, and she and I are in pretty close contact. We check in with each other regularly and talk a lot about problems we might have in common that we’ll both need to solve. There’s an overlap looking at things in the identity area, but at the end of the day, it’s a separate project. She’s pretty focused on hiring her team, and they’re very focused on building a prototype of a protocol. That is different from what Esther and I are thinking about, which is like: There are all these blockchain protocols that exist, and we need to figure out how to make them useful and accessible for real people.

And when I say “real people,” I mean that in a sort of tongue-in-cheek contrast to hardcore crypto nerds like me. Jay is thinking much more about building for people who are creating decentralized networks. That is a very different focus area. Beyond that, I would just say it’s too early to say what Bluesky will mean for Twitter as a product. We are in touch, we have aligned values. But at the end of the day—separate teams.

Why is a centralized Silicon Valley company like Twitter the right place to start to bring more decentralization to internet users? Don’t we have just to start from scratch, build a new platform that is already decentralized?

Rinearson: I started in crypto in 2015, and I have a very vivid memory from those years of watching some of my coworkers—crypto engineers—trying to figure out how to secure some of their Bitcoin like before one of the Bitcoin forks [in which the Bitcoin blockchain split, creating new currencies], and they were panicking and freaking out. I thought there was no way that a normal person would be able to handle this in a way that would be safe. And so I was a little bit disillusioned with crypto, especially from a consumer perspective.

And then last year, I started seeing more interest from people whom I’ve known for a long time and weren’t crypto people. They were just starting to perk their heads up and take notice and start creating NFTs or start talking about DAOs. And I thought that that was interesting, that we were coming around a corner, and it might be time to start thinking about what this could mean for people beyond that hardcore crypto group.

And that was when Twitter reached out. You know, I don’t think that just any centralized platform would be able to bring crypto to the masses, so to speak. But I think Twitter has the right stuff. I think you have to meet people where they are with new technologies: find ways to onboard them and bring them along and show them what this might mean for them. make things accessible. And it’s really, really hard to do that with just a protocol. You need to have some kind of community, you need to have some kind of user base, you need to have some kind of platform. And Twitter’s just right there.

I don’t think I would say that a centralized platform is definitely the way to “bring crypto to the masses.” I do think that Twitter is the way to do it.

But why do the masses need crypto right now?

Rinearson: I don’t know that anyone  needs crypto, and our goal is not to get everyone into crypto. Let’s be clear about that. But I do think that crypto is a potentially very powerful tool for people. And so I think what we are trying to do is show people how powerful it is and unlock those possibilities. It’s also possible that we create some products and features, where people actually don’t even really know what’s happening under the hood.

Like maybe we’re using crypto as a payment rail or again as an identity layer—users don’t necessarily need to know all of those implementation details. And that’s actually something we come back to a lot: What level of abstraction are we talking about with users? What story are we telling them about what’s happening under the hood? But yeah, I would just like to reiterate that the goal is not to just shovel everyone into crypto. We want to provide value for people.

Do you think there is a case for Twitter to launch its own cryptocurrency— a Twittercoin?

Rinearson: I think there’s a case for a lot of things—honestly, there’s a case for a lot of things. We’re trying to think really, really broadly about it.

Crawford: We’re actively exploring a lot of things. It’s not it’s not something we would be making an announcement about.

Rinearson: I think it is really important to stress that when you say “Twittercoin” you probably have a slightly different idea of what it is than we do. And are we exploring those ideas? Yes, we want to think about all of them. Do we have road maps for them? No. But are we trying to think about things really creatively and be really, really open-minded? Yes. We have this new economic technology that we think could unlock a lot of things for people. And we want to go down a bunch of rabbit holes and see what we come up with.

Gian M. Volpicelli is a senior writer at WIRED, where he covers cryptocurrency, decentralization, politics, and technology regulation. He received a master’s degree in journalism from City University of London after studying politics and international relations in Rome. He lives in London.


Highlighted Text in BLUE, BLACK, GREEN, RED by Aviva Lev-Ari, PhD, RN



Read Full Post »

We Celebrate TEN Years of Excellence, LPBI Group: 4/2012 – 4/2022

Author: Aviva Lev-Ari, PhD, RN, LPBI Group Founder

Updated on 1/19/2023

Five Bilingual BioMed e-Series – 37 volumes

Curator, Book Editor & Bilingual BioMed e-Series, Editor-in-Chief:

Aviva Lev-Ari, PhD, RN

  • English Edition:  18 volumes in 17 books, and
  • Spanish Edition (EDICIÓN EN ESPAÑOL): 19 volumes in 19 books


  • 1.0 LPBI: 4/2012 – 12/2022
  • 2.0 LPBI: 1/2021 – Present to 2025

See as well,

2022 Update from LPBI Group 

This article has five parts:

Part 1: Web Site Statistics

Part 2: 2.0 LPBI Group’s Four Missions: The Pipelines for 2021-2025

Part 3: Portfolio of IP Assets

Part 4: Certificates – One Year Academic Internships in six Disciplines

Part 5: Top 14 Articles by Views, All Time


For ten years, now, Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston, MA – flagship Journal had amassed +2.1 MM views


2022 Update from LPBI Group

Author & Curator: Aviva Lev-Ari, PhD, RN


The Founder has  8,148 followers  on LinkedIn.com


Analytics of e-Reputation


The Founder is the Editor-in-Chief for the Journal and for the BioMed e-Series – an eighteen volume series of electronic Books in Medicine


Page downloads on 4-6-2022

N = 147,069 (till end of Feb. 2022)

Equivalent to 74 Books

Abbreviated electronic Table of Contents (eTOCs) of each Volume in the EIGHTEEN-Volume BioMed e-Series


The Team that produced 18 books in Medicine


LPBI Group’s CSO, 2012-2017: Dr. Larry H. Bernstein, MD, FCAP


The Founder is a UC, Berkeley PhD’83 who had worked at Director Level for SRI Int’l, MITRE, PSC, McGraw Hill. Other employer organizations includes: Monitor Company (now Deloitte), Amdahl Corporation (now Fujitsu), PSC (now Dell Technologies).  Positions in Healthcare are described in this link: http://Scientific and Medical Affairs Chronological CV

Aviva Lev-Ari, PhD, RN

Director & Founder


Picture date: 2/6/2022

While you are reviewing LPBI Group’s Portfolio of IP assets


you will note that LPBI Group is venturing into Scientific NFT Marketplaces


We plan to MINT as NFTs several of LPBI Group’s IP Asset Classes, such as

  • Curations among our +6,100 Journal articles – IP Asset Class I
  • eTOCs – Electronic Table of Contents of our 18 Books – IP Asset Class II
  • Gallery of +6200 Biological Images embedded in our Journal articles – IP Asset Class V
  • E-Proceedings of +100 Medical and Biotech Conferences we had covered in Real Time, 2013 – 2022 – IP Asset Class III
  • Tweet Collections of the latest 40 Medical and Biotech Conferences we had covered in Real Time, 2013 – 2022 – IP Asset Class III


Tweet Collection of 2022 #EmTechDigital @MIT, March 29-30, 2022


Analytics for @AVIVA1950 Tweeting at #EmTechDigital


Review our Testimonials


Our PAST is here




Our FUTURE is here






Podcast of our Leaders are here


A stream of Ten INNOVATIONS in the Life of LPBI since

inception in 2012 to 2022

  1. 4/2012 – LPBI was the Launcher of a novel Scientific Curation Methodology for scientific findings in published primary research in the Global e-Scientific Publishing industry https://pharmaceuticalintelligence.com/
  2. As late as 2016, no big publisher, not even one, i.e., Elsevier, John Wiley had curation-based publications: Journals, Books, e-Proceedings or Gallery of thousands of Biological Images as an IP asset class
  3. At LPBI, Curation of scientific findings was performed in +6,000 articles with +2MM e-Views by Global e-Readers
  4. 6/2013 – LPBI was the Publisher of the 1st e-book in Medicine in Kindle Store on the Life Sciences & Medicine Shelf – Upload to this shelf by Amazon.com
  5. 2/2021 – Completion of the 18 volumes, BioMed e-Series in five Specialties in Medicine: each article in each volume is a curation-based publication.
  6. On Amazon.com on 7/2021 – LPBI’s e-books in Medicine enjoy +128,100 PAGE DOWNLOADS – the ONE and ONLY publisher in that range of page downloads. The record is the equivalent of 64 books at an average of 2,000 pages a volume !!!! LPBI smallest book is 1,000 pages and its biggest is +3,700 pages
  7. LPBI launched its Natural Language Processing (NLP) Practice in 1/2020 as Mission #1. NLP is one method of Machine Learning (ML). ML is a family of methods in Artificial Intelligence (AI) which is a field in the Computer Science Academic discipline since the early 60s.
  8. In 4/2021 Linguamatics/IQVIA performed NLP on LPBI’s 33 articles and 20 Biological Images. RESULTS:  +670 entity relations DISCOVERED by Linguamatics and unknown to Pharma and to Insurers, entity relations between:
  • Gene-Disease
  • Gene-Drug
  • Disease-Drug

These results were jointly presented to a Healthcare Insurer, SLC, UT on 7/13/2021, forthcoming meeting in 9/2021.

LPBI and BurstIQ are architecting NOW the first Natural Language Processing – Blockchain Information Technology infrastructure in existence, This statement is TRUE.

  • Updated on 7/28/2021:Fluree Flur.ee, the Web3 Data Platform Open source semantic graph database & LeadSemantics.com presented their solution for NLP and Blockchain on 7/28/2021. Erich G. was lured as Chief architect for LPBI’s Mission #2: NLP & Blockchain
  • Linguamatics, the leader in NLP did not hear of Blockchain and BurstIQ did not have a request for NLP – LPBI PUT THESE TWO TECHNOLOGIES AND PARTIES TOGETHER

See IMAGES SOURCE: BurstIQ image for LPBI


  • On 7/19/2021 – LPBI had launched LPBI India for Synthetic Biology Software for Drug Discovery targeting Galectins – Collaboration with Dr. Raphael Nir, President and CSO, SBH Sciences, Inc., Natick, MA
  • On 7/25/2021 – LPBI announced that it will have the NEWLY to be published BioMed e-Books As Mission #3:

o    Bi-Lingual electronic Table Of Contents (eTOCs), English & Spanish with Montero Language Services, Madrid as the Translator of eighteen Books’ Cover Pages and the 18 books electronic Table of Contents.

o    The Content promotion in the Spanish speaking Countries with GTO, Madrid as AD Agency.

o    NLPs results of Medical Text Analysis with domain knowledge expert Interpretations in Foreign Languages and in Audio: in Spanish and in other languages, forthcoming

o    Original English Book – Only Editorials (Preface, Introductions, Summaries and Epilogue) because the Bi-Lingual part has the eTOCs of the e-Book

o    This is a new genre and a new architecture of 18 MULTIMEDIA SCIENTIFIC e-Books with (a) NLP results of the Medical Text analysis with machine learning, (b) Expert Interpretation of the Visualization Results. Bi-Lingual Podcasts: (c) eTOCs and (d) Bi-Lingual Expert Interpretation in English and Spanish Text and audio Podcasts, and (e) Books’ Editorials in English Audio Podcast

Content promotion proposal by GTO, Madrid

See IMAGES SOURCE: Rendition by GTO, Madrid of BurstIQ Image, above

2.0 LPBI is a Very Unique Organization 

9. The Content Monetization effort includes the Price List for LPBI 1.0 digital products and of LPBI 2.0 – NLP Products

Under development

  • IP Valuation Model per IP asset class is needed to be compared with Master_Financials and to supplement it
  • Pricing Model and Product Mix Models for the digital products to be generated by the process of Text Analysis with NLP are using a Product Price List already developed.
  • The scenarios for a Probabilistic Product Mix for the B2B sector are work-in-progress. Scenarios of Product Mix for $500,000 B2B engagements with NLP scaling up with NLP Alliances. The Alliances are the Labor component and LPBI represent Materials (Content) as 25% of the contract price, on top of total, to be paid by the B2B customer as materials in use for the engagement.
  • B2C Customers on Blockchain will use the Price List for all Digital Products of LPBI 1.0 and LPBI 2.0 – Pay per Use

10. LPBI Group runs FIVE ACADEMIC INTERNSHIPS as Certificate Programs: a One Year long or a One Semester long: Volunteer base offering Verifiable Certificates, as described in https://pharmaceuticalintelligence.com/certificate-1-year/

Read Full Post »

Analytics for @AVIVA1950 Tweeting at #EmTechDigital

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



See also

Tweet Collection of 2022 EmTechDigital @MIT, March 29-30, 2022

Tweet Author: Aviva Lev-Ari, PhD, RN

Selective Tweet Retweets for The Technology Review: Aviva Lev-Ari, PhD, RN



Top Tweet earned 122 impressions

Prem Natarajan Vice President Alexa AI device and broadly decisions what stay on edge vs cloud physical obstacles to learn language less constrained Alexa5 more creative
 1  2

Top mention earned 7 engagements

Agrim Gupta, Stanford Vision Learning Lab, Stanford University Baldwin Effect genotypic modification phynotypic behavior GPT-OpenAI CLIP MetaMorph process transformer Encode Decode
 1  1
Engagement rate

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Equity Sharing Calculation: A Scoring System for Author’s (a) Total Articles (single author) and (b) multiple authors (c) Total Articles Views (d) Author’s Proportion of own articles views in the Top 14 Journal articles by Views and (e) External Citations (f) Influencer on Twitter

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

LPBI Group had developed a Scoring System for attribution of Equity Sharing in IP Asset Class I: Journal articles to Top Authors by number of articles published and by Views at all time for all articles published in the Journal

UPDATED on 10/12/2022 for 4/10/2019

(f) Influencer ranking at World Medical Innovation Forum ARTIFICIAL INTELLIGENCE in MEDICINE

Top 3 Ranked by Betweenness Centrality in Top 10 Influencers   Twitter Analytics by NodeXL for #WMIF19 by 

@PHSInnovation  at World Medical Innovation Forum ARTIFICIAL INTELLIGENCE, Boston, MA USA, Monday, April 8-10, 2019

‘s  Hashtags  – Twitter Analytics published for http://bit.ly/WMIF19 

  • [Top 10 by Mentions – @pharma_BI = 4 with 181 mentions]  

  • [Top 10 by Tweets @AVIVA1950 = 2 with 229 Tweets (N = 152 Direct messages)]


Recognition for LPBI Group’s IP Asset Class III: e-Proceedings and Tweet Collections



UPDATED on 5/24/2022

(e) External Citations

More details are found in



(a) Author’s Total Articles (single author) 

(b) Author’s multiple authors articles

(c) Author’s Total Articles Views 

(d) Author’s Proportion of own articles views in the Top 14 Journal articles by Views

(e) External Citations – See UPDATED on 5/24/2022, above


(f) Global Score across all the parameters

Read Full Post »

Analytics for e-Reputation based on LinkedIn 1st Degree Connections, +7,500 of LPBI Group’s Founder, 2012-2022: An Intangible Asset – Connections’ Position Seniority & Biotech / Pharma Focus

Author: Aviva Lev-Ari, PhD, RN, Founder of 1.0 LPBI, 2012-2020 & 2.0 LPBI, 2021-2025


Data Scientist, Research Assistant III: Tianzuo George Li

LPBI Group Logo

Picture date: 2/6/2022

Aviva Lev-Ari, PhD, RN

Founder of 1.0 LPBI, 2012-2020 & 2.0 LPBI, 2021-2025



We discussed the relations of e-Reputation as an Intangible Asset of the Firm in the following articles:

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

Curator: Aviva Lev-Ari, PhD, RN

Additional parameters of e-Reputation as an intangible asset for LPBI Group’s Founder and for LPBI Group as a Firm are analyzed in other articles, see the following List of Links:

UPDATED on 5/9/2022

Based on 2/13/2022 data download

LPBI Group’s Founder’s 1st Degree Connections on LinkedIn by

Sector Type and by Number of Connections in each Sector


Sector Type Number of Connections
Big Pharma 130
University 99
Academic Medical Center 53
CRO 46
Biotech 35
Cloud Computing 29
Genomics 24
Medical School 22
Medical Devices 18
Medical Equipment 18
Academic Medical Center – Israel 17
Big Pharma – Israel 15
Big Pharma – Japan 15
BioSciences 15
Cloud IT 15
Medical Research Institute 15
Institute of Technology 11
Biological Sciences Research Institute  Israel 10
Healthcare Insurance 10
Scientific Publisher 10
Biotech – Immunotherapy 9
Biotech – Israel 9
Government Agency – Drug Administration 8
Healthcare Insurance Company 8
Big Pharma – France 7
Institute of Technology – Israel 7
Medical Professional Association 7
Research Institute 7
HMO – Israel 6
Large Biotech 6
Media 6
Top Four Accounting 6
University – UK 6
Big Four Accounting 5
BioInstrumentation – Genomics 5
Medical Center 5
Technology Transfer Office – Israel 5
VC 5
Business/diplomacy – Israel 4
Federal Agency 4
Medical Research Institute/Foundation 4
University – Canada 4
Government Office – Israel 3
Top Tier Management Consultinf on IT 3
Top Tier Management Consulting 3
Univeristy – Israel 3
World Largest Thinktank 3
Big Pharma – Swiss 2
Big Pharma – US 2
BioMed Research Institute, ME Independent non-profit 2
BioTech PharmacoGenomics 2
Community Hospital 2
Government funded Basic Research 2
Government funded R&D 2
Government funded R&D – Israel 2
Management Consulting 2
Medical Center – Israel 2
Medical Devices – Israel 2
Medical Office 2
Medical Professional Accociation – Israel 2
Pharma – India 2
Professional Association 2
Professional Medical Society 2
Research Institute – Israel 2
Research Institute on Hightech – Israel 2
Top Four Accounting – Israel 2
Top Tier Management Counsulting – India 2
University – Australia 2
University – Israel 2
VC – Israel 2
3D Bioprinting – Dental 1
Academic Medical Center – Canada 1
Academic Medical Center – Spain 1
Academic Medical Center – Sweden 1
Academic Medical Center- Israel 1
Academic Medical School 1
AI 1
Big Pharma – Europe 1
Big Pharma – Poland 1
BioMed 1
BioMed AI 1
Biotech – Immunotherapy – Germany 1
Biotech & Gne Medicine –               USA & Canada 1
Biotech Consorsium 1
Business – Israel 1
Business Association NE & Israel 1
Community Medical Center 1
Economic Research Institute 1
Governement funded Research 1
Government Ministry of Health – Israel 1
Government Office – China 1
Government Office -Taiwan 1
Government Research Center 1
Healthcare R&D – India 1
HMO & Healthcare Insurance 1
Institute of Technology – India 1
Law Firm 1
Library – Israel 1
Life Science Institute – Japan 1
Medical Center – Canada 1
Medical Center – India 1
Medical Center (VA) 1
Medical Clinic 1
Medical Equipment – Israel 1
Medical Institute/Foundation 1
Medical Professional Society 1
Medical Research Center 1
Medical Research Institute – Academic Medical Center 1
Medical Research Institute – Canada 1
Medical Research Institute (VA) 1
Medical School – Brazil 1
Medical School – Bulgaria 1
Medical School – Canada 1
Medical School – Iran 1
Medical School – Spain 1
Medical School – Thailand 1
Medical Technology & Equipment 1
NGO – Healthcare 1
Pathology – AI 1
Pathology – AI – Israel 1
Pharma – France 1
Pharma manufacturer – Ireland 1
Pharma R&D – Not by Pharma 1
Pharmaceutical & Biotech MEDIA 1
Pharmaceutics – Switzerland 1
Professional Accociation – Denmark 1
Professional Medical Association 1
Research Center                    Independent Non-profit 1
Research Institute – Indonesia 1
Research Institute (Private) – Brazil 1
Research Institute at                  Academic Mmedical Center – Israel 1
Research Institute/Foundation 1
Scientific Publisher – Sweden 1
Top Four Accounting – South East Asia 1
Top Tier Medical Consulting 1
Univeristy – Israel – AFTAU 1
University –  Latvia 1
University –  Oman 1
University –  Romania 1
University – Denmark 1
University – Finland 1
University – Germany 1
University – Greece 1
University – Italy 1
University – Porto Rico 1
University Health Services 1
VC – High Tech & Healthcare – Israel 1
VC – Hightech and Biotech 1
VC Biotech 1
VC Medical Devices & Pharma – Israel 1



The presentation of this one parameter focus on two dimensions: 

  • Dimension #1: The Position Seniority of the Connections, and
  • Dimension #2: The industry concentration in Biotech / Pharma 

Summary and Conclusions:

Founder’s LinkedIn 1st Degree Connections, N = +7,500

The industries represented by multiple 1st Degree Connections of LPBI Group’s Founder are the following:

  • Biotech & Pharma: Teva Pharmaceuticals, Novartis, AstraZeneca, J&J, Philips, ICON plc, IQVIA, Syneos Health, Takeda
  • HighTech IT & Internet: Amazon, Microsoft, Google
  • Academia: Weizmann Institute, Harvard Medical School
  • Others in 2022: Self employed, Home, Freelance

Marquee Corporations:

Their Leaders are 1st Degree Connections of LPBI Group’s Founder 


Corporate Leaders are 1st Degree Connections of LPBI Group’s Founder 

  • 30% of the Total of 7,485 1st Degree Connections are +1,000 Directors, +700 CEOs, +400 VPs
  • +200 positions are of the company Presidents (2.25%)
Position of Interest Frequency Summary (include overlaps)
Position Name  














Industry Focus of the Marquee Corporations who’s Leaders are

1st Degree Connections to LPBI Group’s Founder

Summary of 3 Most Common Positions in Companies with 9 or More Connections



Number of contacts



1st position count



2nd position count



3rd position count
Novartis 16 Manager 3 Lead 3 Director 2
Teva Pharmaceuticals 16 Senior Director 3 R&D Director & Manager 3 Senior Managers (other) 2
Amazon 15 Senior Program Manager 2 associate 2 Marketing & Sales Leader 2
AstraZeneca 14 Senior Director 2 Talent acquisition 2 Vice President 2
Johnson & Johnson 13 Vice President 3 Scientist 3 Director 3
Weizmann Institute of Science 13 Head, Leader, & Director 4 Scientist 3 Researcher 2
Philips 12 Head 2 Leader 2 Architect & Engineer 2
ICON plc   11 Recruiter & Recruitment Consultant 4 Directors 2 Manager of Clinical Operations 2
IQVIA 11 Director 3 Specialist 2 Consultant 2
Syneos Health 11 Director 3 Oncology Sales Representative 2 Clinical Research 2
Harvard Medical School 10 Professor 3 Instructor 2 Fellow 2
Mircrosoft 10 Engineer & Architect 3 Manager 2 Recruiter 2
Takeda 10 Head & Lead 4 Manager 3 Associate Director 2
Google 9 Manager 3 Engineer 2 Scientist & Researcher 2
Self-Employed 127 Consultant 24 Writer & Editor 10 Manager & Managing Director 8
Freelance 24 Consultant 7 Writer & Editor 6 Programmer 2


In Highest Frequency of Leading Positions we find the C-Suite

Of Note: Seniority of the Connections’ Positions – Managers, Directors, CEOs, Founders, Vice Presidents

Of Note: Managers, Directors, CEOs, Founders and VPs


Of Note: Managers, Directors, CEOs, Founders and VPs: Ease of Approachability in decrease order: Most accessible are Director level followed by VP level and least approachable are the CEOs in the corner offices.

Of Note: CFOs, Coordinators, Chairman/Vice Chairman, Experts, Business Owners, Researchers, Medical, Editors, others.


The Data was extracted on 2/13/2022 from LinkedIn Cloud.


First Degree LinkedIn Connections of

                       Aviva Lev-Ari, PhD, RN                                  

Frequency Summary

The Positions of All Connections                        Frequency Summary                                                (overlaps counted once)
Positions Frequency



Manager (other) 787
Director 733
CEO 718
Founder 449
ZZ_ other statistically insignificant positions 433
Vice President 360
Consultant 298
President 196
Specialist 160
Professor 148
Scientist 144
recruiter 138
Advisor 131
Business/Organization Owner 123
Co-Founder 120
Head 116
Managing Director 104
Engineer 86
Analyst 85
Managing Partner 76
Partner (other) 71
Principal 68
Retired 67
Writer 64
(Board) Member 62
Admin 53
Talent Acquisition 52
Account Manager 51
Officer 51
Chief Financial Officer 48
Coordinator 47
(Vice) Chairman 47
Associate 46
Assistant 45
Leader 42
Coach 39
Researcher 39
Account Executive 35
Expert 33
Business Development 33
Senior position (other) 33
Research Related (other) 30
Executive (other) 30
Strategy related (other) 28
Medical (other) 27
Attorney 26
Representative 26
Accounting (other) 24
Developer 24
Editor 24
Designer 23
Faculty 22
Supervisor 22
Principal Consultant 22
Lecturer 22
Agent 22
Intern 22
Sales Related (other) 22
Architect 20
Strategist (other) 19
Chief Operating Officer 19
Teacher 17
Technician 17
Actor 16
Instructor 15
Student 15
Nurse 15
Chemist 14
Mentor 14
Author 14
Investigator 13
Marketing (other) 13
Sales Executive 12
Chief Scientific Officer 11
Broker 11
Cardiologist 11
Chief (other) 11
Venture Partner 10
Postdoctoral Fellow 10

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NCCN Shares Latest Expert Recommendations for Prostate Cancer in Spanish and Portuguese

Reporter: Stephen J. Williams, Ph.D.

Currently many biomedical texts and US government agency guidelines are only offered in English or only offered in different languages upon request. However Spanish is spoken in a majority of countries worldwide and medical text in that language would serve as an under-served need. In addition, Portuguese is the main language in the largest country in South America, Brazil.

The LPBI Group and others have noticed this need for medical translation to other languages. Currently LPBI Group is translating their medical e-book offerings into Spanish (for more details see https://pharmaceuticalintelligence.com/vision/)

Below is an article on The National Comprehensive Cancer Network’s decision to offer their cancer treatment guidelines in Spanish and Portuguese.

Source: https://www.nccn.org/home/news/newsdetails?NewsId=2871

PLYMOUTH MEETING, PA [8 September, 2021] — The National Comprehensive Cancer Network® (NCCN®)—a nonprofit alliance of leading cancer centers in the United States—announces recently-updated versions of evidence- and expert consensus-based guidelines for treating prostate cancer, translated into Spanish and Portuguese. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) feature frequently updated cancer treatment recommendations from multidisciplinary panels of experts across NCCN Member Institutions. Independent studies have repeatedly found that following these recommendations correlates with better outcomes and longer survival.

“Everyone with prostate cancer should have access to care that is based on current and reliable evidence,” said Robert W. Carlson, MD, Chief Executive Officer, NCCN. “These updated translations—along with all of our other translated and adapted resources—help us to define and advance high-quality, high-value, patient-centered cancer care globally, so patients everywhere can live better lives.”

Prostate cancer is the second most commonly occurring cancer in men, impacting more than a million people worldwide every year.[1] In 2020, the NCCN Guidelines® for Prostate Cancer were downloaded more than 200,000 times by people outside of the United States. Approximately 47 percent of registered users for NCCN.org are located outside the U.S., with Brazil, Spain, and Mexico among the top ten countries represented.

“NCCN Guidelines are incredibly helpful resources in the work we do to ensure cancer care across Latin America meets the highest standards,” said Diogo Bastos, MD, and Andrey Soares, MD, Chair and Scientific Director of the Genitourinary Group of The Latin American Cooperative Oncology Group (LACOG). The organization has worked with NCCN in the past to develop Latin American editions of the NCCN Guidelines for Breast Cancer, Colon Cancer, Non-Small Cell Lung Cancer, Prostate Cancer, Multiple Myeloma, and Rectal Cancer, and co-hosted a webinar on “Management of Prostate Cancer for Latin America” earlier this year. “We appreciate all of NCCN’s efforts to make sure these gold-standard recommendations are accessible to non-English speakers and applicable for varying circumstances.”

NCCN also publishes NCCN Guidelines for Patients®, containing the same treatment information in non-medical terms, intended for patients and caregivers. The NCCN Guidelines for Patients: Prostate Cancer were found to be among the most trustworthy sources of information online according to a recent international study. These patient guidelines have been divided into two books, covering early and advanced prostate cancer; both have been translated into Spanish and Portuguese as well.

NCCN collaborates with organizations across the globe on resources based on the NCCN Guidelines that account for local accessibility, consideration of metabolic differences in populations, and regional regulatory variation. They can be downloaded free-of-charge for non-commercial use at NCCN.org/global or via the Virtual Library of NCCN Guidelines App. Learn more and join the conversation with the hashtag #NCCNGlobal.

[1] Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global Cancer Statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, in press. The online GLOBOCAN 2018 database is accessible at http://gco.iarc.fr/, as part of IARC’s Global Cancer Observatory.

About the National Comprehensive Cancer Network

The National Comprehensive Cancer Network® (NCCN®) is a not-for-profit alliance of leading cancer centers devoted to patient care, research, and education. NCCN is dedicated to improving and facilitating quality, effective, efficient, and accessible cancer care so patients can live better lives. The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) provide transparent, evidence-based, expert consensus recommendations for cancer treatment, prevention, and supportive services; they are the recognized standard for clinical direction and policy in cancer management and the most thorough and frequently-updated clinical practice guidelines available in any area of medicine. The NCCN Guidelines for Patients® provide expert cancer treatment information to inform and empower patients and caregivers, through support from the NCCN Foundation®. NCCN also advances continuing educationglobal initiativespolicy, and research collaboration and publication in oncology. Visit NCCN.org for more information and follow NCCN on Facebook @NCCNorg, Instagram @NCCNorg, and Twitter @NCCN.

Please see LPBI Group’s efforts in medical text translation and Natural Language Processing of Medical Text at

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Standard Operating Procedures for Updating the Map of LPBI India

Author: Srinivas Sriram

Co-Author: Abhisar Anand 

To update the map of LPBI India, there are two major steps that are involved that use two different softwares. The softwares are:

  1. Zee Maps (For actually Creating the Map with Landmarks)
  2. Google Slides (For processing the map and making it look nice and downloadable as JPG). 

This SOP Article will delve into how to update the map of LPBI India that is currently created on these softwares in the case that the map needs to be updated for new members of LPBI India or members who leave LPBI India. 

  1. Go to https://www.zeemaps.com/
  2. Click on the “Sign In” button on the Top Right Corner:
  1. Sign in to Zee Maps with the following credentials:
    1. Email: lpbimap@gmail.com
    2. Password: (Get the Password from Dr. Lev-Ari)
  2. Once you are signed in, Click on the “MyMaps” page:
  3. Click on “LPBI India Map” to edit the Map:
  1. Now, you are in the Map. To see all the current landmarks of LPBI India Members, Click on the Side Bar at the very right of the page.

  1. Now, you can see all the current members of LPBI India who are on the Map. 
  2. To add a new person to the map, do the following:
    1. Click on the “Additions” section in the menu on the Left Side of the Page.
    2. Click on “Add Marker – Simple”.
    3. For Entry Name, Give the Name of the Person whom you are trying to add to the Map. 
    4. For Location, provide the Location of the Person whom you are trying to add (Just give the City Name and the Map should auto-complete a suggestion that is the correct location). 
    5. Then, you can click “Preview” to see how the new addition would look on the map, “Reset” to reset your changes, or “Close” to close the entry without saving it. If you are happy with the Entry, you can add the marker by clicking the “Submit” button at the bottom of the entry. 
    6. You have now added someone to the map, and you can see them on the table to the right. 
  1. To delete a person from the map, do the following:
    1. Click the person you would like to delete on the map, and then click the trash can button (as shown in the screenshot).
    2. Now, you have successfully removed someone from the Map, and they will no longer be visible on the table to the right. 
  2. Once you have updated the map per your liking, you now have to move on to the next step of the process. 
    1. First, take a screenshot of the updated map region similar to the example shown below and save it to your local computer. 
  1. You now need to access the Google Slide Document that makes the Map look better. Click on the link below to access the current LPBI India Map. 
    1. https://docs.google.com/presentation/d/1Jszv7_v7_ObjCHdSRIeygr6U9EZ0AwF_8Ud1Mh9R33o/edit?usp=sharing
  2. This Google Slide has:
    1. A screenshot of the Zee Maps Map with text boxes to make the numbers easier to read. 
    2. A table (the same as the table seen on the Zee Maps Screen) that contains the name of the LPBI India Member and the number on the map that corresponds with that LPBI India Member. 
  3. Insert your new screenshot of the Map you just took into the Google Slide Document, and then change the table on the right to make sure that it matches the table shown on Zee Maps. Make sure that for the map, the text boxes that make the numbers look larger match up the locations of the individual people on the map. 
  4. Edge Case: If two people have the same location, you cannot see both of the markers at the same location. This is why in the current map, numbers 3 and 6 and numbers 7 and 9 are on the same marker. Make sure that all the numbers match up and put the multiple numbers on the map if necessary. 
  5. Once you are satisfied with the updated LPBI India Map, you can download the Map in a variety of formats. Follow the instructions below to download the Map in the format that suits your needs. 
    1. On the top left corner, click on “File” (as shown in the screenshot)
    2. Click on “Download”. A variety of formats show up. Click on the format that suits your needs (ex. .jpg, .png, .pptx, etc.). Then, the map should download on your local machine. 
  6. Now, you have successfully updated the map of LPBI India and downloaded it on your local machine! Send the updated map to Dr. Lev-Ari (if someone else is performing the map updates), and this can be used for LPBI India!

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Standard Operating Procedures for Text to Audio Conversion – How to create a Podcast and Embed it on a Post or on a Page

Author: Ethan Coomber, Research Assistant III, Data Science and Podcast Library Development 


Most recent update: 7-12-21

*As of the writing of these steps, the Anchor feature that converts articles to podcasts is relatively new. As of my most recent communication with representatives of Anchor, they are planning on adding features that would simplify this process.

Converting an Article to a Podcast

  • The first thing you will need to do is create an account on Anchor who has recently partnered with WordPress to allow users to link their accounts and convert articles into podcasts. The link to do so is below.
    • https://anchor.fm/wordpressdotcom
      • It is important to note that Anchor will not let you link to a WordPress account if you create a generic account it must be an account linked with WordPress. This link should allow you to do so.
  • Once you have linked your account, you will want to go to the tab for “Episodes”.
  • On the episodes tab, there should be a button that allows you to import articles from your WordPress account.
  • Unfortunately, as of this update, Anchor does not have a feature to allow users to search for a specific article. I have spoken with workers from Anchor who have told me they will work on implementing this feature right away so check and see if they have finished implementing a search bar or some other way to filter. As of this update, the articles are loaded in chronologically with the most recent articles appearing on the first page.
    • If you are looking to convert an article that was recently published on WordPress, it should appear on this page or one of the first few.
    • One option you have to try to find specific articles is to use the (command F) feature of a mac or the (control F) feature of windows. This allows you to search for a specific keyword within a page.
      • With the publishing date of the article you are looking for in mind, you should be able to find the article within a few minutes. Articles that were published earlier will take longer to find than articles published in the last couple weeks. Many of the articles have dates in their titles so as you go through the pages, you will be able to tell if you have passed your articles if the dates in the titles are from before when the one you are looking for was published. Similarly, you will know you have not arrived yet if the titles are from dates after the one you are looking for.
      • Each time you go to a new page, you will need to press the (command F) function, and then the (return) with the title (or a keyword or phrase from the title you are looking for) in the search bar. This will quickly search the page and tell you if the title you are looking for is there. If no results are found, you know you can go to the next one.
        • I have found this speeds up the process as I get in a rhythm of pressing the button for the next page and then quickly searching the page I am on.
        • If you do not press (command F) function, and then the (return), the search tool will not update and tell you if the word you are looking for is in the page.
        • You may want to play around with these features with an article on the first page or two to make sure you understand before searching for an article published several years ago.
  • Once you have found the article you are looking for, you will then press the large create episode button.
  • You will then be presented with the option to “Automatically convert to audio” or “Record” yourself.
  • If you would like to quickly automatically convert the article, select that option.
  • There are several voices you will then be able to select from. You choose the one you like most.
  • Anchor then converts the entire article.
    • As of now there is no way to select only a portion of the text to convert so the entire article (including headers and captions) will be converted.
  • Once the article is converted, you will then press the “Save and continue” button.
  • Several optional features will then pop up. If you would like to add a song or messages to your podcast, this is the place where you would do it. Once the podcast is how you would like it, you then press the “Save changes” button.
  • If you would like to update the episodes “Cover art”. Select the pencil to the right of the podcast.
  • Scroll to the bottom and upload whatever image you would like.

Embedding a Podcast into an article

  • Once you have published an article on Anchor, you are now able to embed it within your article for viewers to listen and read at the same time.
  • When on Anchor, make sure you are on the Dashboard. There, you should see a button that says “View public site”. Click this button.
  • You will then be directed to a page that gives several options. You will then press the button that says “Listen on Spotify”
  • This will then take you to a page on Spotify instead of Anchor. Here, you will see all articles published using your anchor account. It may take a couple minutes for recently converted articles to show up on this page.
  • Once you see your podcast title, when you hover your mouse over the podcast, a box with an arrow pointing upwards will appear in the bottom right of your highlighted podcast. When you click this button, it will copy a link to your podcast on Spotify. You will use this link to embed your podcast.
  • Returning back to your WordPress article, insert a block where you would like your podcast to be embedded. When you press the plus button to insert a block, choose the browse all option. Scroll all the way down to embeds and select the one with the Spotify icon.
  • You will then be able to past the link you previously copied from Spotify, and your podcast will now be embedded.

Editing a previously published podcast

  • Anchor stores all previously published podcasts in the Episodes tab.
  • Once you are in Episodes, select the button in the bottom right that says “Last”. This will take you to where all published podcasts are.
  • If you would like to edit a podcast, click the three dots to the right of the podcast and select “View episode details”
  • This is where you can edit and save your podcast.

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Standard Operating Procedures for creating a DropBox Account

Author: Abhisar Anand
Co-Author: Srinivas Sriram

Please follow these steps in order to register for a DropBox Account

1. Go to https://www.dropbox.com/login

2. Click on the option “create an account”

3. Fill in the corresponding information (First name, Last name, Email, Password, Check the terms box).

4. Click the “Create an account” button.

5. Click on the “Or continue with 2 GB Dropbox Basic plan” option.

6. Go to https://www.dropbox.com/ (login if needed)

7. Email Dr. Lev-Ari regarding requiring access to the LPBI folder with the email you registered within the body of the email.

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