Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com
“A miracle that came true”. This is how Aviva Lev-Ari, PhD, RN founder of LPBI Group’s described what she and her venture had accomplished by partnering with Montero for a “monumental” #Medicine and #LifeSciences translation project. It was “monumental” because it involved 18 books in medicine 😊.
Dr. Lev-Ari is the editor-in-chief behind the Medicine and Life Sciences Scientific Journal, PharmaceuticalIntelligence.com An open access scientific journal that has over 2.2 million views by over 1.4 million visitors. Over 6,170 scientific articles and over 740 categories of research in its ontology.
Between June 2013 and February 2021, LPBI Group’s team published eighteen 𝗲𝗹𝗲𝗰𝘁𝗿𝗼𝗻𝗶𝗰 medical 𝗯𝗼𝗼𝗸𝘀 covering five medical specialties:
These e-books, including 𝟮,𝟳𝟮𝟴 scientific 𝗮𝗿𝘁𝗶𝗰𝗹𝗲𝘀 curated and authored 𝗯𝘆 𝗯𝗶𝗼𝗺𝗲𝗱𝗶𝗰𝗮𝗹 experts and medical 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝘀 pursuing the quest to make the latest research available to healthcare professionals and accessible to the Global community of biological scientists, practicing physicians and medical students.
With 471,000 million speakers in 22 countries, the Spanish language was the most relevant language to publish a new edition.
So, it was time to find the right #LanguageServiceProvider. Dr. Lev-Ari first contacted:
1️⃣ A company that couldn’t handle the project due to its size.
2️⃣ Another provider whose quote they couldn’t accept.
This led LPBI to adjust the scope of work and set certain boundaries, such as the budget for the project and making the decision that the project will focus on translation of the cover page of 18 e-books and the electronic Table of Contents (eTOCs) of these e-Books.
And then Aviva came across Fritz Handtke and Montero on LinkedIn. We held a couple of meetings to:
🤝 Define the scope of the project.
🤝 Create a methodology we could repeat 18 times.
🤝 Show LPBI how we work, including the software used to avoid counting (and charging for) repeated words.
🤝 Introduce our experts in the medical field to them.
Aviva’s acceptance of our quote marked the beginning of a very smooth collaboration.
It took us less than five months, involving three #MedicalTranslators, to deliver the eTOCs in Spanish (for 𝟭𝟵 𝗯𝗼𝗼𝗸𝘀 divided into five series).
The result of this project was “a new genre of the original #biomed e-Series.” In each volume of the Spanish-language Edition: PART A is Spanish audios, PART B is Bilingual texts, and PART C is editorials in English.
When we asked Dr. Lev-Ari about her experience with Montero, she highlighted the following points:
1️⃣ “At all times, there was 𝗼𝗻𝗲 𝘀𝗶𝗻𝗴𝗹𝗲 𝗽𝗲𝗿𝘀𝗼𝗻 𝗮𝘀𝘀𝗶𝗴𝗻𝗲𝗱 𝘁𝗼 𝗺𝘆 𝗽𝗿𝗼𝗷𝗲𝗰𝘁.”
2️⃣ “One of the editors of the series A in cardiovascular is a Spanish-speaking cardiologist. He reviewed 2 books and confirmed the 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆.”
3️⃣ “Their 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝘁𝗶𝗺𝗲 was most favorable. After submitting a file, I got the translation within a week. For any questions, I’d receive a timely response.”
Imagine how thrilled we were to hear her say:
“Congratulations to Montero because they delivered a very monumental project. Without our collaboration, that would have most likely not have happened.”
Thanks to Aviva and LPBI Group for your trust in Montero!
The electronic books are collections of curated articles in biomedical science. The electronic Tables of Contents (eTOCs) of each volume was designed by a senior editor with expertise in the subjects covered in that volume. The curations use as sources published research findings in peer-reviewed scientific journals together with expert added interpretations.
The e-books are designed to make the latest research in the Five Bilingual BioMed e-Series – 37 volumes accessible to practicing health care professionals. These five e-Series cover the following medical specialties: cardiovascular diseases and therapies, genomics, cancer etiology and oncological therapies, immunology, and patient-centered precision medicine.
The material in these volumes can greatly enhance medical education and provide a resource for continued updating and education for health care professionals. In addition to the 37 e-books, LPBI has published more than 6,000 articles in its online scientific journal “PharmaceuticalIntelligence.com”, which has received 2.2 million views since its launch in 4/2012, Top articles had more than 15,000 views.
The authors of the curations are a team of eminent biomedical scholars assembled and led by Dr. Aviva Lev-Ari, Ph.D., R.N., Editor-in-Chief of the BioMed e-Series and the Journal, and LPBI Group’s founder. Dr. Lev-Ari also contributed to many articles in these collections.
As LPBI Group’s leader, Dr. Aviva Lev-Ari, served as an invited Press/Media professional in +70 Global conferences, which she covered in-person in real-time and produced e-Proceedings and Tweet collections cited in many journal and book articles. Dr. Lev-Ari remarked that she was “gratified that the English language e-books had received more than 140,000 page-downloads. This is a strong indication that our work has been successful”. The Spanish Edition, offered at a 25% discount, will reach healthcare professionals in 22 Spanish speaking counties.
Están disponibles 18 volúmenes en la edición en inglés y 19 volúmenes en la edición en español, que incluyen 2 728 artículos elaborados por profesionales biomédicos.
Los libros en formato electrónico son colecciones de artículos seleccionados sobre biomedicina. El índice de contenido electrónico (IDCe) de cada volumen ha sido diseñado por un editor con experiencia en los temas tratados en ese volumen. Las selecciones utilizan como fuentes los resultados de investigaciones publicadas en revistas científicas revisadas por expertos, junto con interpretaciones añadidas por expertos.
Los libros electrónicos están diseñados para dar a conocer las últimas investigaciones recogidas en las cinco series de libros electrónicos bilingües BioMed, con un total de 37 volúmenes a los profesionales sanitarios en ejercicio. Estas cinco series de libros electrónicos abarcan las siguientes especialidades médicas: enfermedades cardiovasculares y su tratamiento, genómica, etiología del cáncer y tratamientos oncológicos, inmunología, y medicina de precisión centrada en el paciente.
El material contenido en estos volúmenes puede enriquecer enormemente la educación médica y aportar un recurso para la actualización y formación continua de los profesionales sanitarios. Además de los 37 libros electrónicos, LPBI ha publicado más de 6 000 artículos en su revista científica en línea «PharmaceuticalIntelligence.com», que cuenta con más de 2,2 millones de visitas desde su lanzamiento en abril de 2012. Los artículos más importantes han tenido más de 15 000 visitas.
Los autores de las selecciones forman parte de un equipo de eminentes académicos reunidos y dirigidos por la Dra. Aviva Lev-Ari, PhD., RN., redactora jefe de la serie de libros electrónicos BioMed y fundadora de LPBI Group. La Dra. Lev-Ari también colaboró en muchos artículos de estas colecciones.
Como líder de LPBI Group, la Dra. Aviva Lev-Ari ha participado como profesional de prensa y medios de comunicación en más de 70 conferencias mundiales, que ha cubierto en persona en tiempo real y ha elaborado actas electrónicas y colecciones de tweets citadas en numerosos artículos de revistas y libros. La Dra. Lev-Ari afirmó: «Estoy satisfecha con que los libros electrónicos en inglés hayan recibido más de 140 000 descargas. Esto es un claro indicio de que nuestro trabajo ha sido un éxito». La edición en español, que se ofrece con un 25 % de descuento, llegará a los profesionales sanitarios de 22 países de habla hispana.
Version #3: English-language with additional details
Curators: Aviva Lev-Ari, PhD, RN and Stephen J. Williams, PhD
Leaders in Pharmaceutical Business Intelligence (LPBI) Group would like to announce the completion of the Translation in the Spanish-language of their’s Five Seriesof BioMedical E-Books, containing 18 Volumes total in the English-language. Translation was performed by Montero Language Services, Madrid, Spain.
Five Bilingual BioMed e-Series – 37 volumes
English-language Edition: 18 volumes in 17 books, and
Spanish-language Edition (EDICIÓN EN ESPAÑOL): 19 volumes in 19 books
All the details on book structure and content in the Spanish-language Edition is found in
These e-Books are a comprehensive review of recent original research on Cardiovascular, Genomics, Cancer, Immunology and Precision Medicine written by Experts, Authors, Writers. These e-books are ushered in the paradigm shifts in how we think about, diagnoses, diagnostics and therapeutics. The results of original research are gaining value added for the e-Reader by the Methodology of Curation. These Biomedical e-Books are well suited for medical and graduate school course curriculum development and as medical textbooks.
All the articles in these e-books were published in
an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of life sciences, pharmaceutical, healthcare & medicine industries. This journal was launched in 4/2012 by Dr. Aviva lev-Ari, PhD, RN who serves as the Editor-in-Chief to the Present.
The venture, DBA, LPBI Group operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and had published 37 Medical e-book in five Bilingual e-Series as Amazon’s Kindle Edition.
Crucial to innovation in the medical field is overcoming the scientific information overload. LPBI Group innovates by:
delivering curation and clinical interpretations of latest biological scientific findings with future goals of providing concept-driven search across the journal, the books and the conference e-proceedings on a networked blockchain platform. The curation methodology offers academic, clinical, and industrial research digital content globally accessible on the Internet and Web 3.0
providing a social platform for scientists and clinicians to enter into discussion using social media as evidenced by multiple comments to journal articles
continued updating to the article repository keeps the e-books content current. All new articles on these subjects, will continue to be incorporated, as published with periodical updates.
incorporation of information from conference covered in real time by EAWs
projects on Text analysis with machine learning
software application to drug discovery in the Galectins domain
Use of Systems Biology for Design of inhibitor of Galectins as Cancer Therapeutic – Strategy and Software
Curator:Stephen J. Williams, Ph.D.
Below is a slide representation of the overall mission 4 to produce a PROTAC to inhibit Galectins 1, 3, and 9.
Using A Priori Knowledge of Galectin Receptor Interaction to Create a BioModel of Galectin 3 Binding
Now after collecting literature from PubMed on “galectin-3” AND “binding” to determine literature containing kinetic data we generate a WordCloud on the articles.
This following file contains the articles needed for BioModels generation.
From the WordCloud we can see that these corpus of articles describe galectin binding to the CRD (carbohydrate recognition domain). Interestingly there are many articles which describe van Der Waals interactions as well as electrostatic interactions. Certain carbohydrate modifictions like Lac NAc and Gal 1,4 may be important. Many articles describe the bonding as well as surface interactions. Many studies have been performed with galectin inhibitors like TDGs (thio-digalactosides) like TAZ TDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside). This led to an interesting article
.
Dual thio-digalactoside-binding modes of human galectins as the structural basis for the design of potent and selective inhibitors
Human galectins are promising targets for cancer immunotherapeutic and fibrotic disease-related drugs. We report herein the binding interactions of three thio-digalactosides (TDGs) including TDG itself, TD139 (3,3′-deoxy-3,3′-bis-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside, recently approved for the treatment of idiopathic pulmonary fibrosis), and TAZTDG (3-deoxy-3-(4-[m-fluorophenyl]-1H-1,2,3-triazol-1-yl)-thio-digalactoside) with human galectins-1, -3 and -7 as assessed by X-ray crystallography, isothermal titration calorimetry and NMR spectroscopy. Five binding subsites (A-E) make up the carbohydrate-recognition domains of these galectins. We identified novel interactions between an arginine within subsite E of the galectins and an arene group in the ligands. In addition to the interactions contributed by the galactosyl sugar residues bound at subsites C and D, the fluorophenyl group of TAZTDG preferentially bound to subsite B in galectin-3, whereas the same group favored binding at subsite E in galectins-1 and -7. The characterised dual binding modes demonstrate how binding potency, reported as decreased Kd values of the TDG inhibitors from μM to nM, is improved and also offer insights to development of selective inhibitors for individual galectins.
Figures
Figure 1. Chemical structures of L3, TDG…
Figure 2. Structural comparison of the carbohydrate…
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 video, slides; March 2021 video, slides). 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
Abstract
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.
Abstract:
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.
JOURNAL OF ECONOMIC LITERATURE
Abstract
Does academic economic research produce material of general scientific value, or do academic economists write only for peers? Is economics scholarship uniquely insular? We address these questions by quantifying interactions between economics and other disciplines. Changes in the influence of economic scholarship are measured here by the frequency with which other disciplines cite papers in economics journals. We document a clear rise in the extramural influence of economic research, while also showing that economics is increasingly likely to reference other social sciences. A breakdown of extramural citations by economics fields shows broad field influence. Differentiating between theoretical and empirical papers classified using machine learning, we see that much of the rise in economics’ extramural influence reflects growth in citations to empirical work. This growth parallels an increase in the share of empirical cites within economics. At the same time, some disciplines that primarily cite economic theory have also recently increased citations of economics scholarship.
Citation
Angrist, Josh, Pierre Azoulay, Glenn Ellison, Ryan Hill, and Susan Feng Lu. 2020.“Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship.”Journal of Economic Literature, 58 (1): 3-52.DOI: 10.1257/jel.20181508
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
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 staff, delegating 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.
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?
To apply it to all the articles in the following e-Series: Series A: 6 volumes, Series B: two volumes, Series C: two volumes, Series D: four volumes, Series E: four volumes
How to Start?
In PART B of every Volume you will find the electronic Table of Contents (eTOCs) of the e-Book
EXCEPTIONS:
In Series C: Cancer Volume One, eTOCs is in A.2
In Series B: Genomics Volume Two eTOCs is in A.2
STEPS in Production of WordClouds for each article in an e-Book
1. You sign in to WordItOut.com
2. You review all the steps to produce a WordCloud from an MS Word File
3. You click on the URL of the 1st article in Volume 1
4. You copy the article into an MS Word File
5. You use this file on WordItOut.com website to produce a WordCloud for the 1st article
6. You edit the output by removing meaning less words like connective term: the a, an, all, some, more
7. You RUN again on a file that does not include the terms REMOVED
8. You select a Scheme of colors for background and for fonts – optimize contrast for visibility and legibility
9. YOU MAINTAIN 8, above for all the articles in ONE volume
10. YOUR FINAL WordCloud for ONE article you upload to the Media Gallery on our Website. You write as Legend Based on Article Title: Quote here Title. Produced on date by your name
11. You go to the 1st article you ADD Media, this WordCloud you had produced BELOW the NAME of the Author, Curator, Reporter. YOU UPDATE the article with your WordCloud. You View Page for QA
12. You move to repeat all of the above for 2nd article in the same volume
13. When you complete ONE volume you announce that Volume X has all the WordClouds in it
14. You move to other Volumes in the series you are working on. If it is Series A, then you continue with Volumes Two, Three, Four, Five, Six
15. YOU START WITH VOLUME ONE AND LET ME KNOW how many hours it took to create all the wordClouds, N=number of articles in Volume One
16. We will decide regarding other Volumes in the same series
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.
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?
[Laughter]
No?
[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
Tweets at #WMIF2022 by @pharma_BI & @AVIVA1950 and All Retweets of these Tweets – 2022 World Medical Innovation Forum, GENE & CELL THERAPY • MAY 2–4, 2022 • BOSTON
Real Time coverage: Aviva Lev-Ari, PhD, RN
Updated on 5/9/2022
Lessons on the Frontier of Gene & Cell Therapy – The Disruptive Dozen 12 #GCT Breakthroughs that are revolutionizing Healthcare
#genetherapy for tuberous sclerosis complex tested on mice found effective in combination with drug in use longer survival to 150 days 10,000 cases in US per year, gene therapy most promising for this gene malfunction #WMIF2022
Take a First Look at Dr. Vijaya Ramesh’s research demonstrating preclinical efficacy of an #AAV-based #genetherapy for tuberous sclerosis complex, setting the stage for future IND-enabling studies & clinical translation. #WMIF2022@MGH_RI@MGHNeurologyhttps://youtube.com/watch?v=-I_XiSyB02I/?cid=cor4079l&utm_medium=social&utm_source=twitter&utm_campaign=mgb-corporate-wmif2022
Top 6 #WMIF2022#GCT#CARTTherapy#DisruptiveDozen@MGBInnovation@pharma_BI@AVIVA1950 1 Restoring sight by edit genes 2 A gene editing solution supply of donor organs 3 Cell therapies for blindness 4 RNA to treat brain cancer 5 #GCT for brain disorders 6 fighting viruses
#KOL on #Cell therapies: #CAR-T cells and #stem-cell-based approaches is moderator for Cell Therapy Landscape: Marcela Maus, MD, PhD Director, Cellular #Immunotherapy Program, #Cancer Center, MGH Associate Professor, Medicine, HMS @MGBInnovation@pharma_BI@AVIVA1950#WMIF2022
Global views #GCT Christine Fox, Novartis Gene Therapies C. Baum, MD, Berlin Institute of Health Nicholas Galakatos, PhD, Blackstone Luigi Naldini, MD, PhD Telethon Institute, Kendra Rose, PhD, Bayer #WMIF2022@MGBInnovation@MassGenBrigham@pharma_BI@AVIVA1950
#Chronic#Neuroinflammation#MS, #AD, #Parkinsons#GCT#genomics Ole Isacson, MD, PhD @McLean Colin Hill CEO, GNS Spyros P., MD, PhD Vigil, Ransohoff, MD, Abata & Third Rock, B. Stevens, PhD, Boston Children’s R. Tanzi, PhD @MGH#WMIF2022@MGBInnovation@pharma_BI@AVIVA1950
#fundraising#GCT#startups Panelists: Shelley Chu, MD, PhD Partner, Lightspeed Stephen Knight, MD President, F-Prime Capital Adam Koppel, MD, PhD, Bain Capital Life Sciences Daniel Krizek Portfolio Manager, Citadel #WMIF2022@MGBInnovation@MassGenBrigham@pharma_BI@AVIVA1950
#fundraising#GCT#startups Panelists: Shelley Chu, MD, PhD Partner, Lightspeed Stephen Knight, MD President, F-Prime Capital Adam Koppel, MD, PhD, Bain Capital Life Sciences Daniel Krizek Portfolio Manager, Citadel #WMIF2022@MGBInnovation@MassGenBrigham@pharma_BI@AVIVA1950
Jean-François Formela, MD, Partner @atlasventure on stage with profound #insights on the #interface and seam line between #Medical applications #investment in #health#innovations#WMIF2022@MGBInnovation@MassGenBrigham@pharma_BI@AVIVA1950#vision and #inspirations
#1 #global#conference#CGT#WMIF2022@MGBInnovation World Medical Innovation Forum #translation and #regenerative#medicine#gene#editing#gene#therapy@pharma_BI@AVIVA1950 Therapeutics Promise #CGT for #Cardiovascular#Diseases since 12/26/2015 https://lnkd.in/dwqM3K3
Someone in the US is diagnosed with #Alzheimers roughly every 60 seconds. Dr. Stephen Haggarty @neuro_mgh shares a First Look at his work to prevent the accumulation of toxic proteins that cause age-dependent #neurodegeneration at #WMIF2022. https://worldmedicalinnovation.org/wp-content/uploads/2022/04/Partners-FORUM-2022-ABSTRACTS-First-Look-220420_0832-X3-HAGGERTY.pdf…
Michael Young, PhD, Schepens Eye Research Institute @MassEyeAndEar, shares preview of new gel delivery system for eye diseases like retinitis pigmentosa at FirstLook research updates @MGBInnovation#WMIF2022
#1 #global#conference#CGT#WMIF2022@MGBInnovation World Medical Innovation Forum #translation and #regenerative#medicine#gene#editing#gene#therapy@pharma_BI@AVIVA1950 Therapeutics Promise #CGT for #Cardiovascular#Diseases since 12/26/2015 https://lnkd.in/dwqM3K3
Michael Young, PhD, Schepens Eye Research Institute @MassEyeAndEar, shares preview of new gel delivery system for eye diseases like retinitis pigmentosa at FirstLook research updates @MGBInnovation#WMIF2022
Aviva Lev-Ari@AVIVA1950May 4 Most impressive Panelist on Disruptive Dozen: 12 Technologies That Will Reinvent GCT in the Next Five Years Galit Alter, PhD Natalie Artzi, PhD Fengfeng Bei, PhD Zheng-Yi Chen, DPhil Matthew Frigault, MD Michael Gilmore, PhD #WMIF2022@MGBInnovation@pharma_BI@AVIVA1950
Visit Amazon’s Series A: Cardiovascular Diseases Page and shop for all Series A: Cardiovascular Diseases books. Check out pictures, author information, and reviews of Series A: Cardiovascular Diseases
is doing a great job of quickly posting sessions YouTube channel for those who cannot attend.
youtube.com
World Medical Innovation Forum
The World Medical Innovation Forum is a global gathering of more than 1,200 senior health care leaders hosted by Mass General Brigham in the heart of Boston. It was established to respond to the…
Visit Amazon’s Series A: Cardiovascular Diseases Page and shop for all Series A: Cardiovascular Diseases books. Check out pictures, author information, and reviews of Series A: Cardiovascular Diseases
Congratulations to William Curry, MD, @WTCNeuroscience the new chief medical officer of #MassGeneral and the MGPO, effective 6/1. We know he will continue his work to improve the outcomes for patients and train the next generation of leaders. @MGHNeurosurg
#WMIF2022 – World Medical Innovation Forum – Social Media Analytics and Transcripts
How will gene and cell therapy change health care? Join CEOs, industry leaders, and Harvard’s top medical faculty to assess the future of medicine and the
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Aviva Lev-Ari
@AVIVA1950
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#WMIF2022#glioblastoma, the most common malignant brain tumor, and one of the most treatment-resistant and fatal human diseases
Dr. Anna Krichevsky shares a First Look at her work developing #RNA-targeting therapies for #glioblastoma, the most common malignant brain tumor, and one of the most treatment-resistant and fatal human diseases. #WMIF2022 Read the full abstract here: https://worldmedicalinnovation.org/wp-content/uploads/2022/04/Partners-FORUM-2022-ABSTRACTS-First-Look-220420_0832-X3-KRICHEVSK.pdf…
Great way to start the week. @MGBInnovation World Medical Innovation Forum. 3 days of #CGT talks! #WMIF2022@MassGenBrigham#worldclass#PatientDriven TY @ChrisMarkCOBURN and team for all you do for patients! @JLL#lifesciencebroker
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
A stream of Ten INNOVATIONS in the Life of LPBI since
inception in 2012 to 2022
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/
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
At LPBI, Curation of scientific findings was performed in +6,000 articles with +2MM e-Views by Global e-Readers
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
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.
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
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.
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
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
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/
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview David Ferrucci Founder, CEO & Chief Scientist, Elemental Cognition machine do not understand human reasoning is different bias inductions extrapulate decisions my machines are not trusted accountability understand why this decision
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Natasha Jaques Senior Scientist, Google Brain Prior work with deep RL adversaries automatic curriculum generalized environment Agent learning emergent complexity domain randomization minimax adversarial paired App Web Navigation
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Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Natasha Jaques Senior Research Scientist, Google Brain social environment and complex behavior generalization and transfer deep RL domain randomization partial observability complex environments Adversarial environment generation
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview JSameena Shah Managing Director, J.P. Morgan AI Research, JP Morgan Chase Data discovery search task aware move away from general search point solution build new components data discovery on use cases problems key not solutions
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Tara Chklovski Founder & CEO, Technovation education sector to empower girl donors and partners bias against minorities and girls financial capability of girls in the future building resilient communities the Planet can thrive
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Tony Jebara VP Eng Head of ML, Spotify Data shared models audio analytics experience user affinity to music ai search page playlist assembling liking skipping ml to find album found attribution content understanding similar tracks
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Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Tony Jebara VP Eng Head of ML, Spotify unlock human creativity in audio listeners-audio recommendations & music creators-curations scale 200MM users, millions podcast titles, 4Bil music playlists music and podcast relations
Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Darcy MacClaren Digital Supply Chain, SAP NA flow offshoring cut cost 1/2020 pandemic in China in 3/2020 supply chain was predicted to stop SAP uses digital-twin supply chain Resiliency is a digital twin ai human areas automation
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Aviva Lev-Ari@AVIVA1950Mar 30#EmTechDigital@AVIVA1950@pharma_BI@techreview Darcy MacClaren Digital Supply Chain, SAP NA David Simchi-Levi Director, Data Science Lab, MIT supply chain Resiliency mapping digitization segmentation smart planning execution logistics expensive loss flexibility demand planing
