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r/science is an Internet forum on Reddit where the community of participants discuss science topics. A popular feature of the forum is "Ask Me Anything" (AMA) public discussions. As of 2014, r/science attracted 30,000100,000 visitors per day, making it the largest community-managed science forum and an attractive place to host discussions. It has over 33 million members as of 2024.
== History ==
=== Nathan Allen ===
Nathan Allen is an American chemist. While working as a chemist at Dow Chemical Company, Allen began to imagine that scientists could use Reddit's "ask me anything" (AMA) interview format to create discussions between scientists and the public. Allen became a forum moderator there and has since been prominent in guiding the culture of the community there and as a spokesperson for the forum. Allen has advocated that chemists should be more active in communicating with the public in online forums such as reddit.
=== AMA series ===
As of 2014, r/science attracted 30,000100,000 visitors per day, making it the largest community-managed science forum and an attractive place to host discussions. In January 2014 Allen began the r/science AMA series with the goal of raising the visibility of scientists who are producing groundbreaking work in their fields but who are not well known outside of their fields. Outgoing links posted in the forum must go to peer-reviewed science articles published within the last six months.
The discussion series was instantly a success, and established the world's largest two-way discussion between scientists and the public. Allen does most of the organization for the talks, including soliciting scientists to participate and training them to communicate in reddit's discussion format.
In May 2018, the series ended due to a change in Reddit's ranking algorithm making AMA talks less visible and less engaging.
== Featured content ==
r/science has an ongoing content partnership with PLOS. As an academic journal, PLOS invites authors who are publishing scientific papers to publicly present their work in r/science and to participate in community "ask me anything" discussions in the forum at scheduled times.
== Editorial decisions ==
Editorial decisions in r/science are made by the moderators who themselves follow rules that they present for the forum. If new rules are introduced then those are discussed with the community of readers. Rules for r/science include guidance that contributors keep discussion on-topic and thoughtful.
Allen led the decision to ban discussion in r/science which gives credibility to climate change denial.
== References ==
== Further reading ==
Quartz published a series of journalism articles describing the outcomes of r/science AMAs
Hasenkopf, Chris (15 January 2017). "Why every scientist should hold an AMA on Reddit and how to do it, step-by-step". Medium.
== External links ==
Official website

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title: "Reinventing Discovery"
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Reinventing Discovery: The New Era of Networked Science is a book written by Michael Nielsen and released in October 2011. It argues for the benefits of applying the philosophy of open science to research.
== Summary ==
The following is a list of major topics in the book's chapters.
Reinventing Discovery
Online Tools Make Us Smarter
Kasparov versus the World, The Wisdom of Crowds, various online collaborative projects
Restructuring Expert Attention
InnoCentive, collective intelligence, Paul Seabright's economic theory, online chat
Patterns of Online Collaboration
History of Linux, Open Architecture Network, Wikipedia, MathWorks' computer programming contest
The Limits and the Potential of Collective Intelligence
communication in small groups, particularly as studied by Stasser and Titus; praxis of science; a discussion of communication among scientists
All the World's Knowledge
Don R. Swanson and Literature-based discovery, predicting influenza with Google searches, Sloan Digital Sky Survey, Allen Institute for Brain Science, Ocean Observatories Initiative, Human Genome Project, Google Translate, playchess.com Tournaments
Democratizing Science
Galaxy Zoo, Foldit, citizen science, eBird, open access, arXiv, PLoS
The Challenge of Doing Science in the Open
Complexity Zoo, academic publishing, BayhDole Act
The Open Science Imperative
Open science, academic journal publishing reform, SPIRES
appendix - The problem solved by the Polymath Project
== Reviews ==
Timo Hannay's review in Nature said that in this book Nielsen gives "the most compelling and comprehensive case so far for a new approach to science in the Internet age".
The Financial Times review said that the book was "the most compelling manifesto yet for the transformative power of networked science".
== References ==
== External links ==
Official website
Interview in Citizen Science Quarterly

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title: "Research Square"
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Research Square is an open-access platform of electronic preprints approved for posting after moderation, but not peer review.
The predecessor of Research Square was American Journal Experts. The platform, Research Square, was established in 2013 and acquired by Springer Nature in 2022.
The server accepts submissions from all fields of research, such as physical, biomedical, and social sciences. As of May 2023, Research Square contains more than 223,000 preprints.
Pre-prints uploaded to Research Square must have a CC-BY license. If it was uploaded elsewhere under a different license (eg. CC-BY-SA) it would violate the terms of that license.
== See also ==
List of academic databases and search engines
List of academic journals by preprint policy
Open-access repository
List of preprint repositories
== References ==

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Sage Bionetworks is a nonprofit organization in Seattle that promotes open science and patient engagement in the research process. It is led by Luca Foschini. It was co-founded by Stephen Friend and Eric Schadt.
== Open science ==
Sage Bionetworks is notable for being an early advocate of open science. The company operates a software platform for collaborative data analysis called Synapse that allows researchers to work together on data curation and computational modeling asynchronously in a manner inspired by GitHub. Synapse also serves as the software infrastructure for running computational challenges. Sage is also developing a citizen-science platform called Bridge.
== Research ==
The bulk of Sage's scientific results emerge from cancer and neurosciences, with notable contributions to the Cancer Genome Atlas Pan-Cancer project. Another Sage initiative, The Resilience Project describes itself as a search for individuals who have genetic changes expected to cause severe illness but who remain perfectly healthy. The hope is to yield insight into factors that protect these individuals from disease. In 2019 Sage Bionetworks has joined Open-AD Drug Discovery Center, which aims to find new Alzheimer's drugs. “This project stitches together open science approaches in computational and experimental research,” Sage president Dr. Lara Mangravite said in a statement.
== History ==
Sage Bionetworks was founded in 2009 as a spinout of Merck & Co., who released software, hardware, intellectual property, and staff connected to its Rosetta Inpharmatics unit. A donation from Quintiles provided early funding.
In March 2011 Sage partnered with CHDI Foundation to develop computer simulations for studying Huntington's disease. At the same time Sage also announced a partnership with Takeda Pharmaceutical Company wherein Sage would do research to identify biological targets for central nervous system diseases.
In February 2013, Sage Bionetworks partnered with the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project to provide expertise and infrastructure for DREAM Challenges on the Synapse.org platform.
In September 2019, Sage announced a partnership with Cornell Tech, the University of California, San Francisco, Open mHealth and The Commons Project to develop an electronic health data management program called CommonHealth. The program would use Health Level Seven International standards for compatibility with both Apple Health and a similar app on Android devices.
== See also ==
The Resilience Project
== References ==
== External links ==
Sage Bionetworks
Synapse
DREAM Challenges

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Science 2.0 is a suggested new approach to science that uses information-sharing and collaboration made possible by network technologies. It is similar to the open research and open science movements and is inspired by Web 2.0 technologies. Science 2.0 stresses the benefits of increased collaboration between scientists. Science 2.0 uses collaborative tools like wikis, blogs and video journals to share findings, raw data and "nascent theories" online. Science 2.0 benefits from openness and sharing, regarding papers and research ideas and partial solutions.
A general view is that Science 2.0 is gaining traction with websites beginning to proliferate, yet at the same time there is considerable resistance within the scientific community about aspects of the transition as well as discussion about what, exactly, the term means. There are several views that there is a "sea change" happening in the status quo of scientific publishing, and substantive change regarding how scientists share research data. There is considerable discussion in the scientific community about whether scientists should embrace the model and exactly how Science 2.0 might work, as well as several reports that many scientists are slow to embrace collaborative methods and are somewhat "inhibited and slow to adopt a lot of online tools."
== Definitions ==
The term has many meanings and continues to evolve in scientific parlance. It not only describes what is currently happening in science, but describes a direction in which proponents believe science should move towards, as well as a growing number of websites which promote free scientific collaboration.
The term Science 2.0 suggests a contrast between traditional ways of doing science, often denoted Science 1.0, with more collaborative approaches, and suggests that the new forms of science will work with Web 2.0 technologies. One description from Science is that Science 2.0 uses the "networking power of the internet to tackle problems with multiple interacting variables - the problems, in other words, of everyday life." A different and somewhat controversial view is that of Ben Shneiderman, who suggested that Science 2.0 combines hypothesis-based inquiries with social science methods, partially for the purpose of improving those new networks.
While the term describes websites for sharing scientific knowledge, it also includes efforts by existing science publishers to embrace new digital tools, such as offering areas for discussions following published online articles. Sometimes it denotes open access which, according to one view, means that the author continues to hold the copyright but that others can read it and use it for reasonable purposes, provided that the attribution is maintained. Most online scientific literature is behind paywalls, meaning that a person can find the title of an article on Google but they can not read the actual article. People who can access these articles are generally affiliated with a university or secondary school or library or other educational institution, or who pay on a per-article or subscription basis.
Traditional scientific journals are part of this social evolution too, innovating ways to engage scientists online and enable global collaboration and conversation. Even the 187-year-old Annals of the New York Academy of Sciences has joined the digital age. The Academy now permits free public access to selected online content and has digitized every volume dating back to 1823.
One view is that Science 2.0 should include an effort by scientists to offer papers in non-technical language, as a way of reaching out to non-scientists. For others, it includes building vast databases of case histories. There is a sense in which Science 2.0 indicates a general direction for scientific collaboration, although there is little clarity about how exactly this might happen. One aim is to "make scientific collaboration as easy as sharing videos of trips home from the dentist," according to one view.
Closely related terms are "cyberscience" focussing on scientists communicating in the cyberspace and "cyberscience 2.0" expanding the notion to the emerging trend of academics using Web 2.0 tools.
== History and background ==
The rise of the Internet has transformed many activities such as retailing and information searching. In journalism, Internet technologies such as blogging, tagging and social networking have caused many existing media sources such as newspapers to "adopt whole new ways of thinking and operating," according to a report in Scientific American in 2008. The idea is that while the Internet has transformed many aspects of life, it has not changed scientific research as much as it could. While firms such as eBay, Amazon and Netflix have changed consumer retailing, and online patient-centered medical data has enabled better health care, Science 2.0 advocate Ben Shneiderman said:
It's time for researchers in science to take network collaboration like this to the next phase and reap the potential intellectual and societal payoffs.
According to one view, a similar web-inspired transformation that has happened to other areas is now happening to science. The general view is that science has been slower than other areas to embrace the web technology, but that it is beginning to catch up.

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Before the Internet, scientific publishing has been described as a "highly integrated and controlled process." Research was done in private. Next, it was submitted to scientific publications and reviewed by editors and gatekeepers and other scientists. Last, it was published. This has been the traditional pathway of scientific advancement, sometimes dubbed Science 1.0.
Established journals provided a "critical service", according to one view. Publications such as Science and Nature have large editorial staffs to manage the peer-review process as well as have hired fact-checkers and screeners to look over submissions. These publications get revenue from subscriptions, including online ones, as well as advertising revenue and fees paid by authors. According to advocates of Science 2.0, however, this process of paper-submission and review was rather long. Detractors complained that the system is "hidebound, expensive and elitist", sometimes "reductionist", as well as being slow and "prohibitively costly". Only a select group of gatekeepers—those in charge of the traditional publications—limited the flow of information. Proponents of open science claimed that scientists could learn more and learn faster if there is a "friction-free collaboration over the Internet."
Yet there is considerable resistance within the scientific community to a change of approach. The act of publishing a new finding in a major journal has been at the "heart of the career of scientists," according to one view, which elaborated that many scientists would be reluctant to sacrifice the "emotional reward" of having their discoveries published in the usual, traditional way. Established scientists are often loath to switch to an open-source model, according to one view.
Timo Hannay explained that the traditional publish-a-paper model, sometimes described as "Science 1.0", was a workable one but there need to be other ways for scientists to make contributions and get credit for their work:
The unit of contribution to the scientific knowledge base has become the paper. Journals grew up as a means for scientists to be able to share their discoveries and ideas. The incentive for doing so was that by publishing in journals their contributions would be recognized by citation and other means. So you have this pact: be open with your ideas and share them through journals and you will get credit... There are all kinds of ways in which scientists can contribute to the global endeavor. ... The incentive structure has not caught up with what we really want scientists to do.
In 2008, a scientist at the University of Maryland named Ben Shneiderman wrote an editorial entitled Science 2.0. Shneiderman argued that Science 2.0 was about studying social interactions in the "real world" with study of e-commerce, online communities and so forth. A writer in Wired Magazine criticized Shneiderman's view, suggesting that Shneiderman's call for more collaboration, more real-world tests, and more progress should not be called "Science 2.0" or "Science 1.0" but simply science.
There are reports that established journals are moving towards greater openness. Some help readers network online; others enable commenters to post links to websites; others make papers accessible after a certain period of time has elapsed. But it remains a "hotly debated question", according to one view, whether the business of scientific research can move away from the model of "peer-vetted, high-quality content without requiring payment for access." The topic has been discussed in a lecture series at the California Institute of Technology. Proponent Adam Bly thinks that the key elements needed to transform Science 2.0 are "vision" and "infrastructure":
Open science is not this maverick idea; it's becoming reality. About 35 percent of scientists are using things like blogs to consume and produce content. There is an explosion of online tools and platforms available to scientists, ranging from Web 2.0 tools modified or created for the scientific world to Web sites that are doing amazing things with video, lab notebooks, and social networking. There are thousands of scientific software programs freely available online and tens of millions of science, technology, and math journal articles online. What's missing is the vision and infrastructure to bring together all of the various changes and new players across this Science 2.0 landscape so that it's simple, scalable, and sustainable—so that it makes research better.
== Proliferation on the web ==
There are numerous examples of more websites offering opportunities for scientific collaboration.

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Public Library of Science. This project, sometimes termed PLoS, is a nonprofit open-access scientific publishing project aimed at creating a library of open access journals and other scientific literature under an open content license. By 2012, it publishes seven peer reviewed journals. It makes scientific papers immediately available online without charges for access or restrictions on passing them along, provided that the authors and sources are properly cited with the Creative Commons Attribution License. According to one report, the PLoS has gained "pretty wide acceptance" although many researchers in biomedicine still hope to be published in established journals such as Nature, Cell, and Science, according to one report. PLoS publishes 600 articles a month in 2012.
arXiv, pronounced archive, is an online-accessible archive for electronic preprints of scientific papers in the fields of mathematics, physics, astronomy, computer science, quantitative biology, statistics, and quantitative finance.
Galaxy Zoo is an online astronomy project which invites members of the public to assist in the morphological classification of large numbers of galaxies. It has been termed a citizen science project. The information has led to a substantial increase in scientific papers, according to one account.
A website entitled Science 2.0 lets scientists share information. It has been cited by numerous publications, many of which have been written stories with links to Science 2.0 articles such as USA Today, CNN, the Wall Street Journal, the New York Times, and others. The Science 2.0 topics included neutrino interactions, cosmic rays, the human eye's evolution, the relation between sex and marital happiness for elderly couples, human evolution, hearing loss, and other topics.
OpenWetWare is a wiki site started by biologists at the Massachusetts Institute of Technology to foster open research, education, and discussion in the biological sciences and engineering.
Some examples of pioneering use of Science 2.0 to foster biodiversity surveys were popularized by Robert Dunn, including urban Arthropods and human body bacteria.
OpenWorm is a collaborative research project with several publications that aims to simulate the nervous system, body mechanics, and environment of the C. elegans worm.
== See also ==
Crowdsourcing
eScience
== References ==
== External links ==
Public Library of Science Archived 2012-09-20 at the Wayback Machine online open access journals
OpenWetWare link to OpenWetWare, a MIT-based biological information sharing wiki
Epernicus - social network for investigators looking for people and techniques to solve research problems
Journal of Visualized Experiments - peer-reviewed journal of videos demonstrating experiment protocols
Mozilla Science Lab - collaborative project to further science on the web
Proteome Commons - collaboration on proteomics
WikiSpecies - open directory of all species of life
Mendeley - academic software for research papers
Zotero - free and open source software for collection, organization, citing, and sharing research sources
SklogWiki - an open-edit encyclopedia dedicated to thermodynamics and statistical mechanics
Scientific Paper Discussion - forum site for public discussion of scientific papers, also protects unpublished scientific papers using cryptographic hash functions

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Science Commons (SC) was a Creative Commons project for designing strategies and tools for faster, more efficient web-enabled scientific research. The organization's goals were to identify unnecessary barriers to research, craft policy guidelines and legal agreements to lower those barriers, and develop technology to make research data and materials easier to find and use. Its overarching goal was to speed the translation of data into discovery and thereby the value of research.
Science Commons was located at the MIT Computer Science and Artificial Intelligence Laboratory in the Ray and Maria Stata Center at the Massachusetts Institute of Technology in Cambridge, Massachusetts.
== History ==
Creative Commons launched the Science Commons project in early 2005. The project sought to achieve for science what Creative Commons had achieved for the world of culture, art and educational material: to ease unnecessary legal and technical barriers to sharing, to promote innovation, and to provide easy, high quality tools that let individuals and organizations specify the terms under which they wished to share their material.
In 2009, Creative Commons terminated the Science Commons project.
== Projects ==
=== Biological Materials Transfer Project ===
The Biological Materials Transfer Project, a Material transfer agreement (MTA), developed and deployed standard, modular contracts to lower the costs of transferring biological materials such as DNA, cell lines, model animals and more. The MTA project covered transfer between non-profit institutions, as well as offering transaction solutions to transfers between non-profit entities and for-profit institutions. It integrated existing standard agreements and new Science Commons contracts into a Web-deployed suite, with the goal of developing a transaction system along the lines of Amazon or eBay by using the licensing as a discovery mechanism for materials.
This metadata driven approach is based on the success of the Creative Commons licensing integration into search engines, further allowing for and facilitating the integration of materials licensing into the research literature itself and databases. The hope being that scientists would eventually be only one click away from accessing and/or ordering the materials referenced in the scholarly literature as they perform their research. Unfortunately, the MTA project's tools were not adopted by more than a very small percentage of the scientific community while Science Commons was active and, for all practical purposes, died out when the Science Commons project folded.
=== Neurocommons ===
Science Commons Neurocommons project set out to create an Open Source knowledge management platform for biological research. The platform combined open access materials (making up the knowledgebase) and open source software (in the form of an analytic platform). The software was still under development when the project ended.
=== Scholar's Copyright Project ===
The Scholars Copyright was developed with Scholarly Publishing and Academic Resources Coalition designed to lower the barriers to Open Access (OA) by reducing transaction costs and eliminating contract proliferation by offering tools and resources catering to both methods of achieving Open Access. The Scholar's Copyright Addendum is still in use by SPARC
==== Open Access Data Protocol ====
The Science Commons Open Access Data Protocol was a method for ensuring that scientific databases can be legally integrated with one another. The protocol was not a license or legal tool, but instead a methodology and best practices document for creating such legal tools in the future, and marking data in the public domain for machine-assisted discovery.
== References ==
== External links ==
Creative Commons
"Sciencecommons.org". Archived from the original on January 2, 2011. (Former official site)
MIT Libraries Podcast with Creative Commons VP for Science John Wilbanks
Popular Science interview with Creative Commons VP for Science John Wilbanks

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Studierfenster or StudierFenster (SF) is a free, non-commercial open science client/server-based medical imaging processing online framework. It offers capabilities, like viewing medical data (computed tomography (CT), magnetic resonance imaging (MRI), etc.) in two- and three-dimensional space directly in the standard web browsers, like Google Chrome, Mozilla Firefox, Safari, and Microsoft Edge. Other functionalities are the calculation of medical metrics (dice score and Hausdorff distance), manual slice-by-slice outlining of structures in medical images (segmentation), manual placing of (anatomical) landmarks in medical image data, viewing medical data in virtual reality, a facial reconstruction and registration of medical data for augmented reality, one click showcases for COVID-19 and veterinary scans, and a Radiomics module.
Other features of Studierfenster are the automatic cranial implant design with a neural network, the inpainting of aortic dissections with a generative adversarial network, an automatic aortic landmark detection with deep learning in computed tomography angiography scans, and a GrowCut algorithm implementation for image segmentation.
Studierfenster is currently hosted on a server at the Graz University of Technology in Austria, and expanded jointly with the Institute for Artificial Intelligence in Medicine (IKIM) in Essen, Germany.
== History ==
Studierfenster was initiated within two bachelor theses during the summer bachelor program of the Institute of Computer Graphics and Vision (ICG) at Graz University of Technology, Austria, in cooperation with the Medical University of Graz, Austria, in 2018/2019.
The name Studierfenster (or StudierFenster) is German and can be translated to 'StudyWindow', whereby window refers here to a browser window. The word Studierfenster is an adaption from the word Studierstube ('study room'), which was an augmented reality project at the Vienna University of Technology in Austria.
== Architecture ==
Studierfenster is set up as a distributed application via a clientserver model. The client side (front-end) consists of HTML and JavaScript with WebGL to enable 2D and 3D visualization, rendered on the client.
The server side (back-end) handles client requests via C, C++ and Python. It interfaces to common open source libraries and software tools like the Insight Toolkit, the Visualization Toolkit (VTK), the X Toolkit (XTK) and Slice:Drop. The server communication is handled by AJAX requests were needed.
Studierfenster employs a Flask server.
== Features ==
=== Dicom browser ===
This allows client-side parsing a local folder with DICOM (Digital Imaging and Communications in Medicine) files. Afterwards, the whole folder can be converted to compressed .nrrd (nearly raw raster data) files and downloaded as a single .zip file.
Nrrd is a library and file format for the representation and processing of n-dimensional raster data. It is intended to support scientific visualization and (medical) image processing applications. With the "Dicom Browser" of Studierfenster, it is possible to select specific Studies or Series, and only convert these.
=== File converter ===
The file converter converts a medical volume file (e.g. a non-compressed .nrrd file) to a compressed/binary .nrrd file. After the conversion, the compressed .nrrd file can be downloaded and used with the "Medical 3D Viewer" for 2D and 3D visualization, and further image processing.
=== Metrics module ===
This can calculate the Dice similarity coefficient and Hausdorff distance between two segmentation masks (in .nrrd format) in a standard web browser.
The resulting table has seven columns: the file names for both files used in the calculation, the calculated Dice similarity coefficient, the calculated Hausdorff distance, the calculated directed HD for both directions, and the information if image spacing was used in the calculation. The table can be sorted, is searchable, and can be exported as a simple copy, an Excel spreadsheet, a comma-separated values file or as a portable document format.
The Metrics Module has been used to compare manual anatomical segmentations of brain tumors
=== VR viewer ===
The VR Viewer (or Medical VR Viewer) enables viewing (medical) data in Virtual Reality (VR) with devices like the Google Cardboard or the HTC Vive (via the WebVR App). For viewing the data in VR, it needs to be converted to the VTI (.vti) format, which can be done with open-source, multi-platform data analysis and visualization application ParaView
== Critics ==
Studierfenster is not a certified medical product; it can only be used for educational, research, and informational purposes.
== References ==
== External links ==
Studierfenster

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Synapse.org is an open source platform for collaborative scientific data analysis. It can store data, code, results, and descriptions research work. It is operated by nonprofit organization Sage Bionetworks.
The Synapse web portal is an online registry of research projects that allows data scientists to discover and share data, models, and analysis methods.
== References ==

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title: "Target 2035"
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source: "https://en.wikipedia.org/wiki/Target_2035"
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tags: "science, encyclopedia"
date_saved: "2026-05-05T03:50:20.289609+00:00"
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Target 2035 is a global effort or movement to discover open science, pharmacological modulator(s) for every protein in the human proteome by the year 2035. The effort is led by the Structural Genomics Consortium with the intention that this movement evolves organically. Target 2035 has been borne out of the success that chemical probes have had in elevating or de-prioritizing the therapeutic potential of protein targets. The availability of open access pharmacological tools is a largely unmet aspect of drug discovery especially for the dark proteome.
The first five years will include building mechanisms (Phase 1 below) which allow researchers to find collaborators with like-minded goals towards discovering a pharmacological tool for a specific protein or protein family, and make it open access (without encumbrances due to intellectual property). One strategic goal is seeding new open science programs on components of the drug discovery pipeline with the goal to bring medicines to the bedside equitably, affordably and rapidly. Phase 1 will also build a framework that welcomes new and (re-)emerging enabling technologies in hit-finding and characterization. An update on the progress was published.
Target 2035 will draw on successes from past and current publicly-funded programs including National Institutes of Health (NIH) Illuminating the Druggable Genome initiative for under-explored kinases, GPCRs and ion channels, Innovative Medicines Initiative's RESOLUTE project on human SLCs, Innovative Medicines Initiative's Enabling and Unlocking Biology in the Open (EUbOPEN), and Innovative Medicines Initiative's Unrestricted Leveraging of Targets for Research Advancement and Drug Discovery. The NIH recently re-iterated their commitment to making their data open to mitigate the tens of billions due to irreproducible data.
Target 2035 will collaborate with the Chemical Probes Portal and open science platforms, e.g. Just One Giant Lab, in order to spread awareness and education of best practices for chemical modulators and the benefits of open science, respectively.
The following draft plan has been outlined in a white paper.
== Phase 1 ==
The first phase, from 2020 to 2025, would be structured to build the foundation for a concerted global effort, and would aim to collect, characterize and make available existing pharmacological modulators for key representatives from all proteins families in the current druggable genome (~4,000 proteins), as well as to develop critical and centralized infrastructure to facilitate data collection, curation, dissemination, and mining that will power the scientific community worldwide. This phase might also create centralized facilities to provide quantitative genome-scale biochemical and cell-based profiling assays to the federated community, as well as to coordinate the development of new technologies to extend the definition of druggability. This first phase will complement and extend ongoing efforts to create chemical tools and chemogenomic libraries to blanket priority gene families, such as kinases and epigenetics families.
One year into Target 2035 has so far yielded infrastructure to house data on chemogenomic compounds reported in the literature. A progress update was published recently. Towards the development of new technologies, Target 2035 started a new initiative Critical Assessment of Computational Hit-Finding Experiments (CACHE) aimed at benchmarking computational methods for hit-finding. The first competition - finding ligands for the WD40 domain of LRRK2 - started in March 2022. The first round of predictions have been submitted. In the meantime, applications for the second CACHE benchmarking - predicting ligands for the RNA-binding domain for Nsp13 - has been posted.
== Phase 2 ==
The second phase, from 2025 to 2035, will be to apply the new technologies and infrastructure to generate a complete set of pharmacological modulators for > 90% of the ~20,000 proteins encoded by the genome. “Target 2035” sounds ambitious, but its concept and practicality is on firm ground based on a number of pilot studies, which revealed the following success parameters:
Collaborate with the pharmaceutical sector to access unparalleled expertise, experience, materials, and logistics
Establish clear and quantitative quality criteria for the output (target chemical tool profiles) to provide focus
Organize the project around protein families it is the most efficient, practical and scientifically sound way to divide this large project into teams
Establish clear open science principles to eliminate or reduce conflicts of interest, to reduce legal encumbrances, and to encourage participation by the community.
== References ==
== External links ==
Official website