The document summarizes a new software called EventFlow that can model innovation processes as temporal sequences using multiple datasets on drug and medical device development. It describes how EventFlow records each product and displays innovation events like clinical trials and FDA approval on timelines. EventFlow can calculate metrics on the duration and sequence of innovation activities. These metrics and visualizations of networks can help analyze regional innovation clusters and identify strategies to strengthen bridging organizations that support the movement of ideas from research to commercialization.
More than an umbrella term, open science is moving towards broadening and integrating the open access movement to scholarly literature on other fronts, such as open scientific data, open scientific tools, open notebook science, open education, and citizen science.
This “movement of movements” transforms the scenario and the dynamics of science collaboration, communication and dissemination, expanding its ability to respond to contemporary new and complex issues, while posing new challenges. On the one hand, new possibilities arise for the generation of social, economic and environmental benefits, as well as innovation, associated to increased reach, speed and quality of production and circulation of scientific knowledge, its results and possible uses. On the other hand, new institutional and technological requirements are imposed on the adoption of open research policies, strategies, and practices (regulations, capacities, infrastructures, and tools), and the costs derived therefrom. A new economics of open science is being developed, together with new business models, with repercussions on the present and future of scientific journals and their relationship with other scientific publication and publicization systems emerging from this framework, as well as with the monitoring, evaluation and research financing apparatuses.
At the same time, it is about facing the challenge of bridging the gap between science (and its various forms of data availability) and policy. Today there is an abyss in this interface that should be narrowing so that, increasingly, political decisions, particularly those that affect social and environmental issues more directly are based on quality and plural science. To strengthen this relationship, efforts are needed to reconcile languages and times that allow virtuous dialogue between these two fields.
In the end, it is also important to recognize the different implications of this changing scenario regarding more and less developed countries, placing new opportunities and barriers for their science, technology and innovation systems and their respective repositioning in the global scenario.
Syllabus
Open science, science communication and the challenges of sustainable development; open publications and innovation; the new economy (politics) of open science and its infrastructures of scholarly communication: costs and benefits (academic, social, and economic); political and institutional requirements; business models emerging from open scientific publications; opportunities and challenges for developing countries.
Evaluating the value of research-by-consortium: Science of Team ScienceMark David Lim
The model of biomedical research-by-consortium has gained traction internationally. But many are faced with challenges on demonstrating the value that they provide to their various stakeholders. This presentation was made at the 2014 Science of Team Science conference and more open-access material can be found at a recent Science Translational Medicine article http://bit.ly/STMConsortia
Need for an Integrated approach to Formulation Research and Knowledge ManagementAjaz Hussain
1. Confidence in Generics: Need for an Integrated
approach to Formulation Research and Knowledge
Management (Ajaz Hussain)
2. Mechanism for an integrated approach to Formulation
Research, Knowledge Management, & Knowledge
sharing with FDA & Industry (Steve Byrn)
3. Integrated approach for evolving standards for
formulation design - case example NTI's (Ken Morris)
4. Integrated approach for evolving standard for analytical
characterization - case example excipient variability
(Eric Munson)
June 18 NISO Virtual Conference: Transforming Assessment: Alternative Metrics and Other Trends
Keynote Speaker: Altmetrics at the Portfolio Level
- Paul Groth, Ph.D., Assistant Professor at the VU University Amsterdam
How to Create a Big Data Culture in PharmaChris Waller
A talk presented at the Big Data and Analytics conference in Boston on January 28, 2014. Emphasis on data and information sharing cultures in companies.
More than an umbrella term, open science is moving towards broadening and integrating the open access movement to scholarly literature on other fronts, such as open scientific data, open scientific tools, open notebook science, open education, and citizen science.
This “movement of movements” transforms the scenario and the dynamics of science collaboration, communication and dissemination, expanding its ability to respond to contemporary new and complex issues, while posing new challenges. On the one hand, new possibilities arise for the generation of social, economic and environmental benefits, as well as innovation, associated to increased reach, speed and quality of production and circulation of scientific knowledge, its results and possible uses. On the other hand, new institutional and technological requirements are imposed on the adoption of open research policies, strategies, and practices (regulations, capacities, infrastructures, and tools), and the costs derived therefrom. A new economics of open science is being developed, together with new business models, with repercussions on the present and future of scientific journals and their relationship with other scientific publication and publicization systems emerging from this framework, as well as with the monitoring, evaluation and research financing apparatuses.
At the same time, it is about facing the challenge of bridging the gap between science (and its various forms of data availability) and policy. Today there is an abyss in this interface that should be narrowing so that, increasingly, political decisions, particularly those that affect social and environmental issues more directly are based on quality and plural science. To strengthen this relationship, efforts are needed to reconcile languages and times that allow virtuous dialogue between these two fields.
In the end, it is also important to recognize the different implications of this changing scenario regarding more and less developed countries, placing new opportunities and barriers for their science, technology and innovation systems and their respective repositioning in the global scenario.
Syllabus
Open science, science communication and the challenges of sustainable development; open publications and innovation; the new economy (politics) of open science and its infrastructures of scholarly communication: costs and benefits (academic, social, and economic); political and institutional requirements; business models emerging from open scientific publications; opportunities and challenges for developing countries.
Evaluating the value of research-by-consortium: Science of Team ScienceMark David Lim
The model of biomedical research-by-consortium has gained traction internationally. But many are faced with challenges on demonstrating the value that they provide to their various stakeholders. This presentation was made at the 2014 Science of Team Science conference and more open-access material can be found at a recent Science Translational Medicine article http://bit.ly/STMConsortia
Need for an Integrated approach to Formulation Research and Knowledge ManagementAjaz Hussain
1. Confidence in Generics: Need for an Integrated
approach to Formulation Research and Knowledge
Management (Ajaz Hussain)
2. Mechanism for an integrated approach to Formulation
Research, Knowledge Management, & Knowledge
sharing with FDA & Industry (Steve Byrn)
3. Integrated approach for evolving standards for
formulation design - case example NTI's (Ken Morris)
4. Integrated approach for evolving standard for analytical
characterization - case example excipient variability
(Eric Munson)
June 18 NISO Virtual Conference: Transforming Assessment: Alternative Metrics and Other Trends
Keynote Speaker: Altmetrics at the Portfolio Level
- Paul Groth, Ph.D., Assistant Professor at the VU University Amsterdam
How to Create a Big Data Culture in PharmaChris Waller
A talk presented at the Big Data and Analytics conference in Boston on January 28, 2014. Emphasis on data and information sharing cultures in companies.
Real World Evidence - getting value from volume with metadataAnn Kelly
Anne Lapkin from Smartlogic and Bill Fox from MarkLogic webinar on Real World Evidence; the value, the opportunity, the problems and the platform of the future
On December 8, 2008, Bill Appelbe, Chief Executive Officer and Chief Scientist of the Victorian Partnership for Advanced Computing (VPAC) in Australia, was in Calgary to give a special presentation to Cybera’s members. The talk, which was broadcast over videoconference to members in Edmonton and Lethbridge, focused on changing trends in cyberinfrastructure development.
Similar to Cybera, VPAC is a state-based research service provider to industry, academia and government. Appelbe's presentation highlighted the growing number of partnerships developing between VPAC and industry partners.
This presentation was provided by Bert Carelli of TrendMD, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Increasing transparency in Medical Education through Open Data Rebecca Grant
Slides presented at the AMEE Virtual Conference 2021, introducing the MedEdPublish platform and data policies. Approaches to sharing sensitive human data, and particulary qualitative data, are discussed.
This presentation was provided by Stephanie Roth of Temple University, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
25 January 2022: Webinar on Adverse Outcome Pathway co-operative activities b...OECD Environment
On 25 January 2022, the OECD held a webinar on Adverse Outcome Pathway (AOP) co-operative activities between Scientific journals and the OECD.
This webinar was organised primarily for Scientific Journal editors or publishers who are interested in reviewing/publishing AOPs and collaborating with the OECD in this activity.
The objective of the webinar was to present the basis for cooperation between scientific journals and the OECD and discuss the lessons learnt so far.
Dan Villeneuve (US EPA) presented the AOP framework and challenges being encountered.
Access the webinar replay at: https://oe.cd/testing-assessment-webinars
The Green Park Collaborative (GPC) has developed a new tool to help health care decision makers confidently and consistently use Real World Evidence (RWE) when making tough coverage and care choices. Called RWE Decoder, the spreadsheet-based assessment tool lets users review and evaluate all existing studies and evidence for both rigor and relevance. Informed by these factors, users can assess study quality, and generate a visual summary to help gauge the evidence under review.
Published RWE studies developed from data-rich electronic medical records or medical claims data are increasingly available from health care systems. However, the quality of this research can vary widely, and payers, clinicians and other health care decision makers often dismiss it out of hand. RWE Decoder and its associated user guide and framework, offer a thoughtful approach to helping these decision makers assess whether RWE studies address their questions and can appropriately guide their choices.
The tool, user guide, and supporting white paper are available here: https://goo.gl/AhbHUw
Sharpen your Unique Sensing Proclivity: Dissolution is a process in mind and ...Ajaz Hussain
Self-authorship bridging the Academia to Industry (A2I) Gap. The challenge in our systems asking why signifies ignorance. Perhaps until a correction is needed. But after corrective and preventive actions (CAPA) often nothing changes. Errors reoccur and we acquire an “immunity to change.”
One of the basic functions of the SciELO Publishing Model is to follow up the performance of journals, national collections, the network and the overall program. In the context of national collections, which in most cases are financed by public resources and are highly selective regarding indexing, the good performance of journals is expected in line with the specific objectives of SciELO to contribute to their sustainable increase of editorial quality, visibility, use and impact. In addition to the specific objectives that apply to the entire network, national collections are governed by priorities determined by national policies and conditions.
The performance of journals and SciELO collections are evaluated by the following criteria:
• Institutionality, which refers to institutions responsible for the journals and their respective research communities as indicators of credibility and operational sustainability of journals;
• Good practices of editing and scholarly communication, which refers to the adherence to the SciELO indexing criteria that implies in adherence to the good practices of scholarly communication and adoption of innovations;
• Visibility, Use and Impact, which refer to the following contexts:
◦ Access and downloads indicators to articles’ full text files in HTML and PDF formats;
◦ Citations indicators or metrics considering different journal indexes;
◦ Web presence indicators or altmetrics.
The scope proposed for this working group encompasses the analysis of journals performance in accordance with the above criteria, taking into account the specificities of different thematic areas and different countries. The analysis and discussion of these three dimensions will be conducted by scholarly communication and bibliometrics experts with the support of representatives of national collections, journal editors and specialists.
Pharma IQ brings you Clinical Trial Supply Europe Conference Profit. Successfully cutting costs and overages whilst increasing the flexibility and reactivity of your clinical supply network to support global clinical trials.
All patients are different, and data collected during product development or Randomised Clinical Trials (RCT) does not always paint the full picture of everyday patients. RWE insights complement the manufacturing process and RCT findings, adding more value and providing real-world impact. While together data from the manufacturing process and RWD paint a fuller picture.
Due to the limitations of the study design, data from the manufacturing process and RCTs are inadequate for demonstrating an intervention’s long-term safety and effectiveness. Moreover, it is possible to compare multiple product or interventions in RWE.
This presentation was provided by Vincent Cassidy of The IET during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Slide deck from 2008 Symposium "Developing an Expert-System for Health Promotion: An Experimental E-Learning Platform" from the APA-NIOSH International Conference on Work, Stress, and Health
Real World Evidence - getting value from volume with metadataAnn Kelly
Anne Lapkin from Smartlogic and Bill Fox from MarkLogic webinar on Real World Evidence; the value, the opportunity, the problems and the platform of the future
On December 8, 2008, Bill Appelbe, Chief Executive Officer and Chief Scientist of the Victorian Partnership for Advanced Computing (VPAC) in Australia, was in Calgary to give a special presentation to Cybera’s members. The talk, which was broadcast over videoconference to members in Edmonton and Lethbridge, focused on changing trends in cyberinfrastructure development.
Similar to Cybera, VPAC is a state-based research service provider to industry, academia and government. Appelbe's presentation highlighted the growing number of partnerships developing between VPAC and industry partners.
This presentation was provided by Bert Carelli of TrendMD, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Increasing transparency in Medical Education through Open Data Rebecca Grant
Slides presented at the AMEE Virtual Conference 2021, introducing the MedEdPublish platform and data policies. Approaches to sharing sensitive human data, and particulary qualitative data, are discussed.
This presentation was provided by Stephanie Roth of Temple University, during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
25 January 2022: Webinar on Adverse Outcome Pathway co-operative activities b...OECD Environment
On 25 January 2022, the OECD held a webinar on Adverse Outcome Pathway (AOP) co-operative activities between Scientific journals and the OECD.
This webinar was organised primarily for Scientific Journal editors or publishers who are interested in reviewing/publishing AOPs and collaborating with the OECD in this activity.
The objective of the webinar was to present the basis for cooperation between scientific journals and the OECD and discuss the lessons learnt so far.
Dan Villeneuve (US EPA) presented the AOP framework and challenges being encountered.
Access the webinar replay at: https://oe.cd/testing-assessment-webinars
The Green Park Collaborative (GPC) has developed a new tool to help health care decision makers confidently and consistently use Real World Evidence (RWE) when making tough coverage and care choices. Called RWE Decoder, the spreadsheet-based assessment tool lets users review and evaluate all existing studies and evidence for both rigor and relevance. Informed by these factors, users can assess study quality, and generate a visual summary to help gauge the evidence under review.
Published RWE studies developed from data-rich electronic medical records or medical claims data are increasingly available from health care systems. However, the quality of this research can vary widely, and payers, clinicians and other health care decision makers often dismiss it out of hand. RWE Decoder and its associated user guide and framework, offer a thoughtful approach to helping these decision makers assess whether RWE studies address their questions and can appropriately guide their choices.
The tool, user guide, and supporting white paper are available here: https://goo.gl/AhbHUw
Sharpen your Unique Sensing Proclivity: Dissolution is a process in mind and ...Ajaz Hussain
Self-authorship bridging the Academia to Industry (A2I) Gap. The challenge in our systems asking why signifies ignorance. Perhaps until a correction is needed. But after corrective and preventive actions (CAPA) often nothing changes. Errors reoccur and we acquire an “immunity to change.”
One of the basic functions of the SciELO Publishing Model is to follow up the performance of journals, national collections, the network and the overall program. In the context of national collections, which in most cases are financed by public resources and are highly selective regarding indexing, the good performance of journals is expected in line with the specific objectives of SciELO to contribute to their sustainable increase of editorial quality, visibility, use and impact. In addition to the specific objectives that apply to the entire network, national collections are governed by priorities determined by national policies and conditions.
The performance of journals and SciELO collections are evaluated by the following criteria:
• Institutionality, which refers to institutions responsible for the journals and their respective research communities as indicators of credibility and operational sustainability of journals;
• Good practices of editing and scholarly communication, which refers to the adherence to the SciELO indexing criteria that implies in adherence to the good practices of scholarly communication and adoption of innovations;
• Visibility, Use and Impact, which refer to the following contexts:
◦ Access and downloads indicators to articles’ full text files in HTML and PDF formats;
◦ Citations indicators or metrics considering different journal indexes;
◦ Web presence indicators or altmetrics.
The scope proposed for this working group encompasses the analysis of journals performance in accordance with the above criteria, taking into account the specificities of different thematic areas and different countries. The analysis and discussion of these three dimensions will be conducted by scholarly communication and bibliometrics experts with the support of representatives of national collections, journal editors and specialists.
Pharma IQ brings you Clinical Trial Supply Europe Conference Profit. Successfully cutting costs and overages whilst increasing the flexibility and reactivity of your clinical supply network to support global clinical trials.
All patients are different, and data collected during product development or Randomised Clinical Trials (RCT) does not always paint the full picture of everyday patients. RWE insights complement the manufacturing process and RCT findings, adding more value and providing real-world impact. While together data from the manufacturing process and RWD paint a fuller picture.
Due to the limitations of the study design, data from the manufacturing process and RCTs are inadequate for demonstrating an intervention’s long-term safety and effectiveness. Moreover, it is possible to compare multiple product or interventions in RWE.
This presentation was provided by Vincent Cassidy of The IET during the NISO event "Researcher Behaviors and the Impact of Technology," held on March 25, 2020.
Slide deck from 2008 Symposium "Developing an Expert-System for Health Promotion: An Experimental E-Learning Platform" from the APA-NIOSH International Conference on Work, Stress, and Health
Think Link: Network Insights with No Programming SkillsMarc Smith
Networks are everywhere, but the tools for end users to access, analyze, visualize and share insights into connected structures have been absent. NodeXL, the network overview discovery and exploration add-in for Excel makes network analysis as easy as making a pie chart.
Network Models of Regional Innovation Clusters and their Impact on Economic G...Scott Dempwolf
This research uses social network analysis to develop models of regional innovation clusters using data from patent applications and other sources. These new models are more detailed than current industry cluster models, and they reveal actual and potential relationships among firms that industry cluster models cannot. The network models can identify specific clusters of firms with high potential for manufacturing job growth where business retention and expansion efforts may be targeted. They can also identify dense clusters of talent where innovation and entrepreneurial efforts may be targeted. Finally, this research measures relationships between network structure at the time of patent application and manufacturing job growth in subsequent years. This will permit the translation of a wide range of network-building activities into the ubiquitous “jobs created” metric. These new tools will help economic developers focus resources on high-yield activities, and measure the results of networking activities more effectively.
2015 #MMeasure-Marc Smith-NodeXL Mapping social media using social network ma...Marc Smith
Networks are a powerful way to understand social media.
This talk reviews the ways the NodeXL application can be used to reveal the social media networks structures around topics.
Agile Strategy: A How-To Guide for Building and Nurturing Industry ClustersGIS Planning
Like attracts like. Success breeds success. Industry clusters are a boon to economic developers because of their magnetic effect on other businesses in the same sector, and the supply chain. But what do you do if you don't happen to be fortunate to already have a biotech, food processing or aerospace corridor in your community? According to guest presenter Ed Morrison, director of Agile Strategy, you go out and build one.
Morrison refers to his method as "strategic doing," accelerating network development in an intentional and disciplined way. This is different than the "analysis paralysis" methods of the past. It forms collaborations quickly by "linking and leveraging" assets across the network.
In this webinar, he discusses how to build regional innovation clusters, spaces where companies that share a similar competitive space decide to form a network, develop a strategic agenda to address common issues, and make anchor investments. This includes:
*Shifting the conversation towards collaboration
*Protocol for quickly building networks
*Developing a strategic, active agenda
*Managing this complex strategy with simple rules
*Identify different stages that clusters move through
2014 TheNextWeb-Mapping connections with NodeXLMarc Smith
Slides from a talk at the 2014 TheNextWeb in Amsterdam.
NodeXL social media network analysis of Twitter reveals six common structures in Twitter networks.
This presentation was made at a large pharmaceutical company's R&D and corporate affairs campus - going a little more indepth than the one from the prior Science of Team Science Conference
Access the webinar: http://goo.gl/p08pTz
These slides were presented in a webinar by Denodo in collaboration with BioStorage Technologies and Indiana Clinical and Translational Sciences Institute and Regenstrief Institute.
BioStorage Technologies, Inc., Indiana Clinical and Translational Sciences Institute, and Regenstrief Institute (CTSI) have joined Denodo to talk about the important role of technological advancements, such as data virtualization, in advancing biospecimen research.
By watching this webinar, you can gain insight into best practices around the integration of biospecimen and research data as well as technology solutions that provide consolidated views and rapid conversions of this data into valuable business insights. You will also learn how data virtualization can assist with the integration of data residing in heterogeneous repositories and can securely deliver aggregated data in real-time.
ASSESSMENT OF BIOMEDICAL LITERATURE
Components of internal and external validity of controlled clinical trials
Internal validity — extent to which systematic error (bias) is minimized in clinical trials
Selection bias: biased allocation to comparison groups
Performance bias: unequal provision of care apart from treatment under evaluation
Detection bias: biased assessment of outcome
Attrition bias: biased occurrence and handling of deviations from protocol and loss to follow up
Requirements, needs
Planning, direction
Information collection
Information Assessment
- Evaluation for accuracy, correctness, relevance, usefulness
- Source reliability assessment (competency and past behavior based)
- Bias assessment (motivators, interests, funding, objectives)
- Conflicts of interest
- Sources of funding, important business relationships
- Grading of individual items (study, report, analysis, article)
Collation of information
- Exclusion of irrelevant, incorrect, and useless information
-Arrangement of information in a form which enables real-time analysis
- System for rapid retrieval of information
External validity — extent to which results of trials provide a correct basis for generalization to other circumstances
Patients: age, sex, severity of disease and risk factors, comorbidity
Treatment regimens: dosage, timing and route of administration, type of treatment within a class of treatments, concomitant treatments
Settings: level of care (primary to tertiary) and experience and specialization of care provider
Modalities of outcomes: type or definition of outcomes and duration of follow up
mHealth and Wireless Technology Conference Partnering with academic organizat...P. Kenyon Crowley
How companies can partner with research organizations to accelerate research and development, evaluation of products, enhance usability, and create value. Includes funding relevant to mobile health companies.
EuroBioForum 2013 - Day 2 | Mark PoznanskyEuroBioForum
EuroBioForum 2013 2nd Annual Conference
27-28 May 2013 - Hilton Munich City, Munich, Germany
http://www.eurobioforum.eu/2013
=======================================
# REGIONAL PERSPECTIVES #
Ontario Genomics Institute, Canada:
Innovative Research, Innovative Translation
Dr Mark Poznansky
President and CEO Ontario Genomics Institute
=======================================
http://www.eurobioforum.eu
Move Your Research Out of the Ivory Tower and Impact Health: Translating Earl...CTSI at UCSF
This presentation highlights how the UCSF Clinical and Translational Science Institute (CTSI) enhances and facilitates early-stage research efforts at UCSF and UCSF/industry partnerships - to develop new treatments, diagnostics and prevention.
Sharing and standards christopher hart - clinical innovation and partnering...Christopher Hart
Acknowledging the increasing need for cooperation and collaboration in data sharing and access. Describing the complexity that this can bring. Then describing some of the ways to simplify that.
Originally presented at Terrapin's Clinical innovation and partnering world March 8-9 2017.
http://www.terrapinn.com/conference/innovation-and-partnering/index.stm
This conference offers delegates an in-depth view of the latest initiatives that are simplifying and improving the clinical trial experience for the patient through data-sharing and setting industry standards. Leading individuals from biopharma partnerships and consortia come together to share the results and impact of their projects, as well as insights on areas ripe for future collaboration. The conference provides delegates with opportunities to learn from one another in regard to what works now and a forum to discuss how to leverage and build on collective experiences to advance innovation across the wider community.
We discuss:
Responsible Clinical Trials Data Sharing – Protecting Intellectual Property While Enabling Public Access to Data.
The Project Data Sphere Initiative – A New Data Sharing and Analytics Model for Cancer Research.
Clinical Trials Transformation Initiative – Advancing Central IRBs, IND Safety and a Quality by Design Approach to Clinical Trial Operations.
Lessons Learned from Pilot Studies on Risk-Based Monitoring Methodology to Identify Risk and Ensure Data Quality.
A Model to Create, Share, and Re-Use Structured Content throughout the Clinical Trial Life Cycle – The Sanofi-TransCelerate Collaboration.
CISCRP Recommendations – Communicate Trial Results to Participants to Improve Experience and Build Support for the Clinical Research Enterprise.
http://www.worldcongress.com/events/PB14014/
Excipient Knowledge Management Mumbai 12 March 2015 Part 1 & 2Ajaz Hussain
Why attention to excipient knowledge management (specifically their functionality) is critical to mitigating risks (or to leverage opportunities) posed by the rapidly increasing complexity and uncertainty
Note: Knowledge management in the context of ‘intellectual property’ is not the focus of this talk
Combining Patient Records, Genomic Data and Environmental Data to Enable Tran...Perficient, Inc.
The average academic research organization (ARO) and hospital has many systems that house patient-related information, such as patient records and genomic data. Combining data from a variety of sources in an ongoing manner can enable complex and meaningful querying, reporting and analysis for the purposes of improving patient safety and care, boosting operational efficiency, and supporting personalized medicine initiatives.
In this webinar, Perficient’s Mike Grossman, a director of clinical data warehousing and analytics, and Martin Sizemore, a healthcare strategist, discussed:
-How AROs and hospitals can benefit from a systematic approach to combining data from diverse systems and utilizing a suite of data extraction, reporting, and analytical tools, in order to support a wide variety of needs and requests
-Examples of proposed solutions to real-life challenges AROs and hospitals often encounter
Research Partnerships to Support Telehealth OpportunitiesP. Kenyon Crowley
Presentation to American Telemedicine Association Business & Finance Special Interest Group on Research Partnerships to Support Telehealth Opportunities. Presentation goal: Understand potential academic partnership opportunities.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
1. Modeling Drug and Medical Device Innovation
as Temporal Sequences using EventFlow
NIH and the Science of Science and Innovation Policy:
A Joint NIH-NSF Workshop
April 7 – 8
Bethesda Maryland
C. Scott Dempwolf, PhD
Assistant Research Professor
University of Maryland – Morgan State
Joint Center for Economic Development
Ben Shneiderman, PhD
Distinguished University Professor
University of Maryland Institute for
Advanced Computer Science (UMIACS)
(and a few networks)
2. Pennsylvania Innovation Networks 1990 – 2007
Emergence of Philadelphia Biopharma cluster and Pittsburgh Nuclear Cluster
Modeled with Pajek & KING
2010
ME: “It’s cool, but…
How do I make it useful?”
BEN:
“You must use NodeXL”
ME:
“Obiwan Shneiderman,
you are my Jedi Master”
3. Innovation
A process of transforming knowledge and scientific
research into a new product in the marketplace.
Think of that process
as a sequence of
related activities
Research Invention Proof Commercialization Product
With this
intended
outcome
7. Activities become sequences through
shared people and organizations,
citations, and other linkages
With this
intended
outcome
8. Innovation Ecosystems
Innovation networks with embedded knowledge & resources along
with intermediaries comprise Innovation Ecosystems.
Activity networks combine to
form innovation networks.
The Regenerative Medicine cluster (ecosystem) in Howard County, MD
Combining two activities:
NSF# 1551041 and today’s presentation
NSF# 1551041 activity network
9. Innovation Metrics
Some are based
on organizations
& resources
None are
based on
intended
outcome
Some are
based on inputs
Some are
based on outputs
Some are
based
on talent
Some are
comparative indexes
Product
Launch
10. Modeling Innovation Sequences with EventFlow
We use newly developed EventFlow
software to model innovation in drugs and
medical devices from multiple datasets:
• RePORTER_PATENTS_C_ALL
• RePORTER_CLINICAL_STUDIES_C_ALL
• CTTI AACT Database
• FDA Orange Book (drugs)
• Drugs@FDA
• Pre-Market Approvals (PMA) (med devices)
• SBIR/STTR (pending)
• CrunchBase (pending)
• NSF (pending)
Supporting and core data sources
• NIH RePORTER
• PatentsView
• USASpending
• STARMETRICS
http://hcil.umd.edu/eventflow/
11. A Quick Tour of EventFlow
Each product (drug or medical device)
is a record in EventFlow
(34,331 records)
Event categories:
• Clinical Trials (commercialization activity)
• FDA Approval (proxy for product launch)
• Patents (invention)
• Research
Overview (Aggregation) Individual Timelines
12. Product-Based Innovation Metrics
Temporal Metrics
How long does innovation take?
How many activities are involved?
What types?
In what sequence?
How long does each take?
Are there gaps?
Is the sequence pattern common
or rare?
13. How long does innovation take? (drugs)
From:
Patent application
FDA approval
(26 products)
14. How long does innovation take? (drugs)
From:
Patent application
FDA approval
(product launch)
(884 drugs in the
FDA Orange Book)
15. How long does innovation take? (med devices)
From:
Start of clinical trials
FDA approval
(1,225 medical devices)
16. How long does innovation take? (med devices)
FDA Approval
during
Clinical Trial
FDA Approval
after
Clinical Trial
17. Illinois Battery Cluster 2010 – 2014
Modeled with NodeXL
Bridge
Broader applications of temporal metrics:
the Illinois Battery Cluster
Innovation Ecosystems
research component
Industry component
Bridging component
18. Research Publication Invention Proof-of-Concept Commercialization Product
Bridge
The Innovation Ecosystem and the Valley of Death
A network representation
of the valley of death
19. Emerging Theory & Research
Bridge What’s in
the Bridge?
• Working Hypothesis
• Regions with denser, more connected
bridging components will be
characterized by faster innovation
sequences and more innovation
sequences leading to new products.
Measured using new
temporal metrics
20. Stem cell products group
• Commercialization support
• Acceleration
• Attract complementary
firms
Delivery devices groups,
ECM group
• Facilitate collaboration
• Niche market development
• Attract complementary firms
Regenerative Medicine &
Nutraceuticals groups
• Develop ‘Keystones’
• Promote local sourcing
• Industry partnerships
• FDI / Business expansion
• Attraction - supply chain
• University partnerships
University groups (JHU, UMCP, UMB)
• Leads for licensing (green ties)
• Key labs (dense subgroups)
• Opportunities for faculty spin outs
• Accelerate student startups
• Corporate Partnerships
Targeted Economic
Development Strategies
At the Cluster Level
Regenerative Medicine Cluster – Howard County, MD
Innovation-Led Economic Development
Drill-down to Company Profiles
• Click to follow link
Nascent / emerging
Growth stage
Infrastructure for
maturing cluster
~Labs
21. Howard County, Maryland - Full Innovation Network
Universities (JHU, UMCP, UMB,
UMBC+)
• Follow-up leads for licensing or other
engagements (green ties)
• Identify key labs (dense subgroups)
and evaluate for expansion /
enhancement
• Identify opportunities for faculty spin
outs
• Identify / accelerate potential
student startups that can be seeded
in this cluster
• Build long-term sponsored research
relationships with keystone
companies
Main Innovation Clusters
• Regenerative Medicine
• Telecom / networks / cyber
• Defense / Security / SBIR
• Nutraceuticals
• Research & Development
Entrepreneurial Acceleration
Opportunities
• Commercialization, acceleration,
entrepreneurial support for early
stage companies located in the
county
• Assistance with market Connections
to capital & cluster keystones
Business Attraction Opportunities
• Focus on early stage companies with
innovation cluster growth potential;
companies are located outside of
the county but have a HoCo
connection
• Develop relationships and help them
plan for move to HoCo for next
growth stage
• Connections to capital
Keystones
• Identify & cultivate keystones in each
innovation cluster
• Identify & cultivate capital networks
around each innovation cluster
Business Expansion & FDI
Opportunities
• Focus BRE on growth stage &
mature companies in innovation
clusters.
• Develop keystones in the process.
• Engage MD DOC in developing FDI.
• Engage foreign-owned companies in
innovation clusters to expand their
presence in the cluster through FDI.
Workforce Development
• Develop industry partnerships
(EARN) around innovation clusters
• Work with universities & community
colleges on talent pipeline
Federal Strategy
pending
The ‘group-in-a-box’ layout organizes
groups from largest to smallest. This
also corresponds to a ‘strategy
gradient’ for economic development.
Research Component
Entrepreneurial
strategies
Attraction
strategies
Research & Tech
Transfer strategies
Retention, Expansion
& Workforce strategies
Industry Component
Bridging
Component (partial)
22. A few Data Issues & Needs
• Data cleaning & disambiguation
• Data matching across datasets
• RePORTER, Clinical Trials, FDA, SBIR
• Matching on full project numbers (not core)
• SBIR – More complete dates; Access to bibliographies for citation
linkages
• FDA, Clinical Trials – Basic information at the front-end
• FDA – ability to roll up drug families i.e. Adderall 10mg, 15mg, 20mg…
23. Upcoming Events
April 13, Wednesday 10am at NIH
Porter Building 35A, Room 610, NIH Main Campus, Bethesda, MD
Interactive Visual Discovery in Event Analytics: Electronic Health Records
Ben Shneiderman
datascience.nih.gov/community/datascience-at-nih/frontiers
May 26, Thursday at University of Maryland Human-Computer Interaction Lab
EventFlow Workshop
hcil.umd.edu/eventflow/
hcil.umd.edu/eventflow-workshop-2016/`
24. Implications for Universities: visualizing labs and research partnerships
Identify key labs (dense
subgroups) and evaluate for
expansion / enhancement
Identify opportunities for
faculty spin outs
Identify / accelerate
potential student startups
that can be seeded in
emerging clusters
Link to Lab and researcher
pages (click to follow)
University of Maryland, College Park
Research labs, research partnerships,
and individual researchers
Editor's Notes
3:00
This slide begins a short series of slides that starts with a broad definition of innovation, then establishes a framework for thinking about innovation as a temporal sequence of connected events. Each slide in the series adds a layer of information that transforms the abstract concept of innovation into a data-driven model.
Inputs and outputs are the basis for how we measure innovation now and are a familiar reference point. Associating individual activities with documents or artifacts sets up the linkages to data sources.
From the data sources we can identify people and organizations involved, which sets up the creation of network models. This slide also introduces the notion of intermediate outcomes from the innovation perspective – things like patents and publications – that may be final outcomes from the perspective of the people working on them. Innovation is not everyone’s goal.
This introduces the idea of an activity network – the building block of innovation networks and ecosystems.
Finally we layer on the data and linkages to show how the activities connect to each other to form temporal sequences.
This slide parallels the previous slide but from the activity network to innovation network to innovation ecosystem perspective.
Where innovation metrics come from now, and more importantly, where they do not. Total elapsed time to the end of this slide is 4:00.
This slide shows the EventFlow screen with the overall data model we have constructed so far, and identifies the data sources we use.
Introduces the basics of EventFlow
This slide shows the 26 drugs that we can trace – at least partially – from research to final approval. It also frames innovation activities from the perspective of products and lists some of the important questions we can ask and important temporal metrics we can derive from analysis with EventFlow (and CoCo).
The distribution and statistics for our 26 drug sample. Measures from first patent application date to final approval date.
The distribution and statistics for all drugs we have data on. Measures from first patent application date to final approval date.
A similar look at medical devices using clinical trials and final approval dates. Introduces the measurement of gaps.
Continues the previous slide, introducing the concepts of overlaps and of visualizing patterns in the overview panel of EventFlow.
There are two general sequence patterns in the data. The images on the previous slide showed sequence patterns for which clinical trials were completed, followed by a lag, followed by FDA approval. The other pattern, shown here on the right has FDA approvals overlapping the span of clinical trials.
We prepared network models fir the Illinois Science & Technology Roadmap. One of those was for the Battery Cluster. From an academic perspective, one of the things we noticed was that the activities tended to be organized into two main components – research and industry – with a small group of activities that seemed to span these two components. We’ll call this third component the bridge – show here in collapsed form as simply a gray band.
Then we recognized similarities between the network graph and our graphic of the so-called “valley of death’. We realized that we might actually be looking at a network representation of that valley of death. If that was the case, what would we expect to find in the bridge? 1) corporate sponsored research; 2) SBIR / STTR’s; 3) intermediaries like accelerators and incubators; and 4) public-private partnerships like federal labs. When we opened up the bridge for a closer look, that is exactly what we found.
This allows us to frame a new working hypothesis about innovation ecosystems and the differences in innovation outcomes between different regions. And the new temporal metrics we are developing with NSF should allow us to test that hypothesis soon. So for us the value of University Centers is this diversity of partnerships around the tasks of developing new methods and metrics; developing new tools and solving practical economic development problems; and synthesizing those activities into new knowledge and understanding about the nature of innovation and its impact on economic growth.
As a practical matter innovation ecosystems and regional innovation clusters are the same thing. Here we show one ecosystem / cluster for regenerative medicine in Howard County Maryland, comprised of those aggregated activity networks. This small, emerging cluster does not show up in traditional cluster analysis because 1) the activity is too recent and 2) the activity is not organized according to existing NAICS codes. Thus this analysis was valuable to Howard County Economic Development. Each group includes people and organizations that are connected based on what they are working on together. The graph is organized with the largest, most connected group in the upper left and the smallest, least connected group in the lower right. It turns out that this layout is useful in helping to organize and target different types of economic development strategies to specific companies and groups so that the overall cluster strategy appropriately targets limited resources for effective economic development. The interactive network tool allows economic developers to zoom in and explore different parts of the cluster in detail. Users can also click on certain nodes to get more detailed information. This interactive network model was build using NodeXL – developed in part by the same computer scientists who created EventFlow.
14:30 – 15:30 But here is how the visualization organizes the information.