Researchers and public health practitioners increasingly use Internet big data as data source. What are some of the ethical problems, and how should they be tackled? The author advocates the creation of a self-regulatory body of researchers, a code of conduct, and a notice/opt-out infrastructure, to avoid a public backlash against social media tracking/monitoring for public health, similar to the Facebook fiasko in 2014 (Cornell study).
Disease Network is the science that has emerged to diagnose a disease from a network aspect
specifically. Networks are the group that interconnect to each others similarly disease networks are
the one that reveal concelled connection among apparently independent biomedical entities like
physiologic process, signaling receptors, in addition to genetic code, also they prove to exists
intitutive in addition to powerful way to learn/discover or diagnose a disease.Due to these networks,
we can now consume the elderly drugs and its method to learn/discover the new drug
accordingly.Example- Colchicine is used in gout but after repurposing it is also used in mediterranean
fever. This is because there are many factors that affect the body during mediterranean fever and
gout, we know that gout is a form of arthritis that causes pain in joints also mediterranean fever is the
one which is accompanied by pain in joints, therefore colchicine is used as a repurposed drug again.In
repurposing of medicines or drugs we first analyse the change in symptoms and identify the target
organ and accorgingly we produce a drug that is compatible with pharmacokinetics of the body. As
the availablity of transcriptomic,proteomic and metabolomic data sources are increasing day by day it helps in classification of disease .Also there are some networks reffered to as complex networks which can be called as collection of linked junctions/ nodes
Presentation at AMIA 2013 Washington DC, Nov 19th, Panel S50 Social Media and Me. I am focussing on the use of social media for research, in particular as tool for filtering the literature, twimpact factor, altmetrics...
Sherri Rose wrote a fascinating article about statistician’s role in big data. One thing I really liked was this line: “This may require implementing commonly used methods, developing a new method, or integrating techniques from other fields to answer our problem.” I really like the idea that integrating and applying standard methods in new and creative ways can be viewed as a statistical contribution.
Researchers and public health practitioners increasingly use Internet big data as data source. What are some of the ethical problems, and how should they be tackled? The author advocates the creation of a self-regulatory body of researchers, a code of conduct, and a notice/opt-out infrastructure, to avoid a public backlash against social media tracking/monitoring for public health, similar to the Facebook fiasko in 2014 (Cornell study).
Disease Network is the science that has emerged to diagnose a disease from a network aspect
specifically. Networks are the group that interconnect to each others similarly disease networks are
the one that reveal concelled connection among apparently independent biomedical entities like
physiologic process, signaling receptors, in addition to genetic code, also they prove to exists
intitutive in addition to powerful way to learn/discover or diagnose a disease.Due to these networks,
we can now consume the elderly drugs and its method to learn/discover the new drug
accordingly.Example- Colchicine is used in gout but after repurposing it is also used in mediterranean
fever. This is because there are many factors that affect the body during mediterranean fever and
gout, we know that gout is a form of arthritis that causes pain in joints also mediterranean fever is the
one which is accompanied by pain in joints, therefore colchicine is used as a repurposed drug again.In
repurposing of medicines or drugs we first analyse the change in symptoms and identify the target
organ and accorgingly we produce a drug that is compatible with pharmacokinetics of the body. As
the availablity of transcriptomic,proteomic and metabolomic data sources are increasing day by day it helps in classification of disease .Also there are some networks reffered to as complex networks which can be called as collection of linked junctions/ nodes
Presentation at AMIA 2013 Washington DC, Nov 19th, Panel S50 Social Media and Me. I am focussing on the use of social media for research, in particular as tool for filtering the literature, twimpact factor, altmetrics...
Sherri Rose wrote a fascinating article about statistician’s role in big data. One thing I really liked was this line: “This may require implementing commonly used methods, developing a new method, or integrating techniques from other fields to answer our problem.” I really like the idea that integrating and applying standard methods in new and creative ways can be viewed as a statistical contribution.
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
Invitational talk from the NSF/NCI workshop "Cyberinfrastructure in Behavioral Medicine" in San Diego on March 31st 2008, talking about what I call infodemiology / infoveillance work
Discuss about Al, machine learning, and the hype cycle
Discuss the knowledge-based classification of proteins
Discuss applications of AI/ML to drug discovery
Participant-centered research design and “equal access” data sharing practice...Jason Bobe
Topics include:
What is "equal access" to data?
How have the roles of human subjects expanded over time?
Where has equal access to data been a success?
What are the barriers to equal access in research?
Presentation for the workshop on "6 Reasons Fake News is the End of the World as we know it" at Harvard University, organized by the Center for Research on Computation and Society https://crcs.seas.harvard.edu/event/fakenews
NIH Drug Discovery and Development - NCTT and CTSAsCTSI at UCSF
Presented at the UC Braid Retreat: Imagine a statewide research engine of pooled resources, data, and expertise that accelerates the “translation” of academic research to direct patient benefit. That's the goal of the University of California Biomedical Research Acceleration, Integration, and Development (UC BRAID) program.
Digital Access to the World's Literature: A Blueprint to Integrate Evidence w...Elaine Martin
Lamar Soutter Library Director Elaine Martin and Consultant Karen Dahlen introduce a digital public health library initiative that supports national and state public health departments. Success stories and next steps to build a sustainable digital library model for all public health department is covered.
Pistoia Alliance datathon for drug repurposing for rare diseasesPistoia Alliance
As part of the Pistoia Alliance Centre of Excellence for AI in Life Sciences, we are running a datathon.
Rare Disease Drug Repurposing Datathon is your chance to advance knowledge on rare diseases and illustrate best practices in data science. Are you ready to help make a difference — and to showcase your organization’s data science work and skills?
A poster presented at the 2016 Annual Meeting of the Medical Library Association on a strategy for identifying emerging technologies through Pubmed searching. This is an outcome from the MLA systematic review project from the association's research initiative.
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
A poster on strategies and uses of Twitter for cancer communication presented at the 2016 Annual Meeting of the Medical Library Association. Second place award for Research Poster at the conference.
Peter Embi's 2017 Clinical Research Informatics Year-in-Review. Presented as closing Keynote address at the 2017 AMIA Summits on Translational Science in San Francisco, CA.
This is a presentation given at the Opal Events meeting ""Drug Discovery Partnerships: Filling the Pipeline". I was speaking in a session with Jean-Claude Bradley regarding "Pre-competitive Collaboration: Sharing Data to Increase Predictability". This presentation discussed some of the work we are doing on Open PHACTS. My thanks especially to Carole Goble, Lee Harland and Sean Ekins for their comments.
Masker Rambut yang Bagus Apa ya, Masker Rambut yg Bagus Apa ya, Masker Rambut yang Bagus Merk Apa ya, Masker Rambut Alami untuk Rambut untuk Rambut Rontok, Masker Rambut Alami untuk Rambut untuk Rambut Rusak, Masker Rambut Alami untuk Rambut untuk Rambut Bercabang, Masker Rambut Alami untuk Rambut untuk RambutKering dan Rontok, Masker Rambut Alami untuk Rambut untuk RambutKering, Masker Rambut Alami untuk Rambut untuk Rambut Mengembang, Masker Rambut Alami untuk Rambut untuk Rambut Lembut.
ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY "AN OVERVIEW OF AWARENESS"FinianCN
ARTIFICIAL INTELLIGENT IN DRUG DISCOVERY:- AN OVERVIEW OF AWARENESS.
AI is showing the potential to be a faster and more efficient way to find and develop new drugs. A growing number of organizations and universities are focusing to minimize the complexities involved in the classical way of drug discovery by using AI computing to envisage which drug candidate are most likely to be effective treatments.
It is hard to measure the adoption of AI in drug discovery. Pharma and biotech companies tend to not publicly disclose competitive technology use.
While organizations are adopting the technology, there is significant untapped potential for those willing to be more aggressive. Which is depending on the realization of the potential with education and relevant success stories
Invitational talk from the NSF/NCI workshop "Cyberinfrastructure in Behavioral Medicine" in San Diego on March 31st 2008, talking about what I call infodemiology / infoveillance work
Discuss about Al, machine learning, and the hype cycle
Discuss the knowledge-based classification of proteins
Discuss applications of AI/ML to drug discovery
Participant-centered research design and “equal access” data sharing practice...Jason Bobe
Topics include:
What is "equal access" to data?
How have the roles of human subjects expanded over time?
Where has equal access to data been a success?
What are the barriers to equal access in research?
Presentation for the workshop on "6 Reasons Fake News is the End of the World as we know it" at Harvard University, organized by the Center for Research on Computation and Society https://crcs.seas.harvard.edu/event/fakenews
NIH Drug Discovery and Development - NCTT and CTSAsCTSI at UCSF
Presented at the UC Braid Retreat: Imagine a statewide research engine of pooled resources, data, and expertise that accelerates the “translation” of academic research to direct patient benefit. That's the goal of the University of California Biomedical Research Acceleration, Integration, and Development (UC BRAID) program.
Digital Access to the World's Literature: A Blueprint to Integrate Evidence w...Elaine Martin
Lamar Soutter Library Director Elaine Martin and Consultant Karen Dahlen introduce a digital public health library initiative that supports national and state public health departments. Success stories and next steps to build a sustainable digital library model for all public health department is covered.
Pistoia Alliance datathon for drug repurposing for rare diseasesPistoia Alliance
As part of the Pistoia Alliance Centre of Excellence for AI in Life Sciences, we are running a datathon.
Rare Disease Drug Repurposing Datathon is your chance to advance knowledge on rare diseases and illustrate best practices in data science. Are you ready to help make a difference — and to showcase your organization’s data science work and skills?
A poster presented at the 2016 Annual Meeting of the Medical Library Association on a strategy for identifying emerging technologies through Pubmed searching. This is an outcome from the MLA systematic review project from the association's research initiative.
BioVariance - Pediatric Pharmacogenomics in Drug DiscoveryJosef Scheiber
This slideset gives an overview of pharmacogenomic and pediatric dosing knowledge and various influence factors. Finally it shows an example on how to use this kind of Data within predictive approaches.
A poster on strategies and uses of Twitter for cancer communication presented at the 2016 Annual Meeting of the Medical Library Association. Second place award for Research Poster at the conference.
Peter Embi's 2017 Clinical Research Informatics Year-in-Review. Presented as closing Keynote address at the 2017 AMIA Summits on Translational Science in San Francisco, CA.
This is a presentation given at the Opal Events meeting ""Drug Discovery Partnerships: Filling the Pipeline". I was speaking in a session with Jean-Claude Bradley regarding "Pre-competitive Collaboration: Sharing Data to Increase Predictability". This presentation discussed some of the work we are doing on Open PHACTS. My thanks especially to Carole Goble, Lee Harland and Sean Ekins for their comments.
Masker Rambut yang Bagus Apa ya, Masker Rambut yg Bagus Apa ya, Masker Rambut yang Bagus Merk Apa ya, Masker Rambut Alami untuk Rambut untuk Rambut Rontok, Masker Rambut Alami untuk Rambut untuk Rambut Rusak, Masker Rambut Alami untuk Rambut untuk Rambut Bercabang, Masker Rambut Alami untuk Rambut untuk RambutKering dan Rontok, Masker Rambut Alami untuk Rambut untuk RambutKering, Masker Rambut Alami untuk Rambut untuk Rambut Mengembang, Masker Rambut Alami untuk Rambut untuk Rambut Lembut.
Grid current-feedback active damping for lcl resonance in grid-connected volt...LeMeniz Infotech
Grid-Current-Feedback Active Damping for LCL Resonance in Grid-Connected Voltage-Source Converters
This paper investigates active damping of LCL-filter resonance in a grid-connected voltage-source converter with only grid-current feedback control. Basic analysis in the s-domain shows that the proposed damping technique with a negative high-pass filter along its damping path is equivalent to adding a virtual impedance across the grid-side inductance. This added impedance is more precisely represented by a series RL branch in parallel with a negative inductance. The negative inductance helps to mitigate phase lag caused by time delays found in a digitally controlled system. The mitigation of phase-lag, in turn, helps to shrink the region of nonminimum-phase behavior caused by negative virtual resistance inserted unintentionally by most digitally implemented active damping techniques. The presented high-pass-filtered active damping technique with a single grid-current feedback loop is thus a more effective technique, whose systematic design in the z-domain has been developed in this paper. For verification, experimental testing has been performed with results obtained matching the theoretical expectations closely.
Web : http://www.lemenizinfotech.com
Web : http://ieeemaster.com
Web : http://www.lemenizinfotech.com/power-system-ieee-projects-2016-2017/
Web : http://ieeemaster.com/power-system-ieee-projects-2016-2017/
Address: 36, 100 Feet Road(Near Indira Gandhi Statue), Natesan Nagar, Pondicherry-605 005
Contact numbers: +91 95663 55386, 99625 88976 (0413) 420 5444
Mail : projects@lemenizinfotech.com
Mobile : 9566355386 / 9962588976
Doing more with less resources used to be a situation common just for academic scientists. This is unfortunately still true for academics but we are seeing others facing many of the same challenges. With the squeeze on budgets and cost cutting resulting from recent worldwide economic challenges, the failure of many drugs to make it through the pipeline to the market, and the increasing costs associated with the drug development process, we are now seeing in the pharmaceutical industry a dramatic shift, perhaps belatedly, to have to accommodate similar challenges of doing more with less
Dr. Dennis Wang discusses possible ways to enable ML methods to be more powerful for discovery and to reduce ambiguity within translational medicine, allowing data-informed decision-making to deliver the next generation of diagnostics and therapeutics to patients quicker, at lowered costs, and at scale.
The talk by Dr. Dennis Wang was followed by a panel discussion with Mr. Albert Wang, M. Eng., Head, IT Business Partner, Translational Research & Technologies, Bristol-Myers Squibb.
Acquiring and representing drug-drug interaction knowledge and evidence, Litm...jodischneider
Presentation to Diane Litman's lab at the University of Pittsburgh about modeling and acquiring evidence for the Drug Interaction Knowledge Base (DIKB) project.
Integrating PHRs into EHR Platforms When electronic health re.docxBHANU281672
Integrating PHRs into EHR Platforms
When electronic health records (EHRs) first entered the market, their primary focus was to collect and analyze patient information within health care settings. As technological capabilities grew, so did the interest in making these records available to patients. In addition, many health care professionals saw benefits in allowing the patient to enter his or her own health data into EHR platforms. Though many patients are already utilizing personal health records (PHRs) to manage and track their own health, some believe that an integrated system would provide a better, more comprehensive picture of a patient’s health history.
As a result, many EHR platforms are now equipped with a PHR tool. This PHR tool allows patients to enter health information as they would in a stand-alone PHR system. In addition, web-based portals within the EHR allow patients to access information entered by their physicians and health care providers.
Like many emerging trends and technologies, there is much discussion about the potential benefits and challenges of this type of integrated system. While many health care professionals are excited about the empowerment provided to patients, others express significant concerns about access, security, ethics, and other implications.
In this Discussion, you explore how integrating PHRs into EHR platforms could impact you and your patients.
To prepare:
Review the media
Patient-Centered Technologies
, and reflect upon Dr. Simpson’
s
statements about the ownership of patient data.
Review the article,“Dreams and Nightmares: Practice and Ethical Issues for Patients and Physicians Using Personal Health Records” found in this week’s Learning Resources. Consider how PHR capabilities can be integrated into EHR platforms.
Examine the “dreams” and the “nightmares” the authors associate with this type of integrated health record. Select one benefit or one challenge of integrating PHRs into EHR platforms. Then, consider its potential impact on health care providers and patients. Why is this considered to be a benefit or challenge for health care professionals and patients?
Post by tomorrow 07/05/2016 a minimum of 550 words in APA format and 3 references.
1) A brief description of your selected benefit or challenge and support your selection.
2) Explain the potential impact on health care professionals and patients.
Required Resources
Readings
Saba, V. K., & McCormick, K. A. (2015).
Essentials of nursing informatics
(6th ed.). New York, NY: McGraw-Hill.
Review Chapter 1, “Historical Perspectives of Nursing Informatics”
In this chapter, the authors explain the transition from paper-based records to electronic records. The chapter provides an overview of the historical events that contributed to the rise of electronic health records.
Chapter 25, “Care Delivery Across the Care Continuum: Hospital-Community-Home”
Chapter 25 analyzes the impact of home health on the heal ...
Presentation from AAPS PharmSci360 (October 23, 2023) in which I describe highlights of my Springer/AAPS book Winning Grants (https://link.springer.com/book/10.1007/978-3-031-27516-6) - presenting a 'how to' guide on writing small business grants - e.g. NIH STTR and SBIR grants. Written by someone experienced in winning such grants.
Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic To...Sean Ekins
The presentation was given at SETAC 2022 Nov 16 and describes our work on Evaluating Multiple Machine Learning Models for Biodegradation and Aquatic Toxicity.
We generated many models that are available to license in our MegaTox software. We found that the support vector machines performed the best after assessing many algorithms for both classification and regression models.
The authors of this work are Thomas R Lane, Fabio Urbina and Sean Ekins.
The contact is sean@collaborationspharma.com
A presentation at the Global Genes rare drug development symposium on governm...Sean Ekins
This presentation from June 12 2020 gives a brief overview of my experience of 15 years of applying for government grants to fund small companies. Prior to this I had no experience of applying for such grants. The bottom line for rare disease groups / families is find a scientist that can do this or assist you. please also see www.collaborationspharma.com
Leveraging Science Communication and Social Media to Build Your Brand and Ele...Sean Ekins
Slides from AAPS Careers session by Maren Katherina Preis, Kyle Bagin, Sean Ekins
Provides some clear steps on how you could use social media to help your career.
Oral presentation given in MEDI session at 2017 ACS in DC.
co-authors Kimberley M. Zorn, Mary A. Lingerfelt, Jair L. de Siqueira-Neto, Alex M. Clark, Sean Ekins
describes drug repurposing and machine learning - for more details see www.collaborationspharma.com
Assay Central: A New Approach to Compiling Big Data and Preparing Machine Lea...Sean Ekins
Oral presentation at 2017 ACS in DC - given by Kimberley Zorn
co-authors include Mary A. Lingerfelt, Alex M. Clark, Sean Ekins
for more details see www.collaborationspharma.com
Five Ways to Use Social Media to Raise Awareness for Your Paper or ResearchSean Ekins
Presentation given at the AAPS 2016 conference in Denver. Some of the slides are from AAPS, Some from Kudos and some from Figshare. One slide is from Tony Williams. All slides used with permission.
CDD: Vault, CDD: Vision and CDD: Models software for biologists and chemists ...Sean Ekins
A perspective on 12 yrs of CDD and developing products and collaborations.
A presentation given at the ACS meeting in San Diego - small business section
This presentation summarizes some early efforts on an open drug discovery collaboration between scientists in Brazil and the US. The amazing virus images were created by John Liebler and can be licensed from him http://www.artofthecell.com/animation/will-the-real-zika-virus-please-stand-up
The homology models were created with Swiss Model by Sean Ekins:
Marco Biasini, Stefan Bienert, Andrew Waterhouse, Konstantin Arnold, Gabriel Studer, Tobias Schmidt, Florian Kiefer, Tiziano Gallo Cassarino, Martino Bertoni, Lorenza Bordoli, Torsten Schwede. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Research; (1 July 2014) 42 (W1): W252-W258; doi: 10.1093/nar/gku340.
Arnold K., Bordoli L., Kopp J., and Schwede T. (2006). The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling. Bioinformatics, 22,195-201.
Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T (2009). The SWISS-MODEL Repository and associated resources. Nucleic Acids Research. 37, D387-D392.
Guex, N., Peitsch, M.C., Schwede, T. (2009). Automated comparative protein structure modeling with SWISS-MODEL and Swiss-PdbViewer: A historical perspective. Electrophoresis, 30(S1), S162-S173.
Ensuring Chemical Structure, Biological Data and Computational Model Quality
A talk given at SLAS 2016 mon Jan 25th in San Diego
covers published work and recent forays with BIA 10-2474
Pros and cons of social networking for scientistsSean Ekins
Over the past 4 years I have been using social networking tools for scientists more inspired by Antony Williams. I realized I am using many tools and there are pros and cons of them. Here is my brief summary.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
Explore how micro-credentials are transforming Technical and Vocational Education and Training (TVET) with this comprehensive slide deck. Discover what micro-credentials are, their importance in TVET, the advantages they offer, and the insights from industry experts. Additionally, learn about the top software applications available for creating and managing micro-credentials. This presentation also includes valuable resources and a discussion on the future of these specialised certifications.
For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Collaborative Technologies for Biomedical Research
1. Collaborative Computational Technologies for Biomedical Research Edited by Sean Ekins, Maggie A.Z. Hupcey and Antony J. Williams With a Foreword by Alpheus Bingham Wiley Series on Technologies for the Pharmaceutical Industry Sean Ekins, Series Editor
2. Biomedical research has become increasingly driven by creating and consuming tremendous volumes of data. At the same time the pharmaceutical industry is utilizing an extended network of partner organizations of various sorts in order to discover and develop new drugs. There is currently little if any guidance for managing information and computational resources across collaborations. Methods, Processes and Tools for Collaborations
3. The book is divided into four sections: Part I. Getting People To Collaborate Part II: Methods And Processes For Collaborations Part III. Tools For Collaborations Part IV. The Future Of Collaborations
4. This book tackles a real set of problems thoroughly from both the human collaborative, the data and informatics side, and is very relevant to activities of running a laboratory or a collaborative R&D project.
5. This book provides the reader with state of the art practical advice. Collaboration will only increase in the future and scientists will be relying on computational applications to enable this.
6. PART I: GETTING PEOPLE TO COLLABORATE 1. The Need for Collaborative Technologies in Drug Discovery Chris L. Waller, Ramesh V. Durvasula and Nick Lynch 2. Collaborative Innovation: the Essential Foundation of Scientific Discovery Robert Porter Lynch 3. Models for Collaborations and Computational Biology Shawnmarie Mayrand-Chung, Gabriela Cohen-Freue, and Zsuzsanna Hollander 4. Precompetitive Collaborations in the Pharmaceutical Industry Jackie Hunter 5. Collaborations in Chemistry Sean Ekins, Antony J. Williams and Christina K. Pikas 6. Consistent Patterns in Large Scale Collaboration Robin W. Spencer 7. Collaborations Between Chemists and Biologists Victor J. Hruby 8. Ethics of Collaboration Richard J. McGowan, Matthew K. McGowan and Garrett J. McGowan 9 Intellectual Property Aspects of Collaboration John Wilbanks
7. PART II: METHODS AND PROCESSES FOR COLLABORATIONS 10. Scientific Networking and Collaborations Edward D. Zanders 11. Cancer Commons: Biomedicine in the Internet Age Jeff Shrager, Jay M. Tenenbaum, and Michael Travers 12. Collaborative Development of Large-Scale Biomedical Ontologies Tania Tudorache and Mark A. Musen 13. Standards for Collaborative Computational Technologies for Biomedical Research Sean Ekins, Antony J. Williams and Maggie A.Z. Hupcey 14. Collaborative Systems Biology: Open Source, Open Data, and Cloud Computing Brian Pratt 15. Eight Years Using GRIDS for Life Sciences Vincent Breton, Lydia Maigne, David Sarramia and David Hill 16. Enabling Precompetitive Translational Research – A Case Study Sándor Szalma 17. Collaboration in the Cancer Research Community: The cancer Biomedical Informatics Grid (caBIG) George A. Komatsoulis 18. Leveraging Information Technology for Collaboration in Clinical Trials O.K. Baek
8. PART III. TOOLS FOR COLLABORATIONS 19. The Evolution of Electronic Laboratory Notebooks Keith T. Taylor 20. Collaborative Tools to Accelerate Neglected Disease Research: the Open Source Drug Discovery Model Anshu Bhardwaj, Vinod Scaria, Zakir Thomas, Santosh Adayikkoth, Open Source Drug Discovery (OSDD) Consortium and Samir K. Brahmachari 21. Pioneering Use of the Cloud for Development of the Collaborative Drug Discovery (CDD) Database Sean Ekins, Moses M. Hohman and Barry A. Bunin 22. Chemspider: a Platform for Crowdsourced Collaboration to Curate Data Derived From Public Compound Databases Antony J. Williams 23. Collaborative Based Bioinformatics Applications Brian D. Halligan 24. Collaborative Cheminformatics Applications Rajarshi Guha, Ola Spjuth and Egon Willighagen
9. PART IV. THE FUTURE OF COLLABORATIONS 25. Collaboration Using Open Notebook Science in Academia Jean-Claude Bradley, Andrew S.I.D. Lang, Steve Koch and Cameron Neylon 26. Collaboration and the Semantic Web Christine Chichester and Barend Mons 27. A Collaborative Visual Analytics Environment for Imaging Genetics Zhiyu He, Kevin Ponto and Falko Kuester 28. Current and Future Challenges for Collaborative Computational Technologies for the Life Sciences Antony J. Williams, Renée J.G. Arnold, Cameron Neylon, Robin Spencer, Stephan Schürer and Sean Ekins
10. Target Audience We have aimed for a complete volume that can be read by all interested in biomedical research and development and with each chapter edited to ensure consistency across the common theme of collaboration and with appropriate explanatory figures and key references. We are confident this book will become a valuable reference work for those interested in collaborative approaches to biomedical research.
11. The time has come to fundamentally re-think how we handle the building of knowledge in biomedical sciences today. This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types. – Bryn Williams-Jones, Associate Research Fellow, Pfizer Considering the present state the pharmaceutical industry finds itself in, the promise of innovative medicines for children and our children's children may well depend on finding new collaborative paradigms with attendant business models. The material for this genesis, though nascent, may well be found in these pages. - Alpheus Bingham, Cascade Consulting; InnoCentive, Inc.; Monitor Talent
12. Sean Ekins, MSc, PhD, DSc is the Principal at Collaborations in Chemistry; Collaborations Director at Collaborative Drug Discovery, Inc., SVP at ACT LLC; Adjunct Associate Professor in the Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy. Dr. Ekins has published >150 papers and book chapters on computational and in vitro drug discovery approaches and previously edited or co-edited three books for Wiley. Maggie A.Z. Hupcey, PhD is a chemist working within the Life Sciences and Healthcare practice of PA Consulting in Princeton, NJ. She has worked on collaborative projects for the design and development of new products and processes in the medical device, drug delivery and drug discovery fields, including pre-submission and post-launch regulatory compliance activities. Antony J Williams, PhD, FRSC is currently VP, strategic development at the Royal Society of Chemistry and holds an adjunct position at UNC-Chapel Hill. He has written chapters for many books and published >100 peer reviewed papers and book chapters on NMR, predictive ADME methods, Internet-based tools, crowdsourcing and database curation. He is an active blogger and participant in the internet chemistry network. About the Authors
14. Related websites for these authors http://www.collaborations.com/CHEMISTRY.HTM http://myprofile.cos.com/ekinssean http://www.amazon.com/Sean-Ekins/e/B003BFP2E0 http://www.chemconnector.com/chemunicating/ http://www.chemspider.com/blog/