STM Solutions today announced the integration of Manuscript Manager, a peer review system for academic journals, into the STM Integrity Hub. This integration enables publishers to establish automated feeds of their submitted content to the Hub. Here, the content is screened for various integrity issues, such as submissions to multiple journals simultaneously, references to retracted works, and manuscripts generated by paper mills. This latest integration, closely following the integration of Editorial Manager and ScholarOne into the Integrity Hub, represents an important milestone. It allows for more journals to safely and confidentially share data, thereby improving the capabilities to look for patterns that are indicative of research integrity concerns across journals and publishers, which is crucial to safeguarding the integrity of the scholarly record.

Joris van Rossum, Product Director of the Integrity Hub, comments: “Since the STM Integrity Hub was launched two years ago, we have seen 35 organizations join — publishers as well as other infrastructure and service providers such as editorial systems. Manuscript Manager allows us many other publishers to join the STM Integrity Hub, forming an even wider ecosystem of organizations sharing data to collectively combat research fraud.”

Andy Beare, CEO of Manuscript Manager, is delighted to be a collaborator in the STM Integrity Hub projects. “These initiatives are important in ensuring high standards and confidence in scholarly publications for the academic community. Our customers will also benefit from having access to real-time reports and alerts as part of an automated and efficient process.”

The STM Integrity Hub, founded by STM members and developed by STM Solutions, helps publishers to safeguard research integrity. It allows publishers of all sizes to share data and experiences and offers a variety of tools to identify and respond to materials that violate established standards of quality, ethics, and integrity. In April 2023, the Integrity Hub released the MVP of a paper mill detection tool designed to flag indicators suggesting a manuscript originated from a paper mill, followed by the October launch of a pilot program for detecting duplicate submissions. These tools will be further developed in 2024 and made available to publishers as widely as possible.

PubHive Ltd., a leading provider of AI-powered scientific literature & safety information workflows, today announced a revolutionary new feature: Local Literature Automation for Online & Paper Journals. This innovative tool streamlines and simplifies the process of tracking, analysing, and reporting on local literature with unprecedented efficiency and accuracy for life science companies, CROs (Clinical Research Organizations) and their pharmacovigilance and drug safety divisions. This groundbreaking solution is set to transform the way organizations / CROs handle regional/local literature publications, enhancing efficiency, simplifying compliance in the process and empowering pharmacovigilance teams.

Say goodbye to siloed information and manual processes. PubHive’s unified platform consolidates local literature for online and paper journals into a single source of truth, ensuring consistency and accessibility across teams and locations. AI-powered features automate tedious tasks like manually performing local literature activities, freeing up PV experts to focus on high-value activities like signal detection and risk assessment.

Key Features of Local Literature Automation for Online & Paper Journals

• Automatic Tracking: PubHive’s Local Literature Auto Tracker effortlessly monitors and tracks publications across territories and products, eliminating the need for manual searching and data entry. This ensures comprehensive coverage for both online and paper journals while minimizing the risk of oversight.
• OCR & Machine-Readable Translation: Paper journals are automatically scanned, converted to digital text using Optical Character Recognition (OCR), and translated into machine-readable formats, making them instantly searchable, all in real-time.
• Multilingual Keyword Highlighting: Search and highlight keywords across multiple regional languages, ensuring no relevant research falls through the cracks.
• Collaboration and Communication: Assign specific territories to different teams, streamlining workflows and fostering regional expertise.
• Compliance-Ready Reporting: Generate comprehensive reports on local literature activity for various compliance needs, including regulatory compliance and oversight.
• Customizable Workflows: Create standardized research pathways tailored to specific PV Local Literature Workflow for ICSR, Signal and Aggregate Safety Reporting. This customization ensures users can access the resources and data tailored to their workflow requirements.

Transforming Local Literature Workflow:

“Tracking local literature for online and paper journals is challenging due to manual effort, language barriers, and incomplete data,” says Raj Vaghela, CEO at PubHive. “Our Local Literature Automation breaks down these barriers, providing pharmacovigilance teams with a powerful tool to discover, analyse, and report on local literature with speed, accuracy, and confidence.”

Beyond Automation: Local Literature Auto Tracker goes beyond simply automating tasks. It offers a comprehensive end-to-end solution for managing local literature across the research and compliance lifecycle of pharmacovigilance.

Benefits for Life Science Companies and CROs:

• Significantly reduced time and effort spent on local literature research.
• Improved accuracy and completeness of local data for informed decision-making.
• Enhanced compliance with local and regional regulations.
• Streamlined collaboration and workflow management for local literature teams.
• Greater access to valuable insights from previously untapped local research sources.

PubHive’s commitment to innovation and efficiency has made it a trusted partner for Life Sciences Companies and CROs worldwide. With the launch of the Local Literature Auto Tracker, PubHive continues to set new industry standards, further solidifying its position as a leader in the scientific literature & safety information workflows.

With PubHive’s Local Literature Automation, organizations can optimize their local literature management processes, reduce manual workload, and ensure compliance with ease. For more information about PubHive’s Local Literature Automation and other cutting-edge solutions, please visit the PubHive website at https://pubhive.com.

Silverchair announced today a new partnership with The Association for Materials Protection and Performance (AMPP), the world’s leading organization dedicated to the protection of assets and performance materials. The new unified digital library on the Silverchair Platform will serve as a repository for AMPP’s vast range of content, including primary research, industry standards, technical and professional publications, and educational materials. It will also provide a platform for AMPP to expand its reach, offering its valuable resources to a wider global audience.

AMPP protects infrastructure and assets worldwide through member and workforce education and credentialing, company accreditation, technological innovation, and global standardization. As part of a content unification initiative, AMPP sought to create a digital library that brings together their wide array of content, including standards, their flagship journal Corrosion, Materials Performance Magazine, Coatings Pro Magazine, 30 books, and more than 22,000 conference papers. The digital library will leverage Silverchair’s scalable, responsive technology to provide access to a wealth of materials for AMPP’s growing audience of scholars and professionals.

“Our partnership with AMPP symbolizes the alignment of our missions to disseminate valuable knowledge and resources on a global scale,” said Will Schweitzer, Silverchair’s CEO. “The AMPP team has ambitious plans for the important resources they publish, and we’re delighted to partner with them in delivering a unified platform and providing their team with the tools and services to assemble varied content sets into the next generation of knowledge products for their audience.”

“We are beyond delighted to partner with Silverchair, creating the way for us to bring much of our content under one umbrella,” said Mandy May, Director, Content Management at AMPP. “This is particularly significant in that we are aggregating legacy knowledge resource content from our historical organizations, providing a tangible way to demonstrate our AMPP mission and vision. It will be a truly user-friendly experience, making our library accessible and the content discoverable for our entire global audience.”

A team of clinical and health care experts from EBSCO Information Services’ (EBSCO) Clinical Decisions embarks on a journey to leverage generative artificial intelligence (AI) technology within its point-of-care resources, with the goal to deliver faster-than-ever access to their industry-leading, evidence-based, expert-curated, trusted information to clinicians, nurses and health care professionals.

In today’s technological health care environment, clinicians must take several steps to access the clinical information they need, inputting a query into a search interface, then reviewing the search results and navigating to a topic to find answers. Clinical experts at Clinical Decisions are exploring the use of AI to bring answers directly to the bedside, making it easy to obtain near instantaneous answers, leveraging the use of large language models (LLMs) within EBSCO’s trusted, evidence-based environment.

When considering the use of AI in a clinical environment, a judicious approach is necessary, especially considering clinical diagnosis and treatment. The Clinical Decisions editorial team, led by Dr. Peter Oettgen, Editor-in-Chief, DynaMed^®, Diane Hanson, Editor-in-Chief, Dynamic Health^™, and Dr. Katherine Eisenberg, Sr. Medical Director, Clinical Decisions, is releasing principles for the responsible use of AI, centered around quality, security and patient privacy, transparency, governance and equity.

EBSCO Vice President of Product Management, DynaMedex^™, Julia Colpitts, says the team is prioritizing a safe environment, first and foremost. “Patient safety is our top priority. Our ‘walled garden’ approach ensures access to trusted, evidence-based content, developed by clinical experts following our rigorous editorial process. With the right safeguards in place, our team is exploring AI-based tools collaboratively, among our team of technologists, clinicians, subject matter experts and clinical editors, to ensure no stone is unturned.”

EBSCO Vice President of Product Management Dynamic Health, Peter Darcy, says this initiative reflects the team’s commitment to enhancing patient care. “By safely and appropriately leveraging the power of AI, we’re looking to decrease time to answer while providing accurate, evidence-based information to health care professionals, when and where they need it. Our goal is to help patients and caregivers arrive at the answers they need, positively impacting patient outcomes.”

For more information on this initiative, please visit: https://more.ebsco.com/Innovation-Center.html.

The Commission welcomes the political agreement reached between the European Parliament and the Council on the Artificial Intelligence Act (AI Act), proposed by the Commission in April 2021.

Ursula von der Leyen, President of the European Commission, said: “Artificial intelligence is already changing our everyday lives. And this is just the beginning. Used wisely and widely, AI promises huge benefits to our economy and society. Therefore, I very much welcome today’s political agreement by the European Parliament and the Council on the Artificial Intelligence Act. The EU’s AI Act is the first-ever comprehensive legal framework on Artificial Intelligence worldwide. So, this is a historic moment. The AI Act transposes European values to a new era. By focusing regulation on identifiable risks, today’s agreement will foster responsible innovation in Europe. By guaranteeing the safety and fundamental rights of people and businesses, it will support the development, deployment and take-up of trustworthy AI in the EU. Our AI Act will make a substantial contribution to the development of global rules and principles for human-centric AI.” 

The European approach to trustworthy AI

The new rules will be applied directly in the same way across all Member States, based on a future-proof definition of AI. They follow a risk-based approach:

Minimal risk: The vast majority of AI systems fall into the category of minimal risk. Minimal risk applications such as AI-enabled recommender systems or spam filters will benefit from a free-pass and absence of obligations, as these systems present only minimal or no risk for citizens’ rights or safety. On a voluntary basis, companies may nevertheless commit to additional codes of conduct for these AI systems.

High-risk: AI systems identified as high-risk will be required to comply with strict requirements, including risk-mitigation systems, high quality of data sets, logging of activity, detailed documentation, clear user information, human oversight, and a high level of robustness, accuracy and cybersecurity. Regulatory sandboxes will facilitate responsible innovation and the development of compliant AI systems.

Examples of such high-risk AI systems include certain critical infrastructures for instance in the fields of water, gas and electricity; medical devices; systems to determine access to educational institutions or for recruiting people; or certain systems used in the fields of law enforcement, border control, administration of justice and democratic processes. Moreover, biometric identification, categorisation and emotion recognition systems are also considered high-risk. 

Unacceptable risk: AI systems considered a clear threat to the fundamental rights of people will be banned. This includes AI systems or applications that manipulate human behaviour to circumvent users’ free will, such as toys using voice assistance encouraging dangerous behaviour of minors or systems that allow ‘social scoring’ by governments or companies, and certain applications of predictive policing. In addition, some uses of biometric systems will be prohibited, for example emotion recognition systems used at the workplace and some systems for categorising people or real time remote biometric identification for law enforcement purposes in publicly accessible spaces (with narrow exceptions).

Specific transparency risk: When employing AI systems such as chatbots, users should be aware that they are interacting with a machine. Deep fakes and other AI generated content will have to be labelled as such, and users need to be informed when biometric categorisation or emotion recognition systems are being used. In addition, providers will have to design systems in a way that synthetic audio, video, text and images content is marked in a machine-readable format, and detectable as artificially generated or manipulated.

Fines

Companies not complying with the rules will be fined. Fines would range from €35 million or 7% of global annual turnover (whichever is higher) for violations of banned AI applications, €15 million or 3% for violations of other obligations and €7.5 million or 1.5% for supplying incorrect information. More proportionate caps are foreseen for administrative fines for SMEs and start-ups in case of infringements of the AI Act.

General purpose AI

The AI Act introduces dedicated rules for general purpose AI models that will ensure transparency along the value chain. For very powerful models that could pose systemic risks, there will be additional binding obligations related to managing risks and monitoring serious incidents, performing model evaluation and adversarial testing. These new obligations will be operationalised through codes of practices developed by industry, the scientific community, civil society and other stakeholders together with the Commission.

In terms of governance, national competent market surveillance authorities will supervise the implementation of the new rules at national level, while the creation of a new European AI Office within the European Commission will ensure coordination at European level. The new AI Office will also supervise the implementation and enforcement of the new rules on general purpose AI models. Along with the national market surveillance authorities, the AI Office will be the first body globally that enforces binding rules on AI and is therefore expected to become an international reference point. For general purpose models, a scientific panel of independent experts will play a central role by issuing alerts on systemic risks and contributing to classifying and testing the models.

Next Steps

The political agreement is now subject to formal approval by the European Parliament and the Council and will entry into force 20 days after publication in the Official Journal. The AI Act would then become applicable two years after its entry into force, except for some specific provisions: Prohibitions will already apply after 6 months while the rules on General Purpose AI will apply after 12 months.

To bridge the transitional period before the Regulation becomes generally applicable, the Commission will be launching an AI Pact. It will convene AI developers from Europe and around the world who commit on a voluntary basis to implement key obligations of the AI Act ahead of the legal deadlines.

To promote rules on trustworthy AI at international level, the European Union will continue to work in fora such as the G7, the OECD, the Council of Europe, the G20 and the UN. Just recently, we supported the agreement by G7 leaders under the Hiroshima AI process on International Guiding Principles and a voluntary Code of Conduct for Advanced AI systems.

Background

For years, the Commission has been facilitating and enhancing cooperation on AI across the EU to boost its competitiveness and ensure trust based on EU values. 

Following the publication of the European Strategy on AI in 2018 and after extensive stakeholder consultation, the High-Level Expert Group on Artificial Intelligence (HLEG) developed Guidelines for Trustworthy AI in 2019, and an Assessment List for Trustworthy AI in 2020. In parallel, the first Coordinated Plan on AI was published in December 2018 as a joint commitment with Member States.

The Commission’s White Paper on AI, published in 2020, set out a clear vision for AI in Europe: an ecosystem of excellence and trust, setting the scene for today’s political agreement. The public consultation on the White Paper on AI elicited widespread participation from across the world. The White Paper was accompanied by a ‘Report on the safety and liability implications of Artificial Intelligence, the Internet of Things and robotics‘ concluding that the current product safety legislation contains a number of gaps that needed to be addressed, notably in the Machinery Directive.

Independent, evidence-based research produced by the Joint Research Centre (JRC) has been fundamental in shaping the EU’s AI policies and ensuring their effective implementation. Through rigorous research and analysis, the JRC has supported the development of the AI Act, informing AI terminology, risk classification, technical requirements and contributing to the ongoing development of harmonised standards.