AI Research
Elsevier Announces Next-Generation AI-Powered Researcher Solution

Driven by customer feedback, new comprehensive AI solution will provide a next-level experience combining latest technology with unmatched content depth, breadth and quality to accelerate breakthroughs, improve impact and productivity
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LONDON, Sept. 17, 2025 /PRNewswire/ — Elsevier, a global leader in advanced information and decision support in science and healthcare, today announced it is developing a next-generation ‘end-to-end’ AI-powered solution for academic and corporate researchers, in collaboration with the research community. The solution aims to transform the research workflow – helping scientists move faster from insights to impact while safeguarding research integrity, transparency and trust.
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The new Elsevier AI solution will empower researchers to identify emerging areas of inquiry and funding opportunities, uncover knowledge gaps, synthesize literature rapidly, connect with collaborators and accelerate productivity. The solution builds on the success of ScienceDirect AI and Scopus AI, and represents a step-change for AI solutions that support the global research community.
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Generic AI tools can fall short of helping researchers focus on original impactful thinking, as they rely on limited academic literature, low-quality data and offer little transparency about how conclusions are reached. Elsevier’s comprehensive AI solution will be designed to address these challenges head-on with a fundamentally different approach.
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What will set the new solution for researchers apart:
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One seamless assistant: Brainstorm ideas, plan projects, review literature, find collaborators, and discover funding opportunities – all in one space with a powerful AI assistant.
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Trust Cards: Showing how evidence was used or inferred, highlighting confidence levels and providing risk assessments for potential inaccuracies.
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Certified content only: Access comprehensive, peer-reviewed, cross-publisher academic content.
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Curated datasets: Answers powered by publisher-neutral datasets e.g. Scopus abstracts and funding data.
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Add your own content: Users can add their own content to supplement what is already included.
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Privacy and security: Built with enterprise-grade security, Elsevier AI-powered solutions are developed in line with its Privacy Principles to safeguard personal data and privacy.
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Publisher-neutral algorithms: An independent Advisory Board will be created to ensure results are prioritized and ranked based on quality, in a transparent, unbiased and responsible manner.
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Elsevier’s new AI solution will be built on millions of peer-reviewed articles and book chapters from the world’s leading academic publishers. The new solution will be publisher-neutral and include subscription and Open Access content, giving researchers unprecedented depth and coverage. The solution will include ScienceDirect’s trusted content, combined with comprehensive data and analytics from Scopus’ 100+ million interconnected records.
AI Research
Advarra launches AI- and data-backed study design solution to improve operational efficiency in clinical trials

Advarra, the market leader in regulatory reviews and a leading provider of clinical research technology, today announced the launch of its Study Design solution, which uses AI- and data-driven insights to help life sciences companies design protocols for greater operational efficiency in the real world.
Study Design solution evaluates a protocol’s feasibility by comparing it to similar trials using Braid™, Advarra’s newly launched data and AI engine. Braid is powered by a uniquely rich set of digitized protocol-related documents and operational data from over 30,000 historical studies conducted by 3,500 sponsors. Drawing on Advarra’s institutional review board (IRB) and clinical trial systems, this dataset spans diverse trial types and therapeutic areas, provides granular detail on schedules of assessment, and tracks longitudinal study modifications, giving sponsors deeper insights than solutions based only on in-house or public datasets.
“Too often, clinical trial protocols are developed without the benefit of robust comparative intelligence, leading to inefficient designs and operations,” said Laura Russell, senior vice president, head of data and AI product development at Advarra. “By drawing on the industry’s largest and richest operational dataset, Advarra’s Study Design solution delivers deeper insights into the feasibility of a protocol’s design. It helps sponsors better anticipate downstream operational challenges, make more informed decisions to simplify trial designs, and accelerate protocol development timelines.”
Advarra’s Study Design solution can be used to optimize a protocol prior to final submission or for retrospective analyses. The solution provides insights on design factors that drive operational feasibility, such as the impact of eligibility criteria, burdensomeness of the schedule of assessment on sites and participants, and reasons for amendments. Study teams receive custom benchmarking that allows for operational risk assessments through tailored data visualizations and consultations with Advarra’s data and study design experts. Technical teams can work directly within Advarra’s secure, self-service insights workspace to explore operational data for the purpose of powering internal analyses, models, and business intelligence tools.
“Early pilots have already demonstrated measurable impact,” added Russell. “In one engagement, benchmarking a sponsor’s protocol against comparable studies revealed twice as many exclusion criteria and 60 percent more site visits than industry benchmarks. With these insights, the sponsor saw a path to streamline future trial designs by removing unnecessary criteria, clustering procedures, and adopting hybrid visit models, ultimately reducing site burden and making participation easier for patients.”
Study Design solution is the first in a series of offerings by Advarra that will be powered by Braid. Future applications will extend insights beyond protocol design to improve study startup, enhance collaboration, and better support sites.
To learn more about Study Design solution or to request a consultation, visit advarra.com/study-design.
About Advarra
Advarra breaks the silos that impede clinical research, aligning patients, sites, sponsors, and CROs in a connected ecosystem to accelerate trials. Advarra is number one in research review services, a leader in site and sponsor technology, and is trusted by the top 50 global biopharma sponsors, top 20 CROs, and 50,000 site investigators worldwide. Advarra solutions enable collaboration, transparency, and speed to optimize trial operations, ensure patient safety and engagement, and reimagine clinical research while improving compliance. For more information, visit advarra.com.
AI Research
Best Artificial Intelligence (AI) Stock to Buy Now: Nvidia or Palantir?

Palantir has outperformed Nvidia so far this year, but investors shouldn’t ignore the chipmaker’s valuation.
Artificial intelligence (AI) investing is a remarkably broad field, as there are numerous ways to profit from this trend. Two of the most popular are Nvidia (NVDA -1.55%) and Palantir (PLTR -0.58%), which represent two different sides of AI investing.
Nvidia is on the hardware side, while Palantir produces AI software. These are two lucrative fields to invest in, but is there a clear-cut winner? Let’s find out.
Image source: Getty Images.
Palantir’s business model is more sustainable
Nvidia manufactures graphics processing units (GPUs), which have become the preferred computing hardware for processing AI workloads. While Nvidia has made a ton of money selling GPUs, it’s not done yet. Nvidia expects the big four AI hyperscalers to spend around $600 billion in data center capital expenditures this year, but projects that global data center capital expenditures will increase to $3 trillion to $4 trillion by 2030. That’s a major spending boom, and Nvidia will reap a substantial amount of money from that rise.
However, Nvidia isn’t completely safe. Its GPUs could fall out of style with AI hyperscalers as they develop in-house AI processing chips that could steal some of Nvidia’s market share. Furthermore, if demand for computing equipment diminishes, Nvidia’s revenue streams could fall. That’s why a subscription model like Palantir is a better business over the long term.
Palantir develops AI software that can be described as “data in, insights out.” By using AI to process a ton of information rapidly, Palantir can provide real-time insights for what those with decision-making authority should do. Furthermore, it also gives developers the power to deploy AI agents, which can act autonomously within a business.
Palantir sells its software to commercial clients and government entities, and has gathered a sizable customer base, although that figure is rapidly expanding. As the AI boom continues, these customers will likely stick with Palantir because it’s incredibly difficult to move away from the software once it has been deployed. This means that after the AI spending boom is complete, Palantir will still be able to generate continuous revenue from its software subscriptions.
This gives Palantir a business advantage.
Nvidia is growing faster
Although Palantir’s revenue growth is accelerating, it’s still slower than Nvidia’s.
NVDA Revenue (Quarterly YoY Growth) data by YCharts
This may invert sometime in the near future, but for now, Nvidia has the growth edge.
One item that could reaccelerate Nvidia’s growth is the return of its business in China. Nvidia is currently working on obtaining its export license for H20 chips. Once that is returned, the company could see a massive demand from another country that requires significant AI computing power. Even without a massive chunk of sales, Nvidia is still growing faster than Palantir, giving it the advantage here.
Nvidia is far cheaper than Palantir
With both companies growing at a similar rate, it would be logical to expect that they should trade within a similar valuation range. However, that’s not the case. Whether you analyze the stocks from a forward price-to-earnings (P/E) or price-to-sales (P/S) basis, Palantir’s stock is unbelievably expensive.
NVDA PE Ratio (Forward) data by YCharts
From a P/S basis, Palantir is about 5 times more expensive than Nvidia. From a forward P/E basis, it’s about 6.5 times more expensive.
With these two growing at the same rate, this massive premium for Palantir’s stock doesn’t make a ton of sense. It will take years, or even a decade, at Palantir’s growth rate to bring its valuation down to a reasonable level; yet, Nvidia is already trading at that price point.
I think this gives Nvidia an unassailable advantage for investors, and I think it’s the far better buy right now, primarily due to valuation, as Palantir’s price has gotten out of control.
Keithen Drury has positions in Nvidia. The Motley Fool has positions in and recommends Nvidia and Palantir Technologies. The Motley Fool has a disclosure policy.
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