Resources
Trends in automated clinical validation
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Beyond Double Programming: A New Approach to Clinical Table Validation with AI
Clinical biometrics teams are under increasing pressure to deliver faster while managing growing study complexity and maintaining confidence in every result. In this short demonstration, you’ll see how Verify Intelligence uses a metadata-driven AI approach to independently generate validation outputs, compare them with production results, and provide complete explainability and traceability throughout the validation process. […] -
Governance in Clinical Development
The Technology Is Ready. The Question Is Whether the Organization Is Governed to Use It. For years, the case against AI in clinical development rested on the technology itself: models weren’t mature enough, data wasn’t structured enough, tools weren’t reliable enough. Those concerns were reasonable at the time, and they are becoming less relevant by […] -
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The Metadata Layer Behind Trusted AI
Why AI Success Depends Less on Models and More on Metadata Most conversations about AI in clinical development focus on the model: which one performs best, how accurate it is, what it can generate. Fewer focus on what actually determines whether that output can be trusted: the metadata behind it. Across biometrics, data management, and […] -
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Programming was never the true bottleneck
AI Didn’t Create a New Bottleneck. It Exposed the One That Was Always There. We recently demonstrated something that would have seemed impossible just a few years ago. 200+ clinical tables. Generated independently. Fully validated. Completed in under three hours. That’s an impressive technical milestone. But it isn’t the most important story. Because when AI […] -
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The New Clinical Review Workflow: Human Expertise + AI Validation
AI Won’t Replace Reviewers. It Will Change What They Spend Time Reviewing. Much of the discussion surrounding AI in clinical development has focused on automation. Can AI identify discrepancies? Can it generate outputs? Can it validate tables faster than humans? These are important questions. But they miss a more significant opportunity. The future of clinical […] -
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Why AI Transparency Matters More Than AI Accuracy
Accuracy Gets Attention. Transparency Earns Trust. When organizations evaluate AI solutions for clinical development, the first question is almost always: “How accurate is it?” It’s a reasonable question. Clinical teams operate in highly regulated environments where quality, consistency, and traceability directly impact submissions, inspections, and ultimately patient outcomes. But as AI adoption matures across the […] -
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Blueprint: Why Data Doesn’t Turn Into Submissions Automatically
Data Doesn’t Become a Submission Just Because It’s Structured One of the biggest misconceptions in clinical development is the belief that once data is standardized, the hard work is done. After all, most organizations already have: Yet submissions are still slow. Why? Because data alone doesn’t explain how a clinical output should be constructed. The […] -
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From Automation to GenAI: The Evolution of Statistical Validation
Back in 2022, we explored the benefits of automating statistical validation for clinical studies. At the time, the conversation centered on efficiency. Automation promised to reduce manual effort, accelerate review cycles, and improve consistency across deliverables. Four years later, the conversation has changed. Today, most biometrics leaders already agree that manual review is inefficient. The […] -
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Blueprint: The Architecture Behind Clinical GenAI
Clinical Teams Don’t Have a Data Problem. They Have an Output Problem. Over the last decade, the industry invested heavily in data infrastructure. SDTM.ADaM.Data lakes.Centralized platforms.Standardized pipelines. Those investments worked. Most clinical organizations can access structured data faster than ever before. Yet one challenge remains stubbornly manual:Turning that data into submission-ready outputs. Whether it’s a […] -
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Blueprint: AI Only Scales After Validation and Integration Are in Place
AI is no longer a question of if in clinical operations.But most organizations are solving the wrong problem. They are investing in models before fixing the systems those models depend on. Across the industry, organizations are investing heavily in AI to accelerate timelines, reduce manual effort, and modernize clinical workflows. These efforts often sit within […] -
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Blueprint: Why Biometrics Still Runs on Documents and Why AI Cannot Scale Until That Changes
AI adoption in clinical biometrics does not stall because the technology is immature.It stalls because the operating model is still document based. Word files, spreadsheets, and static outputs were never designed to support automation, validation, or intelligence at scale. Yet much of clinical data production still depends on these formats to define specifications, communicate changes, […] -
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Blueprint: TLF Validation: The Control Layer of Clinical Data Transformation
In clinical development, tables, listings, and figures are where data becomes decisions. Yet this is also where many digital transformation efforts quietly break down. Despite major investments in automation and analytics, TLF validation remains largely manual, fragmented, and disconnected from the broader data ecosystem. Review happens across emails, spreadsheets, and scattered files. Oversight depends on […] -
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Blueprint: Why Integration Is the Backbone of an Intelligent Biometrics Framework
Digital transformation in clinical data is often framed as an AI problem.In practice, it is an integration problem. Before automation can scale and before AI can be trusted in regulated workflows, clinical organizations must solve a more fundamental challenge. They must connect documents, platforms, and standards into a shared, compliant operating foundation. This blueprint defines […] -
Verify Validate: Automated TLF vs. LoT Checks
Watch this short walkthrough video to see how Verify’s automated TLF vs. LoT checks quickly detect discrepancies between tables, listings, and figures (TLFs) compared to the corresponding list of tables (LoT). Verify quickly flags discrepancies such as TLF title and number mismatches, population misalignment, and missing files, enabling biometrics teams to investigate issues in context. […] -
Verify Validate: Automated LoT Validation Checks
Watch this short walkthrough video to see how Verify’s automated LoT validation checks catch common LoT issues that risk submission quality and can easily go unnoticed by the human eye, including automated identification of duplicate table numbers, overly long titles, and missing fields. Verify quickly flags discrepancies, which enables biometrics teams to investigate in context, […] -
Verify Validate: Automated TLF vs. Mock Shell Checks
Watch this short walkthrough video to see how Verify’s automated TLF vs. Mock Shell checks catch discrepancies between titles and footnotes in tables, listings, and figures compared to corresponding mock shells. Verify quickly flags missing or misaligned titles and footnotes, saving time of manually cross-checking TLFs against mock shells and enabling biometrics teams to investigate […] -
Case Study: How Phastar Uses Verify to Accelerate Clinical Data Review
Accelerating Clinical Data Review: Addressing Fragmentation, Improving Collaboration, and Reducing Review Cycle Times by 35% Download PDF: Phastar-Beaconcure Case Study Industry Challenge: Disconnected Review Workflows, Lack of Automation, and Lengthy Data Review Cycles Clinical data analysis review remains a critical, yet often fragmented, element of the clinical trial process. Many organizations still rely on manual […] -
How Verify Is Positioned to Lead in the FDA’s AI-Driven Future
The FDA’s recent announcement about completing its first AI-assisted scientific review pilot and its aggressive timeline to scale AI across all centers by June 2025 represents a seismic shift in the regulatory landscape. As the COO and Head of Product at Beaconcure, I see this as a tremendous validation of our vision and a significant […] -
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PHUSE US Connect 2025 Summary
PHUSE US Connect 2025 in Orlando, Florida from March 16-19 was a wonderful whirlwind! We had many interesting conversations at our booth and during our four sessions about the future of statistical analysis, how human-in-the-loop feedback can balance AI automation in TLF validation processes, and the growing need for better oversight and visibility in review […] -
Beaconcure Podcast: Clinical Trial Innovation – Spotlight on Quality, Review, and Collaboration
In this video podcast, Névine Zariffa, leading voice in biometrics and data science, and Beaconcure Co-Founder and COO Ilan Carmeli, discuss the future of technology in improving clinical trial efficiency and quality during statistical analysis review. Névine and Ilan discuss some of the challenges reviewers currently face using traditional review processes, and Ilan demonstrates new […] -
PharmaSUG 2024 Summary
On the first day of PharmaSUG 2024 in Baltimore, Beaconcure was thrilled to announce a strategic partnership with Phastar to deliver process revolution in clinical data review. This partnership combines Beaconcure’s advanced technology with Phastar’s extensive experience and vision in the clinical data analytics domain, to streamline clinical trial development and accelerate the delivery of […] -
Beaconcure Webinar Series: Transforming Clinical Review Processes: Beyond Traditional Boundaries
In the rapidly evolving landscape of clinical data analysis, the need for innovative approaches to review and validation processes has never been more critical. This webinar, Transforming Clinical Review Processes: Beyond Traditional Boundaries, is part of a series that delves into aspects of transforming clinical data analysis and review processes. Biometrics expert Irving Dark leads […] -
PHUSE US Connect 2024 Summary
At PHUSE US Connect 2024 in Rockville, conversations at the Beaconcure booth (between rounds of Blackjack!) were lively and interesting, as we delved deep into how the Verify platform leverages automation and AI-enabled processes to replace manual validation processes — now and in the future. Beaconcure Director of Statistics and Life Sciences, Steve Ross, presented […] -
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PHUSE Webinar Wednesday January 2024: Demonstration of Verify
Beaconcure was honored to take part in the PHUSE Webinar Wednesday series on January 31st, 2024. Co-founder and COO Ilan Carmeli joined a fascinating speaker line-up to share a demonstration of Verify, showcasing how AI-enabled processes enhance study validation workflows. The FDA has already received more than 100 studies that incorporate some form of Artificial […] -
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How to Build a Strong AI Foundation
The adoption of Artificial Intelligence (AI) has become a buzzword, promising to revolutionize industries and enhance productivity. However, a common pitfall for many companies is a top-down approach to technology implementation, which can include entering into partnerships with AI companies without first addressing the critical need for a robust infrastructure. In this article, we explore […] -
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PHUSE EU Connect 2023 Summary
PHUSE EU Connect 2023 in Birmingham, UK from November 5-8 was a resounding success. Our Beaconcure conference participants enjoyed discussions at our booth and during engaging sessions with experts on a wide range of clinical data science topics impacting the industry today. At the outset of PHUSE EU, we were pleased to announce the launch […] -
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Identifying Data Anomalies with Verify: Quality Assurance Techniques
Identifying data anomalies can be a challenging, lengthy and laborious process. Verify's quality assurance tools save time and money and minimize the risk of missing data anomalies. -
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Clinical Trial Data Visualization: The New FDA Guideline on Standard Formats for Tables and Figures
Clinical trial data visualization plays a pivotal role in effectively communicating the results of drug trials to regulatory agencies like the FDA. However, inconsistencies in the format and presentation of safety data can hinder the interpretation and evaluation of crucial information by FDA reviewers. The new FDA guideline seeks to address this issue by establishing […] -
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Statistical Programmer’s Top Challenges in Clinical Trial Data Validation
Clinical trials play a vital role in advancing medical knowledge and improving patient care. They involve meticulous data collection, rigorous statistical analysis, and accurate reporting of findings. However, the process of generating outputs from diverse input datasets and adhering to specific requirements can be complex, potentially leading to errors. Different stakeholders in the company can […] -
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The Essential Role of Biostatistics in Clinical Trials
And How to Empower Biostatisticians for Faster Output Approval with Enhanced Quality Biostatistics in clinical trials plays a crucial role in the development of new drugs and medical treatments. Clinical trials serve as the cornerstone for evaluating the safety and effectiveness of potential therapies before they reach the public. Within this realm, biostatisticians shoulder a […] -
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How Automated Data Quality Control Impacts the CSR in Clinical Trials
Biostatisticians and medical writers at enterprise pharmaceutical companies have a huge responsibility on their shoulders: ensuring that the Clinical Study Report (CSR) of the clinical trial is accurate, and ready to be submitted to the regulatory authorities for review. Managing this process within an enterprise can be especially challenging when teams are spread across multiple […] -
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Beaconcure Knowledge Bazaar at PHUSE US Connect 2023
Beaconcure was proud to sponsor the PHUSE US 2023 conference in Orlando earlier this year. As part of our sponsorship, we hosted a series of knowledge bazaar sessions at our sponsor zone during the breaks, which were well-attended by fellow professionals from across the pharmaceutical industry. These sessions provided an excellent opportunity for attendees to […] -
Streamline Your Output
Validation With VerifyBy Roi Kain, Product Marketing Manager If you have some downtime between one analysis to another, why not spend a minute reading about the new features in Verify, Beconcure’s output management platform? These updates are aimed at improving your output management process, reducing your workload, and helping you stand out. Let’s dive in. TLFs ConverterThe […] -
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May 2022 Conferences
During May, Beaconcure has participated in two international conferences: PHUSE US Connect and PharmaSUG Austin. At both conferences, we presented and exhibited. PHUSE US Connect 2022: The US Connect 2022 took place in Atlanta, Georiga, USA between May 1-4. The conference welcomed more than 500 attendees from 120 companies. On the first official day of […] -
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Pfizer Shortens Submission Timelines Using Verify
Automating clinical trial data validation when the world needed it most Prior to the onset of COVID-19, Pfizer recognized an industry need for automated validation of statistical analysis outputs, and collaborated with Beaconcure to develop Verify. When the pandemic hit and the world needed it most, Pfizer was able to leverage Verify during COVID-19 vaccine […] -
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The Future of Statistical Computing: Environment Platforms
While an “ideal” Statistical Computing Environment (SCE) is highly sought for in the pharmaceutical industry, one is yet to be developed. To encourage tech business leaders to develop such a platform, experts from top global pharma companies have compiled their requirements for the ideal SCE. These requirements were published in December 2021 in a white […] -
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Benefits of Automating Statistical Analysis for Clinical Studies
The Current Status Statistical analysis output validation takes time and effort but does not guarantee a high-quality deliverable. Errors are still likely to go uncorrected. When submitting a study to the regulator, the expectation is that the output validation tasks -which are lengthy and expensive timewise – will be done with impeccable accuracy. The validation […] -
Articles
What Makes Multiple Cross-Table Checks Challenging?
The limitation of the current process and the new approach -
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Pharma 4.0
Background The world has experienced three different industrial revolutions since the 18th century, and each time, it has affected the production process of multiple industries. As the activities evolved, technology followed the way. The fourth industrial revolution is happening right now as a continuation of the third – that started in the 20th century. It […] -
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Parsing and Cell Reading
Parsing is the process of analyzing a string of symbols, either in natural language, computer languages, or data structures, confronting the rules of formal grammar. Beaconcure’s take revolves around analyzing clinical data structures that appear in tables and were created with SAS programming. Parsing is the way of the algorithm to take raw clinical tables, […] -
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Why We Should All Strive for Standardization
Standardization is crucial in order to create a true revolution in the clinical trials industry. We are getting closer to the day that all clinical trials will be accelerated by the automation of manual processes. Getting there is inevitably intertwined with analyzing clinical data in a coherent, consistent way. How does this work? Clinical trials […] -
Table Mining
Table mining is the core of our capabilities ensuring full validation of statistical outputs -
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The Emerging Use of Automation
Second Abstract for presentation at the Phuse US Connect 2022 -
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Data Mining of Tables: The Barrier for Automation
First Abstract for presentation at the Phuse US Connect 2022 -
PHUSE/FDA CSS 2021 Poster
A Comprehensive Approach to the Output Validation Process. New Uses for Machine Learning & Artificial Intelligence -
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How Automation Can Improve Cross Table Validation
The combination of the human factor and artificial intelligence is the key to success -
Phuse US Connect 2021
How ML-driven Automation Technology Can Overcome the limitation of Double Programming -
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Q&A Session at PHUSE US Connect 2021
How ML-driven Automation Technology Can Overcome the Limitations of Double Programming -
Industry Survey
Results of Survey into Statistical Programming Practices -
White Papers
White Paper: The Power of Automation in Clinical Data Validation
The Power of Automation in Clinical Data Validation -
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Data Visualization for Clinical Data Validation
Data visualization facilitates a faster, easier and more accurate clinical data validation
From manual QC to a more scalable model
Reduce the validation bottleneck without compromising confidence. Verify helps biometrics teams move beyond resource-intensive validation processes and duplicated programming effort — accelerating QC while maintaining the independence and rigor required for clinical trials.
Less manual effort. Faster validation. Greater confidence.