CiteMed Evidence Cloud Altus: Software for Literature Review That Works the Way Regulatory Teams Actually Work

Summary

Finding software for literature review that genuinely works in a regulated medical device environment is harder than it should be. Most tools were designed for academic research and have been adapted, imperfectly, to regulatory use. CiteMed Evidence Cloud was built from the ground up for EU MDR and IVDR compliance teams who are managing Clinical Evaluation Reports, post-market surveillance, and PMCF obligations at the same time, under real deadline pressure.

The feedback we kept hearing from customers was the same: literature reviews take too long, involve too much manual work, and it is too easy to miss critical evidence. A typical systematic review means screening 500 or more abstracts, extracting data from 50 to 100 full-text articles, and producing comprehensive regulatory reports, all while the clock is running. So we got to work.

The Altus release delivers 280 improvements across every module of CiteMed Evidence Cloud. We rebuilt the navigation from scratch, taught the AI to explain its reasoning rather than just suggest decisions, made it possible to upload a PDF and have metadata extracted in 30 seconds, and laid the foundation for real-time post-market surveillance. Regulatory teams are now screening articles 3 to 5 times faster, configuring extraction fields 40% quicker, and spending 30% less time clicking through menus.

Key Takeaways

• CiteMed Evidence Cloud Altus delivers 280 improvements to software for literature review designed specifically for EU MDR and IVDR regulatory contexts
• AI screening now includes chain-of-thought reasoning so reviewers see exactly why a decision was suggested, not just what it was
• Living Reviews provides continuous post-market surveillance software monitoring without manual search re-runs, directly supporting PMCF obligations
• Regulatory teams are screening 3 to 5 times faster, with extraction configuration time down 40% and errors down 35%
• The Vigilance Module foundation is now live, extending CiteMed Evidence Cloud beyond literature review tools into full incident management and signal detection
• Direct PDF import creates an appraisal ready for extraction in 30 seconds versus 10 minutes previously
• Reference import success rate is up from 85% to 98%, with support tickets for import errors down 67%

Table of Contents

1. Direct Answer: What Is CiteMed Evidence Cloud Altus?
2. Why It Matters: The Problem With Generic Software for Literature Review
3. How It Works: Every Major Update Explained
4. Common Mistakes: Why Most Literature Review Tools Fall Short for EU MDR
5. Best Practices: Getting the Most From CiteMed Evidence Cloud Altus
6. Comparison Table
7. Checklist
8. Definitions
9. Expert Perspective
10. FAQ
11. References
12. Related Resources
13. Call to Action

What Is CiteMed Evidence Cloud Altus?

CiteMed Evidence Cloud Altus is the latest release of CiteMed’s systematic literature review software platform. It covers the Literature module, CiteSource reference library, Admin configuration, and the new Vigilance Module, with 280 improvements delivered across all of them.

It is built for medical device manufacturers and regulatory teams working under EU MDR 2017/745 and IVDR. That matters because software for literature review in this context needs to do more than run systematic reviews. It needs to support ongoing post-market surveillance, PMCF monitoring, and CER writing within a single audit-ready environment, not as separate tools that require manual coordination.

The headline improvements in Altus are AI-powered screening with chain-of-thought reasoning, Living Reviews for continuous database monitoring, direct PDF import in 30 seconds, and the Vigilance Module foundation for incident management and signal detection.

Why It Matters: The Problem With Generic Software for Literature Review

Under EU MDR, literature review is not a project with a start and end date. It underpins Clinical Evaluation Reports, feeds into post-market surveillance, and supports ongoing PMCF obligations throughout the entire device lifecycle. For IVDR performance evaluation the same applies.

The problem is that most citation managers and academic literature review tools were not designed with any of this in mind. They handle one review at a time, with a clear finish line. They do not connect to CER documentation, they do not monitor databases continuously, and they do not produce the kind of audit trail that holds up when a Notified Body starts asking questions.

What regulatory teams actually need from software for literature review under EU MDR is quite specific. A traceable audit trail for every screening decision. AI screening that shows its work rather than producing a black box output. A search protocol builder aligned with MEDDEV 2.7/1 Rev 4. PRISMA-aligned documentation. Continuous database monitoring for PMS and PMCF updates. And integration with clinical evaluation documentation rather than a tool that sits next to it.

CiteMed Evidence Cloud Altus was built around these requirements.

How It Works: Every Major Update in CiteMed Evidence Cloud Altus Explained

Literature Module: AI Screening, Query Building, and Continuous Monitoring

The Literature module is where regulatory teams spend 70% of their time, so that is where most of the Altus investment went. Systematic review software supports rigorous evidence synthesis through structured workflows for screening and data extraction.

The AI screening change is the most significant. Previously, AI tools suggested include or exclude. Now CiteMed Evidence Cloud explains why. For each abstract the AI reads the content, compares it against your inclusion and exclusion criteria, and returns a decision suggestion alongside a confidence score and a plain-language explanation of the reasoning. Something like: “This study discusses paediatric patients, but your review excludes participants under 18.” Reviewers see the logic, decide whether it is right, and override where needed. The result is 3 to 5 times faster abstract screening, with full reviewer oversight and a complete decision audit trail. That kind of acceleration is similar to how tools such as Elicit and Rayyan speed up literature discovery and screening.Shorten with AI

The new block-based query builder lets you construct searches visually using PICO structure — Population, Intervention, Comparison, Outcome — as discrete components. The AI suggests search terms based on your research question, and a syntax validator checks the query before it runs. It catches 90% of errors before they waste time. Teams are running 50% fewer search iterations as a result.

Living Reviews changes how PMCF and post-market surveillance literature monitoring works. Set up a search once, and CiteMed Evidence Cloud monitors PubMed, Embase, and other databases continuously. When new articles match your criteria, you are notified and can import them directly into your existing review. No manual re-runs. No scheduling quarterly search cycles. New evidence surfaces as it is published.

Direct PDF import uses AI to pull metadata automatically. Upload a PDF, get an appraisal created and ready for extraction in 30 seconds, with customizable summaries and extraction tables in AI-assisted workflows such as Elicit. Previously this took ten minutes per article.

The study arm model fixes a long-standing problem in multi-arm trial extraction. Label arms as Treatment, Control, or Placebo rather than Arm 1, Arm 2, Arm 3. Extract data once per arm and aggregate automatically. Extraction configuration time is down 40% and extraction errors are down 35%.

Review workflow improvements in CiteMed Evidence Cloud Altus include split-screen article comparison, auto-scroll to the article you were working on, filtering by review status, section navigation within articles, and historical state tracking so you can see who made every decision and when. Some discovery tools focus on how work is cited and whether findings are supported, contradicted, or simply mentioned, as seen in Scite.ai. Others, such as ResearchRabbit and Connected Papers, visualize connections between papers, authors, and publications to help users understand their relationships.

Report Templates and Forest Plots

Reports have been rebuilt on Vue 3, making them faster and more responsive. The dynamic table of contents updates automatically as you edit. Forest plots are now generated by a built-in statistical analysis engine that calculates pooled effects, heterogeneity, and confidence intervals using Matplotlib rendering, producing publication-quality outputs that embed directly into Word and PDF reports. Large reports with more than 1,000 appraisals no longer timeout.

QC Workflows

New quality control workflows in CiteMed Evidence Cloud Altus are built for 21 CFR Part 11 compliance. Every decision is logged with username and timestamp. Inter-rater agreement is calculated automatically using Cohen’s kappa. The audit trail is complete from the first screening decision through to final report generation.

CiteSource: Reference Library Rebuilt

CiteSource is CiteMed Evidence Cloud’s reference library, deduplicator, and metadata manager. It has been completely redesigned based on user feedback. Import success rate is now 98%, up from 85%. Support tickets about import errors are down 67%. Full RIS compatibility, PubMed TXT drag-and-drop, and correct EndNote XML downloads are all supported.

IP Rights Management adds colour-coded licence tracking: Open Access in green, Subscription in yellow, Permission Required in red. Licence tooltips, usage comments, automatic usage logging, and a copyright stamp on every downloaded PDF are all included.

The Microsoft Word add-in lets writers insert citations directly from CiteMed Evidence Cloud without leaving the document. AMA, Vancouver, and APA citation styles are supported. Reference lists generate automatically and stay in sync with any metadata changes in CiteMed Evidence Cloud.

Admin and Configuration

Role-based access control lets you assign specific roles with full permission inheritance and audit logging. Guest users can be invited with limited access for external collaborators. Centralised device management standardises how devices are defined and reused across projects. Extraction field lists can be configured once in Admin and applied consistently across every project. Polymorphic outcome measures including mean, median, hazard ratio, odds ratio, and ICER with per-arm capture feed directly into report generation, eliminating the manual spreadsheet rebuilding that previously consumed hours of reviewer time.

Vigilance Module

Post-market surveillance software needs to handle more than literature. When adverse events happen, teams need to capture, classify, and report them quickly. The Vigilance Module foundation is now live in CiteMed Evidence Cloud Altus.

Incident intake with structured fields covers device identification, event description, patient outcome, and root cause classification. Lifecycle management tracks incidents through configurable statuses from New through to Closed. Every incident is linked to a device from the centralised library. The audit trail logs every status change, edit, and assignment with a timestamp and user identity. A dashboard view shows all open incidents with filters by severity, device, and status.

Coming in the next release: AI adverse event classification using MedDRA coding, and automated signal detection that identifies emerging safety trends across the incident database before they become regulatory findings.

Coming Soon

AI Copilot arrives in Q2 2026. Ask CiteMed Evidence Cloud questions in natural language: “Show me all articles where the primary outcome was mortality,” “Which extractions are missing data?”, “Generate a summary of safety findings for Device X.” Enhanced reporting with version control, collaborative editing, and approval workflows follows in Q2 2026. CiteSource Smart Lists, which update automatically based on defined rules, are also in development.

Common Mistakes: Why Most Literature Review Tools and Systematic Reviews Fall Short for EU MDR

Regulatory teams run into the same problems repeatedly when trying to use generic software for literature review in a compliance context.

Using academic tools for regulatory workflows produces incomplete audit trails, untraceable screening decisions, and PRISMA counts that do not align with search outputs. Platforms such as Covidence are designed specifically for managing the systematic review workflow, but they still do not cover full EU MDR lifecycle needs. These are exactly the gaps Notified Bodies look for during conformity assessment.

Treating literature review as a one-time project means PMS and PMCF updates require full manual re-runs every cycle, which creates both workload and the risk that new evidence gets missed between updates.

While citation managers do improve organization and reproducibility, relying on them for evidence management leaves three critical gaps: no search strategy documentation, no structured screening workflows to organize sources around review questions, and no critical appraisal functionality. Citation management tools also support references, PDFs, notes, and citations. These are the three areas Notified Bodies scrutinise most closely during CER review.

For a full breakdown of how these gaps play out in regulatory submissions, see our article on common literature review challenges. In practice, effective reviews also depend on other tools, but regulatory teams still need one system to control the audit-ready workflow.

Best Practices: Getting the Most From CiteMed Evidence Cloud Altus

Build your search protocol in CiteMed Evidence Cloud before running any searches. Document your PICO structure, inclusion and exclusion criteria, and database selection within the platform so the audit trail starts from the very first search, not the first screening decision.

Set up extraction field lists in Admin once and apply them across all projects. Inconsistent extraction is one of the most common reasons CER writing takes longer than it should. Standardising configuration across the organization fixes this at the source.

Activate Living Reviews for every device with PMS and PMCF obligations as soon as possible. The longer continuous monitoring runs, the richer and more complete your timestamped surveillance record becomes.

Start logging in the Vigilance Module from day one. The AI signal detection and MedDRA classification features coming in the next release work better with a populated incident database, so early adoption pays off.

Comparison Table: CiteMed Evidence Cloud Altus vs Generic Literature Review Tools

Checklist: Is Your Literature Review Software Ready for EU MDR?

• Software maintains a complete audit trail for every screening decision with username and timestamp
• AI screening explains its reasoning, not just its recommendation
• Search protocol documentation is captured within the platform before searches run
• PRISMA-aligned outputs are generated automatically
• Continuous database monitoring supports ongoing PMS and PMCF literature updates without manual re-runs
• Extraction field configurations are consistent across projects and teams
• Multi-arm trial data is properly structured with per-arm capture
• Forest plots embed directly into regulatory reports
• Incident management and signal detection support post-market surveillance obligations
• Citation integration with Word eliminates manual reference handling
• IP rights management tracks licence status for every article used in submissions

Definitions

CiteMed Evidence Cloud: CiteMed’s integrated systematic literature review software platform designed for medical device manufacturers and regulatory teams operating under EU MDR and IVDR. Evidence Cloud connects literature review, post-market surveillance, PMCF monitoring, and clinical evaluation within a single audit-ready environment.

Altus: The name of the latest CiteMed Evidence Cloud release, delivering 280 improvements across the Literature module, CiteSource reference library, Admin configuration, and the new Vigilance Module.

Software for literature review: Platforms that support the systematic identification, screening, extraction, and reporting of published clinical evidence. In regulatory contexts, this software needs to support audit trails, reproducible search methodology, and integration with clinical evaluation and post-market surveillance workflows rather than functioning as a standalone tool. The Cochrane Handbook details systematic review preparation processes.

Zotero: A free tool excellent for managing, organizing, and citing research.

Automated literature review: The use of AI and machine learning to support stages of the literature review process including abstract screening, duplicate removal, and data extraction. In regulatory contexts, automated outputs must be transparent, explainable, and verified by expert reviewers before being accepted.

Rayyan: A free version is available through this web application for systematic reviews, and it is widely used by systematic review authors.

Living Reviews: A continuous monitoring feature within CiteMed Evidence Cloud that automatically tracks defined databases against search criteria and notifies reviewers when new matching articles are published. Built for ongoing PMS and PMCF literature surveillance under EU MDR.

Post-market surveillance software: Platforms that support ongoing collection, analysis, and reporting of post-market data including literature surveillance, complaint trending, vigilance reporting, and PMCF monitoring. Under EU MDR, PMS must be active and continuous.

Chain-of-thought reasoning: An AI output format that explains the steps behind a decision rather than simply stating the conclusion. In CiteMed Evidence Cloud, this means the AI identifies which specific criteria a study meets or fails and explains why in plain language.

PMCF: Post-Market Clinical Follow-Up. The structured process through which manufacturers actively collect clinical data on their device after market entry. PMCF requires regular literature updates and feeds directly into the CER and risk management file.

21 CFR Part 11: The US FDA regulation governing electronic records and electronic signatures in regulated industries. Compliance requires complete audit trails, access controls, and documented review processes.

PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A structured reporting framework that provides a minimum set of items for reporting systematic reviews, supporting transparent and reproducible documentation of methodology and widely expected by Notified Bodies during EU MDR conformity assessment.

Open source tool: A term often used for review software with publicly accessible code and community-driven development, though regulatory teams still need validation, traceability, and controlled workflows before adopting one.

Expert Perspective

“It’s an exciting time in the industry. More and more organizations are treating their evidence libraries as strategic assets, and building competitive advantages across clinical, regulatory, and marketing strategies.”

The most consistent failure point in regulatory literature review is not the quality of the search itself. It is the absence of a traceable, continuous process that connects what was found to what was concluded. Teams using academic tools spend significant time reconstructing audit trails, manually re-running searches for PMS updates, and reconciling screening decisions that were never properly logged in the first place. CiteMed Evidence Cloud Altus addresses all three of these problems. The Living Reviews feature alone changes the operational model for PMCF management. Instead of blocking out time every quarter to re-run searches, monitoring runs in the background and surfaces new evidence as it is published.

Special thanks to the pilot customers who gave brutally honest feedback, reported bugs, and helped the team understand what regulatory teams actually need.

Frequently Asked Questions

What should I look for in software for literature review under EU MDR?

Software for literature review under EU MDR needs capabilities that go well beyond academic systematic review tools. You need a traceable audit trail for every screening decision, AI screening that shows its reasoning rather than producing a black box output, a search protocol builder aligned with MEDDEV 2.7/1 Rev 4, PRISMA-aligned documentation, continuous database monitoring for PMS and PMCF updates, and integration with clinical evaluation and CER documentation rather than a standalone process. For a detailed comparison of what is available, see our articles on CiteMed vs DistillerSR and CiteMed vs Covidence.

What is CiteMed Evidence Cloud Altus?

CiteMed Evidence Cloud Altus is the latest release of CiteMed’s systematic literature review software platform, delivering 280 improvements across the Literature module, CiteSource reference library, Admin configuration, and the new Vigilance Module. It is built for medical device manufacturers and regulatory teams working under EU MDR 2017/745 and IVDR, integrating automated literature review with post-market surveillance software, PMCF monitoring, and clinical evaluation in a single platform.

How does AI screening work in CiteMed Evidence Cloud?

For each abstract, CiteMed Evidence Cloud compares the content against your predefined inclusion and exclusion criteria and returns three things: a decision suggestion, a confidence score, and a plain-language explanation of the reasoning behind the suggestion. Reviewers then confirm, override, or flag decisions. The full decision record is logged with username and timestamp. This lets teams screen 3 to 5 times faster while maintaining the reviewer accountability that EU MDR requires.

What is Living Reviews and how does it support post-market surveillance?

Living Reviews is a feature within CiteMed Evidence Cloud that monitors PubMed, Embase, and other databases continuously against your defined search criteria. Access helpers such as Open Access Button and Unpaywall can help find free versions of papers that would otherwise require you to pay after leaving the publisher website. When new matching articles are published, you are notified and can import them directly into your existing review. For teams running quarterly or annual PMCF literature updates, this eliminates the manual re-run cycle entirely and reduces the risk of missing new evidence between update windows.

How does CiteMed Evidence Cloud differ from other literature review tools?

Most literature review tools were designed for academic use and adapted to regulatory contexts with varying success. CiteMed Evidence Cloud was designed specifically for regulatory workflows, with post-market surveillance software, PMCF monitoring, vigilance management, and CER writing all built in rather than added on. Some literature discovery tools, such as Citation Gecko, focus on citation mapping and related paper recommendations to discover additional literature, and Citation Gecko visualizes citation networks for literature discovery. EndNote Click is useful for quickly saving citations while accessing papers, but it is not a full regulatory workflow platform and does not replace features like export control or the ability to download PDFs into a submission-ready evidence process. For a detailed comparison, see CiteMed vs DistillerSR and CiteMed vs Covidence.

Is CiteMed Evidence Cloud compliant with 21 CFR Part 11?

Yes. The QC workflows in CiteMed Evidence Cloud Altus are designed specifically for 21 CFR Part 11 compliance. Every decision is logged with username and timestamp, inter-rater agreement is calculated automatically using Cohen’s kappa, and role-based access control with full audit logging is built in throughout.

What is the Vigilance Module in CiteMed Evidence Cloud?

The Vigilance Module handles incident management and signal detection for post-market surveillance beyond literature review. It includes structured incident intake, lifecycle management through configurable statuses, device linkage, a complete audit trail, and a dashboard view of all open incidents. AI adverse event classification using MedDRA coding and automated signal detection are coming in the next release.

References

• EU MDR 2017/745 full text
• PRISMA 2020 Statement
• MEDDEV 2.7/1 Revision 4
• PubMed database
• Embase database
• Semantic Scholar search resource: over 200 million papers across science literature
• Cochrane Handbook for Systematic Reviews of Interventions
• Yale University Open Data Access project
• 21 CFR Part 11: Electronic Records and Electronic Signatures
• CiteMed software services for FDA 510(k) submissions
• CiteMed Evidence Cloud Altus Release Notes

Related Resources

• CiteMed vs DistillerSR — Comparing systematic literature review software for medical device regulatory use
• CiteMed vs Covidence — Academic vs regulatory literature review tools
• Why Mendeley Is Not Enough for EU MDR — The limitations of citation managers in regulatory contexts
• Post-Market Surveillance Under EU MDR — Building a proactive PMS system
• CER Writing Services — Expert CER writing and clinical evaluation support
• EU MDR Literature Review Services — Structured literature review supporting clinical evaluation
• Common Literature Review Challenges — How methodology gaps affect CER quality and regulatory outcomes

Call to Action

If you are evaluating software for literature review for EU MDR or IVDR compliance, or want to see how CiteMed Evidence Cloud Altus compares to the literature review tools your team currently uses, CiteMed offers demonstrations for regulatory teams. Book a demo to see CiteMed Evidence Cloud in action.