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Automated PubMed search strategy from the research question with one-click translation to Embase and Cochrane databases
1. End-to-End Workflow
AI-enabled evidence synthesis with reviewer control
SYMPRO AI supports systematic reviews, targeted reviews, data extraction, risk of bias assessment, and report-writing workflows. Automation accelerates repetitive work, but researchers remain involved in review, validation, and final interpretation.
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De-duplication of citations with manual and auto mode
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AI-assisted and fully automated AI title/abstract screening
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Full-text screening with mini data extraction (study overview)
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PDF highlight
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Conflict analysis/resolution while screening
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Auto-generates PRISMA flow diagrams
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Automatically generates DET templates by analyzing uploaded study files
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Risk of bias assessments across a wide spectrum of checklists with automatic AI-based recommendation of the ROB checklist
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Linkage analysis identifies and categorizes primary studies, linked secondary studies, and relevant supplementary files
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Report writing with automated support for consensus themes
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AI-driven abbreviation list for text and tables
AI technology
SYMPRO AI uses large language models through several LLM API providers and applies retrieval-augmented generation for PDF-grounded screening and extraction tasks. Customer data is not used to train the platform models, and human verification remains required.
2. AI Integration Levels
AccuScreener for literature screening
Teams can choose how much AI participates in screening, from reviewer-led workflows to fully automated screening with targeted human review. Each mode keeps the decision path visible so reviewers understand how work was completed.
A. Level of AI integration
Screening can be performed using artificial intelligence (AI) with configurable levels of automation:
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Manual
Both title/abstracts based first-pass and full-text screening performed by human.
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AI Assistant
AI provides suggestions during title-abstract and full-text screening by applying predefined criteria such as PICOS & hierarchy. In this mode, AI decisions are available for human review.
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AI Screener - Double Blind with Analysts
AI screens studies in parallel with human analysts in a double-blind workflow, enabling side-by-side comparison without exposing either decision stream upfront.
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AI Screener - AI as Sole Screener
AI is the only screener. Human reviewers will only review the screening decisions without conducting initial screening.
B. Blinding modes
Manual and AI-assisted screenings can be configured in either review mode, depending on the protocol and the level of reviewer independence required.
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Single-blind
One decision stream is hidden during screening to reduce reviewer influence while maintaining structured adjudication.
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Double-blind
Independent screening paths stay hidden until comparison, supporting unbiased discrepancy detection and manual resolution.
C. Discrepancy review
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In double-blind workflows, disagreements are surfaced automatically so the reviewer can move straight to manual resolution.
One-click discrepancy identification for human review
Other modules
All other modules (Accusearch for searches, Accusynthesis for data extractions, Accuscripter for study linkage and report generation) are powered by AI with human-in-loop review.
Human oversight and controls
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Admin/Reviewer oversight
Project admin or human reviewer can sample, review, and override any decision - whether made by analysts or AI.
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Usage controls
Developers can set AI usage limits at the organization level, permitting AI operations only within approved governance boundaries.
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Audit & traceability
All decisions or changes made are recorded with the user initials, indicating whether it was generated by AI, analysts or reviewer.
Core working principles
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Evidence traceability
Each AI-generated evidence can be traced to specific article, with supporting text visibly highlighted in the source PDF.
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Reasons for decisions
For screening decisions and extracted fields, the AI's reasoning is displayed so reviewers can verify and validate each outcome, instead of being forced to trust the system blindly.
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Human-in-loop review
All AI-driven decisions can be exported to support external human review. Human experts remain fully accountable for protocols, final judgments, and interpretation of results.
3. Human-Controlled Decisions
Users remain accountable for every decision
SymproAI is designed with the core principle that users remain fully responsible for every screening decision. Here's how that works in practice:
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Configured by project admins
Project admins configure protocols, AI modes, and decision rules before reviewers begin work.
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Decision ownership is visible
Reviewers can see who made each decision, including decisions generated by AI.
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AI supports, users decide
AI outputs are presented as suggestions, not as final decisions.
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Governance through credit limits
Credit limits help governance teams control how much AI is used across the organisation.
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Reviewers can override anytime
A reviewer can override any AI suggestion at any time.
4. Publications and Testimonials
Evidence of applied use
Multiple projects have used SymproAI and made publications as conference abstracts, posters and manuscripts. The selected list is available on our Publications page.
Published evaluations
Review articles
- Real-world evidence corroborates the clinical trial results for management of HER2-positive metastatic breast cancer with T-DM1: a systematic review. J Breast Cancer Research (ACCEPTED).
- Impact of sleep disturbances on health-related quality of life in postmenopausal women: a systematic review. 2026. Menopause 33(1): p 118-128, DOI: 10.1097/GME.0000000000002633.
Conference abstracts
- MSR82 Efficacy and Safety of Modern Biologics Compared to Conventional Therapies in AQP-4 Positive Neuromyelitis Optica Spectrum Disorder: A Fully AI-Automated Targeted Literature Review. Value in Health, 28 (22 Suppl) December 2025.
- MSR88 Validation of a programmed probability score using the screening tool, SYMPRO to assist selection of studies in systematic literature reviews. Value in Health, 26 (12 Suppl) December 2023.
What this indicates
AI-assisted workflows can achieve high agreement and substantial time savings in evidence synthesis, but performance may vary by topic.
We recommend:
- Starting with a pilot project before large-scale adoption.
- Maintaining human decision at every step.
Additional evaluations and publications are currently underway and will be added to our Publications page.
"SYMPRO AI has transformed our evidence synthesis workflow. It cut weeks of manual screening and triage down to a focused, defensible process without sacrificing quality. The audit trail and consistency checks give our team confidence at every decision point."
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Dr. Anjali Rao
Health Outcomes Research Lead
"SymproAI made our screening and extraction process much easier to manage. The interface is clear, collaboration feels smooth, and the progress tracking helped us keep timelines under control. It is a practical platform for teams handling high-volume review work."
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Riya Kapoor
Evidence Review Manager
"A must-have for modern evidence synthesis projects, streamlining the most labor-intensive stages while maintaining rigorous standards. It keeps teams aligned, reduces rework, and makes handoffs cleaner across reviewers. The result is faster delivery with clearer, more reproducible decisions."
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Prof. Laura Chen
Clinical Research Director
5. Data Privacy, Protection and Quality Management
Security-conscious handling of project data
SymproAI is built as a secure web platform and adheres to high security, privacy, and quality standards.
GDPR Compliant
Ensures strong data privacy and protection practices.
ISO 9001 Certified
Follows internationally recognised quality management standards.
GDPR Compliant
Data privacy and protection practices are structured around GDPR-aligned controls.
ISO 9001 Certified
Quality-management processes follow recognized international standards.
No Training Use
Customer project data is not used to train or improve SYMPRO AI models.
Access Control
Role-based permissions restrict visibility to authorized users and configured admins.
Operational commitments
- User rights: You maintain full ownership of all content and outputs you upload or generate.
- No training use: Your data is never used to train or improve SymproAI models.
- LLM provider controls: We use provider data controls and contractual terms intended to prevent submitted content being used for provider training.
- Role-based access: Access controls restrict access to authorised users, typically the project team; organisation administrators have configurable permissions.
- Regional deployment: Enterprise customers requiring EU or US data residency can request separate deployment regions.
- DPAs available: Data Processing Agreements provided to institutional customers.
Full details are in our Privacy Policy, Terms of Service and Trust Center. Security documentation and audit reports are available under Non-Disclosure Agreement for regulators and data protection teams.
5. Limitations
Responsible deployment boundaries
SymproAI does not replace human expertise. Researchers should:
Limitations
- Evaluate performance in pilot runs before full deployment.
- Set clear protocols for how AI will be used at each stage.
- Maintain human review for high-stakes decisions such as eligibility criteria, quality assessment, and final conclusions.
6. Alignment with AI Principles
Responsible AI in evidence synthesis
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Core Principles
Human-in-the-loop controls that keep admins/reviewers accountable.
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Application
Accelerates Evidence Synthesis (ES) by identifying studies, extracting data, assessing risk of bias, and summarizing findings.
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Trustworthy AI
The SymproAI modules are truly tested and well supported by rigorous validation of tools to ensure their enhanced performance and efficiency.
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Rapid Evidence
AI allows for faster, more frequent updates to systematic reviews to meet decision-making demands of living systematic reviews.
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Transparent AI assistance
Transparent AI assistance with visible rationale and decision flags.
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Configurable workflows
Configurable workflows to suit different review standards.
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Security-focused data handling
Security-focused data handling ensures sensitive project data is protected.
7. Resources
Supporting material for teams evaluating SYMPRO AI
Teams using SymproAI can typically access:
8. Contact
Get in touch
Contact
For further information or questions, please reach out to contact@accuscript.org
Full details are also available in our Privacy Policy, Terms of Service and Trust Center.