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Before AI, the industry relied on OCR to digitise paper. But, traditional OCR often falls short because it relies on rigid templates for raw data extraction and lacks the necessary context to interpret complex documents.
AI is a superior way to digitise paper batch records because it understands both context and structure. Furthermore, pharma-specific platforms like Mareana provide an added advantage.
They are specifically tuned for pharmaceutical vocabulary and can even interpret the handwritten margin notes found within these records. To ensure accuracy and maintain a human-in-the-loop, as suggested by pharma regulatory bodies, the system uses a confidence scoring mechanism.
Every extracted field is assigned a confidence score. Low-confidence items are automatically routed to a built-in GxP review UI, where human operators verify and approve the data with electronic signatures.
Once extracted, the data is ready for analysis and manufacturing insights that help optimise the process. This workflow also helps organisations adhere to ALCOA+ principles because every digitised value maintains a direct link back to its original source snippet from the paper record, providing a one-to-one lineage for internal audits and regulatory inspections.
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Frequently Asked Questions
Mareana has helped numerous firms in the Pharmaceutical, Chemical, Medical Device, and Industrial Manufacturing industries.
AI-powered digitisation is the process of converting paper batch records into structured digital data using artificial intelligence. Unlike traditional OCR, AI understands document context, pharmaceutical terminology, layouts, and handwritten notes, delivering more accurate and reliable data for manufacturing and compliance.
AI is superior to traditional OCR because it understands both the content and structure of pharmaceutical documents. While OCR simply extracts text based on templates, AI can interpret complex layouts, recognise handwritten annotations, and improve extraction accuracy, reducing manual corrections and accelerating digital transformation.
AI uses a confidence scoring system to assess every extracted field. High-confidence data is processed automatically, while low-confidence items are flagged for human review. This human-in-the-loop approach helps maintain data accuracy and supports regulatory compliance.
Yes. Advanced pharmaceutical AI platforms are trained to recognise and interpret handwritten margin notes, operator comments, and annotations that traditional OCR systems often struggle to process. This ensures critical manufacturing information is preserved during digitisation.
AI supports ALCOA Plus by maintaining complete data traceability. Every extracted value is linked back to its exact location in the original paper batch record, creating a one-to-one data lineage that supports data integrity, internal audits, and regulatory inspections.
AI-powered digitisation helps pharmaceutical manufacturers improve data accuracy, reduce manual data entry, accelerate batch record review, strengthen regulatory compliance, enable manufacturing analytics, support faster audits, and optimise production processes through structured digital data.
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