Nakel.io provides a digital platform that structures and manages pharmaceutical technology transfers, which often fail due to incomplete data and undocumented tacit knowledge. The platform ingests existing documentation to build digital twins of both sending and receiving sites, automatically extracting and tagging product attributes and process parameters. It then generates critical regulatory documents, such as DoE study plans and tech transfer reports, from the validated data.
Funding
Funding not disclosed
Founders
Product
Problem
Technology transfers in the pharmaceutical industry are frequent but highly damaging when they fail, with risks surfacing late and cascading into repeated out-of-specification batches, delayed regulatory filings, and idle manufacturing slots. The root cause is a data problem: each transfer is a bespoke, manual project involving hundreds of documents and tacit knowledge that never leaves the sending unit, leaving the receiving site with an incomplete picture.
Solution
Nakel.io provides a platform that digitizes and structures the entire tech transfer process. It connects to existing documentation to build digital twins of both the sending and receiving sites, automatically extracting and structuring every product attribute and process parameter with source tracing and confidence tagging. The platform identifies critical data gaps and missing information early, preventing issues from surfacing during execution. It then generates essential documents—including DoE study plans, tech transfer reports, validation documentation, and regulatory dossier baselines—directly from the validated data, ensuring consistency and completeness.
Target Audience
Primary customers are pharmaceutical companies and CDMOs (contract development and manufacturing organizations) that regularly execute technology transfers and need to reduce risk, accelerate timelines, and ensure regulatory compliance.
Features
- Automated ingestion and structuring of documents from MES, QMS, LIMS, and other systems, achieving 96% auto-extraction with 4% flagged for review
- Digital twin creation for both sending and receiving sites, capturing equipment specs, process parameters, and analytical methods
- Confidence-tagged data with source tracing, flagging 13 critical data points on average that are missing or incomplete
- Gap analysis across six classic failure modes: manpower, machines, materials, methods, environment, and measurements
- Automated generation of DoE study plans, tech transfer reports, validation documentation, and regulatory dossier baselines