As IDMP implementation advances in Europe, data is becoming a key asset for the life sciences industry. Currently, pharma companies are focusing on the heavy burden of initial data collection, but ultimately it is data maintenance that will become the prevalent challenge. This can only be tackled by paying continuous attention to the quality and integrity of data. Renato Rjavec at Amplexor explains advanced text mining technologies, applied in the context of end-to-end regulatory information management, can help considerably both with accurate data ingestion and ongoing data maintenance.

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Unlocking the Business Benefits of Text Mining in Regulatory Operations

As IDMP implementation advances in Europe, data is becoming a key asset for the life sciences industry. Currently, pharma companies are focusing on the heavy burden of initial data collection, but ultimately it is data maintenance that will become the prevalent challenge. This can only be tackled by paying continuous attention to the quality and integrity of data. Advanced text mining technologies, applied in the context of end-to-end regulatory information management, can help considerably both with accurate data ingestion and ongoing data maintenance. Amplexor’s Renato Rjavec explains.

The protracted business of collating and cleaning up data, in preparation for the new target operating model for EMA regulatory submissions, in which original product data must be submitted alongside eCTD dossiers, has triggered a whole raft of activity and resource use for European and global life sciences organisations.

The road to full IDMP compliance has not been an easy one; nor does it end with initial registrations. On the one hand, many marketing authorisation holders (MAHs) are still trying to locate source data, vet its quality, and plug any gaps. The information they need may straddle regulatory information management (RIM) systems, Excel spreadsheets and any number of static documents (labelling, CMC documents, and so on). This may be strewn across functions as diverse as Regulatory, Supply Chain, Pharmacovigilance and Commercials – each department frequently employing its own preferred formatting and terminology. Extracting and cleaning up all of these fragments of data to form something meaningful and usable is a massive undertaking.

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