Submitting a drug approval package to the FDA, whether for an NDA, BLA or ANDA, is a costly process.
The final amalgamation of different reports and documents into the overview document set can involve a huge amount of manual checking and cross-checking, from the subsidiary documents to the master.
It is crucial to get the review process right.
Any errors, and the FDA can send back the whole package, delaying the application. But the manual checking involved in the review process is tedious, slow, and error-prone.
A delayed application can also be costly.
How much are we talking about?
While not every drug is a blockbuster, these numbers are indicative of what you could be losing: the top 20 drugs in the United States accounted for $319.9 billion in sales in 2011; so a newly launched blockbuster could make around $2Bn in the first year launched – that’s $6M per day.
If errors in the quality review hold up an NDA for even just a week this could generate significant costs.
So – how can text analytics improve this quality assurance process?
Linguamatics has worked with some of our top 20 pharma customers to develop an automated process to improve quality control of regulatory document submission.
The process cross-checks MedDRA coding, references to tables, decimal place errors, and discrepancies between the summary document and source documents. This requires the use of advanced processing to extract information from tables in PDF documents as well as natural language processing to analyze the free text.