Specialty Pharmaceutical Company · Life Sciences · Philadelphia, PA · 14 weeks
Pharmacovigilance data pipeline automated
A specialty pharmaceutical company handled adverse event reports manually, causing delays that pushed submissions beyond the FDA’s 15-day deadline. We built an automated data pipeline that cut processing time from 18 days to 4 hours and ensured every serious adverse event was submitted on time.
Challenge
The pharmacovigilance team collected adverse event reports from six different channels: call center, field sales, medical affairs, literature monitoring, spontaneous reports, and clinical trials. Each channel used its own data format, forcing the team to manually consolidate and process the information. Despite having eight specialists dedicated to this task, delays persisted, leading to late FDA submissions and warning letters.
Approach
We created an automated pipeline to handle adverse event reports from six sources. It used an AI-assisted engine to apply MedDRA codes, identified duplicate entries, and prepared MedWatch submission packages automatically. We also set up an escalation process for serious events needing 15-day expedited reporting.
Outcome
We cut adverse event processing from 18 days to 4 hours for standard reports and 6 hours for serious cases. This overhaul pushed on-time submission compliance to full within three months. Automating data handling freed up the equivalent of five of the eight specialists’ time, shifting their focus from routine processing to signal detection.
How We Cut MedDRA Coding Time in Half and Slashed Errors with AI
Manual MedDRA coding was killing our speed on adverse event reports. So, we tried out an AI tool that scans the narratives and suggests the right MedDRA preferred terms. Boom, coding time dropped from 45 minutes to just 8 per report. Our pharmacovigilance team didn’t have to start from scratch anymore; they just reviewed the AI’s suggestions. It made a massive difference.
We set up a quick, no-fuss system to catch serious adverse events right away.
The FDA only gives you 15 days to report serious adverse events, crazy tight deadline, right? So, we built this automated triage system to take the heat off. It instantly flags the most urgent cases and fast-tracks them. Then, to keep everyone on their toes, we set reminders for days 7, 10, and 13. It’s simple, but frankly, it changed the game.
Results
- 18 days to 4 hours Adverse event processing time
- Full On-time FDA submission compliance
- 5 of 8 Pharmacovigilance specialists' time freed
- 6 sources Adverse event data sources unified
We kept missing FDA deadlines and getting warning letters. Our team of eight was overloaded but still couldn’t keep up. Once Thinklytics automated the process, we’ve hit every submission on time. Now, the team focuses on signal detection instead of data entry.
In the client's terms
The question
Which of this work should a person still be doing?
The situation
Adverse event reports arrived through six channels: call centre, field sales, medical affairs, literature monitoring, spontaneous reports and clinical trials, each in its own format. Eight specialists consolidated them by hand, and the delays had already produced late FDA submissions and warning letters.
What we found
Eight specialists were spending most of their time reformatting reports rather than looking at them. The regulatory exposure and the waste of expert attention were the same problem seen from two directions.
What it produced
Processing fell from 18 days to 4 hours for standard reports and 6 hours for serious ones. On-time FDA submission compliance reached full within three months. Five of the eight specialists moved off routine processing and onto signal detection.
The roadmap
An automated pipeline ingests all six sources, applies MedDRA coding with AI assistance, identifies duplicates and assembles MedWatch submission packages. A separate escalation path handles serious events subject to 15-day expedited reporting, because those cannot sit in a general queue.
The work behind this result
- Our systems need people in between them, the problem this engagement resolved.
- AI Workflow Automation Consulting
- AI Agent Consulting for Business Workflows
- AI Automation Consulting
- CRM Data Access and Rollback Checklist, for whoever has to approve the spend.
- The 30 day Corporate Drag and Risk Diagnostic, findings yours either way.
Related case studies
- Built a reliable ESG data system that cut sustainability report prep time from 18 weeks to 3 weeks.
- We built a clinical trial data governance system that cut FDA submission prep time from 14 weeks to 3 weeks.
- Implemented a data governance framework in 6 regional offices that cut FOIA response time from 34 to 8 days and stopped $1.2M in yearly compliance penalties.
- Cut NAIC statutory reporting from 6 weeks to 4 days by automating processes, saving $1.1M in yearly compliance labor costs.