OM Pharma · DrugCard

The problem

OM Pharma faced growing pharmacovigilance demands that strained traditional manual processes, including time-consuming literature surveillance and inefficient identification of safety signals.

What was deployed

Vendor

DrugCard

Products

DrugCard

Technique

NLP

Build or buy

Bought off the shelf

Deployment

SaaS

Data used

scientific articles, PubMed integration, non-English publications

Scale

a single 5-product project managed by a 5-person team and centralised data processing for one country

What changed

Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.

Difficulties and limits

• Time-consuming literature surveillance, with safety reviewers spending approximately 25 minutes per article to identify and assess relevant safety information.
• Limited scalability made it increasingly difficult to keep pace with growing volumes of scientific literature across multiple products.
• Fragmented workflows required teams to switch between tools for literature review, relevance assessment, and translation.
• Inefficient identification of safety signals delayed insights and placed additional pressure on pharmacovigilance resources.
• Resource-intensive operations, where highly qualified PV professionals spent significant time on repetitive screening and administrative activities instead of expert safety evaluation.

Sources

• drug-card.io — vendor self-report, 2026-06-26