DrugCard

DrugCard practices have evolved significantly due to increased regulatory pressures, audit frequencies, market complexities, and the advantageous use of AI technology. These changes have induced higher non-compliance risks and employee retention costs, while necessitating swift adaptation to volatile market conditions. DrugCard has positioned itself as the necessary data intelligence solution that enables continuous, transparent, accurate, and scalable drug safety operations without substantial capital expenditures. By automating local literature screening, DrugCard drastically reduces the time and effort required, boosts compliance and ensures a cost-effective pharmacovigilance process.

How DrugCard can help you:

• Provides effective and efficient screening of local medical literature
• Uses AI technology to enhance search results and compliance
• Offers support for 100+ languages and coverage of 400+ local journals
• Delivers time savings of 50-70% for pharmacovigilance tasks
• Sends instant notifications and weekly summary reports for easy audit compliance
• Requires only 2-3 weeks on average to add journals from a new country
• Gives access to a user-friendly, reliable, and regulatory compliant platform

Why choose DrugCard: Key features

• Superior medical journal coverage compared to human-only approaches
• AI and proprietary OCR technology ensures up to 99% accuracy for text recognition
• Automated system that is responsive and removes the need for manual screening
• Significantly increases hit discovery rates with a dramatic reduction in screening time
• Enables reallocation of pharmacovigilance experts to higher-value tasks
• Cost-effective with minimal capital expenditure

Who should choose DrugCard:

• Contract Research Organizations (CROs) seeking improved pharmacovigilance project management
• Pharmacovigilance service providers aiming for process automation and time savings
• Pharmaceutical companies in need of local literature screening for global markets
• Pharmacovigilance teams desiring to focus on signal detection and risk assessment rather than manual literature screening