PV specialists are the backbone of patient safety, yet they face significant challenges:
AI-powered Summarization: Get to know a unique pre-reading PV AI building concise summaries of relevant publications with extracts, highlighting key safety and efficacy insights.
Safety Shield provides in-depth insights into relevant articles through 3 progressive information levels:
SafetyShield can process both public literature and your private data to harmonize and aggregate all potential PV case sources, applying the same methodology throughout.
dedicated to manual reviews. This tedious process not only eats away at valuable research hours but also introduces the risk of human error.
Critical safety issues buried in a sea of data can go unnoticed, jeopardizing patient safety.
Inefficient workflows can create a domino effect, ultimately leading to safety regulatory non-compliance
Frees Up Valuable Time for Specialists: A 70% Reduction in Tedious Tasks. By automating routine pharmacovigilance activities.
Safety Shield allows PV specialists to take immediate action for each safety case.
While efficiency is often associated with productivity, in PV, it plays a crucial role in safeguarding patient well-being.
ArcaScience offers on-site technology setup, ensuring that all sensitive data remains securely in-house. This allows seamless integration with existing systems while maintaining data privacy and security.
ArcaScience integrates all major public scientific databases, including PubMed, Medline, and ClinicalTrials.gov, and can seamlessly integrate any client's databases via on-site instances or private cloud solutions. Additionally, through strategic partnerships, ArcaScience can access and integrate databases behind paywalls
Our AI models leverage state-of-the-art transformer architectures and the most advanced semantic models recognized as the best in the world in their fields (StartusInsight, 2023) ensuring exceptional accuracy and reliability. With robust training on vast, diverse datasets, they deliver precise, actionable insights, maintaining high standards of performance and integrity.
We employ rigorous quality control measures, such as k-fold cross-validation with gold standard datasets, real-time performance monitoring, and iterative model tuning. Our AI models consistently achieve over 95% precision and 98% recall, validated through ROC-AUC scores exceeding 0.99, ensuring they meet the highest industry benchmarks for accuracy and reliability.