Are you realizing the full value in your organization’s sensitive data?
Extracting the value from unstructured data and addressing privacy concerns are common challenges organizations face when trying to glean insights from data. Advancements in artificial intelligence and machine learning (AIML) have led to natural language processing (NLP) and anonymization capabilities that overcome these challenges and empower organizations to safely innovate with data.
By efficiently extracting the information in unstructured data in a privacy-preserving way, organizations can uncover valuable insights and support better decision making across the drug development life-cycle.
Join IQVIA’s Linguamatics and Privacy Analytics teams as we explore ways in which pharma sponsors have used NLP and statistical anonymization to help:
- Spur drug development, evaluate new hypotheses from historical trials, and improve clinical trial design
- Access social media and patient forum data for secondary research, patient stratification and innovation
- Source and link real-world patient data to support drug commercialization and market access
- Discover personal information held in documents and unstructured data sources in support of compliance, such as GDPR