Data and Technology

Innovative. Transformative. Powerful. 

Designing AI models to identify unseen opportunities and increase your pipeline efficiency  

We can help you design AI models, process and applications to

• Predict and identify opportunities for future product development
• Predict pharmacokinetics (PK), drug response (PD) and drug-drug interactions (DDIs) prior to human trials
• Reduce overhead by providing detailed forecasting
• Provide quicker analysis for clinical trial recruitment and study design

FEATURED WEBINAR

Measuring success of a quality risk management approach

As regulatory guidance and data collection in clinical trials has evolved, sponsors face pressure to balance quality, productivity and cost for risk management and monitoring. The industry has adopted risk-based quality management (RBQM), yet the methodology is inconsistent. There is no standard way to measure the impact of the different approaches to RBQM on the effectiveness of clinical trial management. Learn more about our approach to establishing and tracking metrics – including those that could apply across the industry – to measure the success of an RBQM approach.