In collaboration with Novo Nordisk, CTML, and Copenhagen University, the mission of JICI (the Joint Initiative for Causal Inference) is to create an international powerhouse for causal inference aimed at answering pressing statistical questions using both Randomized Control and Observational Studies.
JICI collaborates on developing, implementing and disseminating methods for exploiting vast, new health datasets using state-of-the art advances in machine learning, causal inference, and statistical theory, and to build industry-wide consensus around best practices for answering pressing health questions in the modern methodological and data ecosystem. Development of elaborate statistical techniques that can replace randomization and allow for causal conclusions can support development programs by:
- Reducing the cost of required RCTs by integrating clinical trial data with observational data and thereby boosting the scientific value;
- Producing valid insights based on post-randomization events;
- Supporting the evidence generation beyond RCTs and thereby met new requirements from regulatory and re-imbursement authorities.