Research in the Division of Clinical Trials and Biostatistics advances basic science research, clinical trial design and execution, translational science, and population health through several specialized focus areas.
Clinical trial design and conduct
Faculty and staff members in the Division of Clinical Trials and Biostatistics are leaders in the clinical trials community. They develop new approaches to clinical trial design and analysis to address the promise of precision medicine, rare tumor trials, special populations and alternative endpoints. Specifically, members of the division have experience with:
- Adaptive phase 1I designs
- Biomarker-stratified or biomarker enrichment designs
- Cluster randomized trial designs
- Collection and analysis of adverse event data in oncology trials
- Sequential multiple assignment randomized trial (SMART) designs
- Trial designs with alternative survival endpoints or surrogate endpoints
- Trials with patient-reported outcomes or quality-of-life endpoints
Knowledge discovery and data mining
The primary goal of knowledge discovery and data mining is to develop new methodologies for extracting useful knowledge from data. In health care and biomedicine, the rapid growth of data due to the adoption of electronic health records, wearable devices, online health communities and many curated biomedical databases has created an enormous need for knowledge discovery and data mining methodologies.
Mayo Clinic's knowledge discovery and data mining team aims to develop and implement a suite of data-driven analytic techniques for actionable knowledge from complex, heterogeneous biomedical data. The team explores emerging health data types and researches foundational data mining methods on data representation, data integration and novel analytic visualization to answer significant biomedical questions from the real world. Knowledge discovery and data mining is an interdisciplinary area that relies on Division of Clinical Trials and Biostatistics members' extensive expertise in:
- Data visualization
- High-performance computing
- Machine learning
Advanced survival analysis methodology
Analysis of survival and other time-to-event data has played a key role in Mayo Clinic research since the clinic's earliest days. Researchers within the division have played a pivotal role in the development of survival analysis methodology and software developed in response to analysis needs. More recently, much of the research has focused on multistate models. Read more about survival analysis research in the Division of Clinical Trials and Biostatistics at Mayo Clinic.