IMPORTANT MESSAGE ABOUT COVID-19:
Stanford’s Quantitative Sciences Unit (QSU) wants to reassure the Stanford research community that the QSU is in the fortunate position of being able to safely conduct all our research, in accordance with the new Stanford policies relating to COVID-19. The QSU is prepared to address all the evolving needs for our studies. Please continue to rely on and utilize the QSU for your research and data science priorities.
For COVID-related research, please complete our Project Initiation Form found here: https://redcap.stanford.edu/webauth/surveys/?s=XJ8FW9LALN
COVID DSMB Registry
As part of a larger effort to increase efficiencies and streamline infrastructure for clinical trials, the Stanford Quantitative Sciences Unit (QSU) has established a registry of experts who are interested in serving on (as a member or chair) and/or supporting (as an independent statistician) one or more data and safety monitoring boards (DSMBs) for trials studying interventions related to COVID-19. This registry will be available to researchers who are convening a DSMB. It is intended to be a tool to expedite the process and to fulfill the unique DSMB needs for COVID-related trials. The registry may potentially serve future trial needs as well.
We would like to encourage you to join this registry. Please note that participation in the COVID DSMB Registry in no way commits you to serve on a specific DSMB, although it will inform coordinators of your potential availability and experience.
If you are interested please enter your name and minimal information regarding your expertise click here.
Thank you in advance for considering participating in this important public health initiative.
Access to this tool is coming soon and will also be found on the Society of Clinical Trials COVID Research Resources Hub (https://www.sctweb.org/covid.cfm)!
The mission of the QSU is to facilitate cutting-edge scientific studies initiated by Stanford investigators by providing expertise in biostatistics and informatics, to mentor and educate clinical investigators in research methods, and to mentor data scientists so that they can reach their full potential. The QSU achieves its mission through an interdisciplinary collaborative approach where QSU members become fully integrated into individual research teams.
More About the QSU:
The QSU was created in response to an increasing demand for statistical support and data coordination. QSU members are statistical scientists with expertise in missing data, prediction modeling, statistical computing, database creation, and software development. The QSU currently collaborates on over 100 large-scale scientific projects. We believe that to further science, it is important to facilitate the flow of data to investigators as efficiently as possible. We are also committed to providing sound analyses in a timely fashion. Finally, we believe that interdisciplinary research is best achived by full integration of all investigators. Our members become an integral part of each research team in which we are involved.
Our specific goals are to:
- Design studies that optimize the ease of interpreting results
- Provide high quality data analysis using modern statistical techniques
- Develop new or adapt old methods for optimal analysis as the need arises
- Securely house and track data in a HIPAA-compliant and IRB-compliant manner
- Create user-friendly publicly available software for recommended methods
- Interpret results
- Disseminate findings
- Mentor clinical investigators in research methods
Stanford has a rich history of doing high quality science. We are excited to be part of that process.
Stanford Data Science Resources:
The QSU is part of a larger collection of data science resources within the Stanford School of Medicine. To learn about all these data science resources and to initiate a consultation, please visit the Stanford Data Science Resources web portal.
We strongly believe diversity and inclusiveness is critical for doing good science. The QSU therefore strives to create an inclusive and diverse community where all are welcome and embraced.
Manisha Desai, PhD, Professor of Medicine and of Biomedical Data Science, assembled a community of researchers from the Schools of Medicine and Engineering to find the most effective methodologies for measuring children’s physical activity and sleep. Read more.
Manisha Desai, PhD, Professor of Medicine and Biomedical Data Science at Stanford University, shares some insights about the challenges and progress of current COVID-19 clinical trials. Read more.
Purington N, Andorf S, Bunning B, Chinthrajah S, Nadeau K, Desai M.
Hedlin H, Garcia A, Weng Y, He Z, Sundaram V, Bunning B, Balasubramanian V, Cunanan K, Kapphahn K, Gummidipundi S, Purington N, Boulos M, Desai M.
Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, Balasubramanian Russo AM, Rajmane A, Cheung L, Hung G, Lee J, Kowey P, Talati N, Nag D, Gummidipundi SE, Beatty A, Hills MT, Desai S, Granger CB, Desai M, and Turakhia MP, for the Apple Heart Study Investigators