Clinical Characterisation Protocol (CCP)
Li Ka Shing Programme 2005 filling out patient clinical data | © CTMGH
The Clinical Characterisation Protocol (CCP) is designed for any severe or potentially severe acute infection of public health interest.
It is a standardised protocol that enables data and biological samples to be collected rapidly in a globally-harmonised manner.
The Clinical Characterisation Protocol (CCP) can be used for the rapid, coordinated clinical investigation of confirmed cases of COVID-19.
Below, a summary of changes:
- Flexibility in Tier 2 biological sampling schedules has been demonstrated with the inclusion of tables illustrating the different schedules.
- Suggested biological samples now include a nasal synthetic absorptive matrix (SAM) strip to allow for multiplexed cytokine analysis.
- Optional sub-studies have been included: environmental transmission; serial serology and sampling; large volume convalescent sampling (for serology, mAbs and cellular immunity) and serial BAL for patients requiring ECMO.
- The table detailing sample processing requirements for laboratory analysis has been updated.
The full changelog is available here.
ISARIC offers a web-based eCRF for the CCP and can host the data. For further information please contact email@example.com.
The resources are free to use. ISARIC supports researchers to retain control of the data and samples they collect.
More information on the CCP group can be found here.
Clinical Characterisation Protocol
File tier record
Important information to adapt the CCP
COVID19 information sheets for patients:
Adult Serial Serology
Adult Extra Convalescent
Parent or Guardian
Young (12 to 16 years old)
Child (under 12 years old)
ISARIC cartoon information for children
All the documents available on the link above can also be viewed at this Dropbox link.
If you are interested in using or developing these protocols for global use, please contact firstname.lastname@example.org to join the networking group for the ISARIC CCP Investigators Group (Chair – JK Baillie, University of Edinburgh).