Task list for Lou Ann and Bill:
- invite email the SEND team
- Highest priority (for review at GeneTox):
- Clean up In Vitro MNT
- Review GT specification and also assumptions
- finalize links to TO, DI, DU
- Clean up In Vitro Neutral Red Uptake
- Apply that clean up to all else
- The following has changed.
Add SPTOBID for Sponsor Tobacco Product Identifier(s) to each study TS - and will anything else come out of TS domain for us?SPTOBID for Sponsor Tobacco Product IdentifierFrom the Product Description work:IN TX: SPTOBID (like SPDEVID) for Sponsor Tobacco Product IdentifierTO domain (like DI) for Tobacco Product Identifiers and Descriptors
Add GTTSTCND TX variable with values that tie to a smoking regimen from the TC domainsee an example done with test data and PTTSTCND in PT domain Tobacco Product Testing - like LB [Would Findings be better?]
- Make changes to link to the appropriate examples for TO, DI, DU, etc after ISMT review and Tuesday's Product Description meeting.
- All other (in vivo) Domains, assumptions and also Trial design examples will be copied over verbatim.
- update TIG Example and CT Completion based on updated examples (e.g. smoking regimen)
- Lou Ann - find the pptx picture of sample processing steps and variables?
- In our working docs section:
- RLevering comment at bottom: I uploaded four documents related to the micronucleus assay (MN). The OECD 497 guidelines provide details related to performing the actual assay, for example the three exposure schedules (short and long term), cell lines, positive controls, use of the cytokinesis blocker cytochalasin B, etc. The Health Canada T-503 also provides guidelines for the testing of tobacco smoke in the MN assay. THe other two documents (ICH and ISO 10993) provide additional information regarding the MN assay and other genotoxicity methods for use in testing of pharmaceuticals and medical devices, all relevant to the understanding of the MN assay.
- LAK notes:
- used to compare to assess how well the experiment is working
- If your + and _ controls produce the expected outcome, the test results of the unknown can be trusted
- positive control - has an effect
- negative control - has no effect
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