Sept 22, 2016 Meeting Notes

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Meeting minutes of Nonclinical_Script_Assessment_Project

Sept 22, 2016

Present First Name Last Name Affiliation
Yes Kevin Snyder FDA
Elaine Thompson FDA
Kevin Cahill EPL
Bill Varady Boehringer-Ingelheim
Bob Dorsam FDA
Bob Friedman Xybion
Chris Eley Pfizer
Yes Stephen MacMannis Pfizer
Fred Mura PDS
Yes Anthony Fata PDS
Yes Hanming Tu Accenture
Yes Bill Houser Bristol-Myers Squibb
Carol Gleason Bristol-Myers Squibb
Yes Atul Mishra Pfizer

Action Items from previous process meeting:

  • Bill Houser is still working through his internal company the process to share a couple SAS scripts.
  • Fred Mura will check academic contacts to see if there is interest in R or SAS programming.
  • Elaine will check for Toxicology areas and contacts at George Washington University -- we'll take this off the list.
  • We should reach out to Pinnacle 21 to join us - Bill sent email Aug 17, 2016 and Sept 22 asking if they would be interested in in joining us.
    • Their experience would help us
    • They could benefit from our contributions

Notes from previous coding meeting:

  • We should each try the script on our own data and share the results
    • Stephen tried and encountered an error reading the xpt file. There are multiple analytes in his data, but the data frame only had one analyte.
    • Kevin has successfully used it on a study with multiple analytes.
    • Stephen will try some more.

Meeting Notes:

  • Bill walked us through the action items from previous meetings.
  • Kevin showed the function ideas that he has traced in the file TK_functions
  • Kevin then showed us an example program that implements features of the R module called shiny
  • Our meeting on Sept 29 is canceled; so, Oct 13 will be our next meeting.


  • Bill Houser will create list of priniples that we agree to as general practice.
    • Kevin Snyder found that to analyze the PDS data we need to look at PCTPTNUM to get the hour after dose, but this doesn't work with the Instem dataset. For the Instem script we need PCELTM and PCRFTDTC. He suggested it would probably be worth enabling the script to work with either dataset.
    • We discussed if we should preserve the SEND values or modify them as we prepare the information for analysis. We concluded that we should preserve the SEND values and copy or transform them to variables we use for analysis.
    • As we proceed, we agreed to try to create generalized functions in a library. (concept similar to Unix commands in that they are simple and can be combined in powerful ways).
    • New Function Idea: create a function that will pull rows from a .xpt file that match a subjects defined by a characteristic in another .xpt file (e.g., get the body weight data from only male animals)
  • Bill will follow-up with steering committee on their decisions related to vendor concerns.
  • All should try to the TK analysis script with our private data to see what we can learn.