Presented at Foundry Health's eSource meeting in Chicago, 04-Oct-2017

2. Accelerating the production of safety
summary and clinical safety reports -
a model to aspire to
© 2017 Steffan Stringer, Director of Customer Services, Foundry Health

3. Warning!
— My experience is not the most recent
— I am not
— a physican
— an expert in trial design
— a Data Manager
— a Statistical Programmer
— a Medical Writer

4. Challenge
— Accelerate the speed of delivery for
safety summaries and clinical study
reports
— Without comprising quality (safety)
— Whilst holding the cost
— Leverage eSource?
— Automate the processes to minimise
human intervention!

5. Where is the opportunity?
Safety Summaries
— Single Ascending Dose (SAD) studies
— several groups
— Multiple Ascending Dose (MAD) studies
— fewer groups
Clinical Study Reports (CSR)
But also
— Bioequivalence/Bioavailabiility (BABE)-cookie cutter studies
— Anystudies that want quick delivery of the results-all studies!

6. What is the opportunity?
Safety Summaries
— Used to make a decision whether it is safe to dose-escalate in a SAD study
— and maybe in MAD studies too)
— 5-20 page report
— needed in days
CSR
— 100's to 1000's of pages
— ++ weeks/months

7. Novel anti-influenza drug, London
— Part 1-SAD
— Single ascending doses (at least 5 planned dose levels)
— 8 subjects per dose (6 active + 2 placebo),sentinel dosing
— Part 2-MAD
— Multiple ascending doses
— At least two dose levels; 7–14 days’dosing once a day or twice a day; regimen based on results of Part 1)
— Part 3-food effect
— Single dose with food (8 volunteers from Part 1)
— Part 4-early efficacy
— Viral challenge study in a partner unit
— Part 5-ethnic bridging
— Added by amendment
— Single ascending doses at three dose levels-healthy Japanese men

8. Part 1 -SAD
— For each group/cohort
— Sentinel dosing (1 active + 1 placbo)
— 24h delay (5 active + 1 placebo)
— PK samples shipped for analysis
— Two weeks until they dose escalated
— Paper CRF!

9. Safety Summaries -what does it look like?
Typically
— Plots of safety data for all subjects in a group
— labs
— vitals
— other study-specific safety data
— List of AEs
— PK results
— Narrative to describe results
— Recommendation on whether to dose escalate

10. Safety Summaries -how is it done right now?
— Done by the Doctors writing narrative in Word and inserting Excel
tables
or
— Done by Data Management extracting the results from an eSource
system and processing the data with SAS to create tables and listings
— Publish as PDF

11. Process for CSRs
— Report shells in Word with place-holders for in-text tables and the list all the appendices (tables
figures and listings)-get them approved by the client
— Data Management writes their programs to clean and transform the raw data into the specification
required by the customer e.g.CDISC Study Data Tabulation Model-SDTM1
)
— DM may run through dummy data
— Statistical programmers write programs to create e.g.CDISC Analysis Data Model datasets-ADaM2
)
— Medical writers draft the narrative text of the results
— Reviewed by PI
— Compile the document-blend Word and e.g.SAS output PDF
2
https://www.cdisc.org/standards/foundational/adam
1
https://www.cdisc.org/standards/foundational/sdtm

12. Clinical Reporting with R3
Discovered blog post on using LaTeX and
'R'for producing reports for Drug Safety
Monitoring Boards (DSMBs)
Been intrigued by the possibility of
automating the process in Phase I as much
as possible.
3
http://blog.revolutionanalytics.com/2010/03/clinical-reporting-with-
r.html

13. What is LaTeX?
"LaTeX4
isahigh-qualitytypesettingsystem;it
includesfeaturesdesignedfortheproductionof
technicalandscientificdocumentation.LaTeXis
thedefactostandardforthecommunicationand
publicationofscientificdocuments."
--The LaTeX project
— Open source
— Cross platform
— Mature
— Free
4
https://www.latex-project.org/

14. Example5
section{Equations}
Let us see how easy it is to write equations.
begin{equation}
Delta =sum_{i=1}^N w_i (x_i - bar{x})^2 .
end{equation}
It is a good idea to number equations, but we can have a
equation without a number by writing
begin{equation}
P(x) = frac{x - a}{b - a} , nonumber
end{equation}
and
begin{equation}
g = frac{1}{2} sqrt{2pi} . nonumber
end{equation}
5
Sample LaTeX file,Harvey Gould,Clark University website,2016

16. LyX
"LyX6
isadocumentprocessorthat
encouragesanapproachtowritingbasedon
thestructureofyourdocuments
(WYSIWYM)andnotsimplytheir
appearance(WYSIWYG)."
--LyX wesbite
6
https://www.lyx.org/

17. What is R?
"Risafreesoftwareenvironmentfor
statisticalcomputingandgraphics."
--The R Project for Statistical Computing7
— Open source
— Cross platform
— Widely used in universities-whereas
SAS is not
7
https://www.r-project.org/

18. Example8
> x<-c(0.5,0.2,0.24,0.12,0.3,0.12,0.2,0.13,0.12,0.12,0.32,0.19)
> sum(x)
[1] 2.56
> max(x)
[1] 0.5
> min(x)
[1] 0.12
> range(x)
[1] 0.12 0.50
> mean(x)
[1] 0.2133333
> median(x)
[1] 0.195
> var(x)
[1] 0.01313333
> sd(x)
[1] 0.1146008
8
Statistics Using R with Biological Examples,Kim Seefeld & Ernst Linder,The Comprehensive R Archive Network,2007

19. Mean and Standard Deviation
> x<-c(0.5,0.2,0.24,0.12,0.3,0.12,0.2,0.13,0.12,0.12,0.32,0.19)
> sum(x)
[1] 2.56
> max(x)
[1] 0.5
> min(x)
[1] 0.12
> range(x)
[1] 0.12 0.50
> mean(x)
[1] 0.2133333
> median(x)
[1] 0.195
> var(x)
[1] 0.01313333
> sd(x)
[1] 0.1146008

20. Integrated
Development
Environment9
9
https://www.rstudio.com/

22. Magic
R + LateX

23. Options / Packages
— Sweave10
(included in R)
— knitr11
— R Markdown 12
12
http://rmarkdown.rstudio.com/
11
Elegant,flexible,and fast dynamic report generation with R
10
Friedrich Leisch.Sweave: Dynamic generation of statistical reports using literate data analysis.In Wolfgang Härdle and
Bernd Rönz,editors,Compstat 2002-Proceedings in Computational Statistics,pages 575-580.Physica Verlag,Heidelberg,
2002.ISBN 3-7908-1517-9.

24. Sweave source
documentclass [ a4paper ]{ article }
title { Sweave Example 1}
author { Friedrich Leisch }
usepackage { Sweave }
begin { document }
maketitle
In this example we embed parts of the examples from the
texttt { kruskal . test } help page into a LaTeX {} document :
begin { Schunk }
begin { Sinput }
> data ( airquality , package =" datasets ")
> library (" stats ")
> kruskal . test ( Ozone ~ Month , data = airquality )
end { Sinput }
begin { Soutput }
Kruskal - Wallis rank sum test
data : Ozone by Month
Kruskal - Wallis chi - squared = 29.267 , df = 4 , p - value = 6.901 e -06
end { Soutput }
end { Schunk }
which shows that the location parameter of the Ozone
distribution varies significantly from month to month . Finally we
include a boxplot of the data :
begin { center }
includegraphics { example -1 -002}
end { center }
end { document }

25. Sweave output
"Sweaveprovidesaflexibleframeworkfor
mixingtextandRcodeforautomatic
documentgeneration.Asinglesourcefile
containsbothdocumentationtextandR
code,whicharethenwovenintoafinal
documentcontainingthedocumentation
texttogetherwiththeRcodeand/orthe
outputofthecode(text,graphs)"
--Friedrich Leisch and R-core,2016 13
13
Sweave User Manual

26. rreport Package
"rreport14
producesstatisticalreportsin
LaTeXforclinicaltrials.Itisespeciallyuseful
forproducinginterimreportsfordata
monitoringcommittees(DMCs)."
--Vanderbilt University,Department of
Biostatistics
Developed by Frank Harrell15
.
15
R for Clinical Trial Reporting: Reproducible Research,Quality and
Validation,Frank Harrell,useR! 2007 Conference,2007
14
http://biostat.mc.vanderbilt.edu/wiki/Main/Rreport

27. Generating tables
with rreport16
16
Example Closed Meeting Data Monitoring Committee Report,Frank
Harrell,Vanderbilt University website,2007

28. Generating
graphics with
rreport 16
16
Example Closed Meeting Data Monitoring Committee Report,Frank
Harrell,Vanderbilt University website,2007

29. What about Validation?
— R23
— LaTeX
23
R: Regulatory Compliance and Validation Issues A Guidance Document for the Use of R in Regulated Clinical Trial
Environments,The R Foundation for Statistical Computing,2014

30. Suitable for enterprise?
Integrations
— R for statistical computing & analysis17
17
https://www.tableau.com/solutions/r

31. RStudio18
Desktop
— Open Source Edition-free
— Commercial License-$995/year
Server
— Open Source Edition-free
— Commercial License-$9,995/year
18
https://www.rstudio.com/products/RStudio/

32. Who uses R?
— GSK19
— Novartis20
— FDA21
21
Using R: Perspectives of a FDA Statistical RevieweR,Mat Soukup,presented at useR!,2007
20
Open Source Statistical Software (OS3
) in Pharma Development: A case study with R,Anthony Rossini,David A.James,
presented at useR!,2007
19
How I'm Selling R at GSK,Andy Nicholls,presented at LondonR,2010

33. "AtLillywedooursubmissionsinSASand
theFDAusesRtocheckthem."
--Jyoti Rayamahi,Eli Lilly and Company22
22
R,drug development and the FDA,Joseph Rickert,Revolutions,2013

34. Vision
— Since text and the programmes are
plaintext
— Physicians,Data Managers Statistical
Programmers and Medical Writers
could collaborate together using a
source control system

35. Source control
https://git-scm.com/
https://subversion.apache.org/

36. SUMMARYClinSpark ⇒ SDTM /ADaM ⇒ LaTeX + R ⇒ PDF

37. What we should aspire to
Clinicalreportsascode

38. Advantages
— Easy to re-run an analysis with updated data or revised methods
— Reduce the chance of copy and paste errors
— Avoid manual compilation of Word document and SAS output (TFLs)
— Fully paginates and indexes the document
— Can optionally publish your methods with the results

39. My Secret Agenda
A world where we don't use Windows,SAS,
or MS Word to analyse clinical trial data.
Image by Lori Portka Green is My Happy Place

40. Thank yousteffan.stringer@foundryhealth.com
http://foundryhealth.com/