ConSPIC 2016 presentation_DATTA_KORAK_2016_09_24_for PDF

The 7 year itch
No psychology lessons, I promise.
KORAK DATTA
NOVARTIS HEALTHCARE PVT LTD
DATE: 24 SEPT 2016
Conference for Statistics and Programming in Clinical Research, HICC, Hyderabad, 22-24 September, 2016
Image Courtesy: TripodStories- AB / Wikimedia commons / CC-BY-SA-3.0

Disclaimer
ALL OPINIONS EXPRESSED IN THIS PRESENTATION ARE
THE PRESENTER’S PERSONAL VIEWS, AND DO NOT
REFLECT THE VIEWS OR OPINIONS OF NOVARTIS
24 September 2016 7 YEAR ITCH | KORAK DATTA | NOVARTIS HEALTHCARE PVT LTD 2

Agenda
Background
Examples
Wrap up

A little
background
12 years of schooling in Tripura &
Gujarat,
3 years of bachelors degree,
Another year of PG diploma, both
in Karnataka,
6 months of internship, and now
7 years as a statistical programmer
@ Hyderabad
Aware of languages like C, Perl &
Java, Life science background,
exposed to global environment
early in career, started out with
pharmacokinetics studies, moved
on to SDTM & standardization,
and now settling into Oncology,
currently learning about efficacy
of drugs.

Pechakucha
PechaKucha 20x20 is a simple presentation format where
you show 20 images, each for 20 seconds. The images
advance automatically and you talk along to the images.
The topics, 7 of them today, I will try and run in a format
similar to this. I don’t always have images.
20 min
3 min Background
2 min Wrap-up
15 min 7 topics
~ 128.571
sec each
6 slides per topic,
20 seconds each
Lets get ready to run.

Shelf PERL & C++,
explore SAS

Shelf PERL & C++, explore SAS
. . . . . . . (2)
www.ibab.ac.in // Used with permission from IBAB www.flickr.com/photos/thomasguest/5142421926 // CC BY 2.0 // Used with no modifications

#!/usr/bin/perl
my $command;
print("Enter a command, ");
print("bye to quit.n");
do {
print(">");
# convert command to lowercase
chomp($command = <STDIN>);
$command = lc($command);
# display the command
print("$commandn");
} while($command ne "bye");
http://www.perltutorial.org/perl-do-while/
. . . . . . . (3)
#include <iostream> using namespace std;
int main ()
{
// Local variable declaration:
int a = 10;
// do loop execution
do
{
cout << "value of a: " << a << endl;
a = a + 1;
}while( a < 20 );
return 0;
}
http://www.tutorialspoint.com/cplusplus/cpp_do_while_loop.htm

. . . . . . . (4)
data A;
do i = 1 to 5 by 0.5;
y = i**2; /* values are 1, 2.25, 4, ..., 16, 20.25, 25 */
output;
end;
run;
http://support.sas.com/resources/papers/proceedings11/113-2011.pdf

. . . . . . . (5)
Description Syntax
PRXPARSE define a Perl regular
expression to be used
later by the other Perl
regular expression
functions
IF _N_ = 1 THEN
PATTERN = PRXPARSE(“<expression>");
RETAIN PATTERN;
PRXMATCH Locate the position in a
string, where a regular
expression match is
found
POSITION =
PRXMATCH(PATTERN,STRING);
POSITION =
PRXMATCH(“<expression>",STRING);
PRXCHANGE Perform a pattern
matching replacement
PRXCHANGE(“s/matching
expression/replacement
expression/modifiers“,<times>,
STRING)24 September 2016 7 YEAR ITCH | KORAK DATTA | NOVARTIS HEALTHCARE PVT LTD 10

. . . . . . . (5)
Description Example
* Matches the previous subexpression
zero or more times
cat* matches "cat", "cats", "catanddog"
+ Matches the previous subexpression
one or more times
d+ matches one or more digits
? Matches the previous subexpression
zero or one times
hello? matches "hell" and "hello"
. Matches exactly one character r.n matches "ron", "run", and "ran"
d Matches a digit 0 to 9 ddd matches any three digit number
D Matches a non-digit DD matches "xx", "ab" and "%%"
^ Matches the beginning of the string ^cat matches "cat" and "cats" but not "the
cat"
[xyz] Matches any one of the characters in
the square brackets
ca[tr] matches "cat" and "car"
[a-e] Matches the letters a to e [a-e]D+ matches "adam", "edam" and
"car"
[a-eA-E] Matches the letter a to e or A to E [a-eA-E]w+ matches "Adam", "edam" and
"B13"

. . . . . . . (6)
import java.util.Scanner;
class AddNumbers
{
public static void main(String args[])
{
int x, y, z;
System.out.println("Enter two integers to calculate their sum ");
Scanner in = new Scanner(System.in);
x = in.nextInt();
y = in.nextInt();
z = x + y;
System.out.println("Sum of entered integers = "+z);
}
}
Page source: http://www.programmingsimplified.com/java/source-code/java-program-add-two-numbers

. . . . . . . (6)
Sourcecodefrom:https://www.zomato.com/hyderabad/the-grand-trunk-road-madhapur/reviews

From Molecular
Biology to Lab
data

From Molecular Biology to Lab
data . . (2)
Subjects during graduation – Biotechnology, Biochemistry & Genetics
Favorite part of it – Cell biology, Microbiology, Molecular biology
Studies lab values, units, and cellular physiology.

data . . (3)
Unique side effect:
Cytokine storm
also known as cytokine
cascade and
hypercytokinemia
A potentially fatal
immune reaction
consisting of a positive
feedback loop between
cytokines and white
blood cells, with highly
elevated levels of
various cytokines
Source: http://www.cancer.gov/about-cancer/treatment/research/car-t-cells
“A Living Drug”
T cells are collected from the patient’s own blood and are
genetically engineered to produce special receptors on their
surface called CARs specific to antigens on tumor cells. These
engineered CAR T cells are then grown in the laboratory until
they number in the billions and then are infused into the
patient. After the infusion, if all goes as planned, the T cells
multiply in the patient’s body and, with guidance from their
engineered receptor, recognize and kill cancer cells that
harbor the antigen on their surfaces.

data . . (4)
Lab unit conversion
Not one of my favorite topics in school – units and conversions
Basic knowledge helps detect possible errors like
Inappropriately linked units
Inappropriate conversion factors
Also helps when we need to do additional/non standard conversions
like
Corrected Calcium[mg/dL] = Serum Calcium[mg/dL] - (0.8 *
(Albumin [g/dL]-4))

data . . (5)
WBC various types

data . . (6)
Mechanism of action of drugs
Source: http://www.ms-society.ie/uploads/File/GILENYA%20Information%20Sheet.pdf

Around the world
in 60 minutes

Around the world in 60
minutes . . . . . (2)
Driving to work
How we would leverage US
colleagues drive time to make
updates to our reports.
TC set up to be taken early from
home.
Gave us a good hour to implement
comments.
Colleague could reach office and
quickly review changes, allowing
India office to save time and leave
earlier from office.
Photocourtesy:epSos.de[CCBY2.0],viaWikimediaCommons

Shared responsibilities between programmers to program reports.
At the EoD, a quick TC would help get status update, and second
programmer would pick up tasks as left by first coder.
A quick email/TC again after 12 hours would ensure complete and
coherent information transfer.
Programmer in India could work with trial teams members from
China & Basel, while US programmer would take over interactions with
Japan and within US.
HAQ handled effectively in this fashion.
Around the world in
60 minutes . . . . . (3)
Working on 24 hour clocks
Photocourtesy:Morio[CC-BY-SA-3.0],via
WikimediaCommons

minutes . . . . . (4)
Leverage global knowledge
SMEs exist, but sometimes difficult to find.
Also local talent may not have complete scope of information.
Global SME networks help leverage knowledge better.
Image from: www.pixabay.com

minutes . . . . . (5)
Openness drives collaboration
Sharing, and in turn, listening, increases capability to understand
cultural differences and similarities
Leveraging similarities can help drive collaboration
Example: Working in tandem with regional festivals and holiday
break around the world, to enable associates and colleagues enjoy
family time can boost trust and productivity in the long run.
Cross-Culturalcollaboration

minutes . . . . . (6)
Asking questions, and thorough background study helps in
capability building.
2 approaches:
A complicated analysis can be completed by either just reviewing the SAP
and writing the code, Or
Reading up some background and arranging a TC to discuss a little bit in
depth about the same analysis
Delivery on time is important
With the second approach, programming can be made more
robust, and enable better deliverables in the long run.
Buildingtrustandcapability

Didn’t think they
would call a film

PK . . . . . . . . . . . . . . . . . . . . (2)
. . . . . . . (2)
AUC concept

PK . . . . . . . . . . . . . . . . . . . . . (3)
. . . . . . . .
AUC0–t
stands for the area under
the PK concentration profile
from time zero to time t,
where t is the last time point
at which there is a
quantifiable plasma
concentration.
AUC0–∞
stands for the total amount
of drug present in the blood
– by extending the plasma
concentration over
time(assuming a constant
rate of elimination observed
till the last time point).

PK . . . . . . . . . . . . . . . . . . . . . (4)
. . . . . . . .
Continuous glucose monitoring
“Continuous glucose monitoring (CGM) systems use
a tiny sensor inserted under the skin to check
glucose levels in tissue fluid. The sensor stays in
place for several days to a week and then must be
replaced.”
Source: https://www.niddk.nih.gov/health-information/diabetes/manage-monitoring-diabetes/continuous-glucose-monitoring

AUC in Glucose monitoring
Imagesource:Caipiraergänzt.Eschl(Ownwork)[GFDLorCCBY3.0],viaWikimediaCommons
PK . . . . . . . . . . . . . . . . . . . . . (5)
. . . . . . . .

PK . . . . . . . . . . . . . . . . . . . . . (6)
. . . . . . . .
AUCinGlucosemonitoring-calculation
Evaluationofanopenaccesssoftwareforcalculatingglucosevariabilityparametersofacontinuousglucose
monitoringsystemappliedatpediatricintensivecareunit
GáborMarics,#ZsófiaLendvai,#CsabaLódi,LeventeKoncz,DávidZakariás,GyörgySchuster,BorbálaMikos,
CsabaHermann,AttilaJSzabó,andPéterTóth-Heyn
Sharedunderhttp://creativecommons.org/licenses/by/4.0
BiomedEngOnline.2015;14:37.

From: http://fav.me/d4fp5vy [GFDL or CC BY 3.0]
4 DONE!
3 TO GO!

CDISC compliance,
and the games we
play

CDISC, and the games we play
. . . . . . . (2)
SDTM IG
Choosing the one version of IG vs mixed implementation
from 2 different IGs
For newer domains SDTM IG can provide guidance on how
to create custom datasets
Important to follow IG when designing custom(sponsor-
defined) datasets

. . . . . . . (3)
Audience/User exposure to SDTM & ADaM
Important to listen to feedback
Users have mixed exposure to CDISC and may have
pertinent questions related to implementation
Example:
PK data flow, Exposure data capture, TDM domains

. . . . . . . (4)
ADaMimplementation–verticalstructure
PARAM PARAMCD AVISIT AVISITN CRIT1 CRIT1FL AVALCAT1
ALT > 3 HTOX1_1
HEPATOTOXICITYENDPOINT
9999
Ispatientatriskatbaseline?
Y 1
ALT > 5 HTOX1_2 Y 1
ALT > 8 HTOX1_3 Y 0
ALT > 10 HTOX1_4 Y 0
ALT > 20 HTOX1_5 Y 0
AST > 3 HTOX2_1 Y 1
AST > 5 HTOX2_2 Y 0
AST > 8 HTOX2_3 Y 0
...... ...... ...... ......
ALT or AST > 3 HTOX3_1 Y 1
...... ...... ...... ......
ALTSI or ASTSI > 3 and
BILISI > 2 and ALPSI < 2
HTOX8_1 Y 0

. . . . . . . (5)
Mapping to SDTM
Should we map
all?
Source variables
Sometimes not
straightforward to
decide
FA or SUPP
How to map, and
yet keep CDISC
compliance
Custom domains

. . . . . . . (6)
OpenCDISC validator
Assessing the impact and handling OpenCDISC messages very critical
Consistency between domains utmost important
SD1082 FDAC036 Variable length is too long for actual data Error 7
CT2005 FDAC344 DSDECOD value not found in 'Completion/Reason for Non-Completion' extensible codelist Warning 38
SD1077 FDAC021 FDA Expected variable not found Warning 1
SD1118 FDAC146 Neither DSSTDTC, DSDTC nor DSSTDY are populated Warning 45
SD1201 FDAC213 Duplicate USUBJID/--DECOD/--STDTC record Warning 4
SKIP_SD0064 DM is missing or lacks necessary variables and cannot be used for this cross-dataset validation Notice 1
SD1082 FDAC036 Variable length is too long for actual data Error 7
DS
SUPPDS

Standardization –
the buzz word

Standardization . . . . . . . . . . . . .
. . . . . . (2)
Building your own library of programs and utility macros
Standardize your own codes
Similar structure, implement best practices to utilize less resource
Comments and program headers with correct information

. . . . . . (3)
Awareness of SDFs
◦ Correctness
◦ Efficiency
◦ Readability and Maintainability
◦ Timeliness
◦ Robustness
◦ Reusability
◦ Portability

. . . . . . (4)
Reporting tools
Current rage in the industry – building libraries of reusable
reports – decrease inefficiencies – automate report
programming
Short term vision doesn’t help
User requirements and big picture understanding is
important

. . . . . . (5)
EDC
Data hub
Source
datasets
OUTPUT
INPUT
SAS programs
for ADaM
dataset
generation
INPUT
SAS programs for
SDTM dataset
generation
INPUT
SAS
programs
for report
generation
SDTM
dataset
OUTPUT
ADaM
dataset
OUTPUT

. . . . . . (6)
Standardization efforts
Standardization
efforts
EDC
Data hub
Source
datasets
OUTPUT
INPUT
SAS programs
for ADaM
dataset
generation
INPUT
SAS programs for
SDTM dataset
generation
INPUT
SAS
programs
for report
generation
SDTM
dataset
OUTPUT
ADaM
dataset
OUTPUT

Resisting RECIST

Resisting RECIST . . . . . . . . . . . .
. . . . . . . (2)
Moved from Non-Oncology Pharmacology trials to
Oncology Full development trials
My knowledge about RECIST = 0
RECIST = Response Evaluation Criteria in Solid Tumors
Not RESIST
 A set of published rules that define when cancer patients
improve ("respond"), stay the same ("stable") or worsen
("progression") during treatments.

. . . . . . . (3)
Assessment  Tumour lesion sizes and locations
Analysis  Complex, very complex (to me atleast)
Target Lesions
Non-target
Lesions
New Lesions Overall Response
CR CR No CR
CR SD No PR
PR CR or SD No PR
SD CR or SD No SD
PD Any Yes or No PD
Any PD Yes or No PD
Any Any Yes (PD) PD

. . . . . . . (4)
My first few months in oncology trials  Safety reports –
AEs. Conmeds. Vitals. Etc.
And then I became responsible for a trial

. . . . . . . (5)
The rest of the story:

. . . . . . . (6)
RECIST, my understanding is now close to
Assessments: 6/10
Analysis: 5/10

7 learnings
1. World is round, use the rotations well.
2. Knowledge is everywhere, be sure to seek it
out.
3. Education always contributes, in ways we
don’t appreciate.
4. Learn to see the big picture, and appreciate
it.
5. Asking questions is a good thing. It pays.
6. Information can neither be destroyed nor
created, it can only be transformed from
one form to the other.
7. Have fun.
8. Sometimes we need to
bend the rules a bit, just a
bit.

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