1
Inadequate requirements to analytical keys may
compromise standardised analysis of SEND data – with
focus on laboratory data (LB)
- Why SEND++ should be considered
Master’s thesis
Thomas Gade Bjerregaard
(MI07121)
2
Background – the current data flow to FDA
Local analysis
& statistics
GLP
Plan &
collect data
GLP
Report data
and analysis
FDA review
3
Background – the new defined data flow to FDA
Local analysis
& statistics
GLP
Report data
and analysis
FDA review
GLP
Plan &
collect data
Exchange
format
FDA Analysis
4
Background – the new defined data flow in
generic terms and converted to eData use cases
Local analysis
& statistics
GLP
Report data
and analysis
GLP
Plan &
collect data
Exchange
data
Global
analysis
5
Objective
• Investigate and substantiate scenarios where inadequate
requirements may compromise standardised analysis
• Scope restriction: Laboratory data
 Investigate analytical prerequisites for SEND eData using
laboratory data as example
6
Thesis outline
Presentation outline
• Two core concepts
• Core concept
• Analytical keys
• Laboratory data
• Three Use cases
• GLP
• Exchange
• Analysis
• Two conflicts
• When
• What & How
• Analytical keys
• Two conflicts
• What & How
• Core concept/GLP
• Exchange
• Basic analysis conflict
• When
• GLP
• Exchange
8
Core concept: Analytical keys outline
appropriate/inappropriate comparisons - and caveats
• When
• Planned timing
• Who
• Within study analysis
• Study design ~ treatment groups
• What
• The endpoint under
investigation
• How
• The method of assessment
• Between study analysis
• Animal factors
• Species, strain, age, sex, etc.
• Study factors
• Target, drug, laboratory, husbandry,
etc.
9
Conflict on What & How:
- Characterisation of laboratory measurements
NCoA: Nested Context of an Analyte
Primary

category
Secondary
Category

Analyte

Sample matrix

Method
Analyte
-
-
Eryth
X
-
-
Endpoint
Haematology
Haemogram
Eryth
-
-
-
-
(What?)
X
Urinalysis
X-
X
Eryth
-
-
Eryth
Whole blood
Flow cytometry
-
-
X
Eryth
X
Urine
X
Dipstick
-
-
Eryth
Urine
Microscopy
Study specific
Haematology
Haemogram
Eryth
Whole blood
Flow cytometry
implementation
Urinalysis
X
X-
Eryth
X
Urine
X
Dipstick
X
of endpoint
Urinalysis
-
Eryth
Urine
Microscopy
Test (How?)
10
Conflict on What & How:
- Characterisation of laboratory measurements
Primary

category
Secondary
Category

Analyte

Sample matrix

Method
Analyte
-
-
X
Eryth
-
-
Endpoint
Haematology
Haemogram
Eryth
-
-
-
-
(What?)
X
Urinalysis
X-
X
Eryth
-
-
Eryth
Whole blood
Flow cytometry
-
-
Eryth
X
X
Urine
Dipstick
X
-
-
Eryth
Urine
Microscopy
Study specific
Haematology
Haemogram
Eryth
Whole blood
Flow cytometry
implementation
Urinalysis
X
X-
Eryth
X
Urine
X
Dipstick
X
of endpoint
Urinalysis
-
Eryth
Urine
Microscopy
Test (How?)
Too much information – without control
Scientific
umbrella
Primary
category

Secondary
Category

Analyte

Sample
matrix

Method
LIMS
governance
Presentation title
Impossible to specify analytical criteria
Date
12
The basic conflict
- detachment of information accounting for incompleteness and inconsistency
SDRG
SDRG
SDRG
SDRG
SDRG
SDRG
SDRG
Define
File
Define
File
Define
File
Define
File
Define
File
Define
File
Define
File
SEND
data
SEND
data
SEND
data
SEND
data
SEND
data
SEND
data
SEND
data
Presentation title
Compromised analytical performance
General confusion regarding the components of the NCoA
+
Excess information from the GLP Use Case relative to the 5 variables in SENDIG
+
3 (or 4) of 5 variables corresponding to NCoA are without controlled terminology
+
null values allowed in ‘Expected’ and ‘Permissible’ variables
=
compromised analytical performance in any multi-study environment
Date
14
15
For analysis, CATegory variables should be controlled
NCoA
Primary
Secondary
terminology
category
category
LOINC
terminology
SSIE defining
SEND variables
Option A
Option B
LBCAT
LBSCAT
New
New
NCI list
NCI list
New
New
NCI list
NCI list
Analyte name
Sample
matrix
Method
Component
System
Method
LBTESTCD
LBSPEC
LBMETHOD
LBTESTCD
SPEC
LBTESTCD
SPEC
‘test’
longname /
shortname
LBLOINC
New
NCI list
?
LOINC term
16
For analysis, LBLOINC can substitute control of LBMETHOD
NCoA
Primary
Secondary
terminology
category
category
LOINC
terminology
SSIE defining
SEND variables
Option A
Option B
LBCAT
LBSCAT
New
New
NCI list
NCI list
New
New
NCI list
NCI list
Analyte name
Sample
matrix
Method
Component
System
Method
LBTESTCD
LBSPEC
LBMETHOD
LBTESTCD
SPEC
LBTESTCD
SPEC
‘test’
longname /
shortname
LBLOINC
New
NCI list
?
LOINC term
17
Thesis outline
Presentation outline
• Two core concepts
• Core concept
• Analytical keys
• Laboratory data
• Three Use cases
• GLP
• Exchange
• Analysis
• Two conflicts
• When
• What & How
• Analytical keys
• Two conflicts &
• What & How
• Core concept/GLP
• Exchange
• Basic analysis conflict
• When
• GLP
• Exchange
18
When: ‘Global timing’ or ‘Local timing’
Reference time point
Session
Dosing
Start
of
study
0h
2h
4h
8h
24h
Local timing
0h
2h
4h
8h
24h
Local timing
D 28
D -3
Pre-treatment
Global timing
Treatment
19
The SEND timing variables
SENDIG time
planning
variable
Abbreviated label and CDISC notes from
SENDIG
VISITDY
Planned study day of assessment
LBTPT
Text label for sampling time
LBTPTNUM
Numeric version of LBTPT to aid in sorting
of records
LBELTM
Planned elapsed time from reference to a
time point
LBTPTREF
Text label for reference time point
LBRTPTNM
Numeric version of LBTPTREF to aid in
two layer sorting of records
Corresponding SEND variable for actual time
point
Terminology of Section 5.1.3
LBDY
Actual study day – directly collected, or
calculated from LBDTC and RFSTDTC in the
Demographics data set
LBDTC
The GLP date/time of verification of the
sample collection
N/A
LBRFTDTC
The GLP date/time of verification of the
reference time point
Scheduled date
Session label
N/A
Distance
Reference time point
N/A
LBDY
VISITDY
Record
N:1 synonym
LBDTC
LBTPT
1:1
assumption
LBELTM
relative
N:1 relation
Reference
record
LBTPTNUM
LBREFDTC
LBTPTREF
LBTPTRNM
Identical
1:1 synonym
1:1 synonym
--DTC
--TPT
N:1 synonym
synonym
N:1
--DY
1:1
assumption
Two timing
key sets
--TPTNUM
--ELTM
N:1 relation
--TPTREF
‘VISITDY’
ref-record
22
For analysis, only one key set should be allowed!
- VISITDY cannot be more granular – but session key set can account for grace days
No need for grace days
Absolute
VISITDY key set
Maximum one session per TEST per day
or
Need for grace days
Absolute
VISITDY key set
Relative
Session key set
Two or more sessions per TEST per day (session timed
relative to reference time point)
Relative
Session key set
N/A
24
A study consists of consecutive VISITDY intervals
1
24:00
8:00
2
16:00
24:00
8:00
3
16:00
24:00
8:00
4
16:00
24:00
8:00
5
16:00
24:00
8:00
6
16:00
24:00
8:00
7
16:00
24:00
8:00
8
16:00
24:00
8:00
16:00
24:00
25
VISITDY = 1
--TPT = ‘6 hours post dose’
--TPTNUM = 1
-example
--ELTM
= ‘P6H’ with timed
--TPTREF = ‘Day 1 Dose’
--TPTRNM = 1
VISITDY = 1
Planning relative
to dosing do not adhere to VISITDY
--TPT = ‘12 hours post dose’
1
24:00
8:00
2
24:00
16:00
8:00
session
dosing with three days intervals
--TPTNUM after
=2
--ELTM = ‘P12H’
--TPTREF = ‘Day 1 Dose’
--TPTRNM = 1
3
16:00
24:00
8:00
16:00
24:00
VISITDY = 2
--TPT = ‘24 hours post dose’
--TPTNUM = 3
--ELTM = ‘P24H’
--TPTREF = ‘Day 1 Dose’
--TPTRNM = 1
4
8:00
5
16:00
24:00
8:00
16:00
24:00
8:00
6
7
Dose 2
Dose 1
VISITDY = 4
--TPT = ‘72 hours post dose’
--TPTNUM = 4
--ELTM
24:00
8:00
16:00
24:00 = ‘P72H’
8:00
16:00
--TPTREF = ‘Day 1 Dose’
--TPTRNM = 1
8
16:00
P6H
P6H
P12H
P12H
P24H
P24H
P72H
VISITDY = 4
--TPT = ‘6 hours post dose’
--TPTNUM = 1
--ELTM = ‘P6H’
--TPTREF = ‘Day 4 Dose’
--TPTRNM = 2
P72H
VISITDY = 4
--TPT = ‘12 hours post dose’
--TPTNUM = 2
--ELTM = ‘P12H’
--TPTREF = ‘Day 4 Dose’
--TPTRNM = 2
VISITDY = 5
--TPT = ‘24 hours post dose’
--TPTNUM = 3
--ELTM = ‘P24H’
--TPTREF = ‘Day 4 Dose’
--TPTRNM = 2
VISITDY = 7
--TPT = ‘72 hours post dose’
--TPTNUM = 4
--ELTM = ‘P72H’
--TPTREF = ‘Day 4 Dose’
--TPTRNM = 2
24:00
26
Dose-independent sessions are planned to occur on a specific day
- example with morning/afternoon session on all days
1
24:00
8:00
2
16:00
Day 1 sessions
24:00
8:00
3
16:00
Day 2 sessions
24:00
8:00
4
16:00
Day 3 sessions
24:00
8:00
5
16:00
Day 4 sessions
24:00
8:00
6
16:00
Day 5 sessions
24:00
8:00
7
16:00
Day 6 sessions
24:00
8:00
8
16:00
Day 7 sessions
24:00
8:00
16:00
Day 8 sessions
24:00
27
Suggested convention for --ELTM with semantic overlap to VISITDY
- based om pseudo-intervals for VISITDY
Shift in visual
representation
1
2
3
VISITDY = 1
VISITDY = 2
VISITDY = 3
Day 1
00:00  24:00
Day 2
00:00  24:00
Day 3
00:00  24:00
28
Suggested convention for --ELTM with semantic overlap to VISITDY
- based om pseudo-intervals for VISITDY
VISITDY = -1
VISITDY = 1
VISITDY = 2
VISITDY = 3
Day -1
00:00  24:00
Day 1
00:00  24:00
Day 2
00:00  24:00
Day 3
00:00  24:00
Pseudo-interval
specifications for VISITDY
(Hours)
--STINT = -P24H
--ENINT = (-)P0H
--STINT = P0H
--ENINT = P24H
--STINT = P24H
--ENINT = P48H
--STINT = P48H
--ENINT = P72H
Pseudo-interval
specifications for VISITDY
(Days)
--STINT = -P1D
--ENINT = (-)P0D
--STINT = P0D
--ENINT = P1D
--STINT = P1D
--ENINT = P2D
--STINT = P2D
--ENINT = P3D
Suggested convention
for --ELTM
--ELTM = -P1D
--ELTM = P1D
--ELTM = P2D
--ELTM = P3D
Time zero
29
Suggested convention for --ELTM with semantic overlap to VISITDY
- based om pseudo-intervals for VISITDY
VISITDY = -1
VISITDY = 1
VISITDY = 2
VISITDY = 3
Day -1
00:00  24:00
Day 1
00:00  24:00
Day 2
00:00  24:00
Day 3
00:00  24:00
Pseudo-interval
specifications for VISITDY
(Hours)
--STINT = -P24H
--ENINT = (-)P0H
--STINT = P0H
--ENINT = P24H
--STINT = P24H
--ENINT = P48H
--STINT = P48H
--ENINT = P72H
Pseudo-interval
specifications for VISITDY
(Days)
--STINT = -P1D
--ENINT = (-)P0D
--STINT = P0D
--ENINT = P1D
--STINT = P1D
--ENINT = P2D
--STINT = P2D
--ENINT = P3D
Suggested convention
for –ELTM
(non- ISO8601)
--ELTM =
-P1D/P0D
--ELTM =
P0D/P1D
--ELTM =
P1D/P2D
--ELTM =
P2D/P3D
Suggested convention
for --ELTM
--ELTM = -P1D
--ELTM = P1D
--ELTM = P2D
--ELTM = P3D
Time zero
30
Suggested convention for --ELTM accounting for grace days
- based om pseudo-intervals for VISITDY
VISITDY = -1
VISITDY = 1
VISITDY = 2
VISITDY = 29
VISITDY = 30
Day -1
00:00  24:00
Day 1
00:00  24:00
Day 2
00:00  24:00
Day 29
00:00  24:00
Day 30
00:00  24:00
Pseudo-interval
specifications for VISITDY
(Hours)
--STINT = -P24H
--ENINT = (-)P0H
--STINT = P0H
--ENINT = P24H
--STINT = P24H
--ENINT = P48H
Pseudo-interval
specifications for VISITDY
(Days)
--STINT = -P1D
--ENINT = (-)P0D
--STINT = P0D
--ENINT = P1D
--STINT = P1D
--ENINT = P2D
--STINT = P28D
--ENINT = P30D
Suggested convention
for --ELTM
--ELTM = -P1D
--ELTM = P1D
--ELTM = P2D
--ELTM = P5W
Time zero
31
VISITDY = 1
--TPT = ‘Day 1 morning’
--TPTNUM = 1.1
- example with morning/afternoon
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
Dose-independent sessions are planned relative to study start
1
24:00
8:00
2
16:00
session on selected days
3
VISITDY = 1
--TPT = ‘Day 1 afternoon’
--TPTNUM = 1.2
24:00
8:00
16:00
24:00
8:00
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
16:00
4
24:00
8:00
5
16:00
24:00
8:00
6
16:00
24:00
8:00
7
16:00
24:00
8
VISITDY = 6
24:00
8:00
16:00
8:00 = 16:00
--TPT
‘Day 6
morning’
--TPTNUM = 6.1
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
24:00
Start of Study
Day 1 sessions
Day 6 sessions
P1D
P6D
VISITDY = 6
--TPT = ‘Day 6 afternoon’
--TPTNUM = 6.2
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
32
VISITDY = 1
--TPT = ‘Day 1 morning’
--TPTNUM = 1.1
- example with morning/afternoon
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
Dose-independent sessions are planned relative to study start
1
24:00
8:00
2
16:00
session on selected days
3
VISITDY = 1
--TPT = ‘Day 1 afternoon’
--TPTNUM = 1.2
24:00
8:00
16:00
24:00
8:00
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
16:00
4
24:00
8:00
5
16:00
24:00
8:00
6
16:00
24:00
8:00
7
16:00
24:00
8
VISITDY = 6
24:00
8:00
16:00
8:00 = 16:00
--TPT
‘Day 6
morning’
--TPTNUM = 6.1
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
24:00
Start of Study
Day 1 sessions
Day 6 sessions
P1D
P6D
VISITDY = 6
--TPT = ‘Day 6 afternoon’
--TPTNUM = 6.2
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
33
VISITDY = 1
--TPT = ‘Day 1 morning’
--TPTNUM = 1.1
- example with morning/afternoon
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
Dose-independent sessions are planned relative to study start
1
24:00
8:00
2
16:00
session on selected days
3
VISITDY = 1
--TPT = ‘Day 1 afternoon’
--TPTNUM = 1.2
24:00
8:00
16:00
24:00
8:00
--ELTM = ‘P1D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
16:00
4
24:00
8:00
5
16:00
24:00
8:00
6
16:00
24:00
8:00
7
16:00
24:00
8
VISITDY = 6
24:00
8:00
16:00
8:00 = 16:00
--TPT
‘Day 6
morning’
--TPTNUM = 6.1
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
24:00
Start of Study
Day 1 sessions
Day 6 sessions
P1D
P6D
VISITDY = 6
--TPT = ‘Day 6 afternoon’
--TPTNUM = 6.2
--ELTM = ‘P6D’
--TPTREF = ‘Start of study’
--TPTRNM = 0
34
Dose-independent sessions are planned relative to study start
- example with grace days on ophthalmoscopy
…
1
24:00
8:00
16:00
24:00
22
8:00
16:00
23
24:00
8:00
16:00
24
24:00
8:00
16:00
25
24:00
8:00
16:00
26
24:00
8:00
16:00
27
24:00
8:00
16:00
28
24:00
8:00
16:00
Start of Study
VISITDY = 22
--TPT = ‘Week 4 ophthalmoscopy’
--TPTNUM = 22
--ELTM = ‘P4W’
P72H
--TPTREF = ‘Start of study’
--TPTRNM = 0
Week 4 ophthalmoscopy
P4W
24:00
35
Session key set describing all three planning paradigms
- Absolute day/week number should shift between TPT/TPTREF
…
1
24:00
8:00
16:00
24:00
22
8:00
16:00
23
24:00
24
VISITDY = 22
--TPT = ‘Day 22 afternoon’
--TPTNUM = 22.2
--ELTM = ‘P22D’
--TPTREF = ‘Start of study’
8:00
16:00
8:00
16:00
--TPTRNM
= 024:00
25
24:00
8:00
26
24:00
16:00
27
VISITDY = 26
--TPT = ‘24 hours post dose’
--TPTNUM = 3
--ELTM
= ‘P24H’
8:00
16:00
24:00
8:00
16:00
--TPTREF = ‘Day 25 Dose’
--TPTRNM = 9
28
24:00
8:00
16:00
Dose 9
Start of Study
P6H
P12H
Day 22
sessions
P24H
Week 4 ophthalmoscopy
P4W
VISITDY = 22
--TPT = ‘Week 4 ophthalmoscopy’
--TPTNUM = 22
--ELTM = ‘P4W’
P72H
--TPTREF = ‘Start of study’
--TPTRNM = 0
24:00
36
Findings summary
• What & How
• Expected perceived as optional
 Incompleteness, mixture of intended/unintended causes
• Not adequately standardised
 Inconsistency
• When
• Permissible perceived as optional
 Incompleteness, mixture of intended/unintended causes
• Complex and scenario dependent relations between variables in timing key sets and
incomplete variables landscape
 Inconsistency unless balanced approach is applied
Legacy
SEND-light
SEND+
SEND++
No eData – only paper/pdf
- eData
- as-is LIMS export or manual entry from paper/pdf report
-
eData
Standardised variable structure  SENDIG
Completeness  feasible LIMS export and post processing
Consistency  only formats and NCI code lists
Gap handling
Curation
- eData
- Standardised variable structure beyond SENDIG
- Completeness  all that can be derived
(i.e. also from report or protocol)
- Consistency  only formats and NCI code lists
Curation
- eData
- Standardised variable structure beyond SENDIG
- Completeness  all that can be derived
(i.e. also from report or protocol)
- Consistency  Full standardisation of analytical keys
Direct
Standardised
analysis based
on the correct
analytical keys
Presentation title
Date
38
Complicated stake holder landscape – no easy fix
- every body have their own interpretation of the standards
• Standard developing
organisations
• CDISC
• Controlled terminology
• National Cancer Institute
• Validation rules
• Independent – OpenCDISC
• FDA
• Regulatory agencies
• FDA
• PMDA?
• IT vendors
• LIMS
• Data repositories
• Data processing
•
•
Data management
Data analysis
• Discussion fora
• PhUSE
39
Thank you!
Presentation title
Backup slides
Date
40
Presentation title
Intention must be to mimic local analysis
Local analysis
& statistics
GLP
Report data
and analysis
GLP
Plan &
collect data
Exchange
data
Translations between
data base structures
Global
analysis
Date
41
Presentation title
Real GLP Use Case
Local analysis
& statistics
Collect
Plan
Report
Date
42
Presentation title
The shortcoming of the real GLP Use Case
- Completeness compromised
Local analysis
& statistics
GLP
Report
GLP
LIMS setup
and data
capture
Plan
Who
Analyte
(When)
(What)
(How)
Exchange
data
Global
analysis
When
What
How
Date
43
Curated
data repository
Automated data
repository
Pre-storage
gap handling
&
standardisation
No format
requirements
Data for
storage
Storage type
Standard
analysis
No format
requirements
Consistently standardised
and complete data sets
Curation
into DB
Automated
load to DB
Data repository (DB)
(including derived summary statistics data layers)
DB key based
analysis
Direct storage of data sets (as-is)
File repository
(DB)
File storage
Analysis based onKey
correct
based
keys in
consistently populated
analysis
data sets
Custom
analysis
Analytical
outcome
Standard
file share
Current level of SEND data sets
Source data
Storage process
Automated
file repository
Case by case
customised analysis
Automated/standardised visualisation, analysis,
summary statistics etc.
?