This presentation discusses the transformation of pharmacokinetic (PK) data from its original source to the standard SDTM submission format. PK data comes from various clinical trial sources and needs to populate the SDTM PC and PP domains with linked records in RELREC. Challenges include mapping variables, relating records across domains, and deriving parameters in PP from concentrations in PC. Intermediate ADaM datasets like ADPC are often needed to perform analyses and populate PP. Care is required to represent timing criteria, flags, and other analysis-related attributes correctly between the domains.

1. Metamorphosis of PK data from
Source to Submission
Dr Shanmugavel S Sundaram
This Presentation does not necessarily reflect the opinion of the institutions of those who
have contributed.

2. Agenda
 Why is PK important?
 PK PK everywhere. What is it ? and Why?
 PK a Myth?
 PK phases
 PK Data Sources- Clinical Trials
 SDTM PC
PK data Variables in SDTM PC
PK Data Common Pain Points
PC and PC- Do they gel well…?
 PP Domain Creation
 SDTM- PP and RELREC
 ADaM- ADPC and ADPP-Points to Ponder

3. Why is Pharmacokinetics important?
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● The high failure rate in Clinical trials increases costs of drug
development dramatically in pharmaceutical industry.
● One of the causes for the high attrition rate is inadequate
information from early phase studies to support go/no-go
decisions or to design later-phase clinical studies correctly.
● To address the issue, it is essential to have a good
understanding on what the drug does to the body (PK) and
what the body reacts to the drug (PD). To reduce this risk, it is
essential to fully investigate the pharmacokinetics of a new
drug during each stage of development.

4. PK PK everywhere. What is it ? and Why?
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5. ● Pharmacokinetics is a mathematical description of the time
course of drug and/its metabolite in the body.
● ADME determines the drug concentration in the body.
● What is LADME?
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Pharmacokinetics- A myth

6. Pharmacokinetics- Phases
● Metabolism
o Phase I: Main goal is to produce more Polar compound. Main
reactions that happens are Oxidation, Reduction and Hydrolysis.
• C450: Cytochrome450 enzyme is the main player.
o Phase 2:More water soluble compounds due to Glucoronidation,
Sulfation and Acetylation. Together named as Conjugation
reactions.
● Biotransformation Examples.
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7. Pharmacokinetics- Phases
First Order Elimination Zero Orfer Elimination
Drug decreases exponentially with
Time
Drug decreases Linearly with Time
Rate of Elimination is proportional to
the Drug
Rate of Elimination is Constant
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Cmax ????
t1/2 ?????

8. Pharmacokinetics… Contd…
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9. PK Data Sources- Clinical Trials
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10. SDTM- PC
● Important component of all Clinical Kinetics studies would be the
following.
 Collection of PK samples
 Analysis of PK data
● PC Domain:
 Structure: One record per subject per dose per analyte/time point.
 Hence Concentration Time points are stored across multiple records.
● Derive multiple pharmacokinetic parameters for each individual
Pharmacokinetic (PK) profile
 Cmax,
 tmax,
 AUC,
 half-life, etc
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11. PK data Variables in SDTM PC
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PCTEST –. Represents analyte (Usually). Long, chemical names possible.
Inconsistent spellings frequent
• For urine samples, can contain different info, e.g. specific gravity,
total volume collected.
PCTESTCD – Will need to develop shortened versions of Analyte. Can be
difficult for long names that are similar to one another.
PCCAT – If PCTEST is an Analyte, then PCCAT = “ANALYTE”. If PCTEST is
urine descriptive variable, then PCCAT = “SPECIMEN PROPERTY”.
Note: PCCAT has very different meaning than PPCAT.
PCGRPID – Use in conjunction with RELREC to relate PP to PC.

12. PK data Variables in SDTM PC
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PCSPCCND, PCSTAT – useful for relating PP to PC
PCTPT – Part of unique key for PC. Generally, VISITNUM and VISIT
not as important in uniquely identifying time points in a crossover.
PERIOD and TIMEPOINT are adequate.
PCTPTREF – Generally is the first dose of the period. However,
some studies can have multiple doses and profiles of samples
within a period.
PCRFTDTC – Time in addition to date is critical for phase I
crossovers.
PCENDTC – Used for urine collection where there is a stop and
start. Should be null for blood samples.

13. PK Data Common Pain Points
● Source Data
 May be in different formats: XPT, XLS, TXT
 May be one PK file per analyte
 CRF Time point and Concentration may be in separate files
• Merging/joining will probably not go smoothly
– `Accession number typos, missing records, etc.
 Usually will need to join and/or concatenate datasets before
converting
● Analyte
 Maps to different variables in PP and PC
 Compound/metabolite names may be spelled inconsistently in
different datasets
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14. PC and PC- Do they gel well…?
CRF Timepoints
PK Subject No
PK Period
PK Timepoint
Date-Time
Sample ID
Sample Condition
Not Done
Vomited?
Concentration
PK Subject No
PK Period
PK Timepoint
PK Matrix
PK Analyte
Concentration
Conc Units
Exclude
PK Parameters
PK Subject No
PK Period
PK Matrix
PK Analyte
PK PK Parameter
Value
Units
Exclude
o Three entities
o Two SDTM domains
o PC and PP
o Relationships
o CRF-Time points to
Concentration
o One-to-many
o Concentration to PK
Parameters
o Many-to-many
o Requires use of
RELREC in SDTM
Converting PK data to PP and PC can be challenging since,
the Source data from three different systems

15. PP Domain Creation
● Generating PP Domain from PC is not easy as it seems. Why?
o dose level
o actual time relative to dosing etc…
To feed PC data in to the PK analysis sofiwares like PharmPK
Is not easy. So, we create the intermediate analysis Dataset and this
is……
● ADPC Dataset:
o Contains data from SDTM PC merged with ADSL datasets like
Demography and Treatment information.
o Additional Variables required for PK analysis like Dose Level,
Actual Time relative to dosing are calculated.
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16. PK Data Common Pain Points
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● Relating PP Records to PC Records
● Reading this section of IG will either
Make you head spin Put you to sleep

17. SDTM- PP and RELREC
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● PP domain will be created using the ADaM PC and the Parameters
derived using the PK analysis software.
● RELREC

18. SDTM- RELREC
● The linking of the 2 domains is important and is primary done with,
 Use of variable PCRFTDTC, Date/Time of Reference Point from SDMT.PC
domain against PPRFTDTC, date/Time of Reference Point in SDTM.PP.
These variable holds the [Time for nom time=0].
 Extra links are by PCSEQ and PCGRPID.
 Create a RELREC record for each PP record.
 Go through the list of PC records and create a RELREC record with the
same RELID for each record that was used to calculate the PK parameter in
the PP record.
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19. SDTM- RELREC
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RELREC one to one link through –SEQ. PC observations from row 1 to row
12 (RELID=1) are related to PP observation at row 13 (RELID=1) through
same –SEQ value.

20. ADaM- ADPC and ADPP
Points to Ponder
Similar to the creation of ADPC, the PP domain is merged with ADSL and derived
variables are added to create ADPP. In the BDS structure, following variables derivation
will need to pay attention to:
 AVISIT/ AVISITN : AVISIT and its numeric counterpart AVISITN are derived from the
variables VISIT and VISITNUM from the PC domain.
 All PK concentrations (in ADPC) or all PK parameters (in ADPP) that refer to
the same exposure will have the same AVISIT(N) value.
 ATPT/ATPTN :The planned analysis time points Only for pre-dose values they differ
from the PCTPT and PCTPTNUM The value of PCTPTNUM, which is in general
negative for predose samples, is put to zero in ATPTN.
 PCTPTNUM having the planned time points in minutes, it can be converted
to e.g. hours in ATPTN. These variables are not present in ADPP.
 ANLzzFL: Analysis record flags (ANLzzFL) can be used to select a set of records for
one or more analyses. The “zz” can carry value from 0-99.
 As multiple analysis flags can be assigned, a new variable, analogue to
ANLzzFL, is needed to define the different analysis groups: ANLzzFD
(Analysis Record Flag zz Description).
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21. ADaM- ADPC and ADPP
Points to Ponder
● In ADPC, the main analysis groups are:
● ‘PK analysis’, ‘Descriptive statistical analysis’ and ‘Steady state analysis’.
In ADPP, the main analysis groups are:
 ‘Inferential statistical analysis’ and ‘Descriptive statistical analysis’. Subjects, time
points or PK parameters can be included or excluded from analyses based upon
criteria or as specified in the protocol/SAP.
● AVAL/AVALC. In most cases, it is equal to PCSTRESN, the numeric result in standard
unit. The character counterpart is reported in AVALC
● For example, values that are below the limit of quantification can be put to zero.
● CRITy, CRITyFL, CRITyFN Analysis criteria are evaluated in CRITy. The “y” is used to
categorize the different criteria and will be replaced with a single digit: 0-9.
● Two important criteria in PK analysis are,
● time deviations and
● quantifiable predose values.
If a sample is taken more than 10% too soon, or too late relative to the scheduled time
point, the value can be excluded from the descriptive statistical analysis
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22. Thank You All
PK data is critical in understanding a drug’s safety and
determining its dosing frequency.
o Yet the processes for collection and submission of this data
result in challenges to its representation in an SDTM format.
So… Please Take caution and all the very best….
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