2nd DRAFT for Review
1. Analyses and Displays Associated to Non-Compartmental Pharmacokinetics – with a focus on clinical trials
Draft - Version 0.2
Created 30 Jan 2014
A White Paper by the FDA/PhUSE Development of Standard Scripts for Analysis and Programming Working Group
This white paper does not necessarily reflect the opinion of the institutions of those who have contributed.
2. Table of Contents
Section Page
1. Analyses and Displays Associated to Non-Compartmental Pharmacokinetics – with a focus on clinical trials 1
2. Table of Contents 2
3. Revision History 4
4. Purpose 5
5. Introduction 6
6. General Considerations 8
6.1. Reporting workflow 8
6.2. CDISC PK datasets creation workflow 9
7. Calculation of PK parameters 11
7.1. Main derived PK parameters 11
7.2. NCA Checklist 15
7.2.1. Missing sampling or concentration data 16
7.2.2. Concentration values below the limit of quantification 16
7.2.3. Exclusion of outliers or influential data 16
7.2.4. Use of actual v.s. planned sampling timepoints 16
7.2.5. Reporting of missing PK parameters 17
8. PK Tables, Figures and Listings for Individual Studies 18
8.1. Standard List of Outputs 18
8.2. Annotated PK TFLs 1
8.3. PK TFLs Checklist 1
8.3.1. Individual data handling in listings 1
8.3.2. Individual plots 1
8.3.3. Descriptive statistics in tables 2
8.3.3.1. Statistics in the presence of BQL data 2
8.3.4. Individual data handling in summary tables 2
8.3.5. Mean Plots 3
8.3.6. Formats for individual data and statistics 3
9. Example SAP Language 4
9.1. Data to be analysed 4
9.2. Pharmacokinetic methods 4
10. References 5
11. Acknowledgements 6
List of Tables
Table 61 Symbols and definition of terms used in single and multiple dose NCA 12
Table 62. Main qualifiers for the determination of PK parameters. 13
Table 63 Main formulas for calculation for PK parameters 14
List of Figures
Figure 61 Reporting workflow for pharmacokinetic data 8
Figure 62 Process map for the creation of SDTM and ADaM PK datasets 10
Figure 81. Shell for individual PK concentration listing 1
Figure 82. Shell for individual PK concentration listing 3
Figure 83. Shell for overlaying PK concentration-time profiles 4
Figure 84. Shell for overlaying PK concentration-time profiles 6
Figure 85. Shell for overlaying PK concentration-time profiles 8
Figure 86. Shell for summary of PK parameters 10
Figure 87. Shell for summary of PK concentration 12
3. Revision History
Version 1.0 was finalized xx XXXX 201x.
4. Purpose
Under CDISC, standards have been defined for data collection (CDASH), tabulation (SDTM), and analysis (ADaM) datasets. The next step is to develop standard tables, figures and listings. The Development of Standard Scripts for Analysis and Programming Working Group is leading an effort to create several white papers providing recommended analyses and displays for common measurements, and has developed a Script Repository as a place to store shared code.
The purpose of this white paper is to provide advice on displaying, summarizing, and/or analyzing measures of pharmacokinetic (PK) data in clinical trials. The intent is to begin the process of developing industry standards with respect to analysis and reporting for PK concentrations and non-compartmental PK parameters that are common across clinical trials. In particular, this white paper provides recommended processes for:
· the calculation of PK parameters using non-compartmental analysis (NCA),
· the production of PK listings, tables and figures for inclusion in clinical study reports, and
· the definition of statistical analysis plans (SAP) for PK data
Separate white papers address other types of data.
Model-based PK analyses are considered out-of-scope for this white paper.
This advice can be used when developing the analysis plan for individual clinical trials in which PK data are of interest. Although the focus of this white paper pertains to clinical trials where intense PK sampling is made, some of the content may apply to trials where only sparse samples are collected. Similarly, although the focus of this white paper pertains to clinical trials, some of the content may apply to pre-clinical studies where PK is being assessed.
Development of standard Tables, Figures, and Listings (TFLs) and associated analyses will lead to improved standardization from collection through data storage. (You need to know how you want to analyze and report results before finalizing how to collect and store data.) The development of standard TFLs will also lead to improved product lifecycle management by ensuring reviewers receive the desired analyses for the consistent and efficient evaluation of patient safety and drug exposure. Although having standard TFLs is an ultimate goal, this white paper reflects recommendations only and should not be interpreted as “required” by any regulatory agency.
Detailed specifications for TFL development are in the scope of this white paper. The hope is that code (utilizing SDTM and ADaM data structures) will be developed consistent with the concepts outlined in this white paper, and placed in the publicly available FDA/PhUSE Standard Scripts Repository.
5. Introduction
Industry standards have evolved over time for data collection (CDASH), observed data (SDTM), and analysis datasets (ADaM). There is now recognition that the next step would be to develop standard TFLs for common measurements across clinical trials and across therapeutic areas. Some could argue that perhaps the industry should have started with creating standard TFLs prior to creating standards for collection and data storage (consistent with end-in-mind philosophy), however, having industry standards for data collection and analysis datasets provides a good basis for creating standard TFLs.
The beginning of the effort leading to this white paper came from the FDA computational statistics group (CBER and CDER). The FDA identified key priorities and teamed up with the Pharmaceuticals Users Software Exhange (PhUSE) to tackle various challenges using collaboration, crowd sourcing, and innovation (Rosario, et. al. 2012). The FDA and PhUSE created several working groups to address a number of these challenges. The working group titled “Development of Standard Scripts for Analysis and Programming” has led the development of this white paper, along with the development of a platform for storing shared code. Most contributors and reviewers of this white paper are industry statisticians, with input from non-industry statisticians (e.g., FDA and academia) and industry and non-industry clinicians. Hopefully additional input (e.g., other regulatory agencies) will be received for future versions of this white paper.
There are several existing documents that contain suggested TFLs for PK measurements. However, many of the documents are now relatively outdated, and generally lack sufficient detail to be used as support for the entire standardization effort. Nevertheless, these documents were used as a starting point in the development of this white paper. The documents include:
· ICH E3: Structure and Content of Clinical Study Reports
· ICH E7, Studies in Support of Special Populations: Geriatrics
· US: Guideline for Industry: Structure and Content of Clinical Study Reports
· US: Study and Evaluation of Gender Differences in the Clinical Evaluation of Drugs
· US: General Considerations for Pediatric Pharmacokinetic Studies for Drugs and Biological Products (draft)
· US: Pharmacokinetics in Patients with Impaired Renal Function: Study Design, Data Analysis and Impact on Dosing and Labeling
· US: Pharmacokinetics in Patients with Hepatic Insufficiency: Study Design, Data Analysis and Impact on Dosing and Labeling (draft)
· US: In Vivo Metabolism/Drug Interactions Studies: Study Design, Data Analysis and Recommendations for Dosing and Labeling (draft)
· US: Population Pharmacokinetics
· US: Exposure-Response Relationships: Study Design, Data Analysis, and Regulatory Applications
· Japan: Clinical Pharmacokinetic Studies of Pharmaceuticals
· EU: Pharmacokinetic Studies in man
· EU: Questions & Answers: Positions on specific questions addressed to the EWP therapeutic subgroup on Pharmacokinetics
· EU: Clinical Investigation of the Pharmacokinetics of Therapeutic Proteins
· EU: Points to Consider on Pharmacokinetics and Pharmacodynamics in the Development of Antibacterial Medicinal Products
These guidance documents present high-level requirements for the collection, analysis and presentation of PK results in a variety of clinical trials. They do not provide, however, detailed information that would enable to standardize the presentation of PK results. This white paper tries to fill this gap and provides a set of standard rules and checklists to standardize the production of PK TFLs in clinical trials.
6. General Considerations
6.1. Reporting workflow
The general workflow for the analysis and reporting of PK data in clinical trials involves two major steps, as outlined in Figure 61:
1. Calculation of pharmacokinetic parameters
2. Production of PK TFLs
For each step, we shall define in subsequent sections, a checklist of standard rules that need to be followed. The SDTM to ADaM mapping for PK concentrations (PC) and parameters (PP) will also be discussed.
Figure 61 Reporting workflow for pharmacokinetic data
6.2. CDISC PK datasets creation workflow
According the recommended CDISC process, SDTM Pharmacokinetic Concentration (PC) data, SDTM Pharmacokinetic Parameter (PP) data, ADaM Pharmacokinetic Concentration (ADPC) data and ADaM Pharmacokinetic Parameters (ADPP) are created based on SDTM/ADaM structure data, clinical data, bioanalytical data and the derived PK parameters calculated by scientists. Then, all the related listings, tables and figures can be generated based on ADPC and ADPP data sets.
The general process for creating SDTM and ADaM PK-related datasets is summarized in Figure 62.
Figure 62 Process map for the creation of SDTM and ADaM PK datasets
It works as follows:
1. First, SDTM PC dataset is created based on SDTM structure dataset, clinical datasets, and bioanalytical dataset.
2. Second, based on the ADaM structure dataset, SDTM PC dataset and ADaM ADSL(Subject Level Analysis Dataset) are merged to create ADaM ADPC dataset. ADaM ADPC dataset supports PK parameters calculation. It also provides information to create PK concentration tables and figures.
3. Third, using specific software for non-compartmental analysis such as SAS or WinNonlin, PK parameters are calculated from ADaM ADPC. A derived dataset is created including all these calculated PK parameter information, and SDTM PP dataset is created based on this dataset.
4. Fourth, ADaM ADPP dataset is created based ADaM structure dataset and SDTM PP. ADPP dataset is the PK analysis dataset which is used for producing summary tables, statistical tables, and any other PK analysis.
7. Calculation of PK parameters
7.1. Main derived PK parameters
In Table 61, we present the main PK parameters and terms used for the non-compartmental analysis (NCA).
Table 61 Symbols and definition of terms used in single and multiple dose NCA
Symbol / DefinitionAa / Total amount of drug excreted in expired air
Ae / Total amount of drug excreted in urine
Ae(t1-t2) / Amount of drug excreted in urine from t1 to t2
Aet / Amount of drug excreted in urine over a dosing interval
Af / Total amount of drug excreted in feces
Af(t1-t2) / Amount of drug excreted in feces from t1 to t2
At / Total amount of drug excreted in expired air, feces and urine
AUC / Area Under the Curve from 0 to infinity
AUC(0-t) / Area under the curve from 0 to the time of the last quantifiable concentration
AUCextr / Extrapolated AUC
AUC(t1-t2) / Partial Area Under the Curve between t1 and t2
AUCt / Area Under the Curve over a dosing interval
AUMC / Area Under the first Moment Curve from 0 to infinity
BLQ / Below Limit of Quantification
Cav / Average concentration over a dosing interval
Clast / Last observed (quantifiable) concentration
CL / Total body clearance
CL/F / Apparent total body clearance
CLCR / Creatinine clearance
CLfm/F / Apparent Formation clearance of a metabolite
CLNR / Non-Renal Clearance
CLR / Renal Clearance
CLss/F / Apparent Total body clearance at steady state
Cmax / Maximum concentration
Cmin / Minimum concentration over a dosing interval
C(t) / Drug concentration at any time t
Ctrough / Measured concentration at the end of a dosing interval at steady state
D / Dose
F / Absolute bioavailability. F= fD x fA x fI x fH where fD, fA, fI and fH
represent the fraction dissolved, the fraction absorbed, the fraction
escaping intestinal first pass and the fraction escaping liver first
pass respectively
Frel / Relative bioavailability
fe / Fraction of the dose excreted (urine by default, add qualifier
for other fluids)
lz / First order terminal elimination rate constant or
Apparent first order terminal elimination rate constant, for
compounds presenting release/absorption as limiting steps
LF / Linearity Factor
LOQ / Limit of Quantification
MRT / Mean Residence Time
PD / Pharmacodynamic(s)
PK / Pharmacokinetic(s)
PTF / Peak to trough fluctuation
R / Accumulation ratio
Swing / Percentage of swing
t / Dosing interval
Tinf / Infusion duration
tlag / Time delay between drug administration and the first measurable
(quantifiable) concentration.
tmax / Time of Cmax
t½ / Terminal elimination half-life or
Apparent terminal elimination half-life, for compounds presenting
release/absorption as limiting steps
Vss / Volume of distribution at steady-state
Vur / Volume of urine
Vz / Volume of distribution
Vz/F / Apparent volume of distribution
CLHD / Hemodialysis clearance
CLD / Dialysis clearance or dialysance
CLUF / Ultrafiltration clearance
E / Extraction coefficient
Fr / Fractional removal
QP / Plasma flow through the dialyzer
QUF / Ultrafiltration flow rate
Additional qualifier may be used when parameters need to be further defined for clarification purpose. They are often inserted as subscript. By default, the matrix will in general be plasma. A non-exhaustive list of qualifiers is presented in Table 62.
Table 62. Main qualifiers for the determination of PK parameters.
Matrices / Routes of administrationbl Blood
csf Cerebrospinal fluid
fcs Feces
mlk Breast milk
p Plasma
rbc Red Blood Cells
sal Saliva
ser Serum
ur Urine / im Intra-muscular
nas Intra-nasal
iv Intravenous
po Per os
rec Rectal
sc Subcutaneous
sbl Sublingual
top Topical
Dosing regimen / Binding
ss Steady-state
dayx If multiple administration, this qualifier can be used to specify the day at
which the parameter is calculated / b Bound
u Unbound
The formulas used for the calculation of the main PK parameters by NCA are presented in Table 63, below.