Transcript Bhore Derr Handout 9-29

Improving FDA/Industry Interactions:
Suggestions from FDA/CDER Statisticians
Rafia Bhore, Ph.D.
Janice Derr, Ph.D.
FDA / CDER / Office of Biostatistics
The views expressed in this presentation are those of the
speakers and not necessarily of the U.S. Food and Drug
Administration (FDA).
1
CDER Office of Biostatistics
DB1
Cardiovascular & Renal; Neurological; Psychiatric
DB2
Pulmonary & Allergy; Metabolism & Endocrine;
Analgesics & Anesthetics
Gastrointestinal; Reproductive & Urologic; Dermatologic
& Dental
DB3
DB4
DB5
DB6
Anti-Infective & Ophthalmology; Anti-Viral; Special
Pathogen & Transplant
Oncology Biologics; Oncology Drugs; Imaging &
Hematology
Generic; Pharmacology & Toxicology; Chemistry &
Manufacturing; Safety; Special Projects & Clinical
Pharmacology
2
Communication Dynamics between
FDA and Industry
Chem
Pharm/
Tox
Micro
Clinical
Stats
Project Team
Clin
Pharm
Project Manager
Regulatory Affairs
3
Interactions During Drug Development
Clinical Start
Pre-clinical
Research
Pre-IND
Meeting
Phase I
NDA/BLA Submission
Phase II
EOP II
Meeting
Phase III
Pre-NDA
Meeting
NDA
Review
Labeling
Meeting
4
Good Meeting Management Practices
GMMPs Facilitate input from review disciplines
 Prior to internal meeting (draft responses to
industry questions)
 Internal meeting (preliminary comments to
sponsor)
 Formal meeting (moderated discussion)
 Follow-up (meeting minutes, further discussion)
5
Suggestions from CDER Statisticians
(Good Meeting Practices)
 Use a meeting with FDA as an opportunity to send
in questions about statistical issues
 Ask good questions that will give you useful
answers
 Provide sufficient detail to help us give useful
statistical review comments
 Use the channels of communication to get a
response from FDA statisticians about statistical
issues
6
Investigational New Drug Application
(IND) Stage
Special Protocol Assessment
Statistical Analysis Plans
7
Special Protocol Assessment
SPA Guidance 2002
 Sponsors can submit certain types of protocols
with specific questions prior to start of study
(Guidance recommends 90 days).
 FDA determines if SPA process applies to the
request, and if so, responds to questions within
45 days (PDUFA goal).
 Protocol agreements under SPA are part of the
administrative record. Regulations describe the
circumstances under which the agreements can
be changed.
8
Suggestions from CDER Statisticians
(Special Protocol Assessment)
 Ask good questions that will give you useful
answers
 Provide sufficient detail to help us give useful
statistical review comments
9
Statistical Analysis Plan (SAP)
 Prospective plan of statistical methods not detailed
in the Protocol
 Protocol details design considerations vs.
SAP details analysis considerations
 Design: Endpoints, type of control, planned
comparisons, multiple testing, interim analyses
 Analysis: Statistical models, handling of missing data,
nature of censoring, analysis populations, repeated
measurements over time, study windows, etc.
10
Suggestions from CDER Statisticians
(Statistical Analysis Plan)
 Statistical Analysis Plan (SAP) should be
detailed and prospectively written
 Prospectively submit to FDA for Phase 3
studies and Phase 2 supportive studies
 Open-label studies submit before study begins
 Blinded studies submit prior to last patient
enrolled or first interim analysis (whichever
comes first)
11
Suggestions from CDER Statisticians
(Statistical Analysis Plan contd.)
 Identify critical issues at protocol design
stage or at least Statistical Analysis Plan
writing
 Examples: adjustment for multiplicity, interim analysis plan, noninferiority evaluation, missing data, …
 Commercial Sponsors should encourage cooperative trialists to write a Statistical
Analysis Plan
12
New Drug Application
(NDA) Stage
Integrated Summary of Efficacy
Labeling
13
Integrated Summary of Efficacy
(Suggestions from CDER Statisticians)
 Important component of New Drug Application
Review
 Provide clinically meaningful and logically tight
argument whether drug has necessary evidence for
efficacy claim
 Provide side by side comparison of studies
 NOT necessarily pooled or meta-analysis of efficacy
 Discuss pooling study results with FDA
14
Integrated Summary of Efficacy
Example:
Can YoU PRove Efficacy and Safety of curevir (CURES)
Treatment Success Rate by Study and for Pooled Studies
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
41%
p-value
< p.0001
p-value
= .380
p-value
< .0001
29%
22%
15%
CURES 1 study
18%
CURES 2 study
20%
Test
Placebo
CURES
15
Statistical Input on Labeling Text
FDA Statisticians review labeling text:
 Statistical support for study conclusions, claims and
indications
 Description of study results, summary statistics and
inferential language
 Information in tables and figures
16
Labeling
Example #1:
Statistical Input
Provided
CLINICAL STUDIES
…
The NAGLAZYME-treated
group showed greater mean
increases in the distance
walked in 12 minutes (12minute walk test, 12-MWT)
and in the rate of stair
climbing in a 3-minute stair
climb, compared to the
placebo group (Table 2).
Labeling Example #2:
Statistical Input Needed
Proposed text: “The combination of A and B is
effective in lowering LDL-C levels beyond that
achieved by either agent alone.”
Statistical issue: The study was not designed to
support this conclusion. The study had two arms,
(A+B) combination product, and A monotherapy.
18
Labeling Example #3:
Statistical Input Needed
Proposed table: The symbol “*” was used for
p<0.05, and “**” was used to indicate no
statistically significant difference between the
active treatment arm and the placebo arm.
Statistical issue: This is not a typical way to depict
this outcome and may be confusing to some
readers.
19
Suggestions from CDER Statisticians
(Labeling)
 Provide your statistical perspective in the
development of labeling text.
Labeling Guidance, 2006:
Clinical Studies Section
Adverse Reactions Section
20
Improving Statistical Communication
Provide statistical
input at all stages
Chem
Micro
Stats
Pharm/
Tox
Clinical
Clin
Pharm
Ask good questions
Provide detailed,
timely information
Address critical
statistical issues
21
Acknowledgments
 FDA Statisticians from
 Divisions of Biometrics 1, Biometrics 2, Biometrics 3,
Biometrics 4, and Biometrics 5
 Industry Statisticians /Programmers
 for their promptness in responding to FDA questions!
22