This document discusses issues in trial design and analysis for precision medicine products regulated by CBER. For autologous products, manufacturing failures or delays can impact study power and interpretation by affecting eligibility or disease progression during the trial. Example trials are discussed. For companion diagnostic products, basic study designs like randomize-all or marker-stratified are recommended, with statistical testing across groups using alpha adjustment strategies to control false conclusions of efficacy. Methods for testing efficacy in marker-positive subgroups and overall populations are also discussed.

1. Issues in Trial Design and Analysis of
CBER Precision Medicine Products
Shiowjen Lee, PhD
Office of Biostatistics and Epidemiology
Center for Biologics Evaluation and Research
US Food and Drug Administration
SAMSI Workshop, August 13, 2018
Disclaimer: This presentation reflects views of the presenter and
should not be construed to represent FDA’s view or policies

2. 2
Brief Background
 CBER products with precision medicine
implications:
 Autologous products
 Companion diagnostics products
e.g. inclusion of development of a testing tool for
selection of pts to be treated with an investig.
biologic product

3. 3
Brief Background (cont.) – Autologous Prod.
e.g., CAR-T Therapy manufacturing process
Source: ODAC on July 12, 2017
Cancer Gene Therapy (2015) 22, 79–84
Vector

4. 4
Brief Background (cont.)
 Companion diagnostic products
 Two components
 Investig. biologic product
 Marker test to select pts to be treated
 Ideally
 Marker with biological basis and validated
 Clear cut-point to differentiate M+ and M−
pts

5. 5
Challenges/Issues – Autologous Product
Manufacturing issues
 Manufacturing failure (none or insufficient
product)
Consequence:
a. Affect efficacy outcome, e.g. insufficient prod.
b. Impact study power (in addition to missing obs
or/and delayed effect during trial)

6. 6
Challenges/Issues – Autologous Prod. (cont.)
Manufacturing issues
 Time to completion of product manufacture
a. Subj became ineligible/progression
b. Subj ineligible/progression followed in the study,
but allow to receive other therapies outside study
Consequence:
a. Affect study power
b. Impact interpretation

7. 7
Example – Autologous
Autologous vaccine
Phase 3 study:
– Control: SOC
– Primary endpoint: progression-free survival (PFS)
– Intent-to-treat (ITT) specified as the primary
 Product mfg:
– Length: ~5-10 months

8. 8
Example (cont.): Design Schema and Enrollment
Assess
CR/CRu
BiopsyChemo
Randomize
1:1 Vaccine
Control
5 to 10 Months
Vaccine Production
8 Months
Treatment
350
300
Randomization 150 150
Subjs ineligible/progress
100
95
Start Here

9. 9
• Data analyses of mPFS:
– Inclusion: 25 vs 23 month for V vs C
– Exclusion: 45 vs 30 month for V vs C
• > 30% of subjects became ineligible/progression
• Two sets of analyses different
Example (cont.)
9

10. 10
Example (cont.)
PFS for all randomized subj
proportional hazard
assump. not met

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Companion Diagnostic Product – Basic Study Design
A. Randomize-All design:
B. Marker-Stratified design:
C. Enrichment design:

12. 12
CBER Companion Diagnostic Submissions
 Marker validation and Phase 3 trials concurrently
 Recommend randomized-all or marker-stratified design
 Statistical testing among groups using alpha
adjustment* strategy
*To control overall rate of erroneously concluding trt efficacious when in fact product
isn’t

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Statistical Testing: M+ vs. Overall
Two common statistical testing strategies:
 Hierarchical order testing M+ pts first (use α = 0.05)
then overall (α = 0.05) OR
 Allocate
M+ pts Trt shown benefit (stat. sign.)
Overall Trt shown benefit (stat. sign.)
Q: Label for overall?



=
+=
04.0
01.0
overallfor
ptsMfor
α
α

14. 14
Summary
 Autologous products:
How to account for manufacturing issues into design
and analysis?
 Companion diagnostic products:
What to consider in statistical testing of benefits in M+
and overall pop. to warrant labeling of overall pop?