1. Michael O’Kelly, Centre for Statistics in Drug Development, Innovation
Promoting high-quality and informative exploratory development: obstacles and aids
Michael O’Kelly, Centre for Statistics in Drug Development, Innovation

4. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money

5. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money
“We’ve developed
a similar treatment
with these study sizes before –
your calculations must be wrong”
Take account of the
variability in your assumptions –
but isn’t that Bayesian?
Phase III, same
calculation as
phase II?
sample size

6. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money
Senn and Julious, 2009,
Measurement in clinical trials,
Statistics in Medicine
Responder,
required in
obesity, diabetes, PD, depression....
Percentage
increase
from baseline
endpoints
Fixed “adjustment”
of e.g. QTc, CCI

7. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money
I heard adaptive
designs are great. Let’s
try one right now.
“We can’t afford
the original design –
use an adaptive design instead”
“Use a dose-response curve? But we like having proof of a working dose.”
study
design
But people don’t
usually use log
response
here...
Two doses
worked
for the KOL...

8. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money
“...he must either
destroy himself
or the whole theory
of probable errors”
1922: Fisher identifies the
correct degrees of freedom for
Pearson’s chi-squared
Pearson: “erroneous...the writer has done no service to statistics by giving it broad-cast circulation in the pages of the JRSS...”
Fisher could not
get his rebuttal
published in the
JRSS

9. Obstacles to informative exploratory development
precedent
when clinical - quantitative questions overlap
money
Mixed models
repeated measures
LOCF
This statistical
approach got
approval last time
Bonferroni
and robust models?

11. Aids to informative exploratory development

12. Aids to informative exploratory development
High level executive support for quantitative approach
Continuous education
Better communication
A requirement for one company’s effort to reform trial design: “exhibit desirable behavioural characteristics and communication skills”
Modelling and simulation – an aid to communication
case study

13. Case study: how modelling and simulation helps
partnership arrangement, CRO with sponsor
multifunctional team responsible for development of treatment, MOA not well known
phase IIa small dose escalation study
phase III large two-arm study
phase IIb design that fits with these to get the best dose approved?
lean, two-arm phase IIb study submitted to regulator
alternatives?

14. Case study: how modelling and simulation helps
partnership arrangement, CRO with sponsor
multifunctional team responsible for development of treatment, MOA not well known
phase IIa small dose escalation study
phase III large two-arm study
phase IIb design that fits with these to get the best dose approved?
lean, two-arm phase IIb study submitted to regulator
difficult for team to get handle on risks and benefits of other designs
“get handle on”:
explore, think about, become familiar with, feel some confidence in, talk freely about, lose fear of...
many possible scenarios
scenarios: plausible safety and efficacy profiles across doses

15. Scenario analyses Scenarios to cover best cases…
… through to worst cases

16. Case study : how modelling and simulation helps
Modelling and simulation helped the multifunctional team to think and talk about alternative designs in a quantitative way
team discussed simulation of 1st strategy (1 dose in phase IIb),
->led to 2nd strategy: 4 doses in phase IIb – team discussion of new simulation
->led to 3rd strategy: 2 doses in phase IIb – team discussion of new simulation
->led to 4th strategy: adaptive design 4 doses, select 2
Modelling an entire program allows complex implications to be thought of in graspable terms
implications of the study design
of the statistical model
of the statistical analysis
of plausible potential quirks or irregularities in the efficacy or safety of the doses of the treatment

17. Problems with simulations...
often the results depend heavily on the assumptions
resource-intensive
quality control of simulations rarely described
difficult to prove wrong!
E.g. current “contest of the methods” in dose-finding, PhRMA group and others
Kirby, Colman, Morris, 2009, “Dose response...using smoothing splines”, Pharmaceutical Statistics
“Although not explicitly stated the results for the Dopt method in the PhRMA paper are for a logistic model with a polynomial trend (Dmitrienko, personal communication).”

18. Simulations: what can we do?
collaborative approach to simulation
shared “machinery”
like-for-like comparisons => more rapid discovery of real improvements in study design
e.g. Pfizer MStoolkit software available in R
PSI new special interest group (SIG) for Modelling and Simulation
meeting tomorrow at Amgen in Cambridge !
( Vincent Haddad at
all welcome to attend (numbers limited)

19. Questions?

20. Backup slides: details of the case study results

21. Strategy #1: original plan
Phase IIa
Phase IIb
Phase III
Active
Active
Active dose
500
subjects
500
subjects 12 12 12 12 6 6 6 6
Placebo
500
subjects
500
subjects
Placebo
Placebo

22. Strategy #2: statisticians’ idea: use many doses in IIb
Phase IIa
Phase IIb
Phase III
Active
Active
Active dose
200
200
200
200
500 12 12 12 12 6 6 6 6
Placebo
200 20
500
Placebo
Placebo

23. Strategy #3: team came back with a “less radical” design
Phase IIa
Phase IIb
Phase III
Active
Active
Active dose
333
333
500 12 12 12 12 6 6 6 6
Placebo
333
500
Placebo
Placebo

24. Strategy #4: the virtues of #2 and #3? Adaptive design
Phase IIa
Phase IIb part 1
Phase III
Active
Active
Active dose
100
100
100
100
500 12 12 12 12 6 6 6 6
Placebo
100
500
Placebo
Placebo

25. Strategy #4: the virtues of #2 and #3? Adaptive design
Phase IIa
Phase IIb part 2
Phase III
Active
Active
Active dose
260
260
500 12 12 12 12 6 6 6 6
Placebo
260
500
Placebo
Placebo

26. Scenario analyses
Scenarios to cover best cases…

27. Scenario analyses Scenarios to cover best cases…
… through to worst cases

28. Scenario analysis results – Phase III success
Scenarios with viable doses

29. Scenario analysis results – Phase III success
Scenarios with viable doses

30. Scenario analyses results – stopping in IIb
Scenarios with no viable doses