Modeling and Simulation: Tool for Optimized Drug Development

1
Modeling and Simulation Tool for Optimized
Drug Development

• Martin Roessner
• Biostatistics sanofi aventis
• Bridgewater, NJ

2
Outline

• Background
• Modeling and Simulation (MS) approach
• Clinical Utility Index (CUI)
• Example SERM
• Conclusion

3
Industry challenge

• Drug development process not much changed over
  the last 25 years
• Drug development cost continue to increase (802
  Mill )
• Time to market, attrition rates and the number of
  late stage failures remain unchanged
• The industry needs to radically rethink the drug
  development process to remain competitive
• The industry needs to work smarter not harder

4
Modeling and Simulation is a tool for
quantitative decision-making

• It is a methodology that uses mathematical/statist
  ical models and simulations in a predictive
  manner
• MS provides an integrated framework to use this
  information to optimize the drug development
  process

Preclinical Information PK/PD data Dose response information Clinical outcome data (safety/efficacy) Prior information Historical data, information on related compounds, SBOAs, EPARs, etc. Marketing and Financial projections
5
Implementation of MS

• Development and broad adoption of MS will help
  create value
• Benefits
• Optimized development strategies
• Early termination of unpromising compounds
• Reduction in late stage attrition
• Shorter development time earlier to approval and
  launch
• Increase number of drugs to market
• Enhanced labeling
• More accurate and dynamic risk assessment along
  the development

6
Integrated modeling and simulation can be used
any time there is an important question impacting
project value
Is it worth developing a new dosage form?
Whats the best dose and schedule?
Should we continue this development program?
What is the optimal patient population for this
drug?
Is there a clinical trial design that will show
PoC and find the best dose?
Whats the probability of success in Phase 3?
Is this treatment likely to be as good as the
competitors?
Which indication should we go into first to
maximize the value of the program?
Should we in-license this compound?
What are the most important attributes of a 2nd
generation compound?
7
A modeling approach to decision-making involves
integration of information from a number of
sources
8
A modeling approach to decision-making involves
integration of information from a number of
sources
9
Clinical Utility Index (CUI) - a metric for the
benefit of treatment to the patient (1)

• Every drug has benefits and risks.
• The relative importance of these characteristics
  depend on the disease the drug is intended to
  treat
• They also change with dosage, patient population,
  etc.
• Trade-offs must often be made among the drug
  effects comprising the product profile, balancing
  the benefits and risks.

10
Clinical Utility Index (CUI) - a metric for the
benefit of treatment to the patient (2)

• The CUI quantifies trade-offs by providing a
  single metric for the multiple dimensions of
  benefit and risk.
• It is
• a systematic approach to understand subjective
  preferences
• a transparent way of weighing tradeoffs
• knowledge-driven available data are used if not
  available, rely on expert opinion
• closely related to the Target Product Profile
• It is not
• an objective measure in the sense of a
  physiological measurement

11
The framework for the CUI is elicited from the
project team when combined with models of
response, it provides a relative estimate of the
patient benefit
Identify Metrics
Identify Critical
Assign
and Relevant
CUI
Treatment
Preference
CUI Distributions for
Response
Attributes and
Values for each
Framework
Competing Treatments
Levels for each
Relative Weights
Response Level
Attribute
1
A
E(CUI )
A
P(CUI lt X)
E(CUI )
B
B
Treatment-
0
Response
CUI
Models
Probability of
Estimated
Here, treatment B is
Individual
Product
expected to be superior to A
Attribute Levels
Profile
Expert Opinion
12
Example

• SERM, a Selective Estrogen Receptor Modifier for
  the Treatment of Osteoporosis in Post-Menopausal
  Women
• Two Phase II studies
• 1. Placebo, SERM (2.5mg, 10mg, 50mg) and
  Raloxifene, n118
• 2. Placebo, SERM (0.5mg, 5mg) n79
• Primary efficacy endpoint was change from
  baseline U-CTX
• Included additional safety and activity endpoints
• How does the efficacy, safety and tolerability of
  SERM compare with its major competitor drug and
  at which dose
• Explorative analysis
• Clinical Utility Index (CUI)
• Simulation results and sensitivity analysis
• Is it worthwhile to continue development

13
Possible responses and their clinical value for
each attribute were defined
Attribute Responses Preference Ratio
Efficacy on Bone Worse than Raloxifene Equivalent to Raloxifene Better than Raloxifene 1 10 20
Endometrial Proliferation Worse than Raloxifene The same or better than Ralox. 1 30
Endometrial Lining Thickness Worse than Raloxifene The same or better than Ralox 1 5
Cardiovascular Smaller effect on LDL than Ralox Same or larger effect on LDL vs. Ralox. Same effect on LDL effect on HDL 1 7.5 15
.. .. ..
Food Effect on PK Presence of food effect Absence of food effect 1 2
14
Important attributes were ranked and their
importance weighted
Attribute Rank Rating Relative Weight
Efficacy on Bone 1 100 0.27
Endometrial Proliferation 1 100 0.27
Endometrial Lining Thickness 3 50 0.14
Thromboembolic Disease 4 40 0.11
Hot Flashes 5 30 0.08
Breast Tenderness 6 15 0.04
Cardiovascular 7 10 0.03
Muscle Cramps 7 10 0.03
Atrophic Vaginitis 7 10 0.03
Food Effect on PK 10 5 0.01
15
Models of dose-response provided estimates of
attribute level and uncertainty in these estimates
Dose-Response for Urinary CTX(measure of bone
turnover)
Baseline-adjusted week-12 Difference from
Placebo

• Clear dose response
• Log-Linear model adequately describe available
  data

16
Major Result There was no dose for which SERM
was expected to be considered equivalent or
superior to Raloxifene
60
Based on CUI and simulated drug response
CUI for Raloxifene
50
40
Clinical Utility Index
30
20
10
0
0.25
0.5
1
2.5
5
10
SERM Dose (mg)
17
What if.
If SERM did not cause endometrial proliferation,
available data support effects of SERM would be
similar or better at doses of 1 mg and higher
100
SERM
similar to Raloxifene i.e. no endometrial
proliferation
80
60
Clinical Utility Index
Raloxifene
40
20
0
0.25 mg
0.5 mg
1 mg
2.5 mg
5 mg
10 mg
SERM Dose
18
Impact Further development of SERM was halted,
saving 50-100M in development costs
SERM fails to show equivalent clinical utility to
Raloxifene at all doses examined Based on that
simulation, we stopped funding development of
the compound, says Frank Douglas the ratio
between the therapeutic benefit and the side
effect demonstrated that this compound was not
as beneficial as Evista. Douglas estimates
that the computer model saved the company 50
million to 100 million, the cost of later-stage
clinical trials. We also avoided exposing a lot
of women to a drug that ultimately would have
failed, he adds. And we were able to switch to
another project with a greater chance of
success.
Forbes
10/7/02
19
Conclusion

• Industry needs to operate smarter
• MS provides a framework to optimize drug
  development at various levels
• Clinical Utility Index can be used to assess the
  potential success of a product in the market

20
Acknowledgement

• B. Korsan, K. Dykstra, T.J. Carrothers
  (Pharsight)