Pharmacoeconomics & Health Outcomes
Pharmacoeconomics & Clinical Trials
Pharmacogenomics
Leon E. Cosler, R.Ph., Ph.D.
Associate Professor of Pharmacoeconomics
Albany College of Pharmacy
Road Map
• PE in the clinical trial process
- Unique characteristics to consider
- Ch. 11
• PE and the impact of Pharmacogenomics
- Key definitions and applications
- The costs & effectiveness issues
- Ch. 10
Clinical Trials & Drug Marketing
• Safety & Efficacy
• 2+ clinical trials
• (economics and outcomes not addressed)
• FDAMA 1997
• Sect. 114 standards for economic info.
• New: “competent & reliable evidence”
• OLD: “… from well controlled clinical trials..”
• “widely accepted by experts”
• specific standards never published
Important criteria to consider in RCTs
1. Benchmarks
3. Study design
4. Data Management
5. Analysis / Interpretation
7. Reporting Results
Important PE criteria
1. Benchmarks
• Baseline epidemiology needed
• Natural course of disease
• Burden on society
- Economic burden may be different
• Factors which affect QOL
• Factors which affect patient satisfaction
• Baseline resource use needed
Important PE criteria
2. Study design
• Need to plan along with RCT design
• PE objectives stated early in design
- Primary goal or secondary “ad-hoc”
- Pivotal Phase III vs Phase IV
• Multiple perspectives sometimes needed
• Resource use inside RCT artificial *
• QOL indicators may not be generalizeable
either…
Important PE criteria
2. Study design
• Sample sizes may need to be adjusted
• Clinical parameters may be insufficient
• QOL instruments selected
> General +/- Dx specific often used
- Respondent burden a consideration
Important PE criteria
3. Data Management
• Most RCT data collected from providers
• Some PE data needed from patients
> caregivers and / or parents
• Where to survey?
> office or at home?
> “team” answers
• Frequency
> baseline and final
> more frequently
• Methods for handling missing data
Important PE criteria
4. Analysis / Interpretation
• Pre-specified analysis vs post-hoc
• ITT vs per-protocol
• Confounding variables
• Sensitivity analyses
• Multi-national studies
> Can’t combine economic or HRQOL data
Important PE criteria
5. Reporting Results
• k.i.s.s.
• Summary results not individual Pts.
• Address dropouts and effects
• Sensitivity and robustness of findings
• Pre-specified vs ad-hoc
• ITT vs per-protocol
• Multi-national
Pharmacogenomics
Key Terms
• Pharmacogenetics
- How genetic differences influence Pt.
responses to Rxs
• Pharmacogenomics
- Applying genetic traits for Dxs and Rx
metabolism to Tx management
- Assembling a comprehensive list of SNPs
- SNPs predict Rx efficacy & toxicity
Why do we care?
• ADRs
~ 5th leading cause of death in the U.S.
~ 70K to 100K preventable deaths per year
~ 2 million hospitalizations per year
$1.6B to $4.2B annually to resolve
• Differential Rx efficacy
- 30% of schizophrenics non-responsive
- Interferon B only helps 1/3 of MS Pts
- Chemotherapy responses vary widely
Why do we care?
• Wide dose variations
- propranolol doses may vary by 40x
- Warfarin doses may vary by 20x
- Simvastin dose-dependent
• (~6% no response)
• Narrow Tx window Rxs
- gentamicin
- digoxin
- cyclospirine
What do we know?
• Genetic differences explain metabolism
(normal / wild type genotype)
PM EM UEM
• PM (Poor Metabolizers)
• Prolonged Rx effects
• Toxic ADR
• UEM
• No Tx effects at normal doses
• Toxicity from excessive metabolites
Warfarin Pharmacogenomics
• Polymorphisms in
CYP2C9 influence
drug metabolism
• Polymorphisms in
VKORC1 affect
response
• Should genotype
testing be performed
to individualize
warfarin dosing?
How are costs of care affected?
• Increased • Decreased
- Cost of testing - More drugs approved?
- Cost of add’t appts - Targeted population
- False + and - - Fewer Tx failures
- Low prevalence - Fewer ADRs *
- Rx R&D - Fewer labs needed?
• Old Rxs - 1-time genetic profile
• New biologics
What about Effectiveness?
• Increased • Decreased
- Target responsive Pts - Less effective Txs ?
- High Sensitivity - Weak relationship fit
- High Specificity phenotypes
- Strong relationships
with phenotypes
What about the cost-effectiveness?
• When it’s less expensive
• and maintains or increases effectiveness
OR
• If its more expensive…
• and the gain in effectiveness is worthwhile
• Check out Table 2. Chapter 10
Impact on Clinical Trials
• Positives:
• More drugs may make it through
• Smaller sample sizes
• Faster & cheaper…
• Negatives
• Patients excluded from trials
• Results generalizeability
• New drugs with smaller potential markets
Implications
• Improved treatment outcomes
• Maximize Rx effects
• Reduce / eliminate ADRs
• Improved Pt. adherence?
• Reduce unnecessary Txs and tests
• $750M based on False + PSA test
• unnecessary biopsies
• Ethical issues
• Racial stereotyping?
• Should payers have access to this data?
Drugs and the Human Genome Project
“In the future we may all carry a 'gene
chip assay report' that contains our
unique genetic profile that would be
consulted before drugs are
prescribed…”
That’s (almost) all for today… !
