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Impact of Exploratory Analysis on Drug Approval. Joga Gobburu Pharmacometrics Office Clinical Pharmacology, CDER, FDA. jogarao.gobburu@fda.hhs.gov. Take Home Message. Exploratory (e.g., pharmacometric) analyses are often used to make regulatory decisions
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Impact of Exploratory Analysis on Drug Approval Joga Gobburu Pharmacometrics Office Clinical Pharmacology, CDER, FDA jogarao.gobburu@fda.hhs.gov
Take Home Message • Exploratory (e.g., pharmacometric) analyses are often used to make regulatory decisions • Decisions are not entirely driven by the pre-specified statistical analysis • Need for change • Integrate strengths of both approaches • Think “How exploratory analyses can help drug development?” • Opportunities for collaboration between pharmacometricians and statisticians are abundant • Think about “How can I facilitate this collaboration?”
Pharmacometrics (or Quantitative Experimental Medicine?) • Science that deals with quantifying disease and pharmacology • Applications • Benefit/Risk, dose individualization, trial design • Diverse expertise • Clinical pharmacologists, Pharmacometricians, Clinicians, Statisticians, Bioengineers • Tools • Linear/Nonlinear Mixed effects models, Longitudinal data analysis, Biological models, Stochastic simulations
Impact of Exploratory Analyses 2000-2004 Pivotal: Regulatory decision will not be the same without PM reviewSupportive: Regulatory decision is supported by PM review Bhattaram et al. AAPS Journal. 2005; 7(3): Article 51. DOI: 10.1208/aapsj070351
Pivotal: Regulatory decision will not be the same without PM reviewSupportive: Regulatory decision is supported by PM review Impact of Exploratory Analyses 2005-2006 DCP=Division of Clinical Pharmacology @=survey pending in 1 case
NDA Case Study • Drug is proposed for a ‘rare’ debilitating, fatal disease with no approved treatment. • One trial successful and other failed • Failure likely due to trial execution errors • Potential miscommunication about dose timing • Primary variable: Change in symptom score • Key question • Is there adequate evidence for the effectiveness?
Equivocal Evidence of EffectivenessPivotal Studies DB#1 Dbl-blind (DB) Randomized PBO Controlled Dose Titration N=75 P<0.051 (withdrawal) Agency at this point can ask for more evidence (one or more studies) OR Investigate further across the clinical trial database whether there is a consistent signal of effectiveness or not DB#2 Dbl-blind (DB) Randomized PBO Controlled Dose Withdrawal N=30 P>0.051 1change in score at the end of study
Equivocal Evidence of EffectivenessPivotal + Other Studies DB#1 Dbl-blind (DB) Randomized PBO Controlled Dose Titration N=75 P<0.05 (withdrawal) OL-1 Open label (OL) Withdrawal Dose Titration N=75 DB#2 Dbl-blind (DB) Randomized PBO Controlled Dose Withdrawal N=30 P>0.05 OL-2 Open label (OL) Continue ‘old’ dose N=30
Significant Dose-Response Relationship – DB1, OL1 * p<0.001 Linear mixed effects model employed Estimate of dose-response slope is similar for individual and combined analyses. Results from combined shown here.
Value of Exploratory Analysis • To Patients/FDA • Availability of drug sooner, especially given no approved treatments (debilitating disease) • Efficient solution to challenging patient enrollment • Fewer review cycles (because of this issue alone) • Ultimately might lead to lower drug costs • To Sponsor • Alleviated the need for additional trial(s) to demonstrate effectiveness • Save $$ and time • Pharmacometrics analyses can and do influence approval decisions!
Why did the sponsor not consider making a similar case? Unlikely Unlikely • Unanticipated concern • Lack of expertise (both technical, strategic) • Prescriptive behavior on analysis • Unclear expectations from FDA Likely Likely
Parkinson’s DiseaseCollaboration between Statistics and Pharmacometrics Dr. Bhattaram and Dr. Siddiqui are the project leads with the following team members: FDA Statistics, Clinical, Policy Makers External Statistician, Disease experts
Symptomatic or Protective? Placebo Drug A Drug B
Symptomatic or Protective? Placebo Drug A Drug B
Drug Placebo Protective Drug Discern Symptomatic vs. Protective Effects: Delayed Start Design • Key Questions: • Endpoint ? • Analysis ? • Handling missing data? Placebo Phase Active Phase If drug is protective then patients who received drug longer will have lower scores compared those who receive drug late.
Selegiline ( 5 years) Published Data Mean (SD) of Total UPDRS scores for patients with Parkinson’s disease treated with levodopa alone or in combination with selegiline for 5 years and during the one-month washout period Eur.J.Neurology, 1999, 6: 539-547 The vertical line represents 2 months
Patients with slower progression remain longer in clinical trials (TEMPO) Fraction Remaining
Value of Collaboration between Pharmacometrician, Statistician • Statistician’s Contribution • Primary statistical analysis • Drop-outs • Trial design • Power calculations • Pharmacometrician’s/Disease Expert’s Contribution • Biological/Mechanistic Interpretation • Disease Progression • Drug Effects • Drop-outs • Trial design, alternative analysis
Value of Exploratory Analyses • Collected a large database of clinical trials • Extracted patient population, placebo/disease progression, drug effect (not shown) and drop-out information. • Simulations to answer the key questions mentioned earlier are in progress • Directly useful to advice sponsors • Conference planning is underway Disease Models Background: http://www.fda.gov/ohrms/dockets/ac/06/briefing/2006-4248B1-04-FDA-topic%203%20replacement.pdf
Take Home Message • Exploratory (e.g., pharmacometric) analyses are often used to make regulatory decisions • Decisions are not entirely driven by the pre-specified statistical analysis • Need for change • Integrate strengths of both approaches • Think “How exploratory analyses can help drug development?” • Opportunities for collaboration between pharmacometricians and statisticians are abundant • Think about “How can I facilitate this collaboration?”