DRUG TRIALS SNAPSHOTS. Milena Lolic, MD, MS Medical Officer Professional Affairs and Stakeholder Engagement CDER/FDA

Transcription

1 DRUG TRIALS SNAPSHOTS Milena Lolic, MD, MS Medical Officer Professional Affairs and Stakeholder Engagement CDER/FDA 1

2 Presentation Outline FDASIA 907 Overview What are Drug Trials Snapshots? Where to find them? What is included in Drug Trials Snapshots? What is not included? What are key findings? What is next? 2

3 FDASIA 2012: Section 907 Congress directed FDA to take a closer look at and report on the inclusion and analysis of demographic subgroups in applications for drugs, biologics, and devices FDA delivered its Action Plan to Enhance the Collection and Availability of Subgroup Data in August

4 FDA Action Plan Three overarching priorities for subgroups: Quality of Data Greater Participation Increased Transparency Drug Trials Snapshots 4

5 What is Drug Trial Snapshot? Transparency effort that provides the public with information about who participated in clinical trials that supported the FDA approval of new drugs Safety and efficacy subgroup data Newly-approved drugs and biologics (NMEs and BLAs)* Goal to publish within 30 days of approval *New Molecular Entities and original Biologic Licensing Applications 5

6 6

7 7

8 Date of FDA What is it Drug Active Ingredient Approval Approved For Package Insert ZONTIVITY vorapaxar May 8, 2014 Reduction of heart attacks and stroke in high-risk patients Zontivity ZEPATIER elbasvir and grazoprevir January 28, 2016 Treatment of chronic Hepatis C genotypes 1 or 4 infection Zepatier YONDELIS trabectedin October 23, 2015 Treatment of certain types of advances tissue sarcoma Yondelis XURIDEN uridine triacetate September 4, 2015 Treatment of patients with hereditary orotic aciduria Xuriden VRAYLAR cariprazine September 17, Treatment of Vraylar 2015 bipolar disorder VRAYLAR cariprazine September 17, Treatment of Vraylar 2015 schizophrenia VELTASSA patiromer October 21, Treatment of Veltassa 2015 hyperkalemia VARUBI rolapitant September 1, To prevent Varubi

9 Format of a Snapshot Consumer Info first More Info second Each consumer section has a link to More Info Consumer Info written in consumer-friendly language More Info technical language and data-heavy 9

10 Format of a Snapshot- example Trial 1 Trial 2 Composite response* over 12 weeks VIBERZI 100 mg n=426 VIBERZI 75 mg n=427 Placebo n=427 VIBERZI 100 mg n=382 VIBERZI 75 mg n=381 Placebo n=382 Responder rates (%) Treatment difference (%) 8** 7**** - 13*** 13*** - 95% CI (%) (2.6,13.5) (1.4,12.2) - (7.5,19.2) (6.8, 18,5) - *Simultaneous improvement of Worst Abdominal Pain by 30% and Bristol Stool Score < 5 on the same day for 50% of days over the interval ** p<0.01 *** p<0.001 ****p<

11 Drug Snapshot (content) Information about who participated in the clinical trials AND Information about trial design overall drug efficacy and safety differences in efficacy and safety among sex, race, and age subgroups 11

12 Who Participated in the Clinical Trials? 12

13 More Info Demographic Parameters Sex, n (%) KENGREAL (N=5,581) Treatment Groups Clopidogrel (N=5,564) Overall (N=11,145) Male 3982 (71) 4042 (73) 8024 (72) Female 1599 (29) 1522 (27) 3121 (28) Age (years) Mean (SD) 64.0 (11.0) 63.8 (11.0) 63.9 (11.0) Median (Min, Max) 26, 94 26, 95 26, 95 Age group, n (%) years 2892 (52) 2902 (52) 5794 (52) years 1656 (29) 1662 (30) 3318 (30) >= (19) 1000 (18) 2033 (18) Race, n (%) White 5231 (94) 5206 (94) (94) Black or African American 156 (3) 152 (3) 308 (3) Asian 173 (3) 177 (3) 350 (3) Native Hawaiian or Pacific Islander 13 (<1) 16 (<1) 29 (<1) American Indian or Alaskan Native 5 (<1) 6 (<1) 11 (<1) Unknown 3 (<1) 7 (<1) 10 (<1) 13

14 Were there any observed differences in how well the drug worked in clinical trials among sex, race, and age? Sex: KENGREAL was similarly effective in men and women. Race: The majority of patients in the trial were white. Differences in response to KENGREAL between races could not be determined. Age: KENGREAL was similarly effective in all age groups studied. 14

15 More Info KENGREAL (N=5472) Clopidogrel (N=5470) Odds 95% CI Subgroup x (%) Total n x (%) Total n Ratio LL UL Overall Response/All patients 257 (5) (6) Sex Male 183 (5) (6) Female 74 (5) (7) Age Group >=17-65 years 121 (4) (5) >=65 years 136 (5) (7) >=75 years 55 (5) (7) Race White 243 (5) (6) Black or African American 5 (3) (6) Asian 7 (4) (5) American Indian or Alaskan Native 1 (20) 5 3 (50) Native Hawaiian or Pacific Islander 1 (8) Unknown (29)

16 More Info Figure 4: Difference (95% Confidence Interval) in Average Percent LDL Change at Week 24 (Praluent minus placebo) ; Trials 1 to 5 Combined (N=3499) - C Sex Mal es Females Age Below 65 years 65 years and above Race White Black or African American Asian American Indian or Alaska Native Other Ethnicity Hispanic or Latino Not Hispanic or Latino P - value for statistical test measuring whether the treatment effect differs across subgroups (i.e., p - value for test of treatment - by - subgroup interacti on) for studies 1 to 5 combined : Sex : 0.001; Age: 0.14; Race: 0.25; Ethnicity:

17 Were there any observed differences in side effects among sex, race, and age? Sex: More bleeding was seen in women taking KANGREAL compared to men taking KANGREAL. In the trial, all patients (men and women) treated with KANGREAL had more bleeding compared to patients given another blood thinner called clopidogrel. Race: The majority of patients in the trial were white. Differences in bleeding among races could not be determined. Age: More bleeding was observed in patients 65 and older treated with KANGREAL compared to younger patients taking KANGREAL. In the trial, all patients (in every age group) treated with KANGREAL had more bleeding compared to patients given another blood thinner called clopidogrel. 17

18 More Info 18

19 Examples Drug Indication Total Women 65 and older White African American Asian Aristada Schizophrenia % <1% 47% 40% 13% Natpara Hyperparathyroidism % 7% 96% 1% 2% Stiloto Respimat COPD 3,100 27% 49% 70% 1% 26% Yondelis Advanced sarcoma % 22% 76% 12% 4% Tagrisso Lung cancer % 45% 36% 1% 60%

20 Examples-Oncology Drugs Drug Indication Women 65 and older White African American Ibrance Breast CA 100% 44% 90% 1% 6% Tagrisso Lung CA (NSCLC) 68% 45% 36% 1% 60% Alecensa Lung CA (metastatic NSCLC) 55% 14% 74% 2% 18% Yondelis Sarcoma (metastatic) 70% 22% 76% 12% 4% Lenvima Thyroid CA 49% 40% 79% 2% 18% Farydak Multiple Myeloma 48% 42% 64% 5% 29% Darzalex Multiple Myeloma 45% 45% 76% 10% 6% Ninlaro Multiple Myeloma 43% 58% 84% 2% 9% Asian Cotellic Melanoma 42% 27% 93% 7% non-white Unituxin Neuroblastoma 40% N/A 82% 7% 3% Emplicity Multiple Myeloma 40% 57% 84% 4% 10% Lonsurf Colorectal CA (metastatic) 39% 44% 58% 1% 35% Odozmo BCC (metastatic) 37% 54% 94% <1% unknown Portrazza Lung CA (metastatic NSCLC) 17% 39% 83% 1% 8%

21 Examples-Psychiatric Drugs Drug Indication Women 65 and older White African American Asian Aristada Schizophrenia 32% <1% 47% 40% 13% Rexulti Schizophrenia 37% <1% 63% 24% 7% Rexulti Major depressive disorder 69% 1% 85% 12% 1% Vraylar Schizophrenia 28% <1% 43% 35% 17% Vraylar Bipolar disorder 41% <1% 49% 25% 24%

22 Not in Snapshots Comprehensive drug information Rationale for approval Population in overall drug development program Enhanced safety information 22

23 Drug Trials Snapshots Publications In November 2014, first snapshots were published In 2015, 54 snapshots published Up to date, 61 snapshots published 23

24 Feedback on Snapshots All new NDA and BLA approvals? All phases of the drug development? Intersection data of age, race and sex? Multiple languages? 24

25 Future of Snapshots (more questions) What sample size is required for adequate statistical analyses of subgroups? When does subgroup analysis matter? If analyses are post-hoc, when does clinically meaningful difference matter? 25

26 Thank you to the team Naomi Lowy Laurie Haughey Helene Taira Junyang Wang Hank Hoang Ruthanna Devi John Whyte 26

27 Questions? Thank you 27