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An Overview of the Incivex Drug Development Process: The Road to Finding a Cure for HCV Genotype 1

,

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©2012 Vertex Pharmaceuticals Incorporated

Abdul J Sankoh, PhD,

Vertex Pharmaceuticals, Biostatistics Department

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OPresentation Outline

• The Hepatitis C Virus• The Hepatitis C Virus – Global Distribution of Different Genotype and subtypes– Complications from HCV

• Incivek Development and Regulatory Milestones

• Phase 3 development plan:– Paradigm Shift in the Treatment of HCVg– ADVANCE STUDY (adaptive) Design– ILLUMINATE STUDY (adaptive) Design

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C ( C )What is Hepatitis C Virus (HCV)?

i Hepatitis C is an infectious disease affectingi Hepatitis C is an infectious disease affecting primarily the liver, caused by the hepatitis C virus (HCV).

– A small (55–65 nm in size), enveloped, positive-sense single-stranded Ribonucleic acid (RNA) virus of the f il Fl i i idfamily Flaviviridae: :

– HCV is spread primarily by blood-to-blood contact associated with intravenous drug use, poorly

sterilized medical equipment and transfusion.

3– Hepatitis C only infects humans and chimpanzees.

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Th H titi C ViThe Hepatitis C Virus

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Global Geographic Distribution of HCV Genotypes and SubtypesGenotypes and Subtypes

6 major Genotypes

Zein N N Clin. Microbiol. Rev. 2000;13:223-235

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Hepatitis C Is a Global Disease• ~ 170 million people currently infectedp p y• 3 to 4 million people newly infected annually• 75% of cases in US are Genotype 1

World Health Organization (WHO) website: http://www.who.int/vaccine_research/diseases/viral_cancers/en/print.html Reprinted from Alter MJ, et al. World J Gastroenterol. 2007;13:2436-2441.

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In the US, Prevalence of HCV Higher Than HIV or HBV

Number of infected individuals vsNumber of infected individuals vs number aware they are infected (diagnosed)

Undiagnosed2.7-3.9 million infected

75% undiagnosed

ecte

d

4

3

Undiagnosed

Diagnosed

1.4 million infected65% undiagnosed

1.1 million infected21% undiagnosedum

ber i

nfe

mill

ions

)

3

2

65% undiagnosed21% undiagnosed

Tota

l nu (

1

0

Institute of Medicine. Hepatitis and Liver Cancer: A National Strategy for Prevention and Control of Hepatitis B and C. Washington, DC: The National Academic Press; 2010

HCVHBVHIV

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Natural History of HCV Infection

Acute HCVAcute�HCV

Resolved25%�í 30%

Chronic�Hepatitis�C�70%�í 75%�

20 yrsCirrhosis

10% í 20%�

20 yrs

Hepatocellular�carcinoma(1% í 4%/yr)( /y )Liver�failure

Santantonio T et al, J Hepatology. 2008;49:625-33.NIH Consensus Conference Statement, June 2002.John-Baptiste A et al, J Hepatology. 2010;53:245-51.Seeff LB, Liver International. 2009;29(suppl 1):89-99.

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What Do Patients With HCV Cirrhosis Face?

bDecreased�quality�of�lifea,b• Fatigue��������• Weight�loss• Depression

Complicationsc

• GI�bleeding�(varices,�gastropathy)• Ascites• Bacterial infectionsDepression

• Muscle�wasting• Impaired�cognition

Bacterial�infections• Encephalopathy

í OvertíMinimal

H ll l i• Hepatocellular�carcinomaLiver�Transplantation

• Hepatitis�C�is�most�frequent�indicationd Deathindication• 30%�develop�cirrhosis�5Ͳ7�yrs�postͲtransplante

Death• ~�12,000�deaths/yr�(based�on�death�certificate�documentation)f

• Likely�an�underͲrepresentationg

a Bonkovsky HL, et al. J Hepatol. 2007;46:420-431. b Bonkovsky HL and Woolley JM. Hepatology. 1999;29:264-70. c Planas R, et al. J Hepatol. 2004;40:823-30. d Berg CL, et al. Am J Transplant. 2009;9:907-931. e Berenguer M. Clin Liver Dis. 2007;11:355-376. f Everhart JE, et al. Gastroenterology. 2009;136:1134-1144. g Wise M, et al. Hepatology. 2008;47:1128-1135.

CI-10Time of HCV Acquisition in Patients with

Different HCV Genotypes.yp

Zein N N Clin. Microbiol. Rev. 2000;13:223-235

CI-11Mean Time (years) Between Exposure to HCV and Diagnosis of HCV-Related Complications

Zein N N Clin. Microbiol. Rev. 2000;13:223-235

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Incivek� Key Development & Regulatory Milestonesy p g y

2011 Key developmentPriority review

Approval & Launch

2010

Key developmentmilestonesa

CMC pre-NDA meetingClinical pre-NDA meetingNDA rolling

submission

2008

2009

Study 108 (ADVANCE)

Study 111 (ILLUMINATE)Study C216 (REALIZE) Phase 3

Clinical advice meeting

2007

2008

Study 106 (PROVE-3)

Study 104EU (PROVE-2)

Study 107

Phase 2

Clinical advice meeting

2005

2006Study 103Study 102

Phase 1

Study 104 (PROVE-1)Study 104EU (PROVE 2)

Key regulatorymilestones

2004

2005

a Dates refer to first patient enrolled.

Study 101 Phase 1milestones

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State of HCV Treatment Prior to Incivek Approval• Goal = Sustained Viral Response (SVR)p ( )

– Considered virologic cure• Peg-IFN/RBV standard of care for HCV

– SVR for Genotype 1 naive• 40% í 52% of patients achieve SVRa-f

• Duration of therapy 48 weeksa-fDuration of therapy 48 weeks• Low success rates with retreatment in

nonresponders and relapsers (10% í 25%)g-i

• Peg-IFN/RBV has known toxicitiesa-i

• Rationale for response-guided therapy with potential to shorten therapypotential to shorten therapy

a Pegasys [package insert]. Nutley, NJ: Hoffmann-La Roche Inc.; 2011. b Copegus [package insert]. Nutley, NJ: Hoffmann-La Roche Inc.; 2010. c Hadziyannis SJ, et al. Ann Intern Med. 2004;140:346-355. d Fried MW, et al. NEJM. 2002;347:975-982. e Manns MP, et al. Lancet. 2001;358:958-965. f McHutchinson JG, et al. NEJM. 2009;361:58-593. g Bacon BR, et al. Hepatology. 2009;49:1838-1846. h Jensen DM, et al. Ann Intern Med. 2009;150:528-540. i Poynard T, et al. Gastroenterology. 2009;136:1618-1628.

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Common Factors That May Lead to Lower SVR with Peg-IFN/RBV

• Genotype 1Genotype 1• High HCV RNA levels• Cirrhosis/bridging fibrosisCirrhosis/bridging fibrosis• Age � 40 years• Heavy body weight• Heavy body weight• Insulin resistance• African American and Latino ethnicity• African American and Latino ethnicity• Genetic polymorphisms (IL28B)

HIV i f ti• HIV coinfection

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Telaprevir—A Paradigm Shift in the T t t f HCVTreatment of HCV

Easing Patient Treatment Burden!Easing Patient Treatment Burden!

Abbreviations: AE, adverse event; SVR, sustained virologic response.

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Original Phase 3 Development Program Proposal

• Given strength of Phase 2 data fromGiven strength of Phase 2 data from– Prove1 (Naïve)

P 2 (N ï )– Prove 2 (Naïve)– Prove 3 (Nonresponders)

• Conduct – 1 Phase 3 Naïve Patient Study (ADVANCE)– 1 Phase 3 Treatment Experience Study

(REALIZE)

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ADVANCE Study Designy gStudy- Naïve Treatment- Late Phase

Wk Wk Wk Wk WkWk

Follow up

8 12 24 48 72

SVReRVR+ Follo p

4

Follow-upSVR

Follow-upn = 364 T8/PR Pbo/

PR PR eRVRí:PR to Wk 48

eRVR+: Follow-up

Follow-upSVR

Follow upn = 363 T12/PR PR eRVRí:

SVReRVR+: Follow-up

Follow-up

SVR

eRVR :PR to Wk 48

Follow-upSVR

n = 361 Pbo/PR PR

eRVR = extended Rapid Viral Response; PR= Standard of Care

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FDA & Physicians Want to Know

• Clinically whether some subjects mightClinically, whether some subjects might benefit from additional exposure to SOC

• Statistically, whether 24-week treatment is not inferior to 48-week treatment

• Basically,Basically,– A study comparing 24-week to 48-week

treatment (eRVR+)( )– Thus the ILLUMINATE STUDY

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SVR Rates by eRVR StatusADVANCE Study 108—Treatment-Naive

T12/PR100 97

ctab

le

T12/PRT8/PRPbo/PR

708090

9287

h un

dete

cR

NA

, %

506070

6052

42

tient

s w

ithH

CV

203040

42

Pat

24-week regimen0

1020

195/212 179/207 90/151 82/157

48-week regimen

28/29 139/332

RVR RVR24-week regimen

eRVR+

48-week regimen

eRVRí

eRVR+ eRVRí

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ILLUMINATE Study Designy gStudy 111—Treatment-Naive

Wk

Randomized Wk48

Wk72

Wk24

n = 540 T12/PR PR

Wk12

20 Wk24

Follow-up for SVR

eRVR+PR to Wk 48 Follow-up for SVR

n 540 T12/PR PR

D/CbeforeWk 20

eRVRí PR to Wk 48 Follow-up for SVR

Follow-up for SVRWk 20

CI-21Study Design Rationale and Key Statistical Objecivesy jStudy 111—Treatment-Naive

• Evaluate differences in SVR rates betweenEvaluate differences in SVR rates between 24- and 48-week telaprevir-based regimens in patients who achieved eRVR– Rule out inferiority of 24-week to 48-week

regimen– Non-inferiority margin of 10.5% (from Ph2

data)

CI-22Study Objective:T (T12+C24) not inferior to C (T12+C48)T (T12 C24) not inferior to C (T12 C48)

� FDA’s review comments on SAP with FixedFDA s review comments on SAP with Fixed Margin Approach proposal:

� A Must also demonstrate sum of differencesMust also demonstrate sum of differences� A. Must also demonstrate sum of differencesMust also demonstrate sum of differences� 1: T-C (from ILLUMINATE non-inferiority study)

+� 2: C-P (from historical study- PROVE 1)

� i.e., 1 + 2 = (T-C)+(C-P)=T-P> 0 (statistically)

��B. Even after inclusion of term for interB. Even after inclusion of term for inter--trialtrial variability in estimate of variance of abovevariability in estimate of variance of above

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sumsum..C= PR= standard of care; T= TVR

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Proposed Synthesis ApproachProposed Synthesis Approach

i Question:i Is T>P (test drug effective-assay sensitivity)? – Answered via cross-trial information

(inference)• Estimate effect of C relative to P from

hi t i l t di f C d P i thistorical studies of C and P using meta-analysis (fixed/random effects)

• Show (T-C) +(C-P) > 0 with 95% confidence• Show (T-C) +(C-P) > 0 with 95% confidence(A) + (B)

iAlso address retention fraction of C-effect Connects historical and NI study data for indirect inference: T vs P

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Connects historical and NI study data for indirect inference: T vs P

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Synthesis Approach for Estimating Test Drug y pp g gEffect

i Using historical data from R, DB, A & WCi Using historical data from R, DB, A & WC trials (via meta-analyses- fixed or random effects) to address assay sensitivity (T vs. P) and constancy of control effect (C vs. P):

i Want ¡ T vs. C: Non-inferiority of T to C (Illuminate)¡ C vs. P:Control effect (C better than P)- Prove 1¡¡ T vs. P:T vs. P: Test effect (T better than P) Test effect (T better than P) –– CrossCross--TrialTrial

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SVR Rates Study 111—Treatment-Naive

2 0% difference

100 92 90

2.0% difference2-sided 95% CI (–4.3%, +8.2%)

60

80

SVR

, %

40

60

ents

with

20

149/162 144/160

Patie

0eRVR+

T12/PR24eRVR+

T12/PR48

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Trial Outcome & Imputing Test Drug effect:Trial Outcome & Imputing Test Drug effect:(Sum of Differences- Review Comment A)

i A. From Active-control trial (ILLUMINATE):T (ß ) C (ß ) ß =ß ß (T C difference)– T (ßT) C (ßC) ßTC=ßT-ßC (T-C difference)91.98% 87.50% 4.48%

B From historical trial (Phase 2 Study PROVE 1):i B. From historical trial (Phase 2 Study- PROVE 1):– C0 (ßC) P0 (ßP) ßCP=ßC-ßP(C-P difference)

67.09% 41.33% 25.76%

i 3. Imputing placebo response in active-control trial & demonstrating T effect– That is, estimation of ßTP & 95% CI on ßTP:, TP TP

• A + B = ßTC+ ßCP (T-P difference)# 30.23%; (13.64%, 46.82%)

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; ( , )LL> 0

• FDA DAID ACM for INCIVEK, April 28, 2011.

CI-27Simulation Algorithm to Demonstrate

Superiority of Test Drug (T) to Placebo (C)

i Generate random sample from Binomial distribution p

i Active-control: B(PT; 162); PT = 0.92; 0.93; 0.87

from this sample, estimate PT

B(PC; 160); PC = 0.88; 0.95; 0.88From this sample, estimate PC

i Historical: B(PC_0; 79); PC_0 = 0.67From this sample, estimate PC_0

B(P ; 75); P = 0 41B(P0; 75); P0 = 0.41From this sample, estimate P0

i Based on these sample estimates, left side of

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i (PT-PC) + (PC_0 - P0) > 0 • Repeat above steps M times (say M=10,000) to obtain GI’s (i=1, 2, … M);

Gi form a distribution from which (1) can be evaluated.

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Absolute Difference (%) of Test vs. Active Control- Addressing Variability

Test vs.Active Control Method

AbsoluteDifference (%)

T=92.0%,C=88.0%

T=93.0%,C=95.0%

MC BinomialMC Beta-Binomial

MC Binomial

3.87 3.98

-1.76

,

T=87.0%,C=88.0%

MC Beta-Binomial

MC BinomialMC Beta Binomial

-2.19

-1.091 06

MC Beta-Binomial -1.06

-14 -10.5 -6 -2 0 2 6 10 14

28Beta Binomial to address Variability comment