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IRESSA A Case Study in Personalised Medicine Dr Rose McCormack

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1 IRESSA A Case Study in Personalised Medicine Dr Rose McCormack
Personalised Healthcare AstraZeneca A Presentation for the Translational Genomics Meeting Royal College of Physicians, London 15th January 2013

2 An Overview The drug The biomarkers and clinical trials
Implications for Diagnostics Our experience and learnings An Overview

3 The drug The drug The biomarkers and clinical trials
Implications for Diagnostics Our experience and learnings The drug

4 Gefitinib (IRESSA™): A brief overview
Gefitinib is a once-daily 250mg oral medication that targets and blocks the activity of the EGFR-TK Gefitinib was the first EGFR-TK inhibitor to be approved for use in non-small cell lung cancer Gefitinib has demonstrated longer progression-free survival, better tolerability and quality of life compared with doublet chemotherapy (carboplatin/paclitaxel) in first-line treatment for EGFR mutation-positive advanced NSCLC. On the 1st July 2009 the European Commission granted marketing authorisation for gefitinib for the treatment of adults with locally advanced or metastatic NSCLC with activating mutations of EGFR-TK across all lines of therapy Gefitinib is currently approved for the treatment of 1st line EGFR M+ advanced NSCLC patients in 85 countries worldwide EGFR-TK, an enzyme that regulates intracellular signalling pathways implicated in cancer cell proliferation and survival. Mutation of the EGFR gene occurs in about 10-15% of non-small cell lung cancers (NSCLC) in Europe and around 30-40% in Asia First approved in Japan in 2002

5 The biomarkers and clinical trials
The drug The biomarkers and clinical trials Implications for Diagnostics Our experience and learnings The biomarkers and clinical trials

6 Lessons in Biomarker Analysis
Chromosome DNA mRNA Protein Gene Copy Number (FISH) DNA Mutation Analysis (e.g. ARMS) Expression Analysis (e.g. Array, RT-PCR etc) Protein Expression Analysis (e.g. IHC) PI3K Grb-2 Ras SOS PTEN Akt Raf MEK mTOR STAT 3/5 This diagram shows where the potential predictors of response to EGFR TKIs (EGFR mutations, gene copy number and protein expression) lie in the process of translating chromosome information to protein expression, and the downstream EGFR signalling pathways. Reference Pao & Miller. J Clin Oncol 2005; 23: MAPK Tumour cell survival Tumour cell proliferation Pao & Miller 2005

7 The Trials: A Brief History
ISEL, INTEREST: Unselected trials in pre-treated setting IRESSA registration Japan ISEL INTEREST 2002 2003 2004 2005 2006 2007 2008 2009 EGFR protein expression EGFR gene copy number

8 EGFR mutations: First observed in 2004
Lynch et al 2004 (New Eng J Med 350: ) Activating Mutations in the Epidermal Growth Factor Receptor Underlying Responsiveness of Non-Small-Cell Lung Cancer to Gefitinib Reprinted with permission. © 2005 American Society of Clinical Oncology. All rights reserved. Paez et al 2004 (Science 304: ) EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy Mitsudomi T et al: J Clin Oncol 23 (11), 2005: Mutations of the epidermal growth factor receptor gene predict prolonged survival after gefitinib treatment in patients with non-small-cell lung cancer with postoperative recurrence. The presence of EGFR mutations was first described in 2004. The frequency of these EGFR mutations was found to vary between different clinical sub-populations. Multiple examples of the response to gefitinib in representative four patients with recurrent non–small-cell lung cancer

9 The Trials: A Brief History
ISEL, INTEREST: Unselected trials in pre-treated setting IPASS: Clinically selected trial in first line setting IRESSA registration Japan ISEL INTEREST IPASS 2002 2003 2004 2005 2006 2007 2008 2009 EGFR protein expression EGFR gene copy number EGFR mutations

10 Docetaxel 75 mg/m2 every 3 weeks
INTEREST: Phase III study of gefitinib vs docetaxel in pre-treated NSCLC Endpoints Patients Progressive or recurrent disease following CT Considered candidates for further CT with docetaxel 1 or 2 CT regimens (≥1 platinum) PS 0-2 Primary Overall survival (co-primary analyses of non-inferiority in all patients and superiority in patients with high EGFR gene copy number) Secondary Progression-free survival Objective response rate Quality of life Disease related symptoms Safety and tolerability Exploratory Biomarkers EGFR mutation EGFR protein expression EGFR gene copy number K-Ras mutation Gefitinib 250 mg/day Docetaxel 75 mg/m2 every 3 weeks 1:1 randomization Reference Kim ES et al. Lancet 2008; 372: 1466 patients Kim 2008 10

11 Probability of progression-free survival Probability of survival
INTEREST Results OS: NI margin 1.154, PP population HR (96% CI) =1.020 (0.905, 1.150) n=1433, deaths=1169 Median survival: Gefitinib 7.6m, Docetaxel 8.0m PFS: EFR population HR (95% CI) =1.04 (0.93, 1.18), p=0.466 n=1316, progressions=1137 Median PFS: Gefitinib 2.2m, Docetaxel 2.7m 1.0 1.0 Gefitinib Docetaxel Gefitinib Docetaxel 0.8 0.8 0.6 0.6 Probability of progression-free survival Probability of survival 0.4 0.4 Reference Kim ES et al. Lancet 2008; 372: 0.2 0.2 0.0 0.0 4 8 12 16 20 24 28 32 36 40 4 8 12 16 20 24 28 32 36 40 Months Months Kim 2008 11

12 INTEREST: Summary of key subgroup analyses
Overall Survival ORR (%) Gefitinib v. Docetaxel Progression-free Survival Overall Ever smoker Never smoker Asian Non-Asian EGFR FISH+ EGFR FISH- EGFR Mutation+ EGFR Mutation- 9.1 v Overall Ever smoker Never smoker 19.7 v. 8.7 Asian 6.2 v. 7.3 Non-Asian 13.0 v. 7.4 EGFR FISH+ 7.5 v EGFR FISH- 42.1 v EGFR Mutation+ 6.6 v. 9.8 EGFR Mutation- Overall Ever smoker Never smoker Asian Non-Asian EGFR FISH+ EGFR FISH- EGFR Mutation+ EGFR Mutation- References Kim ES et al. Lancet 2008; 372: Douillard et al. J Clin Oncol; 26 (May 20 Suppl.): Abstract 8001. 0.5 1.0 1.5 2.0 0.5 1.0 1.5 2.0 2.5 HR (Gefitinib vs docetaxel) and 95% CI HR (Gefitinib vs docetaxel) and 95% CI Kim 2008; Douillard 2010 12

13 INTEREST: Overlap of biomarkers
EGFR FISH + n=117 249 patients evaluable for EGFR expression, FISH and mutations n=16 n=84 +++ n=24 EGFR expression + n=189 4 Reference Douillard et al. J Clin Oncol 2009, in press. EGFR mutation + n=39 3 n=8 Douillard 2010 --- n=37 13

14 Carboplatin AUC 5 or 6 and Paclitaxel 200mg/m2 3 wkly
IPASS: Phase III study of gefitinib versus doublet chemotherapy in first line NSCLC Gefitinib 250 mg/day Carboplatin AUC 5 or 6 and Paclitaxel 200mg/m2 3 wkly 1:1 randomization Patients Adenocarcinoma histology Never smokers or light ex-smokers* PS 0-2 Provision of tumour sample for biomarker analysis strongly encouraged Primary Progression free survival (non-inferiority) Secondary Objective response rate Quality of life Disease related symptoms Overall survival Safety and tolerability Exploratory Biomarkers EGFR mutation EGFR gene copy number EGFR protein expression Endpoints 1217 patients from East Asian countries Reference Mok TS et al. N Engl J Med 2009; 361: *Never smokers:<100 cigarettes in lifetime; light ex-smokers: stopped 15 years ago and smoked  10 pack yrs Carboplatin/paclitaxel was offered to IRESSA patients upon progression PS, performance status; EGFR, epidermal growth factor receptor Mok 2009 14

15 IPASS: Progression Free Survival
Objective response rate 43% vs 32% p=0.0001 Probability of PFS 1.0 Carboplatin / paclitaxel Gefitinib N Events 609 453 (74.4%) 608 497 (81.7%) 0.8 HR (95% CI) = (0.651, 0.845) p<0.0001 0.6 Median PFS (months) 4 months progression-free 6 months progression-free 12 months progression-free 5.7 61% 48% 25% 5.8 74% 48% 7% 0.4 Primary objective exceeded: Gefitinib demonstrated superiority relative to carboplatin / paclitaxel in terms of PFS 0.2 Reference Mok TS et al. N Engl J Med 2009; 361: 0.0 4 8 12 16 20 24 Months At risk : IRESSA 609 363 212 76 24 5 Carboplatin / paclitaxel 608 412 118 22 3 1 Mok 2009 15 15 15

16 Time from randomisation (months)
IPASS: EGFR mutation is a strong predictor for differential PFS benefit between gefitinib and doublet chemotherapy Gefitinib EGFR M+ (n=132) Gefitinib EGFR M- (n=91) Carboplatin / paclitaxel EGFR M+ (n=129) Carboplatin / paclitaxel EGFR M- (n=85) 1.0 EGFR M+ HR=0.48, 95% CI 0.36, 0.64 p<0.0001 EGFR M- HR=2.85, 95% CI 2.05, 3.98 p<0.0001 0.8 Probability of PFS 0.6 Treatment by subgroup interaction test, p<0.0001 0.4 Reference Mok TS et al. N Engl J Med 2009; 361: 0.2 0.0 4 8 12 16 20 24 Time from randomisation (months) Mok 2009 16 16 16

17 IPASS: PFS by Biomarkers (ITT)
Treatment-by-subgroup interaction test p-value p= for EGFR gene copy number p= for EGFR expression p< for EGFR mutation Favours gefitinib Favours carboplatin / paclitaxel Known mutation status EGFR Mutation+ EGFR Mutation- Known expression status EGFR+ EGFR- Known FISH status EGFR FISH+ EGFR FISH- 0.25 0.5 1.0 2.0 4.0 Hazard Ratio (Gefitinib : Carboplatin / Paclitaxel) and 95% CI Fukuoka JCO 2011

18 IPASS: Overlap of biomarkers
EGFR FISH+ n=249 EGFR expression + n=266 25 51 13 +++ = 132 28 --- = 31 34 EGFR Mutation+ n=261 15 N=329 with known biomarker status for all 3 biomarkers Fukuoka JCO 2011

19 EGFR Mutation Analysis
Lessons in Biomarker Analysis Chromosome DNA mRNA Protein EGFR Gene Copy Number EGFR Mutation Analysis EGFR Expression Analysis EGFR Protein Expression Analysis What? Choose your biomarker(s) carefully How? The tool that you use to measure your biomarker must be robust and reliable The cut-offs used to define biomarker positive, negative, and unknown subgroups must be appropriate Samples must be available PI3K Grb-2 Ras SOS PTEN Akt Raf MEK mTOR STAT 3/5 This diagram shows where the potential predictors of response to EGFR TKIs (EGFR mutations, gene copy number and protein expression) lie in the process of translating chromosome information to protein expression, and the downstream EGFR signalling pathways. Reference Pao & Miller. J Clin Oncol 2005; 23: MAPK Tumour cell survival Tumour cell proliferation Pao & Miller 2005

20 IPASS: Attrition factors in biomarker analysis
1217 randomised patients (100%) Reasons for samples not evaluable: Sample not available, insufficient quantity to send, cytology only, sample at another site 1038 biomarker consent (85%) 683 provided samples (56%) 565 histology 118 cytology Evaluable for: EGFR mutation: 437 (36%) EGFR gene copy number: 406 (33%) EGFR expression: 365 (30%) Reference Mok TS et al. N Engl J Med 2009; 361: Mok 2009, Fukuoka 2009 20 20 20

21 Implications for diagnostics
The drug The biomarkers and clinical trials Implications for Diagnostics Our experience and learnings Implications for diagnostics

22 IPASS reports September 2008, partway through the European MAA review of INTEREST (Phase III study of Gefitinib vs docetaxel in pre-treated NSCLC) Gefitinib is indicated for the treatment of adult patients with locally advanced or metastatic non‑small cell lung cancer (NSCLC) with activating mutations of EGFR‑TK.

23 Getting the right treatment to the right patient
All NSCLC patients Affected by..... Test Availability and Ease of Test Order Patients tested Easily accessible testing High quality testing (high detection rates) Access to suitable samples Reasonable Test Turnaround Time Needs..... Test sensitivity Test ease of use Interpretation of results Test Turnaround time Test result Positive Treated

24 EGFR mutation testing: diversity in 2009
Japan UK Centralised lab network Testing reimbursed High level of patients tested Tests used: CLAMP INVADER Sequencing Cycleave De- centralised lab network Testing not reimbursed Low level of patients tested Tests used: TheraScreen Sequencing Pyrosequencing

25 Understanding and Supporting the Dx Environment
Patient Physician (respiratory, surgeon, oncologist) Lab service provider/Molecular Biologist Sample Test result Diagnostic company/ies Platform provider Pathologist egfr-mutation.com egfr-test.com

26 Challenges associated with a PHC approach
Physicians adopting a PHC approach Access to testing Diversity of testing methods /capabilities across countries Multiple individuals involved from decision to test to getting results Challenges Testing reimbursement Availability of suitable samples for testing Time taken to generate test results

27 Our experience and learnings
The drug The biomarkers and clinical trials Implications for Diagnostics Our experience and learnings Our experience and learnings

28 The Biomarker Journey Ideally biomarker to indication in biomarker population is a straightforward, well planned process In reality this is a challenging process in which your direction changes e.g. molecular disease segment, clinical characteristics, different biomarkers, techniques, cut-offs etc. Patient/ Disease Biomarker/Dx Tool What patients do you intend to treat? What are you measuring? Do you need a diagnostic to identify those patients? How are you measuring it? Is there an existing assay available to identify the patients? How do you define your cut-offs? Do you need to develop a diagnostic test suitable for selecting patients eligible for therapy? Can you develop an appropriate tool that can be used to measure in a robust and reliable way?

29 Personalised Healthcare development today and in the future
Gefitinib experience Gefitinib had standard drug development Predictive biomarker for gefitinib discovered by external collaborator ~7 years after start of clinical trials Retrospective investigation was required to show the significant clinical benefit for those patients identified by diagnostic test Ultimately identified patients most likely to benefit offers an alternative treatment option to doublet chemotherapy in newly diagnosed advanced/metastatic NSCLC Future Therapies Personalised Healthcare research discovers predictive biomarker in preclinical models before start of clinical development Clinical programme prospectively selects biomarker eligible patients, targeted to patients most likely to respond Early engagement with health authorities and payers Co-development of drug and diagnostic Drug launched globally, linked to diagnostic established within the diagnostic environment

30 Summary Gefitinib is approved in Europe for a biomarker targeted population Gefitinib was developed during a time of rapid progress in the understanding of molecular mechanisms of cancer, therefore the route to approval was not straightforward In future, pharmaceutical companies are unlikely to be able or willing to follow a similar development path for new agents There are several useful learnings for future biomarker targeted products Understand the science Assess efficacy in a biomarker defined, targetted population, as early as possible Maximise tissue samples, no sample means no biomarker result Diagnostic test adoption is as important as the drug Pharmaceutical companies, Physicians, Pathologists, Academics and Regulators are learning about this together Engage early Considerable challenges on both sides Opportunity for collaboration

31 Confidentiality Notice
This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 2 Kingdom Street, London, W2 6BD, UK, T: +44(0) , F: +44 (0) , Author | 00 Month Year Set area descriptor | Sub level 1


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