IRESSA (Gefitinib) The Journey Anne De Bock Portfolio Leader, Oncology/Infection European Regulatory Affairs AstraZeneca
Overview The Drug The Biomarker and Clinical Trials Sampling Lessons Learned
The Drug The Drug The Biomarker and Clinical Trials Sampling Lessons Learned
IRESSA (Gefitinib): A Brief Overview IRESSA (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 and is now approved in >70 countries worldwide. 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 26 June 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.
The Biomarker and Clinical Trials The Drug The Biomarker and Clinical Trials Sampling Lessons Learned
The Journey 1960s Cohen s discovery of epidermal growth factor (EGF) in mice in 1962 pioneers major progress in cell growth/differentiation research Early 1990s 1970s 1994 First clinical trial of anti-egfr agent (mab) confirms MOA Discovery of new class of EGFR-TKIs Gefitinib Phase I trials: favourable tolerability and 1998 good responses in NSCLC Publication of IDEAL 1 and 2 Isolation of human EGF from human urine by Cohen; Identification of EGF receptor by Cohen Early 1980s Mendelsohn proposes EGFR as anticancer target; Human EGFR cloned and sequenced Late 1980s Accumulating evidence that EGFR is associated with tumour progression and EGFR kinase activity can be inhibited in vitro by small molecules 2001 2000 Expanded access programme starts in parallel with Phase II/III trials (IDEALs/ INTACTs) Phase II IDEAL 1 and 2 studies report: gefitinib effective at 250 mg/day (JCO 2003; JAMA 2003)
The Trials: A Brief History IRESSA registration Japan ISEL, INTEREST: Unselected trials in pre-treated setting ISEL INTEREST 2002 2003 2004 2005 2006 2007 2008 2009 EGFR protein expression EGFR gene copy number
EGFR Mutations: First Observed in 2004 Lynch et al 2004 (New Eng J Med 350:2129-2139) Mitsudomi et al 2005 (JCO, vol. 23 no. 11 2513-2520, 2005 ) Paez et al 2004 (Science 304:1497-1500)
Choosing Relevant Biomarkers 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) PTEN PI3K Akt Grb-2 SOS Ras Raf Pao & Miller 2005 mtor STAT 3/5 Tumour cell survival MEK MAPK Tumour cell proliferation
The Trials: A Brief History IRESSA registration Japan ISEL, INTEREST: Unselected trials in pre-treated setting IPASS: Clinically selected ISEL trial in first line setting INTEREST IPASS 2002 2003 2004 2005 2006 2007 2008 2009 EGFR protein expression EGFR gene copy number EGFR mutations
INTEREST: Phase III Study of IRESSA vs Docetaxel in Pre-Treated NSCLC Patients Progressive or recurrent disease following CT Considered candidates for further CT with docetaxel 1 or 2 CT regimens ( 1 platinum) PS 0-2 1466 patients Kim 2008 Gefitinib 250 mg/day 1:1 randomization Docetaxel 75 mg/m 2 every 3 weeks Endpoints 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
Probability of survival INTEREST Results Probability of progression-free survival 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 0.8 0.6 Gefitinib Docetaxel 1.0 0.8 0.6 Gefitinib Docetaxel 0.4 0.4 0.2 0.2 0.0 0 4 8 12 16 20 24 28 32 36 40 Months 0.0 0 4 8 12 16 20 24 28 32 36 40 Months Kim 2008
INTEREST: Summary of Key Subgroup Analyses Overall Overall Survival ORR (%) Gefitinib v. Docetaxel 9.1 v. 7.6 Overall Progression-free Survival Overall Ever smoker Never smoker Asian Non-Asian EGFR FISH+ EGFR FISH- EGFR Mutation+ EGFR Mutation- 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. 10.1 EGFR FISH- 42.1 v. 21.1 EGFR Mutation+ 6.6 v. 9.8 EGFR Mutation- Ever smoker Never smoker Asian Non-Asian EGFR FISH+ EGFR FISH- EGFR Mutation+ EGFR Mutation- 0 0.5 1.0 1.5 2.0 HR (Gefitinib vs docetaxel) and 95% CI 0 0.5 1.0 1.5 2.0 2.5 HR (Gefitinib vs docetaxel) and 95% CI Kim 2008; Douillard 2010
INTEREST: Overlap of Biomarkers EGFR FISH + n=117 EGFR mutation + n=39 Douillard 2010 n=16 4 3 n=73 +++ n=24 n=8 n=84 --- n=37 249 patients evaluable for EGFR expression, FISH and mutations EGFR expression + n=189 14
IPASS: Phase III Study of Gefitinib versus Doublet Chemotherapy in First-Line NSCLC Patients Adenocarcinoma histology Never smokers or light ex-smokers* PS 0-2 Provision of tumour sample for biomarker analysis strongly encouraged Gefitinib 250 mg/day 1:1 randomization Carboplatin AUC 5 or 6 and Paclitaxel 200mg/m 2 3 wkly 1217 patients from East Asian countries PS, performance status EGFR, epidermal growth factor receptor *Never smokers:<100 cigarettes in lifetime; light ex-smokers: stopped 15 years ago and smoked 10 pack yrs Carboplatin / paclitaxel was offered to gefitinib patients upon progression Endpoints Primary Progression free survival (noninferiority) 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 15 Mok et al 2009
Probability of PFS IPASS: Progression-Free Survival (ITT) 1.0 0.8 0.6 0.4 0.2 0.0 n Events Primary Cox analysis and logistic regression with covariates; ITT population HR <1 implies a lower risk of progression on gefitinib Gefitinib 609 453 (74.4%) 24 Carboplatin / paclitaxel 608 497 (81.7%) HR (95% CI) = 0.741 (0.651, 0.845) p<0.0001 Median PFS (months) 4 months progression-free 6 months progression-free 5.7 61% 48% 5.8 74% 48% 12 months progression-free 25% 7% Primary objective exceeded: gefitinib demonstrated superiority relative to carboplatin / paclitaxel in terms of PFS At risk : Gefitinib 609 363 212 76 24 5 0 Carboplatin / 608 412 118 22 3 1 0 paclitaxel 0 4 8 12 16 20 Months ORR 43% vs 32% p=0.0001 Mok et al 2009
Probability of PFS IPASS: Comparison of PFS by Mutation Status within Treatment Arms (ITT) Treatment by subgroup interaction test, p<0.0001 1.0 0.8 0.6 0.4 0.2 Gefitinib EGFR M+ (n=132) Gefitinib EGFR M- (n=91) Carboplatin / paclitaxel EGFR M+ (n=129) Carboplatin / paclitaxel EGFR M- (n=85) EGFR M+ HR (95% CI) = 0.48 (0.36, 0.64) p<0.0001 EGFR M- HR (95% CI) = 2.85 (2.05, 3.98) p<0.0001 0.0 M+, mutation positive; M-, mutation negative 0 4 8 12 16 20 24 Mok et al 2009 Time from randomization (months)
IPASS: PFS by Biomarkers (ITT) Known mutation status EGFR Mutation+ Known expression status Treatment-bysubgroup interaction test p-value p<0.0001 for EGFR mutation EGFR+ EGFR Mutation- EGFR- p=0.2135 for EGFR expression Known FISH status EGFR FISH+ EGFR FISH- p=0.0437 for EGFR gene copy number Fukuoka ASCO 2009 0.25 0.5 1.0 2.0 4.0 Hazard Ratio (Gefitinib : Carboplatin / Paclitaxel) and 95% CI Favours gefitinib Favours carboplatin / paclitaxel
The Diagnostic The Drug The Biomarker and Clinical Trials Sampling Lessons Learned
IPASS biomarker sampling 1217 randomised patients (100%) 1038 biomarker consent (85%) Reasons for samples not evaluable: Sample not available, insufficient quantity to send, cytology only, sample at another site 683 provided samples (56%) Evaluable for: EGFR mutation: 437 (36%) EGFR gene copy number: 406 (33%) EGFR expression: 365 (30%) Fukuoka et al 2009
Lessons Learned The Drug The Biomarker and Clinical Trials Sampling Lessons Learned
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. disease segment, clinical characteristics, different biomarkers, techiniques, cut-offs etc. Patient/ Disease What patients do you intend to target? Do you need a diagnostic to identify those patients? Is there an existing assay available to identify the patients? Do you need to develop a diagnostic test suitable for selecting patients eligible for therapy? Biomarker/Dx Tool What are you measuring? How are you measuring it? How do you define your cut-offs? Can you develop an appropriate tool that can be used to measure in a robust and reliable way?
Personalised Healthcare Development Today and in the Future Iressa experience Future Therapies Predictive biomarker for IRESSA Personalised Healthcare research discovered by external collaborator discovers predictive biomarker in ~7 years after start of clinical trials preclinical models before start of Took ~4.5 further years retrospective clinical development research to show significant increase in 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 Early engagement with payers and health authorities ensures that drug is targeted to patients likely to respond Clinical programme prospectively selects biomarker eligible patients, Co-development of drug and diagnostic Drug launched globally, linked to diagnostic
Summary Gefitinib is approved in Europe for a biomarker targeted population But it took a long time to get there In future, pharmaceutical companies are unlikely to be able or willing to follow a similar development path for new agents Pharmaceutical companies and regulators are learning about this together Engage early Considerable challenges on both sides Opportunity for collaboration
Learning from our Experience Pragmatic interpretation of regulatory guidelines Understand and quite often late-breaking science Innovative medicines to patients Often smaller populations with orphan prevalence Innovative drug development Translation of pre-clinical models into clinical benefit Clinical trial design Europe-wide biobanking Quality assurance, e.g. EUROGAPP Biomarker-based indications
Learning from our Experience Opportunities for collaboration Consortia for challenging science (European equivalent of NCI?) Safety biomarkers Serious/ resistant infection Diagnostic partnerships Challenges of drug-diagnostic reimbursement Adoption of drug diagnostic as important as the drug itself Academic-industry exchange fellowships
Ultimately what we need is an Integrated but Sustainable Drug (Development) Model!!!
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