50 th ASCO Annual Meeting, Chicago Roche Analyst Event Sunday, 1 June 2014
Welcome and introduction Karl Mahler Head of Investor Relations, Roche 2
Agenda Welcome and introduction Karl Mahler, Head of Investor Relations, Roche Realizing the promise of cancer immunotherapy: translating science into medical benefit Ira Mellman, Vice President, Cancer Immunology, Genentech Hy Levitsky, Head, Cancer Immunotherapy Experimental Medicine, pred ASCO 2014 Roche highlights: setting new standards of care Sandra Horning, Chief Medical Officer and Head Global Product Development Oncology strategy and outlook Daniel O Day, Chief Operating Officer, Roche Pharmaceuticals Q&A 3
Roche oncology: continued sales growth A portfolio of differentiated medicines (CHF mn) 25,000 20,000 15,000 10,000 5,000 10 medicines 14 tumor types 40 indications,0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Sales at 2013 exchange rates 4
Science is continually evolving Complexity Unknown >1 mutated gene 3% MEK1 <1% NRAS 1% MET 1% PIK3CA BRAF1% 2% HER2 3% EGFR (other) 4% No oncogenic driver detected 35% ALK 8% EGFR 17% KRAS 25% PDL1 positive EGFR KRAS 2004 2014 Future Pao & Girard. Lancet Oncol 2011; Johnson, et al. ASCO 2013 Classification of lung adenocarcinomas 5
Roche s cancer immunotherapy community Concerted actions while valuing diversity of approaches Late Stage gpartnering Global Product Development and Strategy Roche Partnering gred Ira Mellman pred Hy Levitsky Pablo Umana Molecule teams Support function Oncology Biomarker Development Molecule teams Support function 6
Cancer immunotherapy today Approved in monotherapy, one cancer type, few patients Medical benefit (PFS/OS) Illustrative Kaplan Meier curves 1 2 Time Medical benefit Control Immunotherapy Targeted Therapy 7
Cancer immunotherapy in the future Better patient selection, combinations, broader use? Illustrative Kaplan Meier curves? Medical benefit 1 2 3 Control Immunotherapy Targeted Therapy Immuno doublets & combos with targeted therapies 8
Realizing the Promise of Cancer Immunotherapy: Translating science into medical benefit (I) Ira Mellman, Ph.D. Vice President, Cancer Immunology, Genentech 9
Mechanistic basis of cancer immunotherapy Mellman et al (2011) Nature
The cancer immunity cycle strategy Different drugs target distinct steps CEA-IL2v Avastin Immunosuppression vaccines adjuvants anti-cd40 anti-pdl1 anti-csf-1r Chen & Mellman (2013) Immunity
Using patient data to understand cancer immunity and find new treatments MPDL3280A Phase 1 Data: Urothelial Bladder Cancer Patients Progressive Disease (PD) Why do many patients not respond? No pre-existing immunity? Stable disease (SD) What combinations will promote PRs & CRs? Insufficient T cell immunity? Multiple negative regulators? Monotherapy durable responses (PR/CR) What are the drivers of single agent response? How can PRs be enhanced to CRs? Insufficient T cell immunity? Multiple negative regulators?
Comprehensive approach to biomarker discovery Gene Expression - ichip Molecular Imaging High throughput and comprehensive evaluation of tumor and immune genes CD8 IHC Target expression Live CD8 T cell PET under development Multiplex Immune IHC Spatial assessment of CD8 in response to treatment Dx grade assays for assessment of target expression 12 marker assay for evaluation of multiple immune cell subsets, endothelial cells, and tumor cells Enables spatial assessment of TILs
On-treatment biomarker profile defines response and lack of response Responder rela%ve'expression'(to'bsl)' 16" 14" 12" 10" 8" 6" 4" Baseline' On5Tx' PD-L1 Baseline On-treatment 4 weeks PD-L1 2" 0" PD*L1" Granzyme*A" Granzyme*B" Perforin" EOMES" IFNg" CXCL9" CD8A" Non-responder rela%ve'expression'(to'bsl)'' 16" 14" 12" 10" 8" 6" 4" Baseline' On5Tx' PD-L1 Baseline On-treatment 6 weeks PD-L1 2" 0" PD*L1" Granzyme*A" Granzyme*B" Perforin" EOMES" IFNg" CXCL9" CD8A"
Expression of different immune inhibitory factors may not correlate with lack of response to anti-pdl1 Summary of Best Response in lung cancer Biomarker status ORR a RECIST 1.1 PD rate PD-L2 high b 20% (13/66) 35% (23/66) PD-L2 low b 19% (12/63) 46% (29/63) All c 21% (36/175) 37% (65/175) High tumor PD-L2 expression does not reduce response rate to anti-pdl1 a ORR includes investigator-assessed unconfirmed and confirmed PR/CR by RECIST 1.1. b PD-L2 low/high is defined as patients with tumor PD-L2 level lower/equal to or higher than the median PD-L2 level in all patients. c All patients include PD-L2 high patients, PD-L2 low patients and patients with unknown tumor PD-L2 status. Patients first dosed at 1-20 mg/kg prior to October 1, 2012; data cutoff April 30, 2013. Kohrt et al. SITC 2013
PD-L1 patient immune biomarker analysis guides research and clinical development Immune marker expression analysis (illustrative) Targets elevated in non-responders Indication cbind(1:nc) Myeloid Signature APC Signature NK cell Signature IFNg Signature IB Signature B cell Signature Teff Signature Th2 Signature Compounds moving into clinic Negative regulator NME1 Anti-cytokine NME2 Positive regulator NME3 Treg Signature Th17 Signature Melanoma SCC NSCLC RCC Adeno NSCLC Bladder TNBC HER2+BC CRC HR+BC 2 1.6 2 0.67 1 0.22 0 1.1 1.6 2-1 -2
Example: NME1 is a negative regulator discovered from biomarker analysis Median Tumor Volume (mm 3 ) 10000 1000 10000 100 Median Tumor Volume (mm 3 ) Control anti-pd-l1 NME1 Control anti-pd-l1 NME1 Complete Remission (CR) anti-pd-l1 + NME1 10 0 10 20 30 40 60 Day 1000 anti-pd-l1 + NME1 100 Complete Remission (CR) 10 0 10 20 30 40 60 Day Negative regulator combines in PD-L1 non-responsive model
NME3: positive regulator targeting two steps in the cycle anti-ox40 Accelerate T cell response to antigen anti-ox40 3 4 5 2 Immunosuppression Anti-PDL1 6 Inhibit T regs anti-ox40 1 7
OX40 function and potential in oncology Promote antigen dependent effector T cell activation and T regulatory cell inhibition OX40 engagement on T reg cells Rationale for targeting OX40 in oncology Antigen Presenting Cell OX40 OX40L Dual mode of action: Co-stimulation of effector T cells Inhibition of regulatory T cells T reg Reduced risk of toxicity TCR OX40L OX40 OX40L Suppressive T cell Complementary MoA to blocking inhibitory receptors Potential to overcome suppressive signals from multiple inhibitory receptors OX40 IFN-γ Effector T cell Adapted from Nature Rev Immunol. 4:420 (2004).
Potential for activity in multiple tumor types Pre-clinical efficacy and durability of response OX40 is expressed in a variety of tumors Colorectal cancer Breast cancer Anti-OX40 increases intratumor T eff cells while depleting T regs IFN-γ Fold Change (Rel to Avg Control) Increase in intratumoral T eff cells (CD4+CD8) 20 18 16 14 12 10 8 6 4 2 0-2 -4 control a-ox40 control a-ox40 Foxp3/CD4(%) 60 40 20 Decrease in intratumoral T reg cells (FoxP3+) 0 0 5 10 15 20 day control a-ox40 day 2 day 9
Anti-OX40 can induce durable responses and immunity as a single agent Pre-clinical efficacy and generation of tumor-specific immunity Tumor Volume (mm 3 ) Primary Tumor Challenge (EMT6) 3000 2000 1000 0 0 10 20 30 40 50 Treatment day Control Anti-mouse OX40 Tumor Volume (mm 3 ) Re-challenge (EMT6 or CT26) 2000 1500 1000 500 0 0 10 20 30 day No Treatment CT26 Secondary EMT6 Secondary EMT6 Primary
Increase in Teff cells by anti-ox40 may create need to combine with anti-pdl1 anti-ox40 OX40 OX40L IFN-γ" T cell IFNγ PD-L1 increase PD-1 anti-pdl1 CD8 HLA PD-L1 Tumor cell Chen & Mellman (2013) Immunity T cell receptor
Can combination of anti-pdl1 with chemo- and targeted agents extend benefit to more patients? Hypothetical OS Kaplan Meier curves Control Targeted Therapy Immunotherapy Immunotherapy+ Targeted Therapy Agents must be safe in combination with anti-pd-l1 Targeted/chemo therapy should not interfere with immune response or immunotherapeutic mechanism of action
Combinations may extend the benefit of anti-pdl1 Chemo and targeted therapies Chemotherapy Targeted agent Tumor Volume, mm 3 3000 2500 2000 1500 1000 oxaliplatin Control α-pdl1 Tumor Volume, mm 3 3000 2500 2000 1500 1000 docetaxel Control combo α-pdl1 Tumor Volume (mm3) 2500 2000 1500 1000 MEKi CT26 08-1033O CT26 (Kras mut ) Control MEKi α-pdl1 500 0 0 6 12 16 22 29 36 Dosing Day combo 500 0 0 5 10 15 20 25 Day Dosing 500 0 0 10 20 30 40 50 Dosing control Day GDC-0973 (7.5mg/kg) apdl1 GDC-0973 (3mg/kg) + apdl1 α-pdl1/ MEKi Biomarker analysis in progress to identify combinations with enhanced efficacy
Recognition of cancer cells in the absence of T cell immunity ImmTACs and bispecifics 4 3 5 2 6 Recognition of cancer cells by T cells (CTLs, cancer cells) ImmTACs Bispecifics 1 7
Recognition of cancer cells ImmTACs and bispecifics Targeting intracellular tumor markers Targeting extracellular tumor markers Cancer cell Tumor antigen TCR Knob into holes full-length IgG T cell Immune-mobilizing mtcr Against Cancer* T-cell Dependent Bispecific *In colalboaration with Immunocore
K&H CD19(HD37)/UCHT1 #26975 K&H CD20(2H7)/UCHT1 #26975 K&H CD22(12F7)/UCHT1 #27608 Examples: B-cell Bisfab hucd79a(7h7)/u and HER2 #30972 bispecifics Bisfab hucd79b(17a7)/u #33236 Killing of endogenous B-cells by endogenous T-cells in healthy donor PBMCs % of % endo B cell B Killing depletion 100 80 60 40 20 0-20 0.1 1 10 100 1000 10000 pm Target 1: 8.0 pm Target 2: 22 pm Target 3: 70 pm Target 4: 8.6 pm Target 5: 426 pm 24 hour assay Tumor vol. (% change) 600 500 400 300 200 100 0 TBD efficacy in HER2 tumor mouse model Vehicle TBD Data 1 0 5 10 15 20 25 Days post treatment PBMC=Peripheral blood mononuclear cell
The cancer immunity cycle Many known targets, and likely many unknown Biomarker analysis will aid in prioritizing targets and combinations
Realizing the promise of cancer immunotherapy: Translating science into medical benefit (II) Hy Levitsky, MD Head, Cancer Immunology Experimental Medicine, Roche, Pharma Research and Early Development (pred) 29
The cancer-immunity cycle Trafficking of T cells to tumors Priming and activation Anti-CTLA4 Anti-CD137 (agonist) Anti-CD27 (agonist) IL-2 IL-12 Anti-CEA IL2v (RG7813) Anti-Cytokine (NME 2) Anti-OX40 (agonist) Infiltration of T cells into tumors Anti-VEGF Neo-vascular activators REDs Cancer antigen presentation Vaccines (IMA942 & INO-5150) Anti-CD40 (agonist) TLR agonists IFN-α clinical preclinical Release of cancer cell antigens Chemotherapy Radiation therapy Targeted therapy tumor Chen and Mellman. Immunity 2013 Killing of cancer cells Anti-PD-L1 Anti-PD-1 IDO inhibitors Neg. Regulator (NME 1) Anti-CSF1R (RG7155) Anti-CEA IL2v (RG7813) Anti-Cytokine (NME 2) Recognition of cancer cells by T cells CARs T cell bispecifics ImmTACs 30
1) Inflammatory tumor microenvironment TAM IL-10, TGF-β, CCL-2 MDSC CTL Th IL-2, IFN-γ B NK Tumor immunity Immuno suppression DC Treg Tumors induce an immunosuppressive environment by recruitment of myeloid cells A Depletion B Inhibition C Switching Anti-growth factor receptors Targeting lineage antigens Chemokine receptor blockade Inhibitory receptor agonists TLR agonists TLR - toll-like receptor 31
Anti-CSF1R phase I proof-of-mechanism RG7155 decreases tumor-associated macrophages in patients with various solid tumor types Pleural Mesothelioma, 900 mg RG7155 Significant reduction of tumor-associated macrophages in 11/13 patients treated in monotherapy and 15/15 patients treated in combination with SoC *pre- vs on-treatment tumor biopsies at 4 weeks, i.e. two cycles of treatment; Mφ macrophage cell line; CSF1R colony stimulating factor 1 receptor Ries et al., Cancer Cell 2014 (in press) 32
Anti-CSF1R phase I proof-of-mechanism in PVNS From model disease to development opportunity PVNS - pigmented villonodular synovitis Locally aggressive inflammatory joint disorder Neoplastic proliferation with overexpression of CSF-1 Change in SLD and SUVmax vs baseline (%) 10 0-10 -20-30 -40-50 -60-70 -80-90 -100 Patients who previously failed nilotinib and/or imatinib treatment 900 mg 1,350 mg 2,000 mg 1,000 mg % change in SLD vs baseline (MRI) % change in SUVmax vs baseline (FGD-PET) EORTC RECIST Patients % Partial Response 15/18 83 Partial Metabolic Response Clinically progression-free* 15/17 88 17/18 94 Rapid onset of measurable tumor shrinkage; associated with early functional and symptomatic improvement Ries et al., Cancer Cell 2014 (in press); * longest follow-up 22 months 33
2) Tumor targeted antibody-based immunotherapy of cancer Tumor cell NK cell T cell Macrophage A ADCC: recruit effector cells (NK, MØ) via FcgRIIIa B Support T-cells: supply cytokines and co-stimulatory signals C Activate T-cells: stimulate TCR on T cell Glycoengineered IgG1s Antibody-cytokine fusions, co-stimulatory antibodies T cell bispecific antibodies 34
2) Tumor targeted antibody-based immunotherapy of cancer Tumor cell NK cell T cell Macrophage A ADCC: recruit effector cells (NK, MØ) via FcgRIIIa B Support T-cells: supply cytokines and co-stimulatory signals C Activate T-cells: stimulate TCR on T cell Glycoengineered IgG1s Antibody-cytokine fusions, co-stimulatory antibodies T cell bispecific antibodies 35
Gazyva: first glyco-engineered antibody approved by FDA Obinutuzumab (Gazyva) APPROVED under breakthrough therapy designation Glyco-engineered to better engage immune cells (ADCC = Antibody-Dependent Cell-mediated Cytotoxicity) Unequivocal clinical benefit demonstrated in Phase III (CLL) Out-performed Rituxan/Mabthera in H2H Phase III Glyco-engineered for improved ADCC Moessner et al., Blood 115 (22), p4393, 2010; Goede et al., N Engl J Med 370, p1101, 2014 36
2) Tumor targeted antibody-based immunotherapy of cancer Tumor cell NK cell T cell Macrophage A ADCC: recruit effector cells (NK, MØ) via FcgRIIIa B Support T-cells: supply cytokines and co-stimulatory signals C Activate T-cells: stimulate TCR on T cell Glycoengineered IgG1s Antibody-cytokine fusions, co-stimulatory antibodies T cell bispecific antibodies 37
Amplifying T cell responses in the tumor IL-2 variant immunocytokine First truly High tumor binding targeted affinity immunocytokine to CEA for tumor targeting Inert Fc-part for improved PK & safety IL-2 variant (diminished CD25 binding) to increase number & activity of effector cells vs. immunosuppressive cells Ideal combination partner for ADCC competent antibodies such as Herceptin, obinutuzumab Phase I initiated Dec 2013 Klein et al., abstract number 486, AACR April 6-10, 2013, Washington, DC, USA CEA carcinoembryogenic antigen 38
Antibody-targeted IL-2 variant Preferentially stimulating immune cells in tumors Tumor-targeted cytokine Increasing T-cells in tumors High affinity for CEA 1 (tumor antigen) 1 carcinoembryonic antigen IL2v engineered to boost effector immune cells Targets to tumors in vivo (preclinical) Synergistic with ADCC mediated therapeutic mabs (preclinical) Phase 1 initiated Dec 2013 Vehicle CEA-IL2v treated CEA-IL2v increases T-cells & NK cells in tumors CEA-IL2v T-cell + - NK + - 0 5 10 15 Cells x 10 6 /gm tumor Nicolini et al., AACR poster 2014, San Diego, Abstract Number: 2579 39
Two major categories of solid tumors have been observed at diagnosis Inflamed Non-inflamed 20-30 % of patients T cell markers Expression of chemokines (attract leukocytes) Other immuno-regulatory factors (PD-L1, IDO, FoxP3) Tumor phenotype by T cell staining 70-80% of patients No lymphocytic infiltrates ü single agent immunotherapies rarely clinical response to single agent immunotherapies 40
Most tumors lack tumor specific T cell infiltrates A potential role for vaccination Increase frequency of relevant effector cells Change character of immune response: functional differentiation Alter lymphocyte trafficking Generate long-lived immunologic memory Drive cancer antigen-specific T cells into tumors 41
3) Tumor vaccines and immunoadjuvants Providing specificity and memory to combination immunotherapy Antigen Discovery Normal Cancer Antigen(s) Naked Peptides DNA/RNA Nano-particles Delivery Vehicle (platform) APC Activators Activators of innate immunity ( adjuvants ) DC CD40 agonist mab 42
Cancer vaccines strategy at Roche Incorporating rich antigen portfolio into alternative targeting platforms Tumor targets Vaccine platforms/ Immuno-adjuvants Enable & expand T-cells XPresident Antigen discovery platform Tumor derived peptides Vaccine platforms T-cell bi-specific antibodies Immunocheckpoint inhibitors Co-stimulatory antibodies Exploiting complementary strengths with our partners to co-develop combination assets 43
Anti-CD40 agonistic IgG2 mab Compelling combination partner for cancer immunotherapy Immune checkpoints ADCC competent antibodies CD40 agonist IgG2 mab T-cell agonists Cancer vaccines itme targets Multiple immune doublet opportunities 44
Seeking Synergy NME 4: depleting suppressive macrophages + + + + + + + NME 3: blocking immune checkpoints NME 2 NME 2 NME 2: antigen presenting cell activation NME 1 NME 1: T and NK cell amplification therapeutic vaccine: tumor antigen specific T cell priming Numbering of NMEs is for illustrative purposes only 45
The immunotherapist s dilemma...circa 2014 46
ASCO 2014 Roche highlights: Setting new standards of care Sandra Horning, M.D. Executive Vice President Chief Medical Officer and Head Global Product Development 47
Agenda Setting new standards of care Update on immunotherapy and bladder cancer results Lung: Tarceva +/- Avastin, alectinib Colorectal: Avastin and anti-vegf/ang2 Melanoma: cobimetinib in combination with Zelboraf Hematology: Bcl-2i and polatuzumab ADC (CD79b) 48
Cancer immunotherapy at Roche Pipeline overview Pre-clinical Phase I Phase II Phase III ImmTAC Neg. Regulator NME 1 IMA 942 Anti-cytokine NME 2 T-cell bispecific Anti-PDL1 Solid tumors Anti-PDL1+Avastin Solid tumors Anti-PDL1+cobimetinib Solid tumors Anti-PDL1+Zelboraf Met. Melanoma Anti-PDL1+Tarceva NSCLC Anti-PDL1 + immune m. Solid tumors Anti-PDL1 + Gazyva Heme tumors Anti-PDL1 NSCLC (Dx+) Anti-PDL1 NSCLC Anti-PDL1+Avastin Renal Anti-PDL1 Bladder Anti-PDL1 NSCLC 2/3 L Anti-PDL1 Bladder CSF1R humab CEA IL-2v Anti-OX40 Anti-PDL1 trials Start planned for 2014 Stimulator Anti-CD40 Inhibitor INO-5150 Note: Anti-PDL1 is listed as MPDL3280A in clinicaltrials.gov 49
Urothelial bladder carcinoma (UBC) High unmet need for patients with advanced disease New therapies in RCC, prostate and bladder cancer No. of drugs approved by FDA Prostate cancer RCC UBC US: 74, 690 new cases/year 1-5% metastatic, 20% muscle invasive Metastatic UBC prognosis: 5-year OS ~5% 2 US: no therapies approved for patients who relapse on cisplatin-based chemo Year Galsky et. al. 2013 1 Siegel R, CA Cancer J Clin 2014; 64:9-29. 2 http://seer.cancer.gov/statfacts/html/urinb.html (Feb. 2014) 50
MPDL3280A (anti-pdl1) in metastatic UBC Response by PD-L1 IHC status PD-L1 IHC (n) ORR (95% CI) IHC 3 (n=10) 50% (22-78) IHC 2 (n=20) 40% (21-64) IHC 1 (n=23) 13% (4-32) IHC 0 (n=12) 8% (0.4-35) Dx+ vs Dx- ORR (95% CI) 43% (26-63) 11% (4-26) 2 complete responses in the IHC 2 / 3 cohort 16 of 17 responding patients had ongoing responses at the time of data cut-off * Patients with complete responses. Patients with a CR had < 100% reduction of the target lesions due to lymph node target lesions. All lymph nodes returned to normal size as per RECIST v1.1.ic; tumor-infiltrating immune cells.best response is not known for 7 patients. Diagnostic PD-L1-positive: IHC 2 ( 5% but < 10% ICs); IHC 3 ( 10%. ), PD-L1 negative: IHC 0 (< 1% of Ics) and IHC 1 ( 1% but < 5%). Patients dosed by Nov 20, 2013 with a baseline tumor assessment. Clinical data cut-off was Jan 1, 2014. 51
MPDL3280A (anti-pdl1) in metastatic UBC Treatment related adverse events All Grade n (%) Grade 3/4 n (%) All 39 (57%) 3 (4%) Decreased Appetite 8 (12%) 0 Fatigue 8 (12%) 0 Nausea 8 (12%) 0 Pyrexia 6 (9%) 0 Asthenia 5 (7%) 1 (2%) Chills 3 (4%) 0 Influenza-like illness 3 (4%) 0 Lethargy 3 (4%) 0 Safety profile in bladder cohort consistent with safety in overall phase I population No new safety signals identified in the bladder cohort Clinical data cutoff Jan 1, 2014. Includes events occurring in 3 or more patients. Additional grade 3 or 4 events included thrombocytopenia and decreased blood phosphorous. 52
MPDL3280A (anti-pdl1) in locally advanced and metastatic UBC: next steps in development Breakthrough therapy designation Phase I Phase I results warrant move into pivotal studies Results observed to date suggest higher response rate in PD-L1+ patients Phase II Locally Advanced or Metastatic UBC N=330 Anti-PDL1 1200 mg IV Q3 weeks Primary end-point: Overall Response Rate FPI: Q2 2014 Phase III In preparation, expect start in 2014 Note: Anti-PDL1 is listed as MPDL3280A in clinicaltrials.gov 53
Anti-PDL1 in metastatic non-small cell lung cancer (mnsclc) FIR: Phase II Dx-positive advanced mnsclc PDL1-positive NSCLC n = 130 BIRCH: Phase II Dx-positive advanced mnsclc PDL1-positive NSCLC n = 300 POPLAR: Phase II 2/3L mnsclc All comers 2,3L NSCLC n = 287 Anti-PDL1 1200 mg IV Q3 weeks Anti-PDL1 1200 mg IV Q3 weeks Docetaxel 75 mg/m2 IV Q3 wk Anti-PDL1 1200 mg IV Q3 wk Primary end-point: ORR FPI Q2 2013 Data in-house end 14 Primary end-point: ORR FPI Q1 2014 Primary end-point: OS FPI Q3 2013 Enrollment complete OAK: Phase III 2/3L mnsclc All comers 2,3L NSCLC n = 850 Docetaxel 75 mg/m2 IV Q3 wk Anti-PDL1 1200 mg IV Q3 wk Primary end-point: OS FPI Q1 2014 Phase III trials in first line NSCLC in preparation Note: Anti-PDL1 is listed as MPDL3280A in clinicaltrials.gov 54 54
GNE/Spring PD-L1 IHC reagent potential MPDL3280A (anti-pdl1) for BIC Dx diagnostic program Development of the right assay Negative control (293) Positive control (293-PDL1) Positive tissue control (Placenta) Commercial*1* ProSci #4059 PDL1 IHC d Available lab tests Negative control (293) Positive control (293-PDL1) Positive tissue control Non-specific (Placenta) background Commercial*2* 27A2 Roche/Genentech Proprietary reagent GNE/Spring PD-L1 IHC Three pillars of the successful IHC test: good sensitivity Sensitivity: Detects signal from a few cells highly specific Specificity: Detects PD-L1 no protein background only CONFIDENTIAL INFORMATION DO NOT COPY OR FORWARD Precision: Reproducibly assigns cases to well-defined categories (IHC 0,1,2,3) Note: Anti-PDL1 is listed as MPDL3280A in clinicaltrials.gov PD-L1+ in Trophoblasts trophoblasts SP142 (GNE/Spring) Roche/Genentech* Proprietary*reagent* 55 PD-L1 I Hartm Spring Venta
MPDL3280A (anti-pdl1) development Readouts over the next 12 months Study Indication Readout Anti-PDL1 as single agent Phase I New tumor type First readout Lung Renal Bladder Melanoma Follow-up data Follow-up data Follow-up data Follow-up data Phase II (FIR) NSCLC (PD-L1+) First readout Phase II (POPLAR) 2/3L NSCLC First readout Anti-PDL1 in combination Phase Ib Multiple tumor types First readout Outcome studies are event driven, timelines may change 56
Agenda Setting new standards of care Update on Immuno-oncology and Bladder cancer results Lung: Colorectal: Melanoma: Tarceva +/- Avastin, alectinib Avastin and anti-vegf/ang2 cobimetinib in combination with Zelboraf Hematology: Bcl-2i and polatuzumab ADC (CD79b) 57
Lung cancer disease area Targeting multiple hallmarks of cancer Alectinib Sustaining proliferative signaling Tarceva Evading growth suppressors Deregulating cellular energetics 10 HALLMARKS OF CANCER Avoiding immune destruction apd-l1 Resisting cell death TARGETING MULTIPLE HALLMARKS TO ADDRESS: HETEROGENEITY COMPLEXITY RESISTANCE Enabling replicative immortality Genome instability & mutation Tumor-promoting inflammation Inducing angiogenesis Activation invasion & metastasis Hanahan and Weinberg, 2011 Cell 144:646, 2011. Avastin 58
Tarceva plus Avastin in EGFR+ mnsclc Japanese study JO25567 Non-squamous NSCLC Stage IIIB / IV or postop. recurrence Chemo naïve, PS 0-1 Active EGFR mutation exon 19 del or L858R without T790M R Tarceva 150 mg daily + Avastin15mg/kg q3w N=150 Tarceva 150 mg daily PD PD l Primary endpoint: Progression free survival l Secondary endpoint: Overall survival, Objective Response (Response Rate, Disease Control Rate, Response Duration), QOL, Safety l Exploratory: Biomarker analysis l Stratification: Gender, stage, smoking status, EGFR mutation type Study conducted by Chugai 59
Tarceva plus Avastin in EGFR+ mnsclc Japanese study JO 25567 PFS probability 1.0 0.8 0.6 0.4 0.2 0 0 Progression Free Survival 9.7 16.0 A+T T Median PFS (months) 16.0 9.7 Hazard ratio A+T T 2 4 6 8 10 12 14 16 18 20 22 24 26 28 Time (months) Number at risk A+T 75 72 69 64 60 53 49 38 30 20 13 8 4 4 0 T 77 66 57 44 39 29 24 21 18 12 10 5 2 1 0 0.54 [0.36;0.79] P=0.0015, log rank test Study conducted by Chugai Superior efficacy of A+T combination compared to Tarceva single agent in EGFR+ patients 60
Alectinib in ALK+ve NSCLC Brain-penetrant ALKi with promising efficacy & safety Crizotinib naïve ALK-positive patients post-chemotherapy Breakthrough therapy designation Study results Best Change from Baseline in Size of Target Lesions (%) 0-30 -100 CR PR SD NE Study conducted by Chugai Crizotinib-naive 1 Overall Response Rate 93.5% Crizotinib-failures 2 Overall Response Rate 54.5% CNS Objective Response Rate 3 52% Next steps Filed in Japan in Oct. 2013 Global Phase I/II study expected to readout in 2014 Start of Phase III in 2014 1 Seto et al, Lancet Oncology, Vol. 14, p. 590-598, 2013. 2 Gadgeel et al, WCLC 2013. 3 Ou et al, WCLC, 2013 61
Agenda Setting new standards of care Update on Immuno-oncology and Bladder cancer results Lung: Tarceva +/- Avastin, alectinib Colorectal: Avastin and anti-vegf/ang2 Melanoma: cobimetinib in combination with Zelboraf Hematology: Bcl-2i and polatuzumab ADC (CD79b) 62
Avastin in KRAS wt met. colorectal cancer Impact of the CALGB study Study design Results Untreated KRAS wt advanced or mcrc R Avastin+FOLFOX or FOLFIRI PD Avastin+ chemo Cetuximab+ chemo HR P value OS 29.0 29.9 0.925 0.34 N=1 142 Cetuximab+FOLFOX or FOLFIRI q2w PD PFS 10.8 10.4 1.04 0.55 Primary endpoint: Overall survival 90% powered to detect a HR of 0.80 (2-sided α=0.05), assumption: OS 22 months to 27.5 months, Δ=5.5 months Cetuximab failed to demonstrate survival benefit over Avastin Avastin survival benefit in metastatic colorectal cancer in 1L, 2L and TML 1-3 1 Hurwitz, et al. NEJM 2004; 2 Giantonio et al, JCO, 2007, 3 D. Arnold et al, JCO, 2012 63
CrossMAb: bispecific anti-vegf & Ang2 antibody Neutralizing two complementary angiogenic factors Phase II trial design Ang2 VEGF Open Label Safety Run-in 2 Cycles (4 wks) Induction Up to 8 Cycles (16 wks) Maintenance until PD, max. 24 mon CrossMAb + mfolfox-6 N = 6-18 1L mcrc N=140 Avastin + mfolfox-6 A2V + mfolfox-6 Avastin + 5- FU/LV A2V + 5- FU/LV Primary endpoint: Median progression free survival (mpfs) Secondary endpoints: Safety & tolerability, RECIST ORR, OS & duration of response, PK CrossMAb is listed as RO5520985 in clinicaltrials.gov ASCO 2014: Manuel Hidalgo, abstract #2525 64
Agenda Setting new standards of care Update on Immuno-oncology and bladder cancer results Lung: Tarceva +/- Avastin, alectinib Colorectal: Avastin and anti-vegf/ang2 Melanoma: cobimetinib in combination with Zelboraf Hematology: Bcl-2i and polatuzumab ADC (CD79b) 65
Cobimetinib plus Zelboraf Encouraging results of phase I in BRAF+ve mmelanoma BRAFi-naïve patients BRAFi naïve (n = 63) Vem-Progression (n = 66) Patients with events 1 33 (52.4%) 58 (87.9%) Median PFS (months) 13.7 2.8 95% CI for Median PFS 10.1 17.5 2.6 3.4 13.7m Response rate 87.3% 15.2% % pts alive at 1 year 83% 32% 95% CI for 1 year survival 73-93 19-45 Readout of Phase III trial co-brim expected later in 2014 Presented at EADO May 7, 2014 1 Applicable to PFS 66
Agenda Setting new standards of care Update on Immuno-oncology and Bladder cancer results Lung: Tarceva +/- Avastin, alectinib Colorectal: Avastin and anti-vegf/ang2 Melanoma: Cobimetinib in combination with Zelboraf Hematology: Bcl-2i and polatuzumab ADC (CD79b) 67
Strategies beyond great medicines Hematology Replace and extend Extend BCL-2i Replace BCL-2i ADCs ADC 79b Medical value Gazyva Chemo ADCs ADC 79b ADC 22 Gazyva ADC 22 MabThera MabThera CLL11 GOYA GALLIUM GADOLIN Murano (CLL) Romulus (NHL) Phase Ib CLL(G+Bcl-2i) Bcl-2 i. in collaboration with AbbVie (ABT-199) 68
B-cell hematologic malignancies A portfolio addressing multiple drug targets Anti CD22 ADC Rituxan Gazyva polatuzumab ved. GDC-0199 Adapted from Zenz et al, Nature Reviews Cancer, 2010, p. 37-50 69
ROMULUS: Phase II head to head study in NHL Study design R/R FL, n= 41 2/3+L DLBCL, n= 81 Rituximab (375 mg/m 2 ) + ADC (2.4 mg/kg) administered in every 21-day cycles Randomize 1:1 Anti-CD22 ADC + RTX polatuzumab vedotin + RTX PD PD polatuzumab vedotin + RTX Anti-CD22 ADC + RTX FL: follicular lymphoma, DLBCL: diffuse large B-cell lymphoma Morschhauser, F., ASCO 2014, abstract #8519 70
ROMULUS: Phase II head to head study in NHL Promising results for polatuzumab polatuzumab ved.+rituximab in FL Max % change tumor decrease from BL Regimen R/R DLBCL R/R FL polatuzumab vedotin + rituximab anti-cd22 ADC + rituximab ORR = 56% CR = 15% ORR = 57% CR = 24% ORR = 70% CR = 40% ORR = 62% CR = 10% Polatuzumab ved. selected for late stage development based on high level of anti-tumor activity Morschhauser, F., ASCO 2014, abstract #8519 71
Bcl-2 inhibitor (GDC-0199) single agent in R/R CLL Encouraging responses across patient subgroups Responses All n (%) n = 78 del (17p) n (%) n = 19 F-Refractory n (%) n =41 IGHV Unmutated n (%) n =24 Overall response 60 (77) 15 (79) 31 (76) 18 (75) Complete response 18 (23) 5 (26) 9 (22) 7 (29) Partial response* 42 (54) 10 (53) 22 (54) 11 (46) Stable disease 10 (13) 2 (11) 7 (17) 2 (8) Disease progression 2 (3) 1 (5) 1 (3) 2 (8) D/C Prior to first (W6) assessment 6 (8) 1 (5) 2 (5) 2 (8) Median PFS for patients treated at or above 400 mg has not been reached. In collaboration with AbbVie (ABT-199). J.F. Seymour, ASCO 2014, abstract # 7015 R/R CLL: relapsed/refractory chronic lymphocytic leukemia. 72
Bcl-2 inhibitor (GDC-0199)+R in R/R CLL Efficacy in combining with an anti-cd 20 antibody Best % change from baseline in Lymphocyte Count Response Response rate Complete response Partial response Stable disease Disease progression Discontinued prior to assessment Evaluable* n=25 21 (84%) 9 (36%) 12 (48%) 1 (4%) 1 (4%) 2 (8%) * Evaluable pts have reached the month 7 bone marrow assessment, discontinued, or progressed on therapy High level of complete response and MRD (6/8 CR, 75%) Results supported move into phase III (MURANO) study in R/R CLL In collaboration with AbbVie (ABT 199). Shuo Ma, ASCO 2014, abstract #7013, R: rituximab. MRD: minimal residual disease (PB or BM) 73
Bcl-2 inhibitor (GDC-0199) +R in R/R CLL Encouraging duration of response 200 mg ABT-199 cohort Cohort Dose dose 300 mg 400 mg 500 mg 600 mg 400 mg SE 0 5 10 15 20 25 Months on Study Months on study Most patients are still progression-free, even those on lower doses In collaboration with AbbVie (ABT-199). Shuo Ma ASCO 2014, abstract # 7013 R/R CLL: relapsed/refractory chronic lymphocytic leukemia. SE: safety expansion 74
Bcl-2 inhibitor (GDC-0199) Safety update No further clinical TLS 1 cases since program restart (120 new patients treated) New revised monitoring agreed with FDA: No hospitalization for low/ medium risk patients Hospitalization for high risk patients 2 : at treatment initiation and first escalation one week later In collaboration with AbbVie (ABT-199). 1 TLS: Tumor lysis syndrome. 2 High risk is currently defined at those patients who have large tumors (10+ cm) and those patients who have tumors 5-10 cm and high circulating lymphocyte counts 75
Bcl-2 (GDC-0199) development Next steps Study Indication Status Readout (exp.) CLL Phase II 17p del Enrolment complete 2015 Phase III combo with R (MURANO) R/R CLL Enrolling 2016 Phase III combo with Gazyva 1L CLL Start planned in 2014 2017 and beyond NHL Phase II + R, +BR Follicular lymphoma Start planned in 2014 2016 Phase Ib/II +R-/G- CHOP DLBCL Start planned in 2014 2016 In collaboration with AbbVie (ABT-199) Outcome studies are event driven, timelines may change. R=rituximab, G=obinutuzumab, B=bendamustine 76
Roche hematology pipeline Broad range of indications and approaches Phase I Phase II Phase III Bcl-2 inh (GDC 199) + Gazyva CLL Bcl-2 inh (GDC 199) CLL R/R 17p del Gazyva DLBCL Bcl-2 inh (GDC 199) NHL Erivedge AML Gazyva inhl relapsed Bcl-2 inh (GDC 199) AML polatuzumab ved. (CD 79b) NHL Gazyva inhl front-line Bcl-2 inh (GDC 199) Multiple myeloma pinatuzumab ved. (CD22) NHL Bcl-2 inh. (GDC 199) CLL R/R LSD1 inh (RG6016) AML MDM2 (RG738) AML ADC (RG7598) multiple myeloma Registration Gazyva 1 CLL ChK1 inh (RG7741) lymphoma New Molecular Entity RG 7845 heme tumors Additional Indication 1 Approved in US, submitted in EU 77
Oncology strategy and outlook Daniel O Day Chief Operating Officer, Roche Pharmaceuticals 78
Roche oncology: continued sales growth A portfolio of differentiated medicines (CHF mn) 25,000 20,000 15,000 10,000 5,000 10 medicines 14 tumor types 40 indications,0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Sales at 2013 exchange rates 79
Evolution of science and market in oncology Increasing competition and scientific complexity Anatomic Diseases Little Competition Disease Subsets 73 Key Players Oncogenic Mutations & Emerging Immunotherapy Increasing complexity in science Increasing market competition 30% of Industry Pipelines 1995 2006 Today 80
Roche strategy in oncology Summary 81
Key success factors in the new environment Best Science Smart Development Innovative Business Model Integrated biomarker expertise Top tier scientific talent First or best in class Shift paradigms in development Leverage Combinations Tailored approaches to access 82
Best science: integrated biomarker expertise Premium for innovation Generics OTC Pharma Dia Focus MedTech Personalized Healthcare at Roche Supports development of medically differentiated therapies PHC strategy applied to vast majority of pipeline molecules Leverage fully integrated biomarker and diagnostic expertise Differentiation 83
Best science: need top tier scientists Strong foundation in science key to guide decisions Hypothetical Example MoAs ALK Bcl-2 BCR BRAF CD20 CD22 CD79b CD40 EGFR HER2 Hormone HP IDO IGFR1 Immuno JAK MAPK MDM2 MEK OX40 NaPi2b PARP PI3K VEGF Strategy 1: Try everything High cost approach Strategy 2: Focus on the most promising combinations Requires scientific expertise and smart development ALK Bcl-2 BCR BRAF CD20 CD22 CD79b CD40 EGFR HER2 Hormone HP IDO IGFR1 Immuno JAK MAPK MDM2 MEK OX40 NaPi2b PARP PI3K VEGF 84
Smart development: aim at first and best in class Focus on most promising molecules Major Oncology Drug Launches Market share* Second-in class products Incrementally better products Breakthrough / Best in class crizotinib Zelboraf abiraterone Perjeta ipilimumab Ziv-aflibercept panitumumab nab-paclitaxel afatinib lapatinib ofatumumab cabazitaxe dasatinib axitinib temsirolimus pazopanib nilotinib Kadcyla enzalutamide Years post launch Source: Evaluate Pharma, Decision Resources, Roche internal analysis Note: *Market shares represent either % sales of target product relative to sales competing products in similar indications or patient shares 85
Smart development: paradigm shift I Adaptive clinical trials: Learning on the go Past Time/trial size Ph I Ph II Ph III Small phase I è Proof-of-concept in phase II è Large phase III Similar path for each new indication Present / Future Ph I Pivotal ph II/III indication 1 Pivotal ph II/III indication 2 Pivotal ph II/III indication 3 Large phase I, proof-of-concept for multiple indications è Multiple pivotal phase II/III with adaptive trial design 86
Smart development: paradigm shift I Learning on the go in PD-L1 Past Time/trial size Ph I Ph II Ph III Small phase I è Proof-of-concept in phase II è Large phase III Similar path for each new indication Example PDL1 NSCLC diagnostic approach 2013 2014 FIR PII 1/2L Dx+ ORR (GO28625, N=130) BIRCH POPLAR PII Dx+ ORR PII 2L+ Dx+/- vs. Doce OS (GO28754, N=400) (GO28753, N=300) OAK PIII 2L+ Dx+/- vs. Doce OS (GO28915, N=850) Data from Phase Ia NSCLC, FIR and POPLAR can be used to modify BIRCH and OAK before they read out 87
Smart development: paradigm shift II Surrogate end-points: fast readout of clinical efficacy Good surrogate endpoint in the causal pathway of the disease Disease Intervention Surrogate endpoint True clinical outcome Eg Early Breast Cancer PCR Eg Hematology MRD Neo-adjuvant treatment Pre-surgery, 4-6 cycles SURGERY Adjuvant treatment Post-surgery up to 1 year PCR: Pathological Complete Response Absence of cancer cells 88
Smart development: paradigm shift II Surrogate end-points with Perjeta and Gazya Good surrogate endpoint in the causal pathway of the disease Disease Intervention Surrogate endpoint True clinical outcome E.g. early breast cancer (Perjeta) PCR E.g. hematology (Gazyva) MRD PCR: Pathological Complete Response Absence of cancer cells US approval for Perjeta Sept 2013 MRD: Minimal Residual Disease Provided strong confidence in results earlier 89
Smart development: paradigm shift III Disease area approaches hematology example Pre-clinical Phase I Phase II Phase III Approved MabThera/Rituxan Gazyva GDC-0199 * BCL-2 inhibitor Polatuzumab vedotin anti-cd79b-adc MDM2 antagonist NHL, CLL approved CLL approved in US; ongoing in NHL NHL, CLL, MM, AML NHL AML and solid tumors Erivedge AML, solid tumors Anti-PDL1 Heme Malignancies & solid tumors ADC (RG7598) MM RG7845 Heme malignancies T-Cell Dependent Bispecific (TDB) AB, PIM, CD44, Others Heme malignancies ADC=Antibody-Drug Conjugate; AML=Acute Myeloid Leukemia; CLL=Chronic Lymphocytic Leukemia; NHL=Non-Hodgkin s Lymphoma; *Co-development molecule with AbbVie 90
Smart development: leverage combinations 26 disclosed combinations in 9+ tumor types Solid tumors Breast cancer Perjeta Perjeta Herceptin Herceptin ü ü Kadcyla Perjeta Ph3 Kadcyla Perjeta Ph3 Perjeta Herceptin Ph2, 3 Perjeta Herceptin Ph3 GE-anti-HER3 Perjeta Ph1 Gastric, brain, kidney and others Perjeta Herceptin Ph3 Anti-PDL1 Avastin Ph2 Cobimetinib AKT inh Ph1 Cobimetinib Pictilisib (PI3Ki) Ph1 GE-anti-HER3 Tarceva Ph1 Colon cancer Anti-PDL1 Avastin Ph1 Lung cancer Avastin Tarceva Ph2 Anti-PDL1 Tarceva Ph2 Pictilisib (PI3Ki) Avastin Ph1 Melanoma Cobimetinib Zelboraf Ph3 Anti-PDL1 Zelboraf Ph1 Locally advanced solid tumors Anti-PDL1 Cobimetinib Ph1 Anti-HER3/EGFR Cobimetinib Ph1 Hematological tumors Lymphoma Anti-CD22 ADC Rituxan Ph2 Anti-CD79b ADC Rituxan Ph2 Bcl2 inh Rituxan (+B) Ph1 Leukemia Bcl2 inh Gazyva Ph1 Bcl2 inh Rituxan Ph1 Bcl2 inh Rituxan (+B) Ph1, 3 ü Studies read out/filed/approved 91
Innovative business models: tailored access Developed markets - access through innovative pricing Today Pack based pricing Personalized Reimbursement Models Value based pricing Episode-of-care based Future Undifferentiated $$ by vial + Combinations Indication based Need for data from healthcare systems 92
Innovative business models: tailored access Developing markets multiple approaches Examples of approaches Patient assistance programs + Partnership with Cancer Foundation, Ministry of Health >24,000 more patients treated since 2011 Differential pricing + Access to the public reimbursement >1,900 more patients treated since 2013 Multiple approaches to ensure access to medicines in emerging markets No one-size fits all solution depends on market characteristics and segments Note: Incremental patients treated are current estimates based upon available new patient starts data through YE 2013 17
Key success factors in the new environment Best Science Smart Development Innovative Business Model Integrated biomarker expertise Top tier scientific talent First or best in class Shift paradigms in development Leverage Combinations Tailored approaches to access 94
Roche strategy in oncology Summary 95
Comprehensive approach to cancer Multiple ways to target cancer Tumor microenvironment Angiogenic signaling HER2 signaling Antibody-drug conjugates PI3K/AKT/mTOR Cell death apoptosis Cancer immunotherapy Activating immune system 96
enabling a disease area approach Focused and distinct projects per disease area Tumor type Global incidence (%) Late stage projects Early stage projects Colorectal & gastric 22 2 8 Lung 13 7 7 Breast 11 11 8 Ovarian/GYN 8 3 1 Hematology 7 7 15 Skin 2 4 4 Other 25 6 12 Total 40 55 Multiple assets require disease area strategies 97
2014: Key upcoming oncology readouts Compound Indication Readout cobimetinib (MEKi) Met. melanoma Ph III (co-brim) Kadcyla & Perjeta HER2+ mbc (1 Line) Ph III MARIANNE alectinib (ALKi) NSCLC Ph II anti-her3 EGFR DAF Head and neck, colorectal cancer Ph II (MEHGAN, DARECK) anti-pdl1 Solid tumors Ph I/II updates Outcome studies are event driven, timelines may change 98
Oncology strategy summary 1 Best science: Leveraging our top oncology talent to focus on the most promising molecules and combinations 2 3 Smart clinical development: Delivering first and/or best in class medicines Making smart development decisions and trial designs Using a disease area approach and leveraging combinations Innovative business models: Tailoring approaches to ensure access in both developed and developing markets 99
Doing now what patients need next