Stratified Medicines and Companion Diagnostics

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1 Stratified Medicines and Companion Diagnostics An Industry Viewpoint 2 nd May 2013 Eddie Blair Managing Director Integrated Medicines eddie.blair@integratedmedicines.co.uk About IML Formed in February 2003, ex-gsk Predictive Medicine Group Work within industry, government, other stakeholders 3. Identify test technology and broker relationship 2. Establish value of Combined Product profiles 4. Manage integrated programmes to deliver CDx and SRx 1. Align test and drug Product profiles Value Proposition Calculator Added value of companion programme Business relationship Portfolio Management IP Generation & Exploitation GSK & Smarthaler SE & tuneable magnetic proteins TSB SBRI on sepsis care BLANK.POT 1

2 Stratified Medicines THERAPEUTIC NEED INNOVATIVE MEDICINES Right Medicine Right Patient Right Disease Right Time 3 PATIENT-TARGETED THERAPIES Right Dose Right Response Right Price Stakeholders Healthcare Providers (clinicians, primary practitioners, hospital workers) Government/ Regulators/ Payors Patients (consumer and beneficiary of healthcare) Industry (Pharma co s & associated valuechain, eg, Dx Co, CRO) BLANK.POT 2

3 Keys issues with medicines today are.. Safety and efficacy 5 New market models for pharma* Low Hi volume, low price Billion dollar sales line Cost of medicines Moderate High BLOCK-BUSTER One drug fits all; poor response rates (20-80%) & risk of SAEs (>1%) SEGMENT-BUSTER Drug responses monitored for efficacy and SAEs using diagnostic-type test (CDx) Low volume, hi price NICHE-BUSTER Drug given to specific patients determined by predictive tests (Mol Dx; PGx) 6 *Blair (2009) All Selected Targeted Number of patients treated BLANK.POT 3

4 CDx offers increased revenue through better commercialization* *Trusheim et al NRDD 6: 287 (2007) *Agarwal PharmExec.com (Jan, 2009) 7 Opportunity Map for CDx* Asthma Diabetes CNS Drugs *Davis et al (2009) Nature Rev Drug Disc 8: BLANK.POT 4

5 MIT Stratified Medicine Model* Linking Development & Biomarker Performance to Patients & Markets Sales Biomarker Performance Efficacy & Population Enrichment Adoption Rate & Market Share Cash Flow & NPV Patient Benefits & AEs Pricing: Drug & Diagnostic Market Size *Trusheim et al Nature 2011 PharmaCo-DxCo Relationships* Relationship structure Risk-sharing or hybrid Make-to-order 4. AZ/ Prom Outcome: budesonide Market and penetration $1.9bn (98%R, 2%D) Prometheus Serology 7 test Simple Feefor-service 2. Amgen panitumumab Use-to-order Outcome: Market and expansion KRAS $1.3bn test (99%R, 1% D) Integrated Outcome: 1. Pfizer Co-developed maraviroc test & medicine and $1.8bn (97%R, 3%D) Monogram trofile test 3. Turnaround GSK abacavir Outcome: Product and Rescue 1.8bn HLA (90%R, SNP 10% test D) Lo Diagnostics Partner Influence ( Pharmaceutical Partner Urgency) Hi *Blair (2008), Blair (2010); Blair & Blakemore (2011) 10 BLANK.POT 5

6 NPV* Matrix v2 Full Risk- Sharing (5% drug royalty) NPV A Costs to Dx Co = $FULL Rx revenues to Dx Co = $5% Dx Co Rx risk = Exposed NPV B Costs to Dx Co = $FULL Rx revenues to Dx Co = $5% Dx Co Rx risk = Exposed NPV C** Costs to Dx Co = $FULL Rx revenues to Dx Co = $5% Dx Co Rx risk = Exposed Revenue Scenarios Hybrid Risk & Fee (2% drug royalty) Fee-for- Service (No royalty) NPV D Costs to Dx Co = $PART Rx revenues to Dx Co = $X+2% Dx Co Rx risk = Exposed NPV G** Costs to Dx Co = $0 Rx revenues to Dx Co = $0 Dx Co Rx risk = Part Exposed NPV E** Costs to Dx Co = $PART Rx revenues to Dx Co = $X+2% Dx Co Rx risk = Part Exposed NPV H Costs to Dx Co = $0 Rx revenues to Dx Co = $0 Dx Co Rx risk = Not Exposed NPV F Costs to Dx Co = $PART Rx revenues to Dx Co = $X+2% Dx Co Rx risk = Part Exposed NPV I Costs to Dx Co = $0 Rx revenues to Dx Co = $0 Dx Co Rx risk = Not Exposed 11 New Test Co- Developed with New Drug Existing Test Made/ Used to Order for Newto-Market Drug Relationship Scenarios *NPV discount factor varied (10%, 12.5%, 15%) as surrogate for relative risk **Red text is most-likely revenue-relationship scenario intersection Existing Test Rescues Drug Sales (Repositioning?) The Price vs Value Imbalance* Targeted Therapy Xalkori (critozinib, Pfizer) Zelboraf (vemurafenib, Plexxikon/ Diiachi Sankyo/ Roche) Herceptin (trastuzumab, Genentech/ Roche) Annual Price Companion Diagnostic $115,200 Vysis ALK Break Apart In Situ Hybridisation FISH Probe Kit (Abbott Molecular) $56,400 Cobas 4800 BRAF V600 Mutation Test (Roche Molecular) Test Price Model $1,500 Turnaround (ALK positivity ~7%) $120 $150 Integrated (BRAF V600E mutation ~40%) $70,000 HercepTest (Dako) $500 Turnaround (HER 2 expression score 3+ ~ 10%) Value TBD $144M ($213M**) $620M** 12 * Blair, E.D., Stratton, E.K. and Kaufmann, M. 2012b. ** Projected Annual Sales 2012 based on HY12 roche.com BLANK.POT 6

7 Mitigating Delays Platform Bridging* Patient selection hurdle A CDx development* Based on phase II samples upon agreement with Regulators Phase III trial CDx clin. trial assay IND submission/ coapproval Delayed, but with cdx for patient selection low B Phase III trial Platform A CDx development Platform B based on phase II samples CDx bridging study Platform B based on phase III samples upon agreement with Regulators IND submission/ approval Delayed, but with Plat B CDx for patient selection low C Phase III trial Platform A IND submission/ approval As planned with Platform A for patient selection high CDx development Based on phase II samples upon agreement with Regulators CDx bridging study Platform B based on phase III samples upon agreement with Regulators IND submission/ approval Label change: Plat B CDx for patient selection low *Martina Kaufmann, IML Stakeholders Healthcare Providers (clinicians, primary practitioners, hospital workers) Government/ Regulators/ Payors Patients (consumer and beneficiary of healthcare) Industry (Pharma co s & associated valuechain, eg, Dx Co, CRO) Modified from Brandenberger & Nalebuff, 1996 BLANK.POT 7

8 Relationships 15 British Medical Journal 1999;319 (18 September):762. Key Driver: Changes Predictive to Medicine medical practice Earlier diagnosis + effective treatment = better long term outcome Predictive medicine Reactive medicine Relative Treatment Efficacy Relative Disease Severity 16 BLANK.POT 8

9 Observations If patient is not obviously ill, how will benefit be measured and compensated? How will clinical studies demonstrate preventative benefit in timescale of drug development? Will prevention of one disease merely postpone eventual burden on healthcare system? How will insurers and other parties view risk based on prediction and prevention? 17 Bibliography Little S, Blair ED: Pharmacodiagnostics: technologies, competition, and market models. Insight Pharma Reports Blair ED, Clarke BR & O Neill T (2011) Sustaining development of stratified medicines in the UK healthcare system: a commentary Blair, E.D. Assessing the value-adding impact of diagnostic-type tests on drug development and marketing. Mol. Diagn. Ther. 2008, 12, Personalized Medicine 8: Blair, E.D. Predictive tests and personalised medicine. Drug Discov. World (Autumn) 2009, 22, Blair, E.D. Molecular diagnostics and personalized medicine: Valueassessed opportunities for multiple stakeholders. Pers. Med. 2010, 7, Blair, E.D. Blakemore, J.A. Drug-diagnostic co-development: How to harness the value. Drug Discov. Today 2011, 16, Blair, E.D., Stratton, E.K. Expert and Kaufmann, Rev. Mol. M. The Diagn. Economic 12: Value of Companion Diagnostics and Stratified Medicines. Expert Rev Mol Diagn 2012, 12 (8): Blair, E.D., Stratton, E.K. and Kaufmann, M. Aligning the Economic Value of Companion Diagnostics and Stratified Medicines. J. Pers. Med. 2012, 2, Thomas J, Stratton E & Keppens M (2012) Companion diagnostics: emerging strategies and issues in pharmaceutical development 18 BLANK.POT 9