A2 - Personalized Medicines: Challenges and opportunities from the bench to patients: Pricing and Market Access - Grueger - Salon C
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A2 - Personalized Medicines: Challenges and opportunities from the bench to patients: Pricing and Market Access - Grueger - Salon C






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A2 - Personalized Medicines: Challenges and opportunities from the bench to patients: Pricing and Market Access - Grueger - Salon C A2 - Personalized Medicines: Challenges and opportunities from the bench to patients: Pricing and Market Access - Grueger - Salon C Presentation Transcript

  • Personalized medicines: Challengesand opportunities from the bench to patientsPricing & Market AccessJens Grueger, PhDVice President, Head of Global Pricing & Market Access, Roche Pharma AGCADTH Symposium Personalized Medicine , St. Johns, May 6, 2013
  • Patient isseen bydoctor,and tumoris biopsiedSystem outputsevidence-basedtreatmentoptionsSystem takes indiagnostic, clinical,registry, and EMR data1 23New hypothesesto test in R&D,patients mostlikely torespondidentified(enables smallertrials)5Patients can be more effectivelymatched to clinical trials6MD selects treatmentplan, and patientoutcomes are tracked4Medical PracticeClinicalDevelopmentDatabase and adaptivetreatment algorithmWhat tomorrow’s personalized healthcaresetting may look like
  • Critical questions for Health TechnologyAssessment and market access in a personalizedhealthcare setting• Assessment of added therapeutic value –different across disease segments• Pricing & reimbursement: value based pricewill vary across disease segments• Identification of disease segments will dependon diagnostic technology• Efficacy vs effectiveness: needs to be assessedboth at the medicine and the diagnostic level
  • Example: Vemurafenib in BRAF+ metastatic melanoma asrequested for co-dependent reimbursement process inAustraliaResearch question in FinalDecision Analytic Protocol:Is BRAF genetic testing for V600Eor V600K mutations in tumorsamples of patients withresectable stage IIIB, IIIC orunresectable stage IIIA, IIIB, IIIC orstage IV cutaneous melanoma, inaddition to usual care ortargeted treatment withvemurafenib in patients withunresectable stage IIIC ormetastatic stage IV cutaneousmelanoma, safe, effective andcost-effective compared to usualcare alone without BRAF testing?12 scenarios requested in total, basedon:• Definition of V600 mutation:– All V600, V600E and K, V600E• Stage of disease:– Unresectable stage IIIC or stage IV(trial-based)– Resectable stage IIIB, IIIC orunresectable stage IIIA, IIIB, IIIC orstage IV– Resectable or unresectable stageIIIA, IIIB, IIIC or stage IV– Unresectable stage IIIA, IIIB, IIIC orstage IV
  • In a personalized healthcare setting, we needa differentiated model of value• Medicines will have a different benefitdepending on the specific mechanisms thatunderlie the disease pathology in a patient• Diagnostic procedures will detect differenttargets with different characteristics(sensitivity and specificity)• Optimal patient outcome under real worldconditions will require an alignedcombination of diagnostics, medicines,outcomes measures and patient treatmentpathways
  • Personalised Healthcare will require a newpersonalized reimbursement model based onvalue• The prices for our medicines reflect thevalue that the innovation delivers topatients, providers, and societies• The value of our medicines in a personalizedhealthcare setting varies across differentdisease segments• If prices are based on value, then theyshould vary in line with disease segments
  • Implementing personalized reimbursementmodels will require an appropriate IT andfinancial infrastructure• Medicine will be sold at a nominal price• Different reimbursement arrangements (egpatient access schemes, cost caps, discounts) willbe defined by disease segment and treatmentcombination• Timely information on actual utilization of themedicine will be collected• Financial reconciliation based on utilization data
  • Example UK: Systemic Anti Cancer TherapyDataset can facilitate personalizedreimbursement models• Defined dataset to be reported by all cancer treatment centersfor all patients treated within the NHS• Initial 8 data fields sufficient for personalized reimbursementmodels• Data will be submitted and aggregated by NHS• Personalized reimbursement model is a special form of patientaccess scheme
  • Personalized Reimbursement Models inCanada?• Could the British Columbia Cancer Agency (BCCA) CancerRegistry evaluate the patient outcomes to determine the valuefor each medication?• Could different databases be integrated in Ontario to facilitatethis reimbursement model?– prescription data from the Ontario Drug Benefit ProgramDatabase– physician claims data (OHIP)– hospitalization data (CIHI)
  • Why can’t we make it simple and rathercontinue to work with an “average price”• Value assessment (national and provinciallevel) is conducted by disease segment• Providers and local payers have becomeprice sensitive:– Will be happy to use medicine in “highvalue segment” where value is above theaverage price– Will not support utilization in lowervalue segments, where other treatmentalternatives are deemed more cost-effective• Patient access to innovative targetedtherapies will be limited or delayed
  • Conclusions: personalized healthcare requirea new personalized reimbursement model• Different levels of price/reimbursementdependent on disease segment• In line with value based pricing• Ensures patient access while providingrewards for industry• Practical implementation requires a basicregistry infrastructure like SACT
  • We Innovate Healthcare