Session 169 L, Quantifying Excess Specialty Drug Risk Moderator: Patrick Gallagher, FSA, FCAS Presenters: Patrick Gallagher, FSA, FCAS Robert Bachler, FSA, FCAS, MAAA SOA Antitrust Disclaimer SOA Presentation Disclaimer
Modeling High Cost Rx Discussion of Inputs Rob Bachler, FSA, FCAS, MAAA October 26, 2016
Agenda Available data sources Briefing on specific conditions Important considerations 2
Available Data Sources
Data Sources Publicly Available CDC Website (www.cdc.gov) FDA New and Generic Drug Approvals website Drug manufacturer announcements 4
Data Sources Available for a cost Pipeline databases BioMedTracker, EvaluatePharma, etc Newsletters/Reports 5
Specific High Cost Conditions
Hepatitis C Overview Prevalence: 3,500,000 people in U.S. 1 Genotypes (viral strain) 2 GT 1-73.7% GT 2-14.9% GT 3-7.4% GT 4 through 6-4% combined Many plans require Metavir Score F3 or F4 before treatment 1. Source: http://www.cdc.gov/hepatitis/hcv/hcvfaq.htm#section1 accessed March 16, 2016 2. Sy, Theodore, Mazen, M. Epidemiology of Hepatitis C Virus (HCV) Infection. Int. J. Med. Sci 2006; 3: 41-46. 7
Hepatitis C Treatment Current Hepatitis C products available Brand Approval Date Genotypes treated* Price x 12 week treatment (WAC) Manufacturer **Olysio 11/23/2013 1, 4 $66,360 Janssen Therapeutics Sovaldi 12/6/2013 1, 2, 3, 4, 5, 6 $84,000 Gilead Sciences Harvoni 11/10/2014 1, 4, 5, 6 $94,500 Gilead Sciences Viekira 12/19/2014 1 $83,319 AbbVie **Daklinza 7/24/2015 1, 3 $63,000 Bristol Myers Squibb Technivie 7/24/2015 4 $76,653 AbbVie Zepatier 1/28/2016 1, 4 $54,600 Merck Epclusa 6/28/2016 1, 2,3,4,5,6 $74,760 Gilead Sciences * Information provided by product specific prescribing information or AASLD treatment guidelines **Olysio and Daklinza must be co-administered with Sovaldi WAC Wholesale Acquisition Cost 8
Hepatitis C Treatment Expected Hepatitis C products within the next two years Brand (Generic) Estimated Launch Date Phase of Development Genotype Treated Est. Annual Cost per Patient Manufacturer ABT-493/ABT-530 (glecaprevir/pibrentasvir) Q4 2017 Phase III 1, 2, 3, 4, 5, 6???? AbbVie (sofosbuvir/velpatasvir/gs-9857) Q4 2017 Phase III 1, 2, 3, 4, 5, 6???? Gilead Sciences 9
Hemophilia Overview Bleeding disorder blood does not clot appropriately Hemophilia A Factor VIII deficiency Hemophilia B Factor IX deficiency Lifelong disease Genetically inherited disease Affects predominantly males, females are carriers 20,000 people in the U.S. with hemophilia 1 in 5,000 live births (males) Source: Centers for Disease Control and Prevention. Hemophilia Facts. August 26, 2014. Accessed at http://www.cdc.gov/ncbddd/hemophilia/facts.html on February 22, 2016. Hemophilia A. National Hemophilia Foundation. Accessed February 21, 2015, at https://www.hemophilia.org/bleeding-disorders/types-of-bleeding-disorders/hemophilia-a. 10
Hemophilia Treatment For Hemophilia patients, 94% of total healthcare costs are associated with replacement clotting factors 1 Severity of disease, including inhibitors, determines frequency and dose received 1. Journal of Medical Economics. Burden of illness: direct and indirect costs among persons with Hemophilia A in the United States. March 9, 2015. Accessed at http://www.ncbi.nlm.nih.gov/pubmed/25660324 on March 19, 2016. 11
Hemophilia Treatment Three products recently approved Kovaltry (Hemophilia A) twice weekly dosing Afsytla (Hemophilia A) twice weekly dosing Idelvion (Hemophilia B) dosing reduced to every 14 days Pipeline Trends Better stability Longer acting (once weekly dosing) Decreased inhibitor formation Alternatives for Inhibitor therapy 12
Cancer Overview History of cancer treatments: Cytotoxic chemotherapy Move toward targeted therapies, oral therapies, less side effects 50% of total oncology spend in U.S. is for targeted therapy 1 Cancer therapy 14.5% total specialty spend in 2015 2 19 new oncology drug approvals in 2015 Average cost for full-treatment is $150,000 / year 3 1. Developments in Cancer Treatments, Market Dynamics, Patient Access and Value IMS Institute for Healthcare Informatics. May 2015. 2. Source: ESI Drug Trend Report 2015 accessed at http://lab.express-scripts.com/lab/drug-trend-report on March 23, 2016. 3. IMS Institute for Healthcare Informatics (2014). Innovation in Cancer Care and Implications for Health Systems. 13
Cancer Treatment Recently Approved Approval Date Brand Name Generic Name Indication AWP* per 30 day supply 9/22/2015 Lonsurf trifluridine/tipiracil Colorectal Cancer (CRC) $17,516 11/10/2015 Cotellic cobimetinib Melanoma $7,274 11/13/2015 Tagrisso osimertinib Non-Small Cell Lung Cancer $15,300 11/20/2015 Ninlaro ixazomib Multiple Myeloma (MM) $10,404 12/11/2015 Alecensa alectinib Non-Small Cell Lung Cancer $14,793 4/11/2016 Venclexta Venetoclax CLL / SLL* $11,471 4/25/2016 Cabometyx Cabozantinib Renal Cell Cancer (RCC) $16,500 5/18/2016 Tecentriq Atezolizumab Bladder Cancer $13,792 *CLL / SLL Chronic Lymphocytic Leukemia / Small Cell Lymphocytic Lymphoma *AWP = Average Wholesale Price 14
Cancer Treatment Pipeline Drug Name(s) Manufacturer Indication Expected Approval Atezolizumab Roche NSCLC Oct 19, 2016 Olaratumab Lilly Soft tissue sarcoma Nov 4, 2016 Rucaparib Clovis Oncology Ovarian Cancer Feb 23, 2017 Binimetinib Array BioPharma Melanoma Mar 2, 2017 Brigatinib Ariad NSCLC 2017 Olumetinib Boehringer Ingleheim NSCLC 2017 Ribociclib Novartis Breast Cancer 2017 Entinostat Syndax Breast Cancer 2017 Midostaurin Novartis Acute Myeloid Leukemia 2017 15
Cystic Fibrosis Overview Approximately 30,000 people in the U.S. have cystic fibrosis (CF) Approximately 75% of CF patients diagnosed by age two 40 years median survival age Shift from treating symptoms to disease-modifying therapies Cystic Fibrosis. American Lung Association Accessed at http://www.lung.org/lung-health-and-diseases/lung-disease-lookup/cystic-fibrosis/?referrer=https://www.google.com/ on March 21, 2016. About Cystic Fibrosis. Cystic Fibrosis Foundation. https://www.cff.org/what-is-cf/about-cystic-fibrosis/ on March 21, 2016. 16
Cystic Fibrosis Treatment Current DM Therapies Ivacaftor (Kalydeco TM ) Estimated 5 7% of all CF patients eligible 1 Indicated age > 2 years Cost: $287,000 / year Lumacaftor/Ivacaftor (Orkambi TM ) Estimated 46.5% of all CF patients eligible 1 Indicated age >= 12 years 2 Cost: $239,000 / year 1. http://investors.vrtx.com/releasedetail.cfm?releaseid=856185 accessed on May 25th 2015. 17
Cystic Fibrosis Treatment - Pipeline VX661 Currently in Phase III trials Studied in combination with Kalydeco Treats same population as Orkambi Translarna (ataluren) Approved in Germany for treatment of Duchenne s Muscular Dystrophy Phase III studies for cystic fibrosis 18
Modeling Considerations
Modeling Considerations Diagnosis Data Can be used to estimate prevalence in population Is diagnosis data available? Is diagnosis data specific enough? How accurately can you define the diseased population using codes? 20
Modeling Considerations Predicting utilization uptake What percentage of those with condition will take the medication? How quickly will drug reach peak utilization level? How will drug utilization management impact? Formularies Prior authorization Step therapy Quantity limits 21
Modeling Considerations First-to-market or another me-too? Is the drug first in its class? If not, will it replace current therapy or be considered add-on therapy? How much market share will the new-to-market product displace from current therapies? 22
Modeling Considerations Covered Population Commercial vs. Medicare vs. Medicaid Will cost sharing be prohibitive? Commercial Copay coupon cards Medicare PAP (patient assistance programs) Medicaid minimal cost share 23
Modeling Considerations Curative vs On-Going Will cures reduce other costs? If yes, during the current contract year or in the future? Oncology consideration: Will therapy extend life? If yes, how long and at what cost? 24
Modeling Considerations Changes in Criteria Can be formal (Medicaid Hep C) Can be informal (off-label usage) Oncology Compendia recommendations are covered by Medicare 25
Modeling Considerations Rebates Do manufacturers provide sizable rebates? Does the covered entity receive those rebates? Does the stop loss/reinsurance coverage recapture the rebates? 26
Quantifying Excess Specialty Drug Risk Patrick Gallagher, FSA, FCAS October 25, 2016
Specialty Drug Risk Varies by Payer and Product Relative Size of Specialty Drug Financial Risk Employer ACO/Provider HMO/Insurer Group Individual Medicare Advantage Medicaid Integro USA, Inc., 2015 2
Buying reinsurance: Protect your Frequency or Severity? Large employers purchase stop-loss insurance to protect against catastrophic claims, or severity events. The uncertainty surrounding newly branded drug pricing puts employers at risk of many claimants whose costs are correlated, or frequency events Example: Self-insured employer plan 20,000 members $100M annual budget 100 Year Modeled Severity Event: $5M additional claims 100 Year Modeled Drug Frequency Event: $10M additional claims Integro USA, Inc., 2015 3
Coverage Options for Specialty Drug Reinsurance Whitelist Blacklist Newly Branded All Pharmacy Specific Excess Integro USA, Inc., 2014 4
Modeling Aggregate Specialty Drug Risk Timing of release Price Utilization Interaction with other therapies Integro USA, Inc., 2014 5
Simulation Modeling of Aggregate Specialty Drug Risk Simulation Model for Specialty Rx 1. Drug Facts Source Drug Name Rociletinib (Clovis Oncology) Current Status NDA Filed Drugs.com Anticipated Approval 6/28/2016 Drugs.com Classification Breakthrough TherapyPGx Used for Non-small cell lung cancer (NSCLC). EGFR T790M mutation positive Existing Treatment Tarceva, Gilotrif Express Script Report 2. Assumptions Expected Value Distribution Source (a) Cost $100,000 per year Normal Distribution with CV=0.2 Express Script Report (b) Time available on market in 2016 4 months Uniform between 0 to 8 Months From Anticipated Approval (c) US New Lung Cancer cases 224,210 per year Express Script Report (d) % of NSCLC Cases 85%-90% Cancer.org (e) % of Developing EGFR T790M mutation 5% MyCancerGenome.org (f) Patient Average Life 2 Year <5% 5 year survival rate (g) Frequency of Patients 60 per million (c ) x (d) x (e ) x (f) / US Population 3. Simulation Model Expected Value (h) Population Size 40,000 (i) % of Patient using Rociletinib 60% 4. Simulation Model Output Percentile Drug Cost 50% 27,000 60% 40,000 70% 55,000 80% 75,000 90% 114,000 95% 153,000 Integro USA, Inc., 2014 6
Example Whitelist Simulation Model The first method of delivery for Specialty RX reinsurance is a targeted model, wherein the reinsurer and broker will maintain a whitelist of drugs that might be introduced in the contract period and could materially impact the reinsured s drug costs for the year. Under this model, only agreed upon drugs would be covered. This product is not intended to eliminate increasing drug costs. Instead, the product will address newly branded drugs that might cost catastrophically more than expected. In order to price the risk, a sample benchmark report is generated, which identifies upcoming pipeline drugs and the likely cost of these to the specific client. In this sample benchmark report, we calculate that newly branded drugs will cost this health plan $33.7 million net of its specific reinsurance. This is based on assumptions about: the future annual cost of each drug an estimate of how many patients in the plan s population suffer from this condition (determined by looking at historical use of competing therapies and/or macro data about the prevalence of a condition) an estimate of how many patients will actually be treated during the future period Integro USA, Inc., 2014 7
Estimating Trend Concerns with public studies Motivation for bias Timing Population Skewness of the distribution Known unknowns Legislative risk Population specific risk Prior authorization protocols Consumer incentives Advertising campaigns Pricing risk Integro USA, Inc., 2014 8
Takeaways Stop-loss buyers can more efficiently transfer risk by considering both severity and frequency risk When aggregate stop-loss is expensive, aggregate drug risk (re)insurance is a good complement to specific stop-loss. Reinsurance contracts vary in the list of drugs covered and ground-up vs. excess Ground-up modeling of individual named drugs is difficult but lends itself well to simulation models PBMs publish good information to help parameterize models, but it is important to know their shortcomings Integro USA, Inc., 2014 9