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Aims: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The fifth dimension (δ5) estimates prices on the basis of the risk of efficacy failure of a drug. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib., Materials and Methods: The risk of efficacy failure pricing dimension utilizes a seven-step method: (1) defining risk; (2) extracting data; (3) predicting models; (4) performing Monte Carlo Simulation (MCS) to estimate risk of efficacy failure; 5) estimating ranges for a payback; (6) adjusting for medical inflation; and (7) performing Monte Carlo Simulation (MCS) to estimate the DSP Risk of efficacy failure . A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). We estimated the risk of efficacy failure for osimertinib in terms of overall and progression-free survival versus standard of care. We used the estimated risk to estimate the price reduction on the wholesale acquisition cost (WAC) for the two hypothetical contracts: a 1-year (2019-2020) and 2-year contract (2019-2021). From this we estimated the DSP Risk of efficacy failure ., Results: Based on the risk of OS and PFS efficacy failure for osimertinib in OS and PFS, in the 1-year contract, the DSP Risk of efficacy failure was estimated at $12,652 (or -13.44% the 2018 WAC) for a 30-day prescription. For the 2-year contract (2019-2021), the DSP Risk of efficacy failure was estimated at $13,019 (or -10.93% the 2018 WAC)., Conclusions: We demonstrated that pricing methods based on risk of efficacy failure methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Aims: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The six dimensions have been described separately: (δ1) cost-effectiveness analysis and cost-utility analysis-based pricing; (δ2) willingness-to-pay-based pricing; (δ3) reference-based pricing; (δ4) safety-based pricing; (δ5) risk of efficacy failure-based pricing; and (δ6) adherence-based pricing. The final step is to integrate the various dimension-specific pricing estimates into a composite estimate termed the All-Dimensional Price (ADP). We describe the methodology for this integration and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib., Materials and Methods: For better accuracy in estimating the ADP, we used the prices generated from the six dimensions at scenario levels, not at the dimension-specific price (DSP) level. We pooled the price estimates and performed Monte Carlo Simulations (MCS) for the price scenarios generated by the six dimensions. We used the results of the proof-of-concept exercise involving osimertinib in NSCLC with EGFR mutation to estimate the ADP in two hypothetical contracts: 1-year (2019-2020) and 2-year contract (2019-2021)., Results: The average of the 30-day prescription estimates from the six dimensions averaged $10,819 (SD=$8,486) for the 1-year contract and $10,730 (SD=$8,500) for the 2-year contract. MCS yielded for the 1-year contract an ADP of $10,959 (or -25.02% the 2018 WAC price) and an ADP for the 2-year contract was $10,788 (or -26.19% the 2018 WAC price)., Conclusions: We demonstrated that the integration of the prices from the six dimensions of the Six Delta platform and market conditions is feasible and yields multidimensional prices estimates to support outcome-based pricing/contracting.

Aims: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The fourth dimension (δ4) estimates prices on the basis of assessments of the safety of the drug using an ex ante analysis based on clinical trial data. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib., Materials and Methods: The safety-based pricing dimension utilizes a four-step method: 1) pooling adverse events (AE), standardizing, estimating 95%Cis, and adjusting for time; 2) estimating correction factors and corrected probabilities of AEs; 3) estimating the probability of at least one adverse event (AE) occurring and leading to treatment discontinuation; and 4) estimating ranges for payback percentages and performing Monte Carlo Simulation to estimate a DSP Safety . A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). We estimated the DSP Safety based on the grade 3/4 AEs observed for osimertinib and standard of care. The 2018 wholesale acquisition cost (WAC) of osimertinib at $14,616 for a 30-day prescription was used., Results: AEs3/4 were retrieved from the FLAURA trial. In the 1-year contract, the DSP Safety of osimertinib was estimated at $14,627 (or +0.08% the 2018 WAC) for a 30-day prescription. In the 2-year contract, the DSP Safety of osimertinib was estimated at $14,516 (or -0.68% the 2018 WAC) for a 30-day prescription., Conclusions: We demonstrated that ex ante pricing methods-based paybacks for safety issues leading to treatment discontinuation can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Aims: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The third dimension (δ3) estimates prices on the basis of international drug price referencing methods. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib., Materials and Methods: The reference-based pricing dimension utilizes a six-step method: (1) selecting foreign countries based on a set of four criteria (drug is available in the foreign country, price information is available in the foreign country, foreign countries are members within the organization for Economic Co-operation and Development, pricing methods in the foreign countries involve value assessment); (2) adjusting for exchange rates; (3) generating reference price (RP) scenarios; (4) adjusting with the medical inflation rate; (5) pooling all generated RP scenarios and calculating average and standard deviation (SD); (6) and Monte Carlo Simulation (MCS) to estimate the dimension-specific DSP Reference . A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021)., Results: The United Kingdom and Canada met the four criteria. For the osimertinib 1-year contract price, the average of eight RP scenarios, adjusted for inflation by 0.44%, was $8,892 (SD = $2,606) for a 30-day prescription. MCS yielded a DSP Reference estimate of $9,395 or -35.72% of the wholesale acquisition cost (WAC) of $14,616. For the 2-year contract, the average, adjusted for inflation by 0.72%, was $8,928 (SD = $2,610). MCS yielded a DSP Reference estimate of $9,442 or -35.40% of the WAC of $14,616., Conclusions: We demonstrated that international price referencing methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Aims: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The sixth dimension (δ6) estimates prices on the basis of adherence to the prescribed regimen, whereby manufacturers provide payers with adherence-enhancing programs and whereby payers implement these programs and provide adherence data to the manufacturer. We describe this dimension's methodology and present a proof-of-concept application to the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation with osimertinib., Materials and Methods: We propose two paybacks based on adherence: in-advance (based on clinical trial data) and in-arrear (based on real-world data). The risk of efficacy failure pricing dimension utilizes a 7-step method: 1) defining efficacy endpoints; 2) extracting data; 3) predicting models; 4) estimating in-advance and in-arrear paybacks; 5) suggesting ranges for in-advance and in-arrear paybacks; 6) adjusting for medical inflation; and 7) performing Monte Carlo Simulation (MCS) to estimate the DSP Adherence . A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-year (2019-2021). The 2018 wholesale acquisition cost (WAC) for a 30-day prescription was used and inflated as needed. Herein, the DSP Adherence is estimated exclusively in terms of in-advance payback because real-world data about osimertinib are not yet available and thus the in-arrear payback cannot yet be estimated., Results: For the 1-year contract, the average price for osimertinib was $13,798 (SD=$1,265) and the DSP Adherence was $13,785 (or -5.69% of the 2018 WAC) for a 30-day prescription. For the 2-year contract, the average price was $12,555 (SD=$2,847) and the DSP Adherence was $12,582 (or -13.92% of the 2018 WAC)., Conclusions: We demonstrated that adherence-based pricing methods can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting. The proof-of-concept exercise needs to be expanded with the in-arrear pricing method based on real world data to be secured.