A prismatic view of the epigenetic-metabolic regulatory axis in breast cancer therapy resistance.

Epigenetic regulation established during development to maintain patterns of transcriptional expression and silencing for metabolism and other fundamental cell processes can be reprogrammed in cancer, providing a molecular mechanism for persistent alterations in phenotype. Metabolic deregulation and reprogramming are thus an emerging hallmark of cancer with opportunities for molecular classification as a critical preliminary step for precision therapeutic intervention. Yet, acquisition of therapy resistance against most conventional treatment regimens coupled with tumor relapse, continue to pose unsolved problems for precision healthcare, as exemplified in breast cancer where existing data informs both cancer genotype and phenotype. Furthermore, epigenetic reprograming of the metabolic milieu of cancer cells is among the most crucial determinants of therapeutic resistance and cancer relapse. Importantly, subtype-specific epigenetic-metabolic interplay profoundly affects malignant transformation, resistance to chemotherapy, and response to targeted therapies. In this review, we therefore prismatically dissect interconnected epigenetic and metabolic regulatory pathways and then integrate them into an observable cancer metabolism-therapy-resistance axis that may inform clinical intervention. Optimally coupling genome-wide analysis with an understanding of metabolic elements, epigenetic reprogramming, and their integration by metabolic profiling may decode missing molecular mechanisms at the level of individual tumors. The proposed approach of linking metabolic biochemistry back to genotype, epigenetics, and phenotype for specific tumors and their microenvironment may thus enable successful mechanistic targeting of epigenetic modifiers and oncometabolites despite tumor metabolic heterogeneity.

Long Interspersed Nuclear Element-1 Analytes in Extracellular Vesicles as Tools for Molecular Diagnostics of Non-Small Cell Lung Cancer.

Aberrant expression of the oncogenic retrotransposon LINE-1 is a hallmark of various cancer types, including non-small cell lung cancers (NSCLCs). Here, we present proof-of-principle evidence that LINE-1 analytes in extracellular vesicles (EVs) serve as tools for molecular diagnostics of NSCLC, with LINE-1 status in tumor cells and tissues mirroring the LINE-1 mRNA and ORF1p cargos of EVs from lung cancer cell culture conditioned media or human plasma. The levels of LINE-1 analytes in plasma EVs from ostensibly healthy individuals were higher in females than males. While the profiles of LINE-1 mRNA and ORF1p in African Americans compared to Hispanics were not significantly different, African Americans showed slightly higher ORF1p content, and 2-3 times greater ranges of LINE-1 values compared to Hispanics. Whole plasma ORF1p levels correlated with EV ORF1p levels, indicating that most of the circulating LINE-1 protein is contained within EVs. EV LINE-1 mRNA levels were elevated in patients with advanced cancer stages and in select patients with squamous cell carcinoma and metastatic tumors compared to adenocarcinomas. The observed EV LINE-1 mRNA profiles paralleled the patterns of ORF1p expression in NSCLC tissue sections suggesting that LINE-1 analytes in plasma EVs may serve to monitor the activity of LINE-1 retroelements in lung cancer.

External control arms: COVID-19 reveals the merits of using real world evidence in real-time for clinical and public health investigations.

Randomized controlled trials are considered the 'gold standard' to reduce bias by randomizing patients to an experimental intervention, versus placebo or standard of care cohort. There are inherent challenges to enrolling a standard of care or cohorts: costs, site engagement logistics, socioeconomic variability, patient willingness, ethics of placebo interventions, cannibalizing the treatment arm population, and extending study duration. The COVID-19 pandemic has magnified aspects of constraints in trial recruitment and logistics, spurring innovative approaches to reducing trial sizes, accelerating trial accrual while preserving statistical rigor. Using data from medical records and databases allows for construction of external control arms that reduce the costs of an external control arm (ECA) randomized to standard of care. Simultaneously examining covariates of the clinical outcomes in ECAs that are being measured in the interventional arm can be particularly useful in phase 2 trials to better understand social and genetic determinants of clinical outcomes that might inform pivotal trial design. The FDA and EMA have promulgated a number of publicly available guidance documents and qualification reports that inform the use of this regulatory science tool to streamline clinical development, of phase 4 surveillance, and policy aspects of clinical outcomes research. Availability and quality of real-world data (RWD) are a prevalent impediment to the use of ECAs given such data is not collected with the rigor and deliberateness that characterizes prospective interventional control arm data. Conversely, in the case of contemporary control arms, a clinical trial outcome can be compared to a contemporary standard of care in cases where the standard of care is evolving at a fast pace, such as the use of checkpoint inhibitors in cancer care. Innovative statistical methods are an essential aspect of an ECA strategy and regulatory paths for these innovative approaches have been navigated, qualified, and in some cases published.

Understanding the role of Toll-like receptors in lung cancer immunity and immunotherapy.

Lung cancer is currently the leading cause of cancer-related deaths worldwide. Significant improvements in lung cancer therapeutics have relied on a better understanding of lung cancer immunity and the development of novel immunotherapies, as best exemplified by the introduction of PD-1/PD-L1-based therapies. However, this improvement is limited to lung cancer patients who respond to anti-PD-1 immunotherapy. Further improvements in immunotherapy may benefit from a better understanding of innate immune response mechanisms in the lung. Toll-like receptors (TLRs) are a key component of the innate immune response and mediate the early recognition of pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). TLR signaling modulates the tumor microenvironment from "cold" to "hot" leading to immune sensitization of tumor cells to treatments and improved patient prognosis. In addition, TLR signaling activates the adaptive immune response to improve the response to cancer immunotherapy through the regulation of anti-tumor T cell activity. This review will highlight recent progress in our understanding of the role of TLRs in lung cancer immunity and immunotherapy.

Role of the Histone Acetyl Transferase MOF and the Histone Deacetylase Sirtuins in Regulation of H4K16ac During DNA Damage Repair and Metabolic Programming: Implications in Cancer and Aging.

The accurate repair of genomic damage mediated by ionizing radiation (IR), chemo- or radiomimetic drugs, or other exogenous agents, is necessary for maintenance of genome integrity, preservation of cellular viability and prevention of oncogenic transformation. Eukaryotes have conserved mechanisms designed to perceive and repair the damaged DNA quite efficiently. Among the different types of DNA damage, double strand breaks (DSB) are the most detrimental. The cellular DNA DSB response is a hierarchical signaling network that integrates damage sensing and repair with chromatin structural changes that involve a range of pre-existing and induced covalent modifications. Recent studies have revealed that pre-existing histone modifications are important contributors within this signaling/repair network. This chapter discusses the role of a critical histone acetyl transferase (HAT) known as MOF (males absent on the first) and the histone deacetylases (HDACs) Sirtuins on histone H4K16 acetylation (H4K16ac) and DNA damage repair. We also discuss the role of this important histone modification in light of metabolic rewiring and its role in regulating human pathophysiologic states.

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology.

Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes. These challenges are amplified for underrepresented minority (URM) and other disadvantaged populations, who tend to view the institution of clinical research with skepticism. Participation gaps leave such populations underrepresented in clinical research and, importantly, in policy decisions about treatment choices and reimbursement, thus further augmenting health, social, and economic disparities. Cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence technologies are powerful tools that promise to enhance longitudinal patient engagement across the natural history of disease. These tools also promise to enhance engagement by giving participants agency over their data and addressing a major impediment to research participation. This will only occur if these tools are available for use with all patients. Distributed ledger technologies (specifically blockchain) converge these tools and offer a significant element of trust that can be used to engage URM populations more substantively in clinical research. This is a crucial step toward linking composite cohorts for training and optimization of the artificial intelligence tools for enhancing public health in the future. The parameters of an idealized clinical genomic registry are presented.

LINE-1 Cargo and Reverse Transcriptase Activity Profiles in Extracellular Vesicles from Lung Cancer Cells and Human Plasma.

Long Interspersed Element-1 (LINE-1) is an oncogenic human retrotransposon that 'copies and pastes' DNA into new locations via reverse transcription. Given that enzymatically active LINE-1 can be exported in extracellular vesicles (EVs), and that LINE-1 mRNA and its two encoded proteins, ORF1p and ORF2p, are required for retrotransposition, the present study examined LINE-1 EV loading patterns relative to reverse transcriptase (RT) activity in vivo and in vitro. Density gradient ultracentrifugation identified conserved patterns of LINE-1 mRNA and protein distribution in EVs, with RT activity readily detected in EV fractions containing both LINE-1 mRNA and protein. Unlike whole cell and tissue lysates, the ORF1p in EVs was detected as a dimer. EVs from ostensibly healthy plasma donors showed variable but consistent ORF1p profiles, with residual levels of LINE-1 mRNA measured in some but not all samples. EVs from cancer cell lines had elevated mean LINE-1 levels and 5-85 times greater RT activity than EVs from normal cells or healthy plasma. EV RT activity was associated with EV LINE-1 mRNA content and was highest in cell lines that also expressed an elevated expression of ORF1p and ORF2p. Given that LINE-1 activation is a hallmark of many cancer types, our findings suggest that an EV LINE-1 'liquid biopsy' may be developed to monitor LINE-1 activity during the course of malignant progression.

Patients with Lung Cancer of Different Racial Backgrounds Harbor Distinct Immune Cell Profiles.

Tumors accumulated with infiltrated immune cells (hot tumors) have a higher response rate to immune checkpoint blockade, when compared with those with minimal T-cell infiltration (cold tumors). We report here that patients with lung cancer with different racial backgrounds harbored distinct immune cell profiles in the tumor microenvironment. Compared with African Americans (AA), Caucasian Americans (CA) exhibited increased immune cell infiltration and vasculature, and increased survival. Changes of survival and immune profile were most pronounced among active smokers and nonsmokers, compared with former smokers and total patients. Neighborhood analysis showed that immune cells accumulated around cancer cells in CAs but not AAs. Our findings reveal intrinsic biological differences between AA and CA patients with lung cancer, suggesting that treatment plans should be tailored for patients with different racial backgrounds. Significance: We report biological racial differences among patients with lung cancer where Caucasians present a hot tumor microenvironment compared with cold tumor in AAs. Treatment plans should be customized to maximize therapeutic outcomes.

Stress Responses as Master Keys to Epigenomic Changes in Transcriptome and Metabolome for Cancer Etiology and Therapeutics.

From initiation through progression, cancer cells are subjected to a magnitude of endogenous and exogenous stresses, which aid in their neoplastic transformation. Exposure to these classes of stress induces imbalance in cellular homeostasis and, in response, cancer cells employ informative adaptive mechanisms to rebalance biochemical processes that facilitate survival and maintain their existence. Different kinds of stress stimuli trigger epigenetic alterations in cancer cells, which leads to changes in their transcriptome and metabolome, ultimately resulting in suppression of growth inhibition or induction of apoptosis. Whether cancer cells show a protective response to stress or succumb to cell death depends on the type of stress and duration of exposure. A thorough understanding of epigenetic and molecular architecture of cancer cell stress response pathways can unveil a plethora of information required to develop novel anticancer therapeutics. The present view highlights current knowledge about alterations in epigenome and transcriptome of cancer cells as a consequence of exposure to different physicochemical stressful stimuli such as reactive oxygen species (ROS), hypoxia, radiation, hyperthermia, genotoxic agents, and nutrient deprivation. Currently, an anticancer treatment scenario involving the imposition of stress to target cancer cells is gaining traction to augment or even replace conventional therapeutic regimens. Therefore, a comprehensive understanding of stress response pathways is crucial for devising and implementing novel therapeutic strategies.

Computational modeling of RNase, antisense ORF0 RNA, and intracellular compartmentation and their impact on the life cycle of the line retrotransposon.

Nearly half of the human genome is occupied by repetitive sequences of ancient virus-like genetic elements. The largest class, comprising 17% of the genome, belong to the type 1 Long INterspersed Elements (LINE-1) and are the only class capable of autonomous propagation in the genome. When epigenetic silencing mechanisms of LINE-1 fail, the proteins encoded by LINE-1 engage in reverse transcription to make new copies of their own or other DNAs that are pasted back into the genome. To elucidate how LINE-1 is dysregulated as a result of carcinogen exposure, we developed a computational model of key elements in the LINE-1 lifecycle, namely, the role of cytosolic ribonuclease (RNase), RNA interference (RNAi) by the antisense ORF0 RNA, and sequestration of LINE-1 products into stress granules and multivesicular structures. The model showed that when carcinogen exposure is represented as either a sudden increase in LINE-1 mRNA count, or as an increase in mRNA transcription rate, the retrotransposon copy number exhibits a distinct threshold behavior above which LINE-1 enters a positive feedback loop that allows the cDNA copy number to grow exponentially. We also found that most of the LINE-1 RNA was degraded via the RNAase pathway and that neither ORF0 RNAi, nor the sequestration of LINE-1 products into granules and multivesicular structures, played a significant role in regulating the retrotransposon's life cycle. Several aspects of the prediction agree with experimental results and indicate that the model has significant potential to inform future experiments related to LINE-1 activation.

Pharmacogenomics insights into precision pediatric oncology.

PURPOSE OF REVIEW: Pharmacogenomic insights provide an opportunity to optimize medication dosing regimens and patient outcomes. However, the potential for interindividual genomic variability to guide medication dosing and toxicity monitoring is not yet standard of care. In this review, we present advances for the thiopurines, anthracyclines and vincristine and provide perspectives on the actionability of pharmacogenomic guidance in the future. RECENT FINDINGS: The current guideline on thiopurines recommends that those with normal predicted thiopurine methyltransferase and NUDT15 expression receive standard-of-care dosing, while 'poor metabolizer' haplotypes receive a decreased 6-mercaptopurine starting dose to avoid bone marrow toxicity. Emerging evidence established significant polygenic contributions that predispose to anthracycline-induced cardiotoxicity and suggest this knowledge be used to identify those at higher risk of complications. In the case of vincristine, children who express CYP3A5 have a significantly reduced risk of peripheral neuropathy compared with those expressing an inactive form or the CYP3A4 isoform. SUMMARY: The need for adequately powered pediatric clinical trials, coupled with the study of epigenetic mechanisms and their influence on phenotypic variation and the integration of precision survivorship into precision approaches are featured as important areas for focused investments in the future.

Role of long interspersed nuclear element-1 in the regulation of chromatin landscapes and genome dynamics.

LINE-1 retrotransposon, the most active mobile element of the human genome, is subject to tight regulatory control. Stressful environments and disease modify the recruitment of regulatory proteins leading to unregulated activation of LINE-1. The activation of LINE-1 influences genome dynamics through altered chromatin landscapes, insertion mutations, deletions, and modulation of cellular plasticity. To date, LINE-1 retrotransposition has been linked to various cancer types and may in fact underwrite the genetic basis of various other forms of chronic human illness. The occurrence of LINE-1 polymorphisms in the human population may define inter-individual differences in susceptibility to disease. This review is written in honor of Dr Peter Stambrook, a friend and colleague who carried out highly impactful cancer research over many years of professional practice. Dr Stambrook devoted considerable energy to helping others live up to their full potential and to navigate the complexities of professional life. He was an inspirational leader, a strong advocate, a kind mentor, a vocal supporter and cheerleader, and yes, a hard critic and tough friend when needed. His passionate stand on issues, his witty sense of humor, and his love for humanity have left a huge mark in our lives. We hope that that the knowledge summarized here will advance our understanding of the role of LINE-1 in cancer biology and expedite the development of innovative cancer diagnostics and treatments in the ways that Dr Stambrook himself had so passionately envisioned.

Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting.

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug-gene pairs and drug-drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug-gene and drug-drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

Pricing methods in outcome-based contracting: δ2: willingness-to-pay-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The second dimension (δ2) estimates prices on the basis of four willingness-to-pay (WTP) thresholds. 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: Eight WTP scenarios based on four levels of real gross domestic product per capita (<1GDP/capita, 1 × GDP/capita, 3 × GDP/capita, and >3 × GDP/capita) and two market conditions (monopolistic versus competitive) were assumed. The incremental cost-utility ratio (ICUR) was applied to differently to both markets. In the monopolistic market, assuming no competitors, the cost/QALY ratio for a drug was used; whereas in the competitive market, assuming competitors, the incremental cost-utility ratio (ICUR) was applied. One-way sensitivity analyses were performed and predictive equations were specified to estimate the prices of treatment for the resulting eight WTP scenarios; for which subsequently the average and standard deviation were calculated. A gamma distribution was specified and Monte Carlo Simulation (MCS) was applied to estimate the dimension-specific price based on WTP (DSPWTP). 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) of $14,616 (30-day prescription) was used to estimate the DSPWTP for each contract. RESULTS: The 1-year estimates averaged $4,654 (SD=$6,462) and the MCS yielded a DSPWTP of $4,547 or -68.89% of the 2018 WAC for a 30-day prescription. The 2-year estimates averaged $4,7667 (SD=$6,480) with the MCS generating a DSPWTP of $4,704 or -67.82% of the WAC. CONCLUSIONS: We demonstrated that WTP-based methods that include various WTP thresholds and market conditions generate price estimates across these thresholds and market conditions that can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: δ4: safety-based pricing.

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 DSPSafety. 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 DSPSafety 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 DSPSafety of osimertinib was estimated at $14,627 (or +0.08% the 2018 WAC) for a 30-day prescription. In the 2-year contract, the DSPSafety 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.

Pricing methods in outcome-based contracting: δ5: risk of efficacy failure-based pricing.

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 DSPRisk 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 DSPRisk 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 DSPRisk 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 DSPRisk 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.

Pricing methods in outcome-based contracting: δ6: adherence-based pricing.

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 DSPAdherence. 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 DSPAdherence 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 DSPAdherence 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 DSPAdherence 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.

Pricing methods in outcome-based contracting: δ1: cost effectiveness analysis and cost-utility analysis-based pricing.

AIMS: Six Delta is a six-dimensional independent platform for outcome-based pricing/contracting. The first dimension (δ1) estimates prices on the basis of cost-effectiveness (CEA) and cost-utility analysis (CUA). 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: CEA and CUA were performed using established methods. Probabilistic sensitivity analyses (PSA) were performed to generate cost-effectiveness acceptability curves (CEAC), specifically the PSA incremental cost-effectiveness (PSA ICER) and incremental cost-utility ratio generated CEACs (PSA ICUR). Price of treatment was estimated at three certainty levels (0%, turning point%, 100%). The marketed drug price at turning point was used to estimate prices at 0% and 100% certainty levels, as per PSA ICER and PSA ICUR-generated CEACs. The resulting prices were pooled, inflated, and simulated by Monte Carlo Simulation (MCS) methods to estimate the dimension-specific price based on CEA and CUA (DSPCEA/CUA). A proof-of-concept exercise with osimertinib in NSCLC was performed for two hypothetical outcome-based contracts: 1-year (2019-2020) and 2-years (2019-2021). RESULTS: Turning points were estimated at the 50% certainty level in both PSA ICER and ICUR-generated CEACS. At these points, the wholesale acquisition cost for osimertinib was $14,616 (30-day prescription); inflated by 0.44% for 1-year and by 0.72% for 2-year contracts. Additional prices at 0% and 100% certainty levels were quantified based on the PSA ICER and ICUR-generated CEACs. The MCS yielded a DSPCEA/CUA of $16,391 for the 1-year contract and a DSPCEA/CUA at $16,677 for the 2-year contract for a 30-day prescription. CONCLUSIONS: We demonstrated that conventional CEA and CUA methods generate price estimates at varying levels of certainty that can be integrated into our proposed Six Delta platform for outcome-based pricing/contracting.

Pricing methods in outcome-based contracting: integration analysis of the six dimensions (6 δs).

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.

Pricing methods in outcome-based contracting: δ3: reference-based pricing.

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 DSPReference. 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 DSPReference 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 DSPReference 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.