Personalized medicine and economic evaluation in oncology: all theory and no practice?

Pricing above value: Selling to a market with selection problems

This paper shows that selection incentives in downstream markets distort upstream prices. It is possible for inputs to be priced above the value that the good has for final consumers. We apply this idea to pharmaceutical companies selling drugs to a health insurance market with selection problems. We specify the conditions under which drugs are sold at prices exceeding treatment value. Another feature of the model is an excessive private incentive to reduce market size, e.g. in the form of personalized medicine.

Evaluating the Value for Money of Precision Medicine from Early Cycle to Market Access: A Comprehensive Review of Approaches and Challenges

OBJECTIVES

This study aimed to perform a comprehensive review of modeling approaches and methodological and policy challenges in the economic evaluation (EE) of precision medicine (PM) across clinical stages.

METHODS

First, a systematic review was performed to assess the approaches of EEs in the past 10 years. Next, a targeted review of methodological articles was conducted for methodological and policy challenges in performing EEs of PM. All findings were synthesized into a structured framework that focused on patient population, Intervention, Comparator, Outcome, Time, Equity and ethics, Adaptability and Modeling aspects, named the "PICOTEAM" framework. Finally, a stakeholder consultation was conducted to understand the major determinants of decision making in PM investment.

RESULTS

In 39 methodological articles, we identified major challenges to the EE of PM. These challenges include that PM applications involve complex and evolving clinical decision space, that clinical evidence is sparse because of small subgroups and complex pathways in PM settings, a one-time PM application may have lifetime or intergenerational impacts but long-term evidence is often unavailable, and that equity and ethics concerns are exceptional. In 275 EEs of PM, current approaches did not sufficiently capture the value of PM compared with targeted therapies, nor did they differentiate Early EEs from Conventional EEs. Finally, policy makers perceived the budget impact, cost savings, and cost-effectiveness of PM as the most important determinants in decision making.

CONCLUSIONS

There is an urgent need to modify existing guidelines or develop a new reference case that fits into the new healthcare paradigm of PM to guide decision making in research and development and market access.

A Review of the Challenges of Using Biomedical Big Data for Economic Evaluations of Precision Medicine

There is potential value in incorporating biomedical big data (BBD)-observational real-world patient-level genomic and clinical data in multiple sub-populations-into economic evaluations of precision medicine. However, health economists face practical and methodological challenges when using BBD in this context. We conducted a literature review to identify and summarise these challenges. Relevant articles were identified in MEDLINE, EMBASE, EconLit, University of York Centre for Reviews and Dissemination and Cochrane Library from 2000 to 2018. Articles were included if they studied issues relevant to the interconnectedness of biomedical big data, precision medicine, and health economic evaluation. Nineteen articles were included in the review. Challenges identified related to data management, data quality and data analysis. The availability of large volumes of data from multiple sources, the need to conduct data linkages within an environment of opaque data access and sharing procedures, and other data management challenges are primarily practical and may not be long-term obstacles if procedures for data sharing and access are improved. However, the existence of missing data across linked datasets, the need to accommodate dynamic data, and other data quality and analysis challenges may require an evolution in economic evaluation methods. Health economists face challenges when using BBD in economic evaluations of technologies that facilitate precision medicine. Potential solutions to some of these challenges do, however, exist. Going forward, health economists who present work that uses BBD should document challenges and the solutions they have applied to the challenges to support future researcher endeavours.

Overview of Current Targeted Anti-Cancer Drugs for Therapy in Onco-Hematology

The upgraded knowledge of tumor biology and microenviroment provides information on differences in neoplastic and normal cells. Thus, the need to target these differences led to the development of novel molecules (targeted therapy) active against the neoplastic cells' inner workings. There are several types of targeted agents, including Small Molecules Inhibitors (SMIs), monoclonal antibodies (mAbs), interfering RNA (iRNA) molecules and microRNA. In the clinical practice, these new medicines generate a multilayered step in pharmacokinetics (PK), which encompasses a broad individual PK variability, and unpredictable outcomes according to the pharmacogenetics (PG) profile of the patient (e.g., cytochrome P450 enzyme), and to patient characteristics such as adherence to treatment and environmental factors. This review focuses on the use of targeted agents in-human phase I/II/III clinical trials in cancer-hematology. Thus, it outlines the up-to-date anticancer drugs suitable for targeted therapies and the most recent finding in pharmacogenomics related to drug response. Besides, a summary assessment of the genotyping costs has been discussed. Targeted therapy seems to be an effective and less toxic therapeutic approach in onco-hematology. The identification of individual PG profile should be a new resource for oncologists to make treatment decisions for the patients to minimize the toxicity and or inefficacy of therapy. This could allow the clinicians to evaluate benefits and restrictions, regarding costs and applicability, of the most suitable pharmacological approach for performing a tailor-made therapy.

The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

OBJECTIVE

Precision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies.

METHODS

We performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research.

RESULTS

We identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects.

DISCUSSION

Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.

A multidimensional sight on cardiac failure: uncovered from structural to molecular level

Heart failure is one of the leading causes of death, with high mortality rate within 5 years after diagnosis. Treatment and prognosis options for heart failure primarily targeted on hemodynamic and neurohumoral components that drive progressive deterioration of the heart. However, given the multifactorial background that eventually leads to the "phenotype" named heart failure, better insight into the various components may lead to personalized treatment opportunities. Indeed, currently used criteria to diagnose and/or classify heart failure are possibly too focused on phenotypic improvement rather than the molecular driver of the disease and could therefore be further refined by integrating the leap of molecular and cellular knowledge. The ambiguity of the ejection fraction-based classification criteria became evident with development of advanced molecular techniques and the dawn of omics disciplines which introduced the idea that disease is caused by a myriad of cellular and molecular processes rather than a single event or pathway. The fact that different signaling pathways may underlie similar clinical manifestations calls for a more holistic study of heart failure. In this context, the systems biology approach can offer a better understanding of how different components of a system are altered during disease and how they interact with each other, potentially leading to improved diagnosis and classification of this condition. This review is aimed at addressing heart failure through a multilayer approach that covers individually some of the anatomical, morphological, functional, and tissue aspects, with focus on cellular and subcellular features as an alternative insight into new therapeutic opportunities.

Liquid dynamic medicine and N-of-1 clinical trials: a change of perspective in oncology research

The increasing use of genomics to define the pattern of actionable mutations and to test and validate new therapies for individual cancer patients, and the growing application of liquid biopsy to dynamically track tumor evolution and to adapt molecularly targeted therapy according to the emergence of tumor clonal variants is shaping modern medical oncology., In order to better describe this new therapeutic paradigm we propose the term "Liquid dynamic medicine" in the place of "Personalized or Precision medicine". Clinical validation of the "Liquid dynamic medicine" approach is best captured by N-of-1 trials where each patient acts as tester and control of truly personalized therapies.

Toward precision medicine of breast cancer

In this review, we report on breast cancer's molecular features and on how high throughput technologies are helping in understanding the dynamics of tumorigenesis and cancer progression with the aim of developing precision medicine methods. We first address the current state of the art in breast cancer therapies and challenges in order to progress towards its cure. Then, we show how the interaction of high-throughput technologies with in silico modeling has led to set up useful inferences for promising strategies of target-specific therapies with low secondary effect incidence for patients. Finally, we discuss the challenge of pharmacogenetics in the clinical practice of cancer therapy. All these issues are explored within the context of precision medicine.