The potential to use biomarkers for identifying patients that are more likely to benefit or experience an adverse reaction in response to a given therapy, and thereby better match patients with therapies, is anticipated to have a major effect on both clinical practice and the development of new drugs and diagnostics. In this article, we consider current and emerging examples in which therapies are matched with specific patient population characteristics using clinical biomarkers - which we call stratified medicine - and discuss the implications of this approach to future product development strategies and market structures.

A central question in the assessment of benefit/harm of new treatments is: how does the average outcome on the new treatment (the factual) compare to the average outcome had patients received no treatment or a different treatment known to be effective (the counterfactual)? Randomized controlled trials (RCTs) are the standard for comparing the factual with the counterfactual. Recent developments necessitate and enable a new way of determining the counterfactual for some new medicines. For select situations, we propose a new framework for evidence generation, which we call “threshold‐crossing.” This framework leverages the wealth of information that is becoming available from completed RCTs and from real world data sources. Relying on formalized procedures, information gleaned from these data is used to estimate the counterfactual, enabling efficacy assessment of new drugs. We propose future (research) activities to enable “threshold‐crossing” for carefully selected products and indications in which RCTs are not feasible.

Drug prices in the United States remain the highest in the world. 1 New payment approaches are needed, a point illustratedbythenewtreatmentsforhepatitisCvirus(HCV) infection that are highly effective but also very expensive, at least from the view of many payers, physicians, and patients. Five years after the introduction of these drugs, and due in many cases to budgetary constraints of state Medicaid programs and prisons, only 15% of the estimated population of more than 3 million individuals with HCV in-fectionintheUnitedStateshavebeentreated. 2 Yettheoptimal way to treat HCV is at the population level, that is, by treating every patient possible, with as much speed as is possible. Doing so would reduce the health consequences for those infected, generate the most future savings from improved health, and help decrease future transmission of HCV from person to person.The Department of Health of the State of Louisiana, a statewithahighprevalenceofHCVinfectionandlowtreatment rates, recently published a Request for Information regarding an alternative payment approach, seeking to engage a drug corporation in a subscription-based arrangement to pay for HCV treatment for the state's residents. 3 Gilead Pharmaceuticals indicated the corporation's willingness to explore the idea. 4 The National Governors Association has released a white paper endorsing subscriptionbased models for treating HCV infection as well. 5 In a few media outlets, the idea has been referred to as "the Netflix model," a term used to describe subscription-based models in general. 6 Netflix is a videostreaming service that provides unlimited content for a flat fee; the analogy is a pharmaceutical corporation VIEWPOINT

Co-developing a drug with a diagnostic to create a stratified medicine - a therapy that is targeted to a specific patient population on the basis of a clinical characteristic such as a biomarker that predicts treatment response - presents challenges for product developers, regulators, payers and physicians. With the aim of developing a shared framework and tools for addressing these challenges, here we present an analysis using data from case studies in oncology and Alzheimer's disease, coupled with integrated computational modelling of clinical outcomes and developer economic value, to quantify the effects of decisions related to key issues such as the design of clinical trials. This illustrates how such analyses can aid the coordination of diagnostic and drug development, and the selection of optimal development and commercialization strategies. It also illustrates the impact of the interplay of these factors on the economic feasibility of stratified medicine, which has important implications for public policy makers.

Objectives: To estimate, at the indication level, durable gene and cellular therapy new product launches in the United States through 2030, and the number of treated patients. Methods:A statistical analysis of clinical trials pipeline data and disease incidence and prevalence was conducted to estimate the impact of new cell and gene therapies. We used Citeline's ® Pharmaprojects ® database to estimate the rates and timing of new product launches, on the basis of the phase of development, duration in phase, and probability of progression. Disease incidence and prevalence data were combined with estimates of market adoption to project the size of reimbursed patient populations. Results:We project that about 350 000 patients will have been treated with 30 to 60 products by 2030. About half the launches are expected to be in B-cell (CD-19) lymphomas and leukemias.Conclusions: Cell and gene therapies promise durable clinical benefit from a single treatment course. High upfront reimbursement for these products means that the total costs could exceed what the healthcare system can manage. This creates a need for precision financing solutions and new reimbursement models that can ensure appropriate patient access to needed treatments, increase affordability for payers, and sustain private investment in innovation.