“Supermodel” is not a term I was expecting to hear at this year’s ISPOR Europe conference in Copenhagen, which had the Digital Transformation of Healthcare as its overarching theme. But then again, the term made sense in the context of a session on personalised precision medicine. Jan Geissler, founder of patient cancer advocacy group Patvocates, questioned whether there is a danger with genomic testing and advanced therapies (such as CAR-T therapies) of “creating the next supermodel medicine: lovely to look at, very costly, accessible only to a few, and of real value to many?”

Speakers during this Special Interest Group session reiterated precision medicine’s potential to improve outcomes without increasing healthcare costs. Case in point, precision medicine has played an important role in declining mortality rates (specifically five-year cancer survival rates) in a range of cancer indications in the US. However, to unlock the full potential of precision medicine, access to diagnostics and treatment is key. The session highlighted the continued challenges with implementing genomic testing in the US, including next-generation sequencing.

The presentations reminded me of the current challenges faced throughout Europe for adoption of advanced therapies, including calls from the Spanish Society of Haematology and Hemotherapy (SEHH) to “democratise” access to CAR-T therapies. The SEHH has complained about insufficient number of reference centres for these therapies due to alleged use of inaccurate population/geographical criteria by the Spanish Ministry of Health (MoH). The Society has asked for an expansion of centres to include those willing to conduct allogenic transplants even if lacking in experience.

CAR-T therapies are also being used as test cases for Valtermed, Spain’s new information system to determine therapeutic value in clinical practice of medicines of high health and economic budget impact in the National Health Service. Novartis‘s Kymriah and Gilead’s Yescarta, CAR-T treatments for blood cancers, are among seven drugs financed publicly through payment-by-results agreements that will have their outcomes measured by Valtermed. According to the MoH, these medicines have been prioritised due to the need to reduce clinical, financial and/or social uncertainty. As a “live system”, Valtermed is designed to provide information to help with drug coverage decisions.

Using RWE to revisit HTA decisions

A formal system for using real-world evidence (RWE) in the context of revisiting HTA decisions was at the centre of another lively ISPOR session, in which representatives from the Office of Health Economics (OHE), the National Institute for Health and Care Excellence (NICE) and Novartis debated its merits. The Cancer Drugs Fund in England was highlighted as an example for RWE collection post-adoption to inform subsequent HTA decisions, albeit for only three drugs so far. Another example showcased was France’s requirement for manufacturers to fund a post-listing study (looking at how a new drug is being used), which is then consulted every 5 years during the drug’s reassessment.

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According to the NICE representative, revisiting HTA decisions with RWE is a resource-intensive exercise, impossible to replicate for every product. There is increasing pressure as more products arrive with higher uncertainty (such as gene therapies, rare therapies and immunotherapies), where reevaluation would be valuable. But there are already capacity constraints, as under the 2019 Voluntary Scheme for Branded Medicines Pricing and Access, the HTA body will be appraising all new active substances by April 2020.

The pros of RWE-driven reevaluation, from the NICE stakeholder perspective, include up-to-date HTA decisions, linked to disinvestment in therapies that are no longer cost-effective, and RWE studies being more generalizable to NHS patients. The cons center on more uncertainties, driven by poor quality of data, or missing data, and bias due to lack of randomization.

From the Novartis representative’s perspective, given resource intensiveness, RWE collection is not appropriate for routine reevaluation of HTA decisions due to the potential risk of limiting access to safe and cost-effective drugs. Manufacturers would rather see conditional approval, with further data collection when a reimbursement decision is not possible due to the level of uncertainty at launch, such as for rare diseases. In these instances, a decision needs to be made in terms of who funds the RWE collection, the timeframe for reappraisal, and the temporary pricing and reimbursement conditions.

The industry speaker drew attention to the need to consider downstream price increases, particularly when industry is paying for data collection. The rationale provided was that only allowing price cuts creates a perverse incentive for the manufacturer to price a drug to the absolute maximum at the outset, whereas a risk-averse HTA body will push for the opposite. And the latter might result in the manufacturer questioning the rationale for investment in RWE collection. The ramifications of the RWE data being better, worse, or in line with RCT data were contemplated, but ultimately it was decided this depends on who funds the data collection.

There was consensus between the OHE and manufacturer perspectives for the need to overcome generalizability issues when using RWE from different countries, such as different clinical management strategies and different outcomes of interest. The industry speaker highlighted that it is not sustainable for every payer to insist that manufacturers provide observational study data from their own market.

There is a clear need for payers and manufacturers to work together in generating RWE data, as is the case in Spain’s recently created Valtermed. In fact, this is the fruit of collaboration between the Spanish MoH, the regions (the actual budget holders), healthcare professionals and the pharmaceutical industry. Against this backdrop, greater collaborative efforts between key stakeholders have emerged as the way forward to avoid a new generation of supermodel medicine.