In earlier blogs, we discussed the Cell and Gene Therapy (CGT) landscape, the many complexities these therapies involve, and the role that automation can play to make their manufacture faster, safer and more cost-effective.
As complex CGTs enter the clinic, a central question is how to price and reimburse a potentially curative therapy in a way that makes it affordable for patients, while remaining commercially viable for pharma companies. This blog examines the issues faced by payers, and the role that Alternative Payment Models (APMs) may play in resolving these.
A hefty price tag
The cost of CGT is substantial and can vary widely. For example, CAR T treatment can cost approximately $450 thousand per dose (Kymriah at $475k, Yescarta at $373k), and gene therapies can cost from $2-3.5 million per dose (Zolgensma comes in at $2.1m, Roctavian at $2.5m, Zynteglo at $2.8m, Skysona at $3.0m and Hemgenix at $3.5m). Although these figures are, naturally, subject to variability, they indicate the scale of costs faced by payers.
These costs can’t be looked at in isolation either, when deciding whether to reimburse a new complex therapy, payers need to consider how the cost vs efficacy balance compares to available treatments, and also whether potential downstream healthcare costs could be negated by treating these patients better earlier on.
Price is just one factor
Complicating this question of pricing further is the fact that there is no ‘one size fits all’ solution; every CGT requires its own, bespoke pricing and reimbursement solution, which must take into account not only characteristics of the therapy and disease area, but also different regional payer dynamics.
Moreover, payers are concerned not only about the budget impact of the price tag itself, but a number of other issues. Some of the main concerns include: uncertain durability of outcomes, use of unvalidated or novel efficacy endpoints, lack of robust clinical data, and the small number of eligible patients1,2,3.
Introducing some solutions
This is where alternative payment models (APMs) have a role to play. The most common of these are outcomes-based models, also called value- or performance-based models. They allow the cost and risk of the therapy to be more evenly shared between the payer and the pharma company.
Outcome-based models generally function in one of three ways:1,2,4,5
1) Performance-based annuity payments linked to outcomes, where the payer makes one or more payment to the pharma company conditional on achieving agreed outcome targets.
2) Outcome-based rebates, where the full cost is paid upfront and the pharma company reimburses the payer if/when agreed outcome targets are not achieved.
3) Coverage with Evidence Development (CED), where price and reimbursement are based on a combination of longer-term follow-up from clinical trials and data from real-world practice.
Different models are favoured by different regional payers. For example looking at CAR T, the UK and France use a CED approach, Germany uses a combination of CED and rebates, and Spain and Italy use performance-based annuity payments4. For higher-cost gene therapies, performance- or rebate-based models are typically favoured4, as seen for Zolgensma, Zynteglo and Roctavian. It is also possible that CGTs may use a combination of these outcomes-based models, such as blended performance-based annuity payments with rebates.
Defining the parameters
Central to the success of any of these models, is selecting the ‘correct’ outcome by which to benchmark the outcomes-based agreement. This is not as straightforward as one might think. To use gene therapy as an example, would correct gene expression or improved patient functionality be a better measure of efficacy? Another question here is how will an APM adapt if a more accurate outcome measure emerges? Does this new outcome fundamentally change how we are thinking about the CGT’s cost-efficacy benefit, do the APM contract terms need to change, and do previously treated patients now change over to this measure? And who bears the risk of switching over to this new outcome measure.
There are several other variables, too. These include the need to define the target threshold for success, the timeframe, how best to measure the outcome, and who is responsible for the judging itself. The model must also account for the probability of achieving the target outcome, the time this will take, and its durability. The practical burden of collecting the real-world data required to measure these outcomes also needs to be considered1,2, as most healthcare systems aren’t sufficiently equipped to monitor patients this closely. And if patient outcomes can’t be followed up, this could prove problematic for both the payer and pharma company to execute on payment/rebate terms.
Comparisons to current options
While there are many considerations, ultimately, the cost vs efficacy balance will be a key decider in the success of a CGT, particularly how this compares to the standard of care therapy for a specific disease. This means that some diseases may inherently be better suited to a CGT solution, if the current standard of care carries a high economic burden. Here, the ICER (Institute for Clinical and Economic Review) plays an instrumental role in conducting comparative cost research to inform CGT pricing2.
CGT uptake will also depend on how well patients are treated by current options. In SMA, for example, patient prognosis is poor so the value proposition for GT is very high; as such, Zolgensma has seen strong adoption. In haemophilia, by contrast, patients are generally well served by current treatments so there is less pressure driving GT adoption.
Competition driving evolution
The use of APMs will no doubt increase as CGTs become more commonplace, however the bespoke nature of these models, also variable by region, means that any set guidance or plug-and-play system probably remains some way off. So what does this mean for the competitive environment for CGTs? The way current APMs are set up tends to favour larger pharma companies vs smaller biotechs, based purely on their ability to buffer and absorb large upfront costs, as well as manage uncertain payment milestones without risking their cashflow position.
This suggests that biotech’s will likely end up positioning as early-stage CGT developers, with the end goal of big pharma acquisition. On one hand, this sounds a bit like an enforced oligopoly, but on the other hand, it could be seen as mutually beneficial where the different players get to do what they do best. More agile biotechs do the innovating, and then hand over to big pharma (for a substantial payout) to do the commercial heavy lifting. As much as we want to see the little guy underdog go all the way, more than one biotech that has gone under as a result of missing their optimal acquisition window, and then lacking the resource to bring the asset to market themself.
Amid all this flux and uncertainty, ultimately more CGT options and better APMs can only be heading in the right direction for patients. It’s not perfect yet, but these new life changing treatment options do now exist for patients, and there has been substantial progress in making these ultra-high-cost treatments more affordable and accessible.