Among the most significant advances in medical science in recent years has been the development of cell and gene therapies. Unlike traditional treatments, this new class of therapies, in many cases, holds the potential for a cure with the administration of just a single dose, or a very short course of treatment.
While this provides promise for healthcare systems and patients, there is uncertainty and associated challenges for healthcare providers and payers alike. Cell and gene therapies often have high upfront costs resulting in “sticker price shock.” Current list prices range from tens of thousands to more than US$3 million for a course of treatment, depending on “value,” development and manufacturing costs and the size of the patient population involved.
Much of the challenge arises due to the mismatch between the desired financial models employed by manufacturers and payers to assessment of value and risk management associated with clinical and economic uncertainty. Governments, healthcare providers, and insurers are simply not set up to pay extremely high upfront costs for therapies regardless of their potential curative or lifelong benefits. Manufacturers, on the other hand, need to make a return on their investment based on the “potential” value of the asset to recover their research, development and production costs. There is also the additional complexity and often very high costs associated with the personalisation and administration of the therapies.
Short-term affordability challenge
Healthcare systems and insurers have grown accustomed to a ‘pay as you go’ system for the treatment of long-term illness and are not geared to meet the very high upfront costs of once-off or short-term treatments with long-term benefits. There is often a short-term affordability challenge. While payers may have the resources to pay over time, front-loading the costs with significant uncertainty and risk that the associated treatments will not deliver benefit poses an often unsurmountable hurdle to funding. In summary, payers are often unwilling to take a risk and pay upfront for “potential” value.
The situation is further complicated by the relative lack of evidence for those long-term benefits. Many gene therapies have been approved on the basis of relatively short-term and small clinical trials involving just a few hundred patients or less. Regulators may approve them based on benefit-risk assessment. However, payers may not be willing to take the financial risk on a product with unproven long-term benefits.
An example of how this can lead to commercial failure is Glybera (Alipogene tiparvovec), a therapy designed to reverse a condition causing severe chronic pancreatitis. Despite being approved and launched in the US market at a price of $1 million per patient, it was subsequently withdrawn having only ever been administered to one patient. In Europe, it never even made it as far as commercial launch at all as the health technology assessment agencies in both France and Germany did not recognise its long-term benefits.
One of the issues at play here is the fact that assessment bodies are not set up to evaluate wider system and societal benefits, such as savings on avoiding future treatments and procedures that would no longer be necessary, and improvements to patient quality of life and productivity.
Stakeholders in the ecosystem have proposed solutions to many of these challenges, and are devising new contracting arrangements aimed to deliver value-based pricing along with innovative payment structures. These include outcomes-based payments, which are linked to the clinical benefits of the therapy and the actual economic savings it delivers over time. These arrangements can also include a rebate mechanism where the payer has refunded all or part of the payment made earlier in the contract if specified target health outcomes are not realised.
Such arrangements have the beauty of obviating the need for a large upfront payment while linking long-term payments to the efficacy and durability of the therapy. However, they are not easy to design or implement. Agreement must be reached on the metrics and there need to be measures in place to monitor mechanisms and data collection infrastructure that both sides can trust.
Furthermore, there is additional complexity due to the fact that different jurisdictions have different approaches to evaluating the potential value and benefits of medicines, have their own price-setting and payment regimes, and have legal frameworks which need to be taken into account when dealing with highly sensitive personal data.
