Typically, pharmaceutical and biotech companies have focused their Clinical Outcome Assessment (COA) development efforts solely on the requirements necessary for regulatory approval. While we recognize that is extremely important, today we are going to discuss how pharmaceutical companies may reap benefits from a longer term approach. An approach that addresses long-term market access hurdles can lead to continued product differentiation in the face of ongoing competition and subsequent long-term payer acceptance. Drug development strategies that optimize COA data – including patient, clinician, and observer reported outcomes (PRO, ClinRO, and ObsRO) – can be used strategically to support regulatory approval and, increasingly, post-marketing success.
The development of COA endpoints, wherever you are in the product lifecycle, should always answer three clear questions (in order):
1. What messages are you trying to test and convey?
- Create the messages you want to deliver at the end of your work
- Identify the concepts, or what you want to measure, that will support your messages
- What you want to measure depends upon:
- Who is in your target patient population
- Who you want to influence with your results – regulators, payers, clinicians, and/or patients themselves
2. How are you going to measure the concepts behind the messages?
- Select instruments, based on your own research, that measure exactly what you want to measure
- Only select instruments after deciding on what to measure
3. How are you going to implement the study that gives you the data?
- Implement the instruments in study designs that give you the optimal endpoints to evaluate what you want to measure
This takes you beyond the very limited thinking regarding regulators and the narrow concepts of what you measure, to the broader focus on what the impact of this product is on the patient’s Health Related Quality of Life (HRQOL). It should also get you thinking about how you are going to convey that information in the most compelling way. For example, if you are dealing with a debilitated population, maybe it’s mobility information you want to convey. If it is a very healthy population, maybe it’s strong physical exertion. This is why really understanding the message and patient population and then focusing on the concept is important. Once this is established, you need to determine how you are going to measure and implement that concept, and finally, you need to select which instrument you will use. We suggest following this process for all stakeholders – not just for regulators.
With that foundation in place, we can now move to where we think the market is heading and how pharmaceutical companies can prepare for those changes. We believe that several combined elements – such as payer interest, big data and manufacturer needs – suggest that there will be an increased demand for and use of phase 4 economic reviews. Ultimately, payers and reviewers are going to evaluate your drug and make the decision whether to cover it (or not) and at what price.
As always, payers are interested in cost control and soon they will be able to measure costs very well. Also, there is the diffusion of use of more formal Health Technology Assessment (HTA) methods, which uses only generic utility measures – unless other credible measures are provided by you. Finally, there is always the pressure to drive therapeutic substitution.
With the ability to slice and dice data from populations into subgroups, it is much easier to measure hard outcomes. There is relentless pressure to measure outcomes, so a manufacturer will need to prove a drug’s benefits.
Product differentiation is increasingly important, yet there is a need to control development costs. You’ll want to be able to defend long-term product value without needing to run another huge trial or contract discount.
Based on these factors, if you anticipate additional reviews, you’ll want to start thinking about the type of data payers will want to examine. If you talk to payers directly, some may lead to you believe that they only care about budget impact and not much else. However, there are good reasons for investing in the collection of COA data. It is true, payers are looking to treat their patients and to do so at a good price. However, once the product characteristics are known, it is in the payers’ interests to say they care less about patient benefit. The fact that they say it doesn’t matter doesn’t make it true. So never stop selling benefit to stakeholders! This is where COAs can help, because you can come in with credible measures rather than some qualitative statements. Payers need to gather product information, design the rules for the selection, and conduct a selection. All of these are affected by the medical community, particularly inside the payer and also patients. So the implication is that tangible benefits data will be helpful to a manufacturer during a negotiation, and in the “game” before the negotiation.
You may be thinking, “What will payers likely ask/want at these frequent, ad-hoc reviews?” Here is a list we’ve put together to help you get started:
- Why is your drug better than your competitor’s?
- Show us something new in our patient population – we’ve already seen your registrational data.
- Your competitor went generic. We want a discount.
- Please respond to your competitor’s observational studies in our patients showing that its life-cycle costs are lower than yours.
- We just read an AHRQ/NICE/PCORI study that shows that all the drugs in this class have only tiny differences. Give us a reason not to implement the obvious implications of that finding – which is to engage in competitive contracting.
You’ll need to get started early on answering these questions because the lead time to respond is usually very short (weeks or a few months). How long might it take to produce credible data in publications, which could then be taken to review bodies that control access? We estimate the total time from brainstorming to publication is approximately 5 years.
- Planning COA strategy: 1 year
- Beta testing COA instruments: 1 year
- Full scale trial in the field: 2 years
- Write up and publications: 1 year
Post-marketing COA could be a valuable addition in a difficult market. ERT is readily available to support you – whatever the size, complexity and therapeutic area of your clinical program. Contact us to speak with an expert consultant on how to optimize your COA strategy. This is an opportunity to speak with a Senior Scientist and discuss what reasonable steps you can take to reduce risks and ensure the success of your clinical development program.
If you enjoyed this blog and would like to learn more, please visit www.ert.com/webinars to view a full 1-hour presentation on this topic.
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