What Matters: realizing value for innovation

Overcoming hurdles to market access is no small matter. Increasingly, cost-effectiveness and cost-containment are trumping safety and efficacy. What Matters is the place to examine and address the challenges facing biopharma in gaining market access.

If your passion is realizing value for innovation, welcome to the conversation.


Part III: 4 Market Access Assumptions Misleading Biotechs

Part III: Global market access planning begins after phase III clinical trials

A founding principle for Context Matters is the connection between clinical trial design with regulatory and reimbursement decisions—the earlier you start thinking about market access the better. Aubagio® offers a great example of the connection of clinical trial design with reimbursement and regulatory decisions.

Part II: 4 Market Access Assumptions Misleading Biotechs

The health technology assessment (HTA) process takes time, but how much delay in market access should you expect? The time it takes for an HTA agency to issue a reimbursement decision can be a major factor in the overall market access timeline. While HTA agencies publish timelines to set an expectation, those timelines are not always adhered to and decisions that take longer slow down speed to market. This can result in significant business repercussions for the manufacturer including decreased ability to gain market share and increase in time to revenue generation. So, when formulating a market access strategy, an understanding of the observed time for decision versus the published timelines can help to plan and set appropriate expectations. We also want to identify other important factors of market access that take place after a decision is issued and have the potential to affect market access.

4 Market Access Assumptions Misleading Biotechs

Biotechnology companies often do not have the market access resources comparable to large pharma. While this can pose a challenge, there is a considerable opportunity for biotechs to reduce this disadvantage by using health technology assessment (HTA) data in innovative ways to inform and drive their market access decision-making.

With our innovative technology platform and focus on data quality, we have been helping biotech companies understand the market access space for bellwether HTA agencies for the past seven years. Throughout our experience with biotechnology companies, we continually see four assumptions about the HTA process and market access:

Accelerating Immuno-Oncology Therapies to Market

In their 2015 industry report, the Pharmaceutical Research and Manufacturers of America (PhRMA) estimated over 800 cancer therapies were in the industry pipeline—citing that approximately 80% of these drugs have the potential to be first-in-class medicines. One of the most groundbreaking areas in oncology today is checkpoint inhibitor immuno-oncology (I-O) treatments, with the American Society of Clinical Oncology (ASCO) naming immunotherapy as its 2016 Advance of the Year. Checkpoint inhibitor I-O treatments unlock immune system cells, allowing the cells to recognize and fight cancer tumors, and have shown early efficacy gains that have given hope to many oncology researchers, physicians, and patients. An exciting breakthrough that raises the question—what is the fastest and safest way to get these new treatments to patients?

Implications and Use Cases for HTA Decision Predictive Models

Predictive modeling can be a powerful tool for understanding how multiple factors contribute to an event. As outlined in previous posts, Context Matters created a model that used variables from oncology assessments by the Scottish Medicines Consortium (SMC) to identify the most influential variables for a positive reimbursement decision by that agency and used the model to demonstrate the impact that economics (i.e., patient access schemes and ICERs) have in predicting positive SMC decisions for oncology drugs. However, as discussed in our previous post, Understanding Predictive Modeling, not all models are created equal. One measure of a predictive model’s quality is its ability to deliver actionable results and insights. If a model is not able to inform the initial hypothesis and provide a path forward, it is just an academic exercise. But what does it mean for a predictive model to be “useful” and to deliver “actionable results”? What are some of the implications and use cases for predictive models of Health Technology Assessment (HTA) agency decisions?

Key Drivers of HTA Decisions for "Life-Changing" Drugs

There are mechanisms in place to reward innovative and “life-changing” drugs. Most of these mechanisms exist in the regulatory process, but what about the reimbursement process? Are “life-changing” drugs rewarded by health technology assessment (HTA) agencies with positive reimbursement decisions? This original research applies a data-driven approach to evaluate the key drivers of HTA agency decisions for drugs that provided significant improvement in benefits over existing therapies.