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As More Gene Therapies Come to Market, Access and Affordability Remain Concerns

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Operational forecasting for patients who are eligible for gene therapies will be crucial for addressing the accessibility and affordability challenges with these agents, especially as more gene therapies are expected to enter the market in the next few years.

There are 8 FDA-approved gene therapies, most of which are indicated for cancer. Additionally, 2 more approvals are expected by the end of the year and at least 4 are projected in 2024.

There are 8 FDA-approved gene therapies, most of which are indicated for cancer. Additionally, 2 more approvals are expected by the end of the year and at least 4 are projected in 2024.

As the list of gene therapies in the pipeline continues to grow, utilizing operational forecasting for eligible patients can help address ongoing accessibility and affordability challenges related to these therapies, according to panelists at the Academy of Managed Care Pharmacy’s annual Nexus meeting in Orlando, Florida.

During the session, panelists gave an overview of the gene therapy market and pipeline, as well as highlighted the utilization of clinical trial inclusion and exclusion criteria applied to health insurer data and how it can be used to create a gene therapy candidates forecast.

The current gene therapy pipeline contains 2075 candidates. So far, the FDA has approved 8 gene therapies, with 2 more approvals expected by the end of 2023 and at least 4 more anticipated in 2024. Although the increase in therapies is exciting, Pat Gleason, PharmD, assistant vice president at Prime Therapeutics, noted that the initial list prices of gene therapies at the time of FDA approval can range from about $800,000 to $3.5 million.

There are many challenges affecting gene therapy affordability and accessibility, including fixed pricing associated with alternative payment models and forecasting candidates. Additionally, defining gene therapies can be complicated as the mechanisms and processes associated with gene therapies have dramatically changed over the past 20 years.

“There is a gray area around how you define gene therapy. And this becomes important when you engage in any kind of forecasting. So, if you think back to the early 2000s, you would describe gene therapy with 2 fundamental approaches. The more basic approach would be drawing blood from a patient, taking that blood, reprogramming it with genetic material, and then reintroducing it back into the body. The second method would be that direct administration of a gene treatment into the body…. But now we have new tools that can carry gene components that can fix DNA directly. And so, this is an exciting area [to watch],” described Landon Z. Marshall, Pharm D, PhD, principal health outcomes researcher, Prime Therapeutics.

Marshall outlined the 4 operational phases of identifying current future utilizers for a given gene therapy:

  • Step 1: aligning the definition of gene therapy; gene therapies should have a curative intent and 1-time administration
  • Step 2: obtaining up-to-date information on the regulatory status and assessing the overall clinical development status of the gene therapy
  • Step 3: examining analytics of gene therapies using methods like therapy-specific identification algorithms, which maintain and update each algorithm for existing therapies on a monthly basis, as well as building new analytics for new gene therapies that are added to the forecast
  • Step 4: forecasting potential candidates, gene therapy uptake and market demand, and manufacturer market capacity

“Building key features within your analytic process really allows you to kind of turn on and turn off some of these therapy-specific algorithms. So, the goal here is really to build an analytic process that enables you to strategically design your forecast and build a supporting code in a way that really eases maintenance and updates,” explained Marshall.

Gleason emphasized some of the challenges associate with forecasting gene therapy uptake, including limitations with medical and pharmacy claims data, lack of published information for rare diseases, the unique clinical aspects of novel therapies coming down the pipeline, and limitations of forecasting, such as appeal overturn and health plan impact.

In the future, Gleason said that managed care pharmacists will need to understand the impact of gene therapies on rare disease populations as well as increasing specificity in International Classification of Diseases, 10th Revision codes by integrating a variety of data sources. He also suggested the incorporation of gene therapies and remarked that value-based purchasing agreements, offer-based contracts, and warranties in this marketplace will be essential.

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