In recent years, rare disease products, or orphan drugs, have observed an increase in research and development (R&D) focus from pharma, biopharma, and biotech companies. A study forecasts orphan drug sales to reach $217bn by 2024, apportioning one-fifth of the total global prescription drug market(1). This shift in focus is expected as orphan drugs benefit from accelerated clinical development timelines, relatively lower commercialization costs(2), higher market valuation(2), and financial inflows for developing improved diagnosis and treatment approaches(3).
The “blockbuster model” that traditionally drove the pharma industry seems to have lost its relevance to rare disease drugs, which offer a greater return on investment (ROI) (2).
While developing orphan drugs can prove extremely rewarding for life sciences companies, launching and promoting rare disease treatments can be exceptionally challenging. It is challenging to identify the right patients, the reimbursement environment keeps changing, and distribution models need frequent enhancements. Therefore, while planning the launch and go-to-market strategy for orphan drugs, pharma companies need to carefully assess their target market and patient personas to design a Marketing Mix (MMx) model that answers the rare disease landscape’s uniqueness.
Vipul Pandey, Director – Decision Science, Axtria, is an expert in the Rare Disease MMx analytics and consulting space, and I had the opportunity to sit down and talk with him. In our conversation, he speaks about his experience working with the top ten pharma companies, his point of view on this therapy area, the associated challenges, and the way forward for commercial organizations operating in this space.
“Rare disease products, also known as orphan drugs, affect a tiny percentage of the total patient population, typically less than 200K patients in the US. From an MMx standpoint, there are three critical challenges posed by orphan drugs:
Read Axtria’s white paper on “Challenges And Opportunities To Commercialize Orphan Drugs For Rare Diseases In The US” here.
“For traditional pharma drugs, it is still okay to build a single MMx model where all the marketing channels are evaluated based on their impact on overall sales or prescription volume. However, given their uniqueness, it becomes imperative to build patient-centric MMx models for orphan drugs. These models need to evaluate the impact of promotions on getting new patients to therapy and increasing patient adherence. This approach aligns with the philosophy that not all channels are designed with the same objective, and they should be given appropriate credit for the roles that they play in the system.”
Orphan drug MMx models need to evaluate the impact of promotions on getting new patients to therapy as well as their impact on increasing patient adherence.
Read Axtria’s white paper on “Designing A Patient-Centric Commercial Strategy” here.
“The choice of datasets used for the MMx of an orphan drug depends on several factors. Although, two are critical to note.
“Technology can play a crucial role in streamlining the MMx process. For example, having a marketing data hub can help reduce the data collection effort, which often takes about 30-40 percent of the total time spent in a typical standalone MMx project. Besides, having the complete process set up in industrialized analytical tools like Dataiku, KNIME, or Alteryx can further streamline the model refresh process. However, it should be noted that the models may require significant calibration or even changes in the model structure itself if there are substantial changes in the market landscape. These changes can be as varied as a new product launch, a competitor’s loss of exclusivity (LOE), or a global event, such as the COVID-19 pandemic.”
Read Axtria’s case study on “Orphan Drug Commercialization For An SMB Pharma Organization Enabled By Axtria DataMAx™” here.
This discussion lays down the predominant challenges of the rare disease commercial landscape and acknowledges the role of sophisticated data, analytics, and technology needed to sustain in the long run. Speaking from his experience of working with several orphan drug engagements, Vipul suggests that rare disease commercial models should focus on the patient and continue through the entire treatment cycle – including adherence. He also recommends using robust data management and industrialized analytics capabilities to speed the time-to-market and ensure productivity gains. Given the highly complex ecosystem, rare disease commercial operations must be planned, executed, and assessed with utmost precision and understanding.