To determine the trade-offs across key biosimilar attributes that surveyed medical oncologists are willing to make when considering which biosimilar to prescribe, we included an adaptive choice-based conjoint (ACBC) module in the survey. Following appropriate analysis, ACBC data allow for the simulation of physician preference share and likelihood to prescribe of user-defined target product profiles (TPPs). Conjoint analysis is based on the idea that any product or service is seen by consumers as a combination of attributes or features, each of which contributes to their overall interest in the product or service.

We report on key ACBC analysis findings and one market simulation performed on three hypothetical TPPs (see the “Conjoint Analysis-Based Simulation of a Market Scenario”). The Excel-based Target Product Profile Simulator allows for the creation of up to seven user-defined TPPs with varying performance across the attributes included in the survey. To access the Excel-based Target Product Profile Simulator, see the “Downloads” section of the report.

Through research conducted by Decision Resources Group, we identified six attributes relevant to the assessment of biosimilar development opportunities in the oncology space to be included in our analysis. We included attributes for which are known to be key differentiators of biosimilars in the oncology space, including price:

  • Availability of clinical data in the indication I am prescribing for.
  • Inclusion in treatment guidelines.
  • Type of manufacturer.
  • Reimbursement restrictions.
  • Postmarketing data (time on market).
  • List price.

To select clinical attributes for our conjoint analysis, we considered insight from surveyed clinicians on key clinical and commercial factors influencing biosimilar prescribing choice as well as regulatory guidance on biosimilar development. Surveyed physicians' perception of the efficacy and safety of a biosimilar compared with its reference brand are key factors influencing its uptake. We included attributes that inform the type of clinical data available at launch, which can range from none (i.e., indication extrapolation) to full Phase III data, as well as the duration of postmarketing data. External factors (e.g., market access) also influence biosimilar prescribing choice; here, we included attributes that capture inclusion in local or national treatment guidelines and general payer policy. Surveyed physicians reported that trust in a biosimilar, and therefore prescribing comfort and choice, is influenced by manufacturer type; for this attribute, we included all key developer types evident in the global pipeline, ranging from large multinational biopharmaceutical companies to companies in emerging markets. Unsurprisingly, cost is the central driving factor that influences biosimilar uptake; here, we allowed for a range of list price discounts up to 50% relative to the reference brand.

Table of contents

  • Biosimilars - Current Treatment - Biosimilar Target Product Profiles (Oncology)

Author(s): Neela Rambaruth

Neela Rambaruth is a Business Insights Analyst in the Oncology division at DRG. Neela joined DRG in 2018 and has since authored the Disease Landscape and Forecast report for non-small-cell lung cancer. Neela is currently working on the Disease Landscape and Forecast report for Hepatocellular carcinoma and the survey for Immune checkpoint US Access and Reimbursement.

Prior to joining DRG, Neela Rambaruth was a Postdoctoral Scientist at University College London, where she investigated the interaction of novel drugs with a therapeutic receptor involved in cardiovascular disease.  She also held another postdoctoral position at Imperial College London, where she studied host-pathogen interaction in tuberculosis. Dr Rambaruth holds a PhD in Breast Oncology from the University of Westminster.  Her doctorate focused on the identification of novel biomarkers associated with metastatic breast cancer. She has also published several peer-reviewed articles in oncology and therapeutic drug discovery.


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