Previously, Global Pricing Innovations (GPI) employed a multi-criteria decision analysis (MCDA) analogue-based approach to construct a robust, accurate and comprehensive value framework for orphan indications. This provided insights on payer perceptions by leveraging health technology assessment (HTA) documents, published sources, and payer interviews to assess the importance of various factors in determining the overall value of pharmaceutical assets.
Key Insights
Methodology
Building on previous GPI research in the orphan drug sector, a similar framework was developed for oncology. This included additional complexities specific to oncology, such as line of therapy, biomarker specificity, and type of combination. This research focuses on German payer perception of drug value and utilises the oncology value framework for two approaches dependent on specific indications: 1. Comparator selection approach, which involves price benchmarking when suitable comparators are available and 2. Analogue selection approach, which follows analogous regression forecasting in rarer oncology indications with limited/no suitable comparators.
Result
Payer perception of value for oncology drugs in Germany
Payer perception of value for oncology drugs in Germany
Through interviews and research with German payers, we identified that the value of a drug in Germany can be characterised by 23 attributes, which are grouped into four key value domains: Burden, Product characteristics, Trial design and Clinical benefit.
The relative importance of these domains varies, with different weightings assigned to each domain based on payer perception.
- Domair
- Definition
Burden
The patient, societal and treatment burden and potential unmet need considered as part of payer decision-making for a new product
Product characteristics
The features of a new product and the associated indication considered as part of payer decision-making Trial design
Trial design
The setup and methodology of a clinical trial providing evidence for a new product considered as part of payer decision-making
Clinical benefit
The perception of clinical trial results for a new product that will be considered as part of payer decision-making
Although product characteristics may not be a primary value driver for payers, all four domains—including product characteristics—are deemed important for selecting the appropriate comparators/analogues in value-based pricing analysis.
Case 1: Comparator selection approach in the presence of direct comparators within a specific indication
Approaches for value-based pricing analysis: Comparator selection vs Analogue selection
Depending on the market landscape for an asset in a specific indication, both the comparator selection and analogue selection approach demonstrate robust and data-driven insights for value-based pricing which facilitates an improved understanding of asset value and price within a given market landscape.
Case 1: Comparator selection approach in the presence of direct comparators within a specific indication
Example: In Germany, Libtayo (Cemiplimab) was approved for first-line treatment of advanced or metastatic NSCLC with PD-L1 expression ≤ 50% in 2021. Following the approval, the post-AMNOG price (i.e., the negotiated reimbursement price) was made available in 2022. At the time of Libtayo’s launch for first-line treatment of advanced or metastatic NSCLC, the direct comparators available within the specific indication were: Imfinzi (Durvalumab), Tecentriq (Atezolizumab), Keytruda (Pembrolizumab) and Opdivo (Nivolumab).
Due to the similarity of its overall value (Asset X/Libtayo = 25; Imfinzi = 27, Tecentriq= 28) amidst these comparators, Libtayo was predicted to not receive a price premium. As a result, the price would be set within the predicted range of €74,307 to €79,451 (Figure.2).
With the actual annual cost of Libtayo being ~€75,862, our prediction demonstrates the robustness in the methodology in determining an early value-based price point within a crowded indication.
* Keytruda was excluded from the comparator list for analysis as it was the first to launch in this indication, resulting in a higher initial price, while Opdivo was excluded as it received a lower price through AMNOG negotiations and was benchmarked against chemotherapy, not other immunotherapies
Case 2: Analogue selection approach in the lack of presence of direct comparators within a specific indication
Approaches for value-based pricing analysis: Comparator selection vs Analogue selection
Depending on the market landscape for an asset in a specific indication, both the comparator selection and analogue selection approach demonstrate robust and data-driven insights for value-based pricing which facilitates an improved understanding of asset value and price within a given market landscape.
Case 2: Analogue selection approach in the lack of presence of direct comparators within a specific indication.
Example: In Germany, in 2018 Imfinzi (Durvalumab) was approved for locally advanced unresectable NSCLC in patients whose tumours express PD-L1 ≥ 1% who had not progressed following platinum-based chemotherapy and concurrent radiotherapy.
As the first treatment approved for this specific indication, no direct comparators were available at the time of launch.
To establish a relevant price point, analogues were selected based on broader therapeutic indications, ensuring alignment with the same line of therapy. This led to the selection of Keytruda (Pembrolizumab), Kisqali (Ribociclib), Tagrisso (Osimertinib), Tecentriq (Atezolizumab), and Tafinlar (Dabrafenib), considering their similarity in disease burden, the absence of alternatives at launch, and availability of post-AMNOG pricing data.
Based on the actual estimated annual post-AMNOG price of Imfinzi, (€77,052), demonstrating the robustness of this approach in determining an early price point (Percentage difference: 0.92%).
It is important to note, however, that the accuracy of an analogue-based approach in forecasting the right price point is dependent on the choice of analogues, highlighting the importance of selecting the most relevant analogues for comparison.
Conclusion
Conclusion
