The Return On Investment of Better CDx Planning Based on Early PD-L1 Observations in NSCLC | Diaceutics

The Return On Investment of Better CDx Planning Based on Early PD-L1 Observations in NSCLC

April 4th, 2016

Sanna Jousi

Sanna Jousi of Diaceutics assesses the financial benefits of integrating the planning, analytical and action steps for successful development and commercialization of testing into targeted therapies.

The anti PD-1 therapy market promises to be the largest single oncology market, with peak sales projections of $33 billion (http://www.fiercepharmamarketing.com/story/pd-1-wave-report-says-its-33b-tsunami-bms-surfing-first-place/2015-03-04). Five major pharma companies have active asset programs in the space, each leveraging testing in second and first line cancer treatments differently. Merck and BMS have already launched Keytruda and Opdivo. A number of indications and therapy strategies will be specifically interdependent on the efficiency of the PD-L1 testing market so this merits a better understanding of the financial relationship between diagnostic market efficiency and lost therapy revenues.

Current PD-L1 testing options use IHC, the same platform which enabled the HER2 Herceptin franchise but which also took five to seven years to optimize. Retrospective analysis has identified up to $3 billion in lost revenue opportunity for Herceptin due to IHC testing issues.

To help determine the similar readiness of PD-L1 IHC testing to support therapy launches, Diaceutics has tracked key diagnostic drivers in real time and modelled their impact on estimated lost anti PD-1 therapy revenue for one indication only—second line NSCLC—in its first year of launch and over the following four years.

We have used the Diaceutics Financial Planner to reverse-model the current relationship between PD-L1 testing and therapy revenues generated to date. The metrics were used on target population patient penetration, dosing and laboratory adoption observed to date in second line NSCLC (US).

Using this platform we assessed the sensitivity of several drivers. Second line NSCLC drivers modelled:

  • Dosing advantage in high expressers
  • More accurate test answers
  • Greater conversion to therapy from test positives
  • Greater test adoption by physicians
  • All drivers optimized together

Disclaimer: This is an illustrative model only and is not intended to reflect existing or future therapy forecasts in the anti PD-1 space

The Base Case (Scenario 1) looked at revenues predicted within the model from 2015 to 2019 in second line NSCLC. The projected cumulative base case value for a therapy label dependent upon testing is $1.3 billion in the US market (Figure 1).

drug-revenue-2015-2019Figure 1. Drug revenue ($m) 2015-2019

Looking at the relative dollar impact of each optimized driver (cumulative five year revenues) revealed that whilst optimized dosing in high expressing PD-L1 patients (>50%) is the biggest single contributor, improving test accuracy and driving greater demand for testing confer significant revenue gains (Figure 2).

revenue-gainsFigure 2. Relative dollar impact of each optimized driver.

Using the model to determine the relative percentage impact of each optimized driver (cumulative five year revenues) showed that having all drivers optimized would confer an additional eight per cent of revenue over the single drivers alone.

Another way to consider this is as year on year lost treatment revenue. The model suggests that therapies have already lost around $40 million in treatment opportunity due to suboptimal testing. This accumulates over five years to $744 million in lost therapy opportunity in second line NSCLC alone, otherwise achieved if all drivers had been optimized (Figure 3).

lost-treatment-opportunityFigure 3. Lost treatment opportunity in second line NSCLC ($m).

Finally, when looking at the ROI of diagnostic driver investments expressed in anti PD-1 therapy dollars we saw that investment in greater test accuracy delivers the single greatest dollar for dollar return, but having all drivers optimized provides $24 for every $1 invested in diagnostics for this indication.

Conclusion

A suboptimal PD-L1 diagnostic marketplace is already resulting in lost treatment opportunities. As the dependence upon PD-L1 testing grows over the years and across indications, this is highly likely to magnify.

The Diaceutics model suggests that up to $744 million in lost treatment revenue is at stake in this one indication alone.

Based on this indication, an investment in optimizing the PD-L1 diagnostic marketplace is likely to confer more than $20 additional therapy revenue for every $1 spent on diagnostic investment. Improved quality of testing will deliver the greatest dollar for dollar return and linking higher dosing to high PD-L1 expressing patients should see the single highest dollar amount return.

Pharma asset and management teams are always concerned about the ‘opaque impact’ of investing in diagnostic optimization. By employing real time tracking of the PD-L1 market and reporting this in ‘lost treatment dollars’ it is our intention to highlight the significant financial benefit of earlier and better planning in diagnostic market optimization.

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