In this call, the following activities were performed to bolster our business case, select a primary indication and develop a decision model which allows for a rational way to make development choices and anticipate on future events.
First, the competitive landscape for the treatment of chronic kidney disease was further investigated with particular emphasis on the patient journey (i.e. when is patient diagnosed, what is the state-of-the-art treatment, first-line/second-line/etc. treatment). We discovered that mCura1 is initially best applied in the later stages of the disease, because there is the greatest unmet need compared to the current available medicines. Furthermore, we expect mCura1 to display the most prominent therapeutic activity in the later, more complicated stages of disease. Next, we identified for each indication within the CKD-category the most appropriate sub-groups. Initial proof-of-concept in these groups lays the foundation to role mCura1 out in the larger CKD-population.
In the second step of the project, we analyzed the IP-landscape in further detail and found our current strategies to maintain freedom-to-operate to be effective. The deeper analysis, however, also showed some trends in the type of matter that is being claimed and areas that might become more crowded in the near-future. Based on this information, we prioritized some of our development programs involving the technological basis of our platform, and that might be potentially impacted by advances in the aforementioned areas.
Next, we built a decision model with as much detail as possible, delineating possible development paths, anticipating experimental outcomes and most importantly, the consequences of choices being made. Using the risk-adjusted net-present-value (rNPV) as a well-established mathematical model to weight possible choices against each other, we identified some significant late-stage risks in the mCura1 development plan. We designed various risk-mitigating measures, including advancing another drug candidate ahead of mCura1, to validate common components. To this end, we built a decision matrix, which allows for the comparison of over 200 indications across more than 25 parameters, including unmet need, market value and the competitive landscape. Based on this, we selected 16 indications and designed development programs for each. Together, these results form a decision model to guide mCura1 and various other drug candidates through development and onward to commercialization.
Finally, we calculated a rNPV for the mCura1 program in various development scenarios and conclude that mCura1 should be further developed (Go).
The updated business plan is currently being used in discussions with private investors, with the ultimate goal to obtain financing for further development.
