Need:

The COO of a small pharma company had started to receive licensing term sheets for an asset that MSC had helped value and was interested in comparing differently structured term sheets based on the valuation.

Assignment:

MSC consulted the client about its ideal deal outcome and the type of terms the client was interested in negotiating further. Based on this input, MSC created a management tool for comparing different term sheets. The model provided negotiation flexibility in how to structure the deal regarding geographies, R&D milestones, commercial achievements, sales targets, etc., with a dynamic re-calculation of the total deal value based on the target patient population. In the end, the client chooses the deal partner with the most attractive profile and offer, which turned out to be one of the largest preclinical deals in the area. In addition to scoring a great deal, the model also enabled the company management to perceive its deal strategy in a higher perspective and think more strategically about how much of an asset’s value to capture when deciding to divest anything in its portfolio.

Need:

The management of an oncology company with an ongoing clinical phase 2 trial needed an independent valuation base for one of its key assets for a meeting with an interested venture capitalist.

Assignment:

MSC conducted strategic workshops with the management and gathered relevant source data to conduct a thorough valuation of the clinical asset. A number of market assumptions were made in consultation with the client and a number of workshop discussions led to consensus around the target TPP to be valued. Based on an extensive epidemiology analysis in the client’s targeted regions (EU28+3, China and the US), a projection of the number of the eligible patients according to the TPP was made. Benchmark analyses were then made to estimate relevant pricing, R&D costs as well as the expected pre-market and market related miscellaneous costs. Overhead costs, of the client’s most likely big pharma partner, were modeled to calculate the most likely net income from royalty payments. Lastly, risk-adjustments were made based on clinical data to estimate the likelihood of approval for the current development stage in the specific indication to model a net present value for the oncology type. To model a likely deal value, 500+ recent oncology deals were analyzed based on client specific characteristics – resulting in estimated ranges for typical upfront payments, milestone amounts (and types) and royalty percentages. The two resulting scenarios were close and helped the CEO convince the venture capitalist about the value of the company’s drug.