Market size is one of the critical elements in commercial due diligence, new product planning, commercial assessments for licensing/partnering and investments. Computing from the first principle is a robust approach and help clients understand the fundamental drivers of the opportunity. For a typical pharmaceutical asset, the process is summarized below:
- Number of patients: This involves using demographic and epidemiological data, and uses the following formula:
- Country population x Prevalence/Incidence x Diagnosis rate x Treatment rate
- Addressable Segment: In this step, the total number of patients is further drilled down to identify the segment where the therapy/intervention will be used. For example:
- If the treatment is second line therapy, then computation needs to factor-in the fraction of patients who fail first-line treatment.
- Similarly, if the therapy uses a biomarker, then the computation should include only the fraction of patients who are biomarker positive.
- Patients on product: This step effectively estimates what fraction of the addressable patients would be treated with the therapy considering the competitive landscape. This process also utilizes KOL interviews/market research to compute the market share, and leads to estimation of patients on product.
- Annual product requirement: Here we multiply the number of doses per year and the fraction of patients who complete the medication schedule (compliance) i.e. we ignore the fraction of patients who stop medication for various reasons. This provides unit sales of the product on an annual basis.
- Price: We compute the price using various approaches. Analogue pricing involves looking at the price of comparable drug and pricing similarly. If there are good pharmacoeconomic indicators, cost saving arguments, etc., then there is opportunity for a premium price by articulating a compelling value story to the payers. A typical pharma company will discount the list price for favourable pricing and reimbursement, and a wider market access strategy, so factor this in the model. A good practice is to conduct sensitivity analysis around price.
- Peak sale: Product peak sale is estimated rather simply by multiplying annual unit sale with expected price.