Manufacturing Resource Planning for Ethical Pharmaceuticals Using Market Models
Michael Latta · The Journal of Business Forecasting Methods & Systems · 1998
Explains in detail how market models can be used in the pharmaceutical industry to get a better handle on manufacturing resource planning (MRP) forecasts one should prepare monthly forecasts taking into account seasonality, competitive actions, and other changes in market conditions as monthly actual sales are recorded, they should be incorporated into a new monthly MRP forecast. Manufacturing resource planning (MRP) is one of the most difficult forms of forecasting in the pharmaceutical industry. The forecasting professional must provide a liason function between the functional silos of marketing and manufacturing. Typically, marketing is responsible for providing an MRP forecast to the manufacturing group on a monthly basis. Since the accuracy of these forecasts has a major impact on the bottom line (and sometimes on the annual bonus percentage), the method used to generate the forecast must be understood by both the marketing and manufacturing teams. Market models provide a powerful and flexible way of providing these MRP forecasts in a comprehensible format. In an earlier article on market models in the pharmaceutical industry appearing in these pages, it was argued that market models expressed in Excel spreadsheets are useful tools for developing demand forecasts. A market model involves a market definition representing everything the marketing team knows about the market structure and dynamics. This approach allows the forecasting professional to capture assumptions about the market and utilize available data from industry studies, syndicated research reports, government statistics, and proprietary marketing research surveys. The market model then converts this information into a demand forecast. Excel provides a widely available way of representing the market definition and performing the computations necessary to forecast unit demand and resultant financial performance. A hypothetical example (Thyroidex marketed by ON(:COS Pharma) was used to illustrate how market models can be developed and used to compute base case, upside, downside, and worst case forecasts of demand. By way of review, in the Thyroidex patient model, we are assuming 20,000 newly diagnosed cases of thyroid cancer each year with a total population of advanced thyroid cancer patients of 100,000; with 10,000 newly diagnosed patients with thyroid cell changes that are pre-cancerous, with a total population of 50,000, early stage thyroid pre-cancer patients. In clinical practice, oncologists consider 50% of the advanced patients and 25% percent of the early patients to be potential candidates for Thyroidex. When an advanced patient is prescribed Thyroidex, 80% of the time the daily dose is taken as prescribed. Since Thyroidex is a one tablet a day drug, this means the average patient takes 292 tablets a year. When an early patient is prescribed Thyroidex, compliance drops to 50% and the average patient takes 182 tablets a year. Thyroidex has an advanced disease market share of 75% with the other 25% going to radiation cocktails as adjuvant therapy, and it has a market share of 10% in early patients with the remainder simply being observed with no therapeutic intervention. These assumptions are represented in a Thyroidex Patient Market Model in Table 1. This patient market model forecasts realized sales of $11,401,687 of Thyroidex for 1998. CREATING A BASE CASE USING THE PATIENT MARKET MODEL The factors and assumptions of the patient market model can be rearranged and used to create a base case. This base case can then be used to forecast annual unit demand and corresponding financials over the forecast period using Excel. The forecast period can be either short term (next year), medium term (five years), or long term (ten years). For any forecast period, the market definition and assumptions forming the base case define the inputs to the model with forecasted tablets and dollars as the outputs. The inputs include: Market growth based on industry statistics or proprietary research, Days of therapy, Size of patient subgroups, Market shares, Tablet price, and Discount and charge back percentages from company financial records. …