Forecasting demand and planning capacity is a critical component for all biopharmaceutical companies preparing to launch a new product. To create this forecast, it must factor in its estimate of the size of future sales, the timing
of the launch, the dosage of the product, its strategy for building its market and a host of other variables. Variations in any one of those factors can lead to drastically different demand scenarios. If a company overestimates demand, it may end up investing in too much capacity and therefore find itself paying more per unit of the product than it needs to, thus impacting its margins. If it underestimates demand, it risks not being able to satisfy demand, therefore losing revenue. This white paper provides best practices for building better forecasts, determining demand and mitigating risk.

Why Forecasting is so Difficult

Forecasting demand is a complex endeavour. For instance, it’s not unusual for the forecasted and actual dosage of a product to vary by a factor of as much as three. Obviously, that makes a big difference to a demand forecast. If a manufacturer has built capacity in anticipation of a new product and its clinical trial is delayed for any number of reasons, that manufacturer’s capital is tied up in a fallow facility. For a small company for which liquidity is critical, that can be catastrophic. When planning for capacity, a manufacturer must consider both volume and scale. Both are important; the effect of scale is to make costs non-linear with volume. For example, say a manufacturer makes a 2,000-litre subculture batch at a cost of about $1.5 million to $2 million, including raw materials. For a titre of 1 gram per litre, that’s about 1.6 kilos of active pharmaceutical ingredient (API) with yield losses at a cost of $1,250 a gram. A 20,000-litre batch, which would cost $4 million, would yield about 16 kilos of product at $250 a gram. That’s 80% less than the 2,000-litre batch, which is much more cost effective.