Developing a new drug is a satisfying scientific achievement. Bringing that new drug to market and making a profit is essential
to the continued existence of a company, and manufacturing costs are crucial to overall profit margins.
Operational planning and early cost analyses are key to generating optimal, robust, and economical commercial processes. Companies
can use models of their processes to understand and minimize production costs and optimize their manufacturing operations.
This leads to efficient processes and better scheduling and consumables control. The ultimate result is a successful, and
This article, the third in the "Elements of Biopharmaceutical Production" series, will discuss various tools available to
perform the modeling required to understand, develop, and optimize manufacturing processes, facilities, and operations. Anurag
S. Rathore discusses incentives and steps during process development. Then four industry experts present their viewpoints,
insights, and experience. Peter Latham and Howard Levine describe modeling tools; John Curling discusses problems of early
and late scale-up; and Oliver Kaltenbrunner discusses how to modify classical chemical engineering costing to the realities
Anurag S. Rathore: Incentives
The average cost to bring a new drug to market currently is about $802 million.1 Consequently, drug develo-pers are searching for tools and methods to contain R&D costs without compromising clinical test
data. Competition is so intense that FDA is reviewing more than 100 pharmaceutical and biotechnology products that are in
phase 3 clinical trials or beyond - the largest number of products so close to approval at one time.1
Production costs loom large in management planning. The optimal time to bring them under control is early in process development
while the processes are being designed and various options are still under consideration. Intense product competition, patent
expirations, the introduction of more second-generation therapeutics, and pricing constraints are forcing close scrutiny of
the economics of bringing drugs to market.
The sales price ($/g) of the different drug products generally decreases with increasing production volume. Biogen's Interferon,
a small-volume drug, sells at $2,940/g. Large-volume drugs such as intravenous immune globulin (IVIG) typically sell at $40
to $60/g.2 Also, the split between the cost of upstream and downstream unit operations reportedly depends on the source organism. The
upstream processing costs are lower (14 to 19% of total) for a recombinant E. coli or Streptomyces derived product and significantly higher (40% of total) for a mammalian cell culture product.3
Figure 1: Modeling tools vary at each stage of product development.
Many pharmaceutical and biotechnology companies are using and developing a variety of sophisticated techniques for evaluating
and minimizing the costs of each new therapy with the goal of generating optimal, robust, and economical commercial processes.
Performing cost analysis during process development can prove to be extremely helpful for several reasons.
1. When the process for a new therapeutic product is defined during initial process development, use an early cost of goods
sold (COGS) analysis to identify manufacturing cost drivers (for example, Protein A and virus removal steps). Then focus your
efforts on evaluating new technologies and process options such as increasing lifetimes of the chosen resins or membranes.
2. Take a detailed look at the cycletimes for different unit operations. The process design can be modified to increase productivity.
For example, use big bead resins for faster chromatography and appropriately sized equipment and utilities. Also, a model
could be used to evaluate the cost difference between a single large bioreactor and multiple small bioreactors.
3. Cost models of existing products can generate useful data for analyses of future products. Even for companies that outsource,
models can help predict the production cost and can serve as a starting point for negotiations with contract manufacturers.
Several development teams have recently written about their approaches to design more economical processes. If they look interesting,
consult the references. Remember, their applicability depends on similarity to your product and constraints specific to your
facility. Recent cases include the following:
- Using ion-exchange (IEX) chromatography as an alternative to Protein Achromatography.2,4 IEX is cheaper (media cost/g processed is $0.30 for High S Macroprep vs. $16.25 for rProtein A Sepharose) and is also free of contaminating immunoglobulins.2 However, additional steps may be required if IEX is used and may require process development time.
- Using membrane chromatography (MC) as an alternative to conventional resin column chromatography.5 MC requires higher medium and equipment costs, but lower buffer, labor, and validation costs might make it a more economical
- Using fully disposable, presterilized, and prevalidated components in the bioprocessing plant instead of conventional stainless
steel equipment.2,6 A comparison of two cases showed that the disposable option substantially reduced capital investment (60% of the conventional
plant). The running costs for the disposable option were 70% higher than for the conventional plant; however, there was a
nine-month reduction in time-to-market with the disposable option.
4. Optimize the facility to minimize downtime and improve efficiency of changeover and maintenance procedures. Some facility
changes meeting these objectives include: addition or upgrade of manufacturing area or equipment; upgrade of utility systems;
modernization of control systems; and coupling or decoupling of several process steps to improve operational flexibility and
maximize equipment utilization.
5. Focus process development efforts on increasing the titer of fermentation and cell cultures.7 A fivefold improvement in titer combined with a 40% improvement in downstream recovery resulted in a sevenfold reduction
in processing volume plus a fourfold reduction in COGS and associated capital requirements.
Peter Latham and Howard Levine: Software Models for Analyzing Manufacturing Costs
There are many tools to perform COGS analysis of biotherapeutic products. Not all of these tools are appropriate at all times.
Often, the tool used to evaluate costs will have a major impact on the quality, reliability, and cost of the estimates obtained.
The success of any modeling exercise depends on the questions asked and the accuracy and sensitivity of the expected answers.
Figure 2: The structure of a calculation-based model is simple.
The tools described here are calculation-based models, Monte Carlo simulations, and discrete event simulations. Figure 1 summarizes
the best time to use each of these tools during product development.