The authors: Howard L. Levine, Ph.D., President and Founder. Thomas C. Ransohoff, Senior Consultant

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2 The authors: Howard L. Levine, Ph.D., President and Founder Dr. Levine has over 20 years of experience in the biopharmaceutical industry. Prior to founding BioProcess Technology Consultants to provide process development, manufacturing, quality control and quality assurance assistance to biopharmaceutical clients, Dr. Levine was Vice President of Manufacturing Operations at Repligen Corporation. There, he was responsible for all process development and manufacturing activities, including production of therapeutic proteins and monoclonal antibodies and recombinant Protein A. Dr. Levine previously held positions of increasing responsibility in process development and manufacturing at Genentech, Amgen, and Xoma. Dr. Levine is currently a member of the Editorial Advisory Boards of BioPharm Magazine, BioProcess International, and Bio/Pharmaceutical Outsourcing Report. He is also a member of the Neose Technologies, Inc. GlycoAdvance Advisory Board, and is on the Scientific Advisory Boards of AsepCo and the Boston Area Chapter of the International Society of Pharmaceutical Engineering (ISPE). He was chairman of the Parenteral Drug Association s (PDA) Task Force on Chromatography Validation; has lectured extensively on manufacturing strategy, downstream processing, and manufacturing in biotechnology; and is co-editor of a directory of biologics contract manufacturers. Dr. Levine holds a Ph.D. in chemistry from the University of Chicago and completed a postdoctoral fellowship at Harvard University. Thomas C. Ransohoff, Senior Consultant Mr. Ransohoff is a Senior Consultant with over 15 years of experience in the biopharmaceutical industry. Mr. Ransohoff s areas of expertise include development and scale-up of biopharmaceutical processes; separations and purification technologies; cgmp manufacturing; and process economics. Before joining BioProcess Technology Consultants, Mr. Ransohoff was Vice President, Operations at TranXenoGen, Inc., responsible for purification process development and facilities. Prior to that he was Vice President, Bioseparations at Dyax Corp, where he was instrumental in establishing a business unit to develop novel affinity separations products using phage display technology. At Repligen, Mr. Ransohoff was Senior Director, Manufacturing, responsible for cgmp pilot plant operations producing material for clinical trials and reagent products such as Protein A for commercial sale. He is a member of the Editorial Advisory Board of BioPharm Magazine and has served on a number of scientific advisory boards, including the National Research Council Committee on Opportunities in Biotechnology for Future Army Applications and the Boston Area Chapter of ISPE. Mr. Ransohoff has a Bachelor s degree from MIT and a Master s degree from UC-Berkeley, both in Chemical Engineering. 2

3 Table of Contents I. INTRODUCTION... 4 Biopharmaceutical Manufacturing Background... 5 Objectives of Capacity Analysis... 9 II. FORECASTING SUPPLY OF CAPACITY Methodology Market Segmentation Analysis of Manufacturing Capacity III. FORECASTING DEMAND FOR CAPACITY Methodology Commercial Products Clinical Product Candidates Results Commercial Products Comparison of Manufacturing Capacity Supply and Demand IV. ESTIMATING VARIANCE AND RISK Rationale The Practical Importance of Demand Variance and Risk Monte Carlo Simulation The Mechanics of Monte Carlo Simulations Total Demand Capacity Required Per Product Model Results V. DISCUSSION Overall Conclusions from the Analysis Importance of Capacity Forecasting for Biologic Products Improved Ability to Forecast Industrywide and Company Capacity Imbalances REFERENCES

4 Figur igures and Tables Table 1: Comparison of Fed-Batch and Perfusion Bioreactor Productivities... Figure 1: Market Segmentation for Pipeline and Capacity Analysis... Figure 2: Forecast of Industrywide Mammalian Cell Culture Bioreactor Capacity... Figure 3: Forecast of Industrywide Microbial Fermentation Capacity... Figure 4: Distribution of Bioreactor Capacity by Size... Figure 5: Current Distribution of Cell Culture Capacity by Company Type... Figure 6: Forecast 2007 Distribution of Cell Culture Capacity by Company Type... Figure 7: Methodology for Estimating Commercial Capacity Requirements... Figure 8: Methodology for Estimating Pipeline Capacity Requirements... Table 2: Probability of Success and Development Time Estimates Used in the Analysis... Figure 9: 2003 Probability of Success and Turnover Rate Analysis... Figure 10: Number of Biopharmaceutical Products by Development Phase... Figure 11: Percentage of Monoclonal Antibody-Based Biopharmaceutical Products... Figure 12: 2003 Estimated Demand for Mammalian Cell Culture-Derived Products... Figure 13: 2003 Estimated Annual Cell Culture Volume Requirements... Figure 14: Sales Growth of the Top 5 Monoclonal Antibody and Ig-Fusion Products... 4

5 Figur igures and Tables Figure 15: Forecast Growth in Demand for Cell Culture Volume for Commercial Products... Figure 16: Industrywide Supply and Demand for Mammalian Cell Culture Capacity... Figure 17: Monte Carlo Simulation Approach... Figure 18: Monte-Carlo Forecast Distributions of Supply and Demand... Figure 19: Monte-Carlo Distribution Outputs 5

6 I. Introduction Because of the enormous uncertainties associated with development of a biopharmaceutical product, the future supply and demand for manufacturing capacity is continually changing... The biopharmaceutical industry is a dynamic one with many significant risks and uncertainties associated with product development, commercialization, and financing. Among these risks is the ability of biopharmaceutical companies to manufacture sufficient quantities of their products to meet the market demand. In recent years there has been significant concern over a potential capacity crunch in biomanufacturing capacity, especially for monoclonal antibodies, leading to a number of analyses on this topic. 1,2,3,4 Manufacturing capacity concerns were heightened by several high-profile capacity shortages for individual products in the late 1990 s and early 2000 s when both Immunex and Berlex were unable to manufacture sufficient amounts of their products (Enbrel and Betaseron, respectively) to meet market demand. As a result, Berlex lost market share to Biogen and Immunex was acquired by Amgen. Because of the enormous uncertainties associated with development of a biopharmaceutical product, the future supply and demand for manufacturing capacity is continually changing as new data from clinical trials, market penetration rates for new products, and progress on construction projects emerge. Therefore, any analysis of manufacturing capacity must be updated on a regular basis providing a current picture of industrywide utilization rates with a historical perspective. Additionally, a detailed analysis of manufacturing supply and demand enables the identification of capacity drivers and long-term trends in biopharmaceutical manufacturing. For example, as will be shown in our analysis that follows, bioreactor capacity requirements are driven by a relatively small number of products, a trend that we believe will continue due to the wide range of doses and patient populations in the development pipeline. An industrywide analysis of manufacturing capacity also allows tracking and validation of industrywide statistics such as probability of success at various clinical stages and commercialization. Finally, recognizing that the biopharmaceutical industry is a global one, ongoing analysis of manufacturing supply and demand will enable tracking of geographical trends in manufacturing capacity. For the purposes of this chapter, we define biopharmaceuticals as therapeutic proteins and monoclonal antibodies that are produced using the large-scale culture of prokaryotic or eukaryotic 6

7 cells. These are only two of many distinct biomanufacturing technologies others not covered in this chapter include vaccines, cell and gene therapy products, synthetic peptide and oligonucleotides, and transgenic plant and animal-derived products. Nonetheless, the approaches outlined in the chapter can generally be applied to a wide range of biologic products. Finally, our work focuses on manufacturing facility limitations, especially bioreactor capacity limitations, which many argue is less important than potential human resource limitations in the manufacture of biopharmaceutical products. 5 While we do not necessarily disagree with this assessment or on the potential for other limitations on the ability of biopharmaceutical companies to manufacture their products, our analysis is focused on bioreactor capacity, which has historically been important in defining manufacturing capacity for fermentation-derived products. Biopharmaceutical products... are among the most technically complex commercial products to manufactur acture e in any y industr try. Biopharmaceutical Manufacturing Background Biopharmaceutical products are complex macromolecules with limited stability that must be manufactured to meet high purity and quality standards. The manufacturing processes used to produce these products generally rely on the large-scale culture of genetically modified organisms followed by extensive recovery and purification steps. Detailed analytical methods are used to characterize and evaluate the quality of the final product. These products are among the most technically complex commercial products to manufacture in any industry. As an industry, the biopharmaceutical industry is still relatively young and our understanding and knowledge of biopharmaceutical process and analytical methods continues to increase at a significant rate. Commercialization of biopharmaceutical products began with the development of recombinant human insulin in the mid-1970 s by several companies as a replacement for animal-derived insulin products. The first recombinant therapeutic proteins to be approved for marketing by FDA were Humulin and Novolin, which were commercialized by Eli Lilly and Novo, respectively in Since that time, over 80 recombinant proteins and monoclonal antibodies have been commercialized in the United States for the treatment of a wide range of diseases. 6 7

8 The industr try y will continue to expand beyond comfortable definitions driven by the opportunities to harness advances in life science research to create novel approaches for treating disease. While the majority of approved biotechnology products are recombinant proteins or monoclonal antibodies, the nature and types of products under development within the biotechnology industry has expanded significantly beyond this definition. Biotechnology now includes many other types of products, such as novel vaccines, gene and cell therapy products and proteins produced in transgenic plants and animals, and various peptide and nucleic acid products. Even small molecules made by traditional synthetic chemistry are often considered biotechnology products if they were derived or discovered from new biologically oriented research tools such as genomics. The industry will continue to expand beyond comfortable definitions driven by the opportunities to harness advances in life science research to create novel approaches for treating disease. During the first 10 to 15 years of the biotechnology industry, virtually all products were manufactured by the company developing the product largely because there was no alternative. The regulatory framework within FDA for biologic products (which most biopharmaceuticals were considered) further reduced the attractiveness of any strategy other than in-house manufacturing. This regulatory framework had two fundamentally challenging aspects for manufacturers of biopharmaceutical products: The first was the philosophy that process defines product, which had been developed for regulating traditional biologics (e.g., vaccine and blood-derived products) that were so complex that analytical quality control tests were generally insufficient to define a product. Therefore, products were additionally defined by their manufacturing processes and the facility in which they were manufactured (including scale and specific equipment used in processing operation). As a result, the early regulations for biologic products required that material for pivotal Phase III clinical trials be produced by the commercial manufacturing process in the commercial facility. The practical result of this regulatory approach to biopharmaceuticals was that companies 8

9 felt that they needed to invest in a licensable, full-scale production facility before entering pivotal clinical trials. a The second was the requirement that companies submit two license applications for commercialization of a new biologic product a PLA, or Product License Application, and an ELA, or Establishment License Application. Biologics regulations required that the PLA and ELA be held by the same company. And, in order to hold an ELA, companies had to either perform significant manufacturing steps themselves or have been responsible for the clinical testing of the product and perform the final manufacturing steps of the process. The PLA and ELA were very specific about who held them, what products they applied to, and how and where the product was manufactured. Changes to any of these criteria required submission of a new license application and reapproval of the license. In this environment, any approach other than in-house manufacturing would result in significant loss of control of the product. The practical result of this structure was to discourage development of a contract manufacturing sector in the biopharmaceutical industry. For all of the above reasons, the first biotechnology companies invested high levels of resources and capital in manufacturing process development, staff and facilities well in advance of knowing the outcome of pivotal clinical trials. In the early 1990s, several biotechnology products failed in late-stage clinical trials after companies had already invested significant capital in manufacturing facilities. Few were more publicized than the failure of Synergen s Antril (anakinra). This product failed to demonstrate efficacy in treating sepsis in a Phase III trial in 1994 after the company had made a substantial investment in a manufacturing facility. The resulting financial distress soon led to the acquisition of Synergen by Amgen. b,7 [T]he first biotechnology companies invested high levels of resources and capital in manufacturing process development, staff and facilities well in advance of knowing the outcome of pivotal clinical trials. a b Another practical consequence of this regulatory framework is that generic biologics are essentially impossible in this framework. With conventional small molecule therapeutics, the same active pharmaceutical ingredient can be made using significantly different processes and be considered equivalent based on analytical and limited human safety and bio-distribution data. As long as the process at least partly defines the product, this can never be true for biological products. Anakinra was eventually approved as Kineret TM and is now marketed by Amgen to treat rheumatoid arthritis 9

10 By the mid-1990s, the availability of contract manufacturers and other outside service provider viders had increased to a level that enabled biopharmaceutical product developers to consider routes other than in-house manufacturing. The challenges faced by Synergen and others during the early 1990s led both regulators and industry to re-examine this approach to the development of biopharmaceutical products. By the mid-1990s, the availability of contract manufacturers and other outside service providers had increased to a level that enabled biopharmaceutical product developers to consider routes other than in-house manufacturing. Regulatory changes, such as the 1997 FDA Modernization Act (FDAMA), were also implemented during this period that enabled contract manufacturing in several important ways. Among the most important changes for biopharmaceutical manufacturers was the replacement of the Product License and Establishment License for biologics with a single Biologics License (BLA). This new license, similar to the traditional New Drug Application used for small molecules, had the practical impact of enabling product companies to retain control of their products whether manufacturing was conducted in-house or through a CMO. Following the introduction of the BLA, guidance documents were published defining well-characterized biologics (now referred to as specified biologics ) and the use of comparability protocols to support process changes during development and after product approval. 8 This change enabled companies with well-characterized products to improve processes, increase manufacturing scale, and even change manufacturing facilities without conducting extensive additional clinical trials, assuming comparability could be demonstrated. As a result of these changes, the use of contract manufacturers for production of biopharmaceuticals increased significantly in the late 1990s. This is particularly true for early-stage companies with a high cost of capital, particularly when viable contract manufacturing options exist. The growing availability of contract manufacturing options has made outsourcing a viable option for many products, even for larger companies with more ready access to capital. Much has been written about the make vs. buy decision, 9,10, 0,11 so that topic will not be covered here. Until recently, industrywide capacity for manufacturing of biopharmaceutical products was not a topic receiving significant 10

11 attention or media coverage. That all changed abruptly in the year 2000 when several factors led to a significant concern that manufacturing capacity may not be available to meet the needs of the industry s developing monoclonal antibody pipeline. Immunex failed to construct or contract for adequate capacity to manufacture Enbrel, one of the most successful biopharmaceutical products ever commercialized. This led to rationing of the product and eventually, the sale of the company to Amgen. c,12 The unparalleled level of financing of biotech companies in led to a large bolus of products entering clinical trials in Capacity for production of clinical materials was difficult to find, leading to delays in product development and rising concern about the ability of the industry to fully meet the manufacturing demand for new biopharmaceutical products. A report was issued by JP Morgan presenting the first industrywide analysis of mammalian cell culture capacity. 4 The reports conclusion was a dire prediction that demand for manufacturing capacity will exceed current capacity by a factor of four by The JP Morgan report was quickly followed by other analyst reports forecasting similar doom and gloom for the biopharmaceutical industry. 13, 3,14 As a result of the financing environment in and the concern regarding future capacity for the growing number of biotherapeutics particularly monoclonal antibodies many mammalian cell culture construction projects, some on speculation, were initiated. A capacity crunch is now less commonly suggested than several years ago, and in fact, an increasing number of product companies are now offering to perform contract manufacturing to utilize excess capacity in their facilities. A report... by JP Morgan... was a dire prediction that demand for manufacturing capacity will exceed current capacity by a fact actor or of four by c Amgen has since opened its Rhode Island facility and is implementing an agreement originally signed by Immunex to gain capacity at Genentech. Additionally, Wyeth is constructing a facility in Ireland to manufacture Enbrel. This led to the recent observation by a Wyeth executive that four out of the six top capacity holders will be making Enbrel by

12 Objectives of Capacity Analysis Many of the early biopharmaceutical manufacturing capacity analyses made overly simplified assumptions with respect to product requirements and were based on limited product and facility coverage. One of our objectives was to go beyond this aggregate analysis to provide a more detailed and granular analysis of the supply and demand for manufacturing capacity in this industry. The overriding goal in doing this was to improve the methodology and basis for capacity analyses and to improve our understanding of the level of confidence in forecasts of future supply and demand. To better define trends in both supply and demand of manufacturing capacity as well as to estimate the risk or uncertainties associated with these projections, we have used statistical tools such as Monte Carlo analysis in an attempt to quantify the risk of future capacity shortages and to incorporate the uncertainties in product development and commercialization into future capacity forecasts. A Monte Carlo simulation, named for the casinos of Monte Carlo, Monaco, uses statistical simulation to analyze a multitude of outputs and scenarios based on a range of inputs. Such a statistical simulation method calculates multiple scenarios of a model by repeatedly sampling values from the probability distributions for each of the input variables and using those values to calculate the output for each potential scenario. The result is a distribution of outputs showing the probability of each output over the range of input variables rather than the single output of a calculation based model. 12

13 II. For orecas ecasting Supply of Capacity Methodology In order to evaluate the supply of capacity and the availability of capacity at various operating scales, we attempted to assess manufacturing capacity on a plant-by-plant basis for both mammalian and microbial biopharmaceutical manufacturing. To do this, we have constructed a database of recombinant proteins and monoclonal antibodies in development and on the market. Our database is based on publicly available information and undoubtedly has less than 100% coverage in this area, especially for products in the early stages of development. Many of these late-stage development products are ill-defined and often kept confidential by the companies developing them. Despite these limitations, however, we feel that our database provides a good cross section of the industry and serves as an excellent basis on which to base estimates of demand for future manufacturing capacity. We have also attempted to identify and include most of the major manufacturing plants and capacities in each area and a high percentage of smaller pilot facilities. Again, identification and quantification of pilot facilities and capacities used for late-stage clinical trial manufacturing is difficult due to the diverse nature of such pilot plants. Our focus was primarily on product demand for the European and U.S. markets, however, we have also attempted to identify large-scale GMP capacity in Asia and emerging markets in this area as these facilities will certainly compete in the future in the global biopharmaceutical production market. Not included in our database or analysis were non-cgmp facilities and facilities whose capacity is used to make products that were not included in the project scope, such as traditional biologics, vaccines, small molecule therapeutics, gene therapy products, and synthetic peptides and oligonucleotides. We should note, however, that significant amounts of capacity, especially microbial fermentation capacity, exists in the non-gmp area for biologic products used in non-pharmaceutical applications. The first step in our analysis was to identify the current online clinical and commercial manufacturing capacity. Information on bioreactor volumes and numbers, site location, production technology, and clinical/commercial capabilities was obtained from a wide range of public sources. One particularly useful [O]ur database provides a good cross section of the industr try y and serves es as an excellent basis on which to base estimates of demand for future manufacturing capacity. 13

14 [P]revious analyses of biopharmaceutical manufacturing capacity have assumed that production of biopharmaceutical products is done exclusively by fed- batch fermentation. source was the Directory of Contract Services and associated online database. 15, 5,16 Additionally, industry reports, regulatory filings, and company press releases and reports were used. Next, construction projects that are in progress or in late-stage planning were added to the analysis. Information on these projects again was assembled primarily from industry reports, regulatory filings, and company press releases and reports. In some cases, supplemental information was obtained through discussions with heads of manufacturing and various biotechnology companies. Similar information was collected for these projects as for the current facilities, including the number and size of bioreactors, downstream processing capabilities, and overall facility size. Additionally, a forecasted year online for these manufacturing projects was estimated. In most cases, capacity figures for manufacturing facilities are published by the manufacturers. In some cases; however, companies have chosen not to publicize this information. Where exact information on installed manufacturing capacity was not available, we estimated manufacturing capacity based on available information, such as the reported square footage or cost of the project compared to the industry average cost per square foot or cost per liter of installed capacity or the estimated product output of the plant coupled with estimates of overall process yield and production lot frequency. All previous analyses of biopharmaceutical manufacturing capacity have assumed that production of biopharmaceutical products is done exclusively by fed-batch fermentation and ignores the fact that a significant share of the industry uses alternative cell culture technology, particularly perfusion culture. Because of the continuous nature of perfusion cultures, the annual output of a perfusion bioreactor is significantly higher than that of a similar sized bioreactor operating in a fed-batch mode. To account for these differences in productivity, a perfusion factor of 10 was used to adjust perfusion bioreactor capacity to an equivalent fed-batch capacity. This factor was derived from a comparison of operating parameters for both fed-batch and perfusion bioreactors such as that shown in production in Table 1. The equivalent fed-batch 14

15 Table 1: Comparison of Fed-Batch and Perfusion Bioreactor Productivities Bioreactor size 10,000 L 1,000 L Operating mode Fed-batch Perfusion Perfuse 1,000 L per day for 100 days Expression level 0.5 g/l g/l Purification yield 60% 60% Batches per year 20 2 Annual output of bioreactor 100 Kg crude MAb 100 Kg crude MAb 60 Kg purified MAb 60 Kg purified MAb capacity figures were used in the supply and demand analysis, since these are more relevant to product supply. d Once all of the information related to plant capacities had been compiled, the data was used to forecast plant, company-wide, and industrywide capacities for the period This was done for both mammalian cell culture and microbial fermentation capacities. Market Segmentation We have segmented the biopharmaceutical manufacturing market into four quadrants based on a distinction between products that are currently commercially marketed and those that are in clinical development and a determination of the likely method of expression: mammalian cell culture or microbial fermentation. This market segmentation, shown in Figure 1, allowed us to further refine the analysis of manufacturing capacity. In our analysis, a facility was included in the commercial field if, in our opinion, it was capable of producing commercial material with no more than modest renovations. Facilities intended for (or dedicated to) the production of clinical trial materials were considered clinical facilities. d On an adjusted (i.e., equivalent fed batch) basis, perfusion capacity is <20% of total industry capacity, so this method of accounting for perfusion capacity does not dramatically skew the analysis. Should perfusion reactors become more prevalent, it may be appropriate to treat this capacity on a wholly separate basis. 15

16 Figure 1: Market Segmentation for Pipeline and Capacity Analysis* Commercial Cell Culture: Commercial Microbial: Clinical Cell Culture: Clinical Microbial: *The number of facilities within each market segment is shown for facilities operating in 2003 and those projected to be online by As shown in Figure 1, the number of companies with commercial cell culture capacity is forecast to grow by approximately 20% between 2003 and In both the mammalian cell culture and microbial fermentation area, the number of companies with clinical manufacturing capacity includes companies with commercial capacity (as they can also produce clinical materials) as well as companies with only clinical capacity. We represent this number as a low-end value because many product companies do not publicly disclose their clinical capacity. Additionally, we have further segmented the market based on the two types of providers of manufacturing services to the biopharmaceutical industry: 16

17 Contract Manufacturing Organizations (CMOs) or Dedicated Contractors whose primary business is to provide toll-based manufacturing services. These companies do not typically manufacturer their own products in their facilities. Product Companies or Excess Capacity Contractors whose primary business is to develop proprietary products but which may provide manufacturing services to others from time to time to use excess capacity. These companies also use capacity to produce their own products, and not all Product Companies will contract for use of excess capacity. This segmentation by provider type is not shown in Figure 1, but is included in the additional analyses described elsewhere in this chapter. 17

18 Year Analysis of Manufacturing Capacity As described above, the total industrywide capacity forecast for production of biopharmaceutical products in any given year can be estimated by adding the online capacities from the tracked facilities. This forecast is shown for mammalian cell culture bioreactor capacity in Figure 2 for the years 2003 through As described previously, the capacity of bioreactors typically operating in perfusion mode has been adjusted to the equivalent fed-batch bioreactor volume. A similar projection of microbial fermentation capacity targeted for production of biopharmaceuticals for the years is shown in Figure 3 Figure 2: Forecast of Industrywide Mammalian Cell Culture Bioreactor Capacity Total Installed Volume, ('000 Liters) CMO Product Co. 18

19 Figure 3: Forecast of Industrywide Microbial Fermentation Capacity Year Total Installed Volume, ('000 Liters) CMO Product Co. Each capacity forecast is segregated between CMO and product companies. Interestingly, for both mammalian cell culture and microbial fermentation capacities, product companies currently control approximately 70 80% of the industry capacity. The CMO share of manufacturing capacity is forecast to increase slightly over the period, reflecting a growing reliance on contract manufacturers for the production of biopharmaceutical products. Additionally, these forecasts do not reflect an increasing trend for product companies with excess capacity to enter the contract manufacturing business. Finally, the above forecasts do not differentiate between clinical and commercial manufacturing capacity, however, clinical manufacturing capacity currently runs at approximately 5% of total industry capacity on a bioreactor volume basis. On a perfusion-adjusted basis, total installed capacity for mammalian cell culture is estimated at just over one million liters in 2003, growing to approximately 2.2 million liters in [C]linical manufacturing capacity currently runs at approximately 5% of total industr try y capacity on a bioreactor volume basis. 19

20 [T]he number of product companies and CMOs operating greater than 50,000 L of total capacity is forecast to nearly double over the next five years The distribution of mammalian cell culture capacity today and in 2007 by total installed reactor volume capacity is shown in Figure 4. As shown in Figure 4, the number of product companies and CMOs operating greater than 50,000 L of total capacity is forecast to nearly double over the next five years. This increase is driven by the increasing doses and market penetration of biopharmaceutical products. The number of both types of companies with total installed bioreactor capacity of 5,000-50,000 L will also increase during this period. Figure 4: Distribution of Bioreactor Capacity by Size Total Reactor Volume >50000L 5000L L Number of CMO Companies >50000L 4 6 Total Reactor Volume L L Number of Product Companies 20

21 One other important trend identified in our capacity analysis is the magnitude and breadth of the industrywide capacity expansion in mammalian cell culture capacity. As apparent from the already mentioned forecasts, the industry s total installed bioreactor capacity is set to more than double over the next five years. This increase is a result of both expansion of manufacturing capacity at companies who currently have manufacturing facilities as well as construction of new facilities by companies who currently do not have biomanufacturing capabilities. The result is a significant number of firms (both CMO and Product Companies) adding substantial cell culture capacity and a somewhat broader distribution of large-tank capacity amongst a larger number of biomanufacturing companies in e [T]he industr try y s s total installed bioreactor capacity is set to more than double over the next five years. Figure 5: Current Distribution of Cell Culture Capacity by Company Type* Lonza 16% Others 9% Sandoz 11% BI 64% Contract Manufacturers Others 25% Amgen 9% Biogen Idec 17% *All companies having a forecast of at least 4% of the total capacity their category in 2003 are shown. Wyeth 4% Medimmune 4% Imclone 4% Genentech 37% Product Companies e Counteracting this improved broader distribution of biomanufacturing capacity is the consolidation trend in the industry. For example, the recent merger of Biogen and IDEC to form Biogen Idec reduced the number of companies with forecast large tank capacity by one. 21

22 Figure 6: Forecast 2007 Distribution of Cell Culture Capacity by Company Type* Others 17% Diosynth 6% BI 37% Lonza 20% DSM 8% Celltrion 12% Contract Manufacturers Others 25% Abbott 5% Amgen 16% *All companies having a forecast of at least 5% of the total capacity their category in 2007 are shown. Wyeth 15% Genentech 18% Biogen Idec 21% Product Companies 22

23 III. For orecas ecasting Demand for Capacity Methodology As with the analysis of the supply of biomanufacturing capacity, we used a bottom up approach to estimate demand for manufacturing capacity. In this chapter, we will focus on the demand for mammalian cell culture capacity; although a similar analysis can be prepared for microbial fermentation capacity. Our analysis was based on a product-by-product approach to estimate demand for capacity. The objective of the pipeline analysis was to achieve a significant sampling of the biopharmaceutical product pipeline and nearly complete coverage of commercial products. The percentage of the pipeline products that were analyzed was weighted towards products in late-stage clinical trials as these products will have the greatest impact on demand for manufacturing capacity over the next decade. For purposes of our analysis, we have segmented the biopharmaceutical manufacturing market as defined above and shown in Figure 1. Multiple sources were used to compile the product pipeline information to ensure as complete and accurate coverage as possible. One particularly useful resource was the BioPharm Services (BPS) database covering biopharmaceutical products 1 7. Other data sources included scientific and medical literature, industry reports and databases, and company web sites and publications. Even with these broad sources, our coverage of the product pipeline is certainly not 100% complete as some information pertaining to products in development remains confidential to the developing companies. To correct for this, we have estimated that our combined database covers 100% of marketed products, 95% of products currently in Phase III clinical trials, 85% of those products in Phase II, and 65% for Phase I candidates. Our projections of manufacturing capacity demand take into account these percentages and are adjusted accordingly. Using the available data we conducted separate demand analyses for current commercial products and clinical product candidates. The following is a description of the methodologies used for each analysis. 23

24 Commercial Products Analysis of the demand for commercial products is critical to the assessment of supply and demand. The current requirements and forecast growth in the demand of approved products particularly monoclonal antibodies but also non-antibody products such as recombinant factor VIII forms the foundation for the current supply structure and for the majority of the near-term (<5 year) increases in demand for capacity. For commercial products, where sales information is generally available, we were able to use the approach outlined in Figure 7 to estimate demand. We first estimated current product demand (kilograms of drug product required per year) by using product sales figures and estimated average selling price. For most products, this information is readily available sales figures through company financial filings or industry reports, 3,14 and drug sales prices f through the Red Book 1 8. Using a BioProcess Technology Consultants estimate of 25% bulk overage g required to manufacture a given unit dose of drug product, we back-calculated the amount of bulk drug substance required (kilograms of bulk drug Figure 7: Methodology for Estimating Commercial Capacity Requirements Inputs Outputs Per patient dosing (g/pt/yr) Source: Prescribing info, reg. documents Product sales (2003 WW sales $/yr) Source: Industry and co. financial reports Product pricing ($/mg) Source: Red Book Expression level/overall yield (g/l) Source: Published data and estimates Technology for manufacture Source: Literature and internal evaluation } } Treatment population (pt/yr) Product amount required (kg/yr) Cell culture volume required (L/yr) Mfg site determined where possible f g Sales prices used in our calculation are either the listed Discount Price or 85% of the listed Average Wholesale Price. This bulk overage includes overfill losses, scrap or rejected material, and additional non-marketed material required to support any commercial product (e.g., ongoing validation and stability analyses). 24

25 substance per year). Our analysis focused on bulk drug substance as this is the most common output of biopharmaceutical manufacturing facilities. Drug product manufacturing (filling and finishing operations) are usually conducted in different facilities using conventional pharmaceutical equipment and are outside the scope of our analysis. The required cell culture volume for each product was then calculated based on the estimated quantity of bulk drug required and an estimate of overall process yield (grams of bulk drug substance per liter of cell culture reactor volume). The type of technology used to manufacture the product (microbial fermentation or mammalian cell culture) and process yield estimates were derived from a number of sources, including regulatory approval documentation, published literature, company reports, and/or our own estimates based on the type of product and general published information. Separately, patient dosing information (amount per dose, frequency, and duration) was estimated for each product s primary indication. Dosing information sources for commercial products were typically regulatory approval documents or prescribing information literature. The average annual amount of drug required per patient was then estimated from the dosing information and published reports. Disease prevalence estimates were also obtained for most indications from the BPS database. By dividing the number of patients treated by the disease prevalence we were able to estimate market penetration for each commercial product. Future bulk and reactor volume requirements were based on estimates of sales growth rates that we based on historical growth rates, company forecasts (where available) and market penetrations for each product. Using the information already developed on pricing and process yields, we were able to forecast the amount of bulk product and volume of reactor volume required in future years. Clinical Product Candidates The overall demand for manufacturing capacity for clinical trial material is significantly less than the demand for commercial 25

26 production for most therapeutic products. For example, a monoclonal antibody product that could require hundreds of kilograms per year to support product sales may require less than 10 kg of material over the five to eight years of product development prior to commercial launch. Industrywide, the amount of material required for clinical trials represent a small fraction of the total production requirements for both mammalian cell culture and microbial fermentation-derived products (<7% on both a mass and reactor volume basis). More importantly for forecasting future demand for mammalian cell culture capacity, a subset of molecules in clinical trials will contribute to future demand for capacity in a more substantive way after receiving marketing approval. Because no sales data or pricing information are available for product candidates in clinical development, future amounts and volume requirements for these pipeline products must be estimated differently from commercial products. Our approach for this analysis of clinical product candidates is outlined in Figure 8. Figure 8. Methodology for Estimating Pipeline Capacity Requirements Inputs Per patient dosing (g/pt/yr) Source: Literature, databases Indication Prevalence (pt/yr) Source: Databases Market Penetration (% prev/yr) Source: Based on indication & # products per indication Expression level/overall yield (g/l) Source: Published data and estimates Technology for manufacture Source: Literature and internal evaluation } } Outputs Product amount required post launch* (kg/yr) Cell culture volume required post-launch* (L/yr) *Launch date & probability weight determined by development phase BPTC estimates 26

27 Product dosing information for the candidates analyzed was obtained from a wide variety of sources as described previously. Dosing information is more difficult to find for clinical products than commercial products; however, it is available for many products in development, especially those in late-stage clinical trials. In cases where a range of doses was being investigated, such as in Phase II studies, a dose in the mid-high end of the range was selected. Frequency and duration of treatment were estimated based on the study design and the indication. For example, if a study design used a treatment of twice weekly administration for 12 weeks but the indication was clearly chronic, chronic administration twice weekly was assumed for estimating future demand for the product. Using this information, an estimate of product amount per patient per year post approval was derived for all products analyzed. We competed such product-specific analysis on >95% of approved, BLA-stage, and Phase III products, and >55% of Phase II products in our database. While Phase I products are included in our database, they were not a focus of this product-based pipeline analysis because they are typically at least four to eight years away from market launch if successful and are being evaluated for safety profiles often over a wide range of doses. Future demand for Phase I product candidates was based on an extrapolation of Phase II demand. Estimates of future demand for clinical product candidates were derived by combining the information on product dose (annual per-patient amounts) with forecast number of patients treated to estimate annual bulk drug substance required and with estimated yields to estimate cell culture or fermentation volume required. To estimate the probability and timing for launch for each product analyzed, industry-average timing and success factors were used. These factors, shown in Table 2, were developed by averaging reported factors from several sources 4,1 4. As shown in Figure 9 on the next page, our calculated 2003 actual success factors and turnover rates were found to be somewhat lower than these estimates, particularly for Phase III studies. We plan to continue to monitor actual success rates and development times in future years as these factors are critical to accurately estimating the future demand for biomanufacturing capacity. Continued pressure on the FDA and other regulatory agencies to improve the 27

28 Table 2. Probability of Success and Development Time Estimates Used in the Analysis Clinical Phase Probability of Success to Next Clinical Phase Probability of Success to Approval Duration of Development Phase (months) I 76% 19% 12 II 45% 26% 18 III 65% 58% 18 BLA 90% 90% 12 Figure Probability of Success and Turnover Rate Analysis Phase II 40% 45% Phase III 30% 64% 2003 performance BPTC model values BLA 86% 90% 0% 20% 40% 60% 80% 100% Success rate (to next stage) Turnover statistics (2003): No BLA products remained in the same stage (all either approved or rejected) 60% of Phase III products remained in Phase III (i.e., only 40% moved forward or failed) 61% of Phase II products remained in Phase II 28

29 review time for new products, improvements in the efficiency with which companies screen product candidates, and increasingly difficult unmet disease areas may change these probabilities and time estimates in the future. Consequently, future analyses of manufacturing demand should reflect these changes. Patient population estimates for clinical products were based on disease prevalence estimates, and estimated market penetration, factoring competition with existing treatments and other treatments in development. Disease prevalence information was obtained from the BPS database and other sources. Five-year market penetration estimates were based on penetration rates for similar approved products and indications. Market penetration was assumed to occur with decreasing growth rates over the 5-year post-launch period. Where multiple approved products and/or development candidates exist for a single indication, the indication market penetration was reduced by a factor to reflect the competition as follows: MP cand MP cand MP ind N ap NPi P Pi =MP ind / (1 + 1*N ap + ΣP Pi *NP i ), where = Forecast market penetration for candidate = Total market penetration estimate for indication, based on approved product data = Number of approved products for same indication = Number of other products in Phase i for same indication, where i phase of development for product candidate = Probability of success for products Phase i of development Estimation of process yields was more challenging for clinical product candidates than for commercial products because relatively little is published on actual process yields for developmental products. Where actual yield information was available, we used this information. Where this information was not available, we estimated process yields based on product type and capabilities of the developing organization. The manufacturing technology used to produce product candidates was more readily estimated or determined from published information and was used 29

30 to assign products to the mammalian cell culture or microbial pipeline database. Using all of the information described above, future product demand and cell culture volume requirements were estimated for each product analyzed. Market-wide demand for capacity for each year through 2008 was estimated from the product-based demand numbers by combining the following: Sum of forecast demands for commercial and BLA products The assumptions can be changed as warranted and the pipeline maintained as new information becomes available to enable this analytical method to be a dynamic tool that provides relevant pipeline-based information. Sum of forecast demands for Phase III products adjusted for analysis coverage to account for products in the pipeline but not analyzed and for our estimate of pipeline coverage to account for products not in the pipeline Sum of forecast demands by year for Phase II products similarly adjusted Estimate of forecast demand by year for Phase I products using Phase II demand/product ratio with later launch timing and lower launch probabilities factored in. In this way, we have developed a comprehensive product-based method for forecasting future demand for biopharmaceuticals manufacturing capacities. Obviously, the results are highly dependent on the assumptions made and on the pipeline information. The assumptions can be changed as warranted and the pipeline maintained as new information becomes available to enable this analytical method to be a dynamic tool that provides relevant pipeline-based information. Results The overall pipeline by product type is presented in Figure 10. One important distinction between our estimates of the number of products in development relative to that of others is that our analysis considers each product to be a distinct molecule. Whereas others consider a molecule under development for multiple indications to be multiple products, our analysis considers such molecules as a single product. We believe this is a better approach to defining the number of products in development even though it results in lower numbers of products than seen in other analyses for two reasons. First, each molecule in 30