Economic Analysis of Availability of Follow-on Protein Products. Methodology

07/27/2009

The first of two stages of research and analysis identified the likely candidates for FoPPs. In this stage, we examined broad categories of biological products using searches of the Internet, published literature, and other sources (e.g., market research reports) to locate relevant information. We also conducted semi-structured interviews with experts from federal agencies, industry, academia, and health economists. Each biologic category was examined with regard to criteria identified as important through the preliminary search and interviews. The results of this review informed the selection of a subset of biologic categories for further consideration. We then analyzed individual biologics within these selected categories based on additional criteria identified as relevant to the potential for development of a FoPP. From these analyses, we generated a list of the most likely candidates for FoPPs.

Estimation of the cost impact of FoPP competition for the selected biologic drugs proceeded in two stages. First, we estimated costs associated with the utilization of the originator biologic products, assuming the status quo of no FoPP entrants (sometimes identified here as the "world without" scenario). We then estimated total costs for the "world with" scenario, which includes the costs associated with the originator biologic products and any competing FoPP(s). Describing the "world with" scenario involved modeling changes in current marketplace dynamics resulting from the introduction of FoPPs, including anticipated: (1) lower prices, (2) substitution away from originator biologics currently on the market, and (3) market expansion. The net difference between the "world without" and "world with" costs is the estimate of the incremental cost impact associated with the entry of FoPPs.

The analysis used a high-level approach to estimating the potential cost impact associated with competition from FoPPs, suitable for accommodating drugs spanning multiple, widely varying disease areas. We characterized each originator product along a series of dimensions, including market size, molecular complexity, pre-entry market competitiveness, and fixed costs of FoPP entry. These product characteristics were inputs into models of FoPP entry, the subsequent evolution of brand and FoPP prices, overall market size, and brand and FoPP market shares, i.e., the components necessary to calculate the cost-impact of FoPP entry. The models of market entry, pricing and demand were grounded in a series of microeconomic studies of the economics of the pharmaceutical industry generally, and the biological industry specifically.[1],[2],[3],[4],[5] Default parameter estimates were derived from the published literature and market studies, supplemented by input from experts in clinical matters, pharmacoeconomics and pharmaceutical economics. A summary description of the approach is provided in Figure 1.

Figure 1: Schematic of Model Framework for Analysis of Cost Impact of
FoPP Availability (Base-Case Analysis)

Schematic of Model Framework for Analysis of Cost Impact of

Figure 1 is entitled "Schematic of Model Framework for Analysis of Cost Impact of FoPP Availability (Base-Case Analysis)". The figure is a diagram of two columns, one being "WORLD WITHOUT FoPPs" and the second being "WORLD WITH FoPPs." Each column has 5 seperate steps of calculations which then lead to Step 6, which is a calculation shared by both columns. This particular diagram demonstrates the likely number of FoPP entrants is a key determinant of the estimates of cost impact of FoPP competition.

 

The base-case analysis of the incremental cost impact associated with FoPP availability used straightforward assumptions regarding FoPP entry, FoPP pricing, FoPP market share, and overall market size. The model was then run iteratively under a series of alternative assumptions on entry, pricing, market share and market size. Finally, the base case results were subjected to sensitivity analyses involving variation of selected underlying model parameters through a pre-determined range of plausible values. Particular attention was given to modeling varying assumptions designed to represent a potential range of

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