Economic Analysis of Availability of Follow-on Protein Products. Estimation of Cost Savings Associated with FoPPs


Our approach to estimating cost savings associated with FoPPs consisted of first estimating expenditures on innovator/branded biologic products assuming no FoPP competition, i.e., the "world without" scenario. We then estimated total drug expenditures associated with the originator biologic products and any competing FoPP(s), i.e., the "world with" scenario. Describing the "world with" scenario involves modeling changes in current marketplace dynamics resulting from the introduction of FoPPs, including: (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.

Our model takes 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. The structure of the model is diagrammed in Figure 2. We characterize 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 are 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 are grounded in a series of microeconomic studies of the economics of the pharmaceutical industry generally, and the biological industry specifically[57],[58],[59],[60],[61] Default parameter estimates were derived from the published literature and market studies, supplemented by input from experts in clinical matters, pharmacoeconomics and pharmaceutical economics.

Figure 2: 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 FoPP Availability (Base-Case Analysis)

Figure 2 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.


In this model, the likely number of FoPP entrants is a key determinant of the estimates of cost impact of FoPP competition (following Grabowski et al. 2007). Fewer FoPP entrants will yield less competition, a higher relative FoPP price (lower discount on FoPPs), and smaller cost impact. Additional determinants derived in the model include the FoPP price discount, the degree of market uptake of FoPPs (captured by FoPP market share), and expansion of overall market size in response to (presumably less expensive) FoPP alternatives. The modules estimating market entry, pricing and demand are grounded in a series of microeconomic studies of the economics of the pharmaceutical industry generally, and the biological industry specifically[62],[63],[64],[65],[66],[67] Default parameter estimates external to the model were derived from the published literature, market research studies, supplemented by the input of clinical consultants and experts in

Step 1: Estimating the number of entrants into a biologic product market

Step 1 in the model, the estimation of the number of FoPP entrants, is based on a re-formulation of the framework proposed in the Grabowski et al. (2007) paper, "Entry and competition in generic biologicals," which makes use of the market entry framework of Bresnahan and Reiss (1991).[68] The details of the derivation are presented in the technical Appendix A. We chose the Grabowski framework as a methodological point of reference because it was one of the few papers to explicitly model entry into a biologics (rather than generics) market.

Estimation of FoPP entry into the market for a specified biologic proceeds in two steps. First, the entry decision is analyzed as if the market were one for small-molecule drugs; the resulting estimate of the number of FoPP entrants is then adjusted for institutional differences between markets for biologics and small molecule drugs. Thus, we first estimate the number of generic entrants expected to enter a standard small molecule market equivalent in size to the biologic market of interest (as measured by market revenue). This number is then adjusted for differences between the markets for biologics and small molecules in price-cost margins and fixed costs of entry.

Step 2: Estimating "brand" and "FoPP" prices

Step 2 of our model, estimating the brand price after FoPP entry and FoPP price discount, draws on the analysis of Reiffen and Ward (2005) and Bhattacharya and Vogt (2003). In this stage, we model the FoPP price relative to the "brand" price as a function of the expected number of FoPP entrants.

The choice of Reiffen and Ward merits additional discussion. An important attribute of their analysis is the estimation of the discount attributed to generic entry as a non-linear function of the number of generic competitors. However, the estimated discounts associated with generic entry are somewhat smaller than those of alternative analyses, e.g., Saha et al. (2006) and Grabowski et al. (2007). We contend (based on our stage 1 analysis and supported by the biosimilar experience in Europe) that high fixed costs of entry into these markets are likely to result in few FoPP entrants per drug. The effect of few competitors is bolstered by the expectation that FoPP products are unlikely to be considered identical to the innovator products. (We return to this point in greater detail, below). Biologic markets after FoPP entry may, therefore, be better characterized as imperfectly competitive, even oligopolistic markets, resulting in smaller price discounts than would occur in a market with either much greater numbers of entrants or non-differentiated products.

Step 3: Estimating "brand" and "FoPP" market shares

Step 3 of our model, estimating the cumulative FoPP market, share draws on the analysis of Saha et al. (2006). As we are interested only in predicting market share, rather than analyzing the structural relationships between the determinants, we use the OLS analyses of Saha et al. to estimate FoPP market share as a function of FoPP price discount, the number of FoPP entrants, the overall market size, and the level of HMO coverage within the market.

Step 4: Estimating market size post-FoPP entry

Multiple studies of pharmaceutical benefits design (e.g., Gaynor, Li and Vogt, 2007; and Joyce et al., 2002)[69],[70] have demonstrated that the demand for pharmaceutical products decreases as prices increase. Similarly, the entry of FoPPs and the associated biosimilar price discount are anticipated to induce an increase in pharmaceutical demand and, therefore, in market size.[71] Although some studies show that generic entry in the small molecule market can depress overall market size as brand producers cut back on advertising, we believe that this effect will be negligible in the biologic market, as FoPP producers are likely to try and establish an independent market identity (as does, e.g., Sandoz's Omnitrope®, which is a FoPP for Pfizer's hGH, Genotropin®).

Therefore, we model the increase in market size as a function of the weighted decrease in price, where the weights are the relative "brand" and "FoPP" market shares, which are affected, in turn, by the predicted number of FoPP entrants.

Steps 5-6: Estimating cost impact FoPP entry

The model calculates cumulative cost impact over the period 2009-2019. The base-case analysis of the incremental cost impact associated with FoPP availability uses straightforward assumptions to estimate FoPP entry, FoPP pricing, FoPP market share, and overall market size. The model then re-calculates the cost impact under a series of alternative assumptions on entry, pricing, market share and market size. Finally, the base case results are subjected to sensitivity analyses involving variation of selected underlying model parameters through a pre-determined range of plausible values.

Given the uncertainty regarding new approval pathways for FoPPs, it is important to develop estimates of the cost impact of the availability of FoPPs that are sensitive to the effects of differing levels of rigor for regulatory approval. In this model, the rigor of the approval model affects the estimated cost impact through two pathways: 1) the time to market entry of the FoPP and 2) the fixed costs of satisfying regulatory requirements. The time to market and the costs of clinical trials are assumed to increase with the level of regulatory stringency.

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