Does Increased Spending on Pharmaceutical Marketing Inhibit Pioneering Innovation?

Journal of Health Politics, Policy and Law Journal of Health Politics, Policy and Law

Does Increased Spending on Pharmaceutical Marketing Inhibit Pioneering Innovation? Denis G. Arnold Jennifer L. Troyer University of North Carolina at Charlotte

Abstract The pharmaceutical industry has been criticized for developing and aggressively marketing drugs that do not provide significant health benefits relative to existing drugs but retain the benefits of patent protection. Critics argue that drug marketing increases health care expenditures and provides a disincentive for pioneering drug innovation. However, evidence that marketing expenditures have any relationship to new drug approvals has been anecdotal. We hypothesized that, at publicly traded pharmaceutical firms, increased marketing expenditures will result in a reduced volume of pioneering new drugs in comparison to less innovative new drugs. We also hypothesized that additional research and development spending will result in an increased volume of pioneering new drugs in comparison to less innovative drugs. Results confirm our hypotheses. Specific policy recommendations for altering firms’ incentives for the development of pioneering drugs are provided. Keywords pharmaceutical industry, innovation, marketing, patent, health care

reform

The pharmaceutical industry has been criticized for developing and aggressively marketing drugs that do not provide significant benefits relative to existing drugs but retain the benefits of patent protection (Angell 2004; Applbaum 2006, 2009; Avorn 2004). Patent protection in the pharmaceutical industry provides an incentive for pharmaceutical companies to

We gratefully acknowledge the financial support for this project provided by the Jule and Marguerite Surtman Foundation and the Belk College of Business, University of North Carolina at Charlotte. We would also like to thank Judith Walsh, Samuel Abankwa, Mike Dickson, Samantha Paustian-Underdahl, and Rebecca Glavin for research assistance. Journal of Health Politics, Policy and Law, Vol. 41, No. 2, April 2016 DOI 10.1215/03616878-3476093 2016 by Duke University Press

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make large investments in research and development (R&D) in exchange for higher than competitive prices for new drugs during the period that they are under patent protection. The protection increases the incentives for innovation, which has public health implications since new drugs can improve life expectancy and the quality of life (Lichtenberg 2005). However, the high price of patented pharmaceutical products results in higher costs to individuals in the form of higher insurance premiums, higher outof-pocket payments for medications, and higher taxes to pay for government-funded care. Expensive new pharmaceuticals can also result in higher operating costs for businesses in the form of higher insurance premiums and higher taxes. If the benefits of new drugs with patent protection are negligible in comparison to alternative therapies (e.g., over-the-counter medication, generic prescription medications, or lifestyle changes), then patent protection, and the high cost of these drugs, is difficult to justify. According to Kalman Applbaum (2009: 16), the current system of patents and regulations “encourage[s] drug firms to sideline the uncertain and difficult search for pioneering cures to serious diseases in favor of what they call ‘meaningful product differentiation strategies,’” where “meaningfulness is defined relative to an image of novelty, efficacy, and safety that firms endeavor to influence through myriad forms of propaganda.” A growing body of literature argues that marketing strategies, rather than public health considerations, drive R&D priorities in the pharmaceutical industry, despite the industry’s claims to the contrary (for a summary of this literature, see Gagnon 2013: 571). Jerry Avorn (2004: 206) argues that “the current reward structure in the marketplace induced many to spend too much money and effort on developing, promoting, and defending molecules of minimal worth, rather than devoting more of their R&D investment to truly groundbreaking medical research.” From a strategic perspective, this behavior appears rational for managers because it seems to result in value creation for both shareholders and the stakeholders who accept the marketing messages. To date, the evidence to support the claim that marketing expenditures have any relationship to pharmaceutical innovation has been anecdotal. In this article, we evaluate the impact of differing levels of marketing and R&D expenditures on the generation of more and less innovative new drug application (NDA) approvals by firms. We go on to discuss the implications of our findings and offer policy recommendations for improving the rate at which firms produce pioneering new pharmaceuticals.

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Innovation versus Marketing

Discussions of pharmaceutical innovation vary with respect to the meaning of innovation. In some instances, innovation is used broadly to refer to any new drug that receives a patent regardless of its therapeutic benefits. In other instances, the terms pioneering and me too are invoked without a clear sense of the relationship between these terms and the US Food and Drug Administration’s (FDA) NDA classifications. Some researchers focus on the development of new molecular entities (NMEs) (or new chemical entities) (DiMasi, Hansen, and Grabowski 2003; Sampat and Lichtenberg 2011), while others focus on drugs granted FDA “priority review” status (Light and Lexchin 2012). However, FDA classifications allow for more fine-grained distinctions than have previously been utilized by researchers. Varieties of NDA Innovation

For NDAs, the FDA (2012a, 2014) distinguishes between “priority review” status, which means “a drug that appears to represent an advance over available therapy,” and “standard review” status, which means “a drug that appears to have therapeutic qualities similar to those of an already marketed drug.” Priority review is granted when preliminary estimates indicate that the drug has the potential to provide “(1) safe and effective therapy where no satisfactory alternative therapy exists; or (2) a significant improvement compared to marketed products . . . including nondrug products or therapies” (FDA 2007: 2). All nonpriority applications are regarded as standard review applications. Priority review status results in “additional FDA attention and resources” relative to standard review (FDA 2012b). With respect to chemical types, during the period of our study the FDA (2014) distinguished between NMEs and other non-NME categories such as new active ingredients, indications, formulations, combinations, and dosage forms. Differentiating between these categories allows for more sophisticated analyses of drug innovation (GAO 2006). Both the FDA and the US Government Accountability Office (GAO 2006) distinguish between four levels of NDA innovation based on review classifications and chemical types, as shown in table 1. The FDA and the GAO agree that NMEs that receive priority review status are the most innovative new drugs, and we refer to these as pioneering drugs. The FDA and the GAO also agree that the least innovative drugs are standard review, non-NMEs drugs, and we refer to these as



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Table 1

Degrees of Pharmaceutical Innovation

Rank

GAO

FDA

Classification

1 2 3 4

Priority NME Standard NME Priority non-NME Standard non-NME

Priority NME Priority non-NME Standard NME Standard non-NME

Pioneering Moderately innovative Moderately innovative Weakly innovative

Note: NME = new molecular entity

weakly innovative drugs. The FDA and the GAO disagree on the ranking of the second and third tiers of innovative drugs, with the FDA ranking priority reviewed non-NME drugs second and the GAO ranking them third and with the FDA ranking standard review NMEs third and the GAO ranking them second. We refer to these two tiers in combination as moderately innovative. From 1993 to 2004, 14 percent of approved NDAs were evaluated as pioneering priority NMEs by the FDA, while 58 percent were evaluated as the weakly innovative standard non-NMEs (GAO 2006: 23). The remaining 28 percent were evaluated as moderately innovative standard NMEs and priority non-NMEs. While our analysis includes all NDA approvals during the period of our study, it excludes biologic license applications (BLAs) consistent with the approach of the GAO’s (2006: 39) assessment of drug innovation. BLAs are excluded for two reasons. First, the FDA drug classification scheme does not apply to biologics, and so there is no basis for making similar distinctions between levels of innovation among biologics as with NDAs. Second, as explained below, biologics represent a small percentage of drug approvals during the period of our study. Marketing

The pharmaceutical industry has seen an overall rise in expenditures on marketing coincidental with the FDA’s change in policy that permitted direct-to-consumer advertising (DTCA) on television. According to one study, overall pharmaceutical promotional expenditures increased from $11.4 billion in 1995 to $28.9 billion in 2005, and expenditures as a percentage of sales increased from 14.2 to 18.2 (Donohue, Cevasco, and Rosenthal 2007). These marketing expenditures include DTCA, detailing to physicians, journal advertising, and free samples. An alternative analysis of pharmaceutical marketing in the United States puts annual pharmaceutical marketing expenditures for 2004 at $57.5 billion (Gagnon and



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Lexchin 2008). This amounts to 35.7 percent of 2004 sales and is 1.95 times the $29.555 billion in R&D spending reported by the industry trade group Pharmaceutical Research and Manufacturers of America (PhRMA 2008b: 52, 58). Not all of this marketing has been legal (Almashat et al. 2010; Almashat and Wolfe 2012; Qureshi et al. 2011). For the period 1991–2012, there were 239 settlements with pharmaceutical companies in the United States, totaling $30.2 billion (Almashat et al. 2010; Qureshi et al. 2011). Most of these settlements were the result of fraudulent marketing strategies such as off-label marketing, downplaying of drugs risks in promotional materials, and kickbacks to physicians. The persistent utilization of illegal marketing in the pharmaceutical industry, despite the significant financial and reputational costs, is one indication of the important role of marketing in enhancing revenues. Managers can satisfy shareholder expectations for return on investment by focusing on marketing less innovative drugs at the expense of R&D into pioneering drugs. This behavior is rational for pharmaceutical company managers when three conditions hold. First, the increased costs of marketing and settlements for illegal marketing activity can be absorbed by the additional revenue generated. In this way, increased marketing (including illegal activity and practices that violate a company’s professed standards, code of ethics, and industry guidelines) creates increased value for shareholders. Second, regulatory incentives such as patent exclusivity for developing weakly innovative, moderately innovative, and pioneering drugs are not robustly differentiated. Once a new drug is patented in the United States or the European Union it receives a twenty-year patent. No distinction is made in patent law regarding NMEs that are pioneering and those that are less innovative. Third, managers are rewarded by internal incentive structures for creating short- and medium-term value by generating sales regardless of the innovativeness or health benefits of the drug or the integrity of the marketing campaign, rather than rewarded for pioneering innovation and ethical marketing campaigns. The risk to public health is that increased value creation via marketing reduces the need for R&D, thereby reducing pioneering innovation and increasing incremental innovation via less innovative new drugs. Principal-agent theory predicts that executives who are rewarded for long-term value creation will invest heavily in R&D (Ederer and Manso 2013; Manso 2011). Such investment has the potential to maintain an active drug development pipeline, with increased potential for pioneering drug development, while better serving public health. However, because R&D is risky, executives who are financially penalized for research streams that



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do not generate significant profits would be expected to be risk-averse (Brody 2007: 93–95). Executives who are rewarded primarily for shortterm value creation would be expected to de-emphasize R&D in favor of an alternative strategy such as one that relies on investing heavily in the marketing of less innovative drugs. Hypotheses

In this article we present new data to assist policy makers in assessing the efficacy of existing incentive structures for marketing expenditures and R&D expenditures in the pharmaceutical industry. Specifically, we consider the impact of increased marketing expenditures on priority NMEs, that is, pioneering, drug innovation, by publicly traded firms with at least 50 percent of revenues from the North American Industry Classification System (NAICS) pharmaceutical preparation manufacturing category and comparable international firms.1 We expect to find that the effect of additional firm-level spending on marketing and administration will result in a higher volume of weakly innovative new drugs in comparison to pioneering new drugs. We also expect the effect of spending on marketing and administration on the volume of moderately innovative new drugs to fall between the magnitude of the effects we see for pioneering and weakly innovative new drugs. In addition, we consider the impact of increased spending by firms in our sample on R&D on pioneering drug development, where we expect to find that the effect of additional R&D spending on pioneering drug development will be larger than the effect of R&D spending on weakly innovative drug development. We also expect the effect of spending on R&D on the volume of moderately innovative new drugs to fall between the magnitude of the effects we see for pioneering and weakly innovative new drugs. If firm expenditures on marketing are primarily utilized for public health education as the industry claims (PhRMA 2008a, 2009), then we would not expect additional marketing expenditures to result in a higher volume of weakly innovative new drugs in comparison to pioneering new drugs. This is because genuinely educational campaigns would not be expected to prioritize weakly innovative drugs in comparison to pioneering drugs. Our analysis should help 1. There can be considerable diversification among pharmaceutical manufacturers. To ensure that our analysis did not include firms where the majority of revenues came from nonpharmaceutical products, we limited our analysis to firms with at least 50 percent of revenues from the pharmaceutical preparation manufacturing category. As a sensitivity analysis, we conducted the empirical exercise using a cutoff of 70 percent; the results were similar in terms of sign for this smaller sample of firms.



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inform a diverse range of stakeholders concerned about public health regarding the relationships between marketing expenditures, R&D expenditures, and the development of new drugs that range from pioneering to weakly innovative. Methods

We used measures of NDA approvals by the FDA for publicly traded firms from 1999 to 2009 as our dependent variables. We utilized the database Drugs@FDA to identify the review classification, chemical type, and company for 876 priority or standard review NDAs approved during this period. This includes approved NDAs developed by publicly held companies, privately held companies, government agencies, and nonprofit organizations. We identified forty-five cases where the database did not list the chemical type or the review classification or both. We obtained the missing data directly from the FDA’s Center for Drug Evaluation and Research.2 In four cases the chemical type or the review classification was unknown due to anomalies with the application records, and we excluded those NDA approvals from our study. All priority and standard review NDA approvals were considered except for “over-the-counter switches,” which are not related to innovation.3 Each approved NDA fit into one of four categories based on the FDA review process and whether the drug was an NME, as discussed above: priority review and NME (priority NME), priority review but not NME (priority non-NME), standard review and NME (standard NME), and standard review but not NME (standard nonNME). In our discussion and tables, we refer to priority NME drugs as “pioneering” and to standard non-NME drugs as “weakly innovative.” For analysis purposes, the priority non-NME and standard NME drugs were collapsed into one category; in the discussion of results, we refer to these categories as “moderately innovative.” All orphan drugs received either priority or standard review and were categorized accordingly. For the analysis, we used a firm-level sum of new standard and priority drug approvals from all subsidiaries in a given year, where the sample is limited to publicly traded firms as discussed below. Biologics were not included in our 2. As a result of our information requests, the FDA Division of Drug Information updated its publicly available databases so that all of the previously missing information we identified is now available to the public via the Drugs@FDA web pages. The same information is not available in the FDA Orange Book. 3. A total of eight FDA chemical types were utilized during the period of our study. Those included in the study were NME, new active ingredient, new dosage form, new combination, new formulation, new indication, and drug already marketed without an approved NDA.



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analysis because they are not categorized in the same manner as NDAs by the FDA and because they represented only 3.5 percent of the total number of combined approved NDAs and BLAs in our sample. The sample was limited to firms with a majority of revenue from pharmaceutical preparation manufacturing. The Compustat Segment NAICS File was used to identify firms for the analysis sample with at least 50 percent of revenue from 1999 to 2009 from NAICS code 325412 (pharmaceutical preparation manufacturing). However, NAICS business segment data are not available for non-US firms. When data were not available regarding the NAICS operating segment, as was the case for thirty-two firms in the sample, we searched the text of a firm’s annual reports to determine participation of the firm in the areas of pharmaceutical preparation manufacturing. For instance, the text of the annual report could indicate that nearly all of the firm’s focus was on activity related to the pharmaceutical industry. Based on review of the textual data from the annual reports by three independent reviewers, we assigned a proportion of revenue from each operating segment and included those firms with 50 percent or more of revenue from pharmaceutical preparation manufacturing. The volume of NDA approvals for a firm in a year was matched to current and past values from the firm’s Form 10-K filings with the Securities and Exchange Commission available in Mergent or Compustat for the period 1990–2009 for firms with at least one NDA approval by the FDA from 1999 to 2009. The key explanatory variables from the financial statements are contemporaneous and lagged values for R&D expenditures and selling, general, and administrative (SG&A) expenditures by year. Consistent with standard practice in marketing science research, we use SG&A as a proxy for marketing expenditures by the firm, where SG&A includes more than just marketing but is a good proxy for the level of a firm’s expenditures on its market research, sales effort, trade promotion expenses, and other related activities (Dutta, Narasimhan, and Rajiv 1999; Le´vesque, Joglekar, and Davies 2012; Luo 2008; Mizik and Jacobson 2007; Morgan and Rego 2009).4 In addition, the 10-K filings provide information regarding net income and total revenue, used as control variables in the analysis. Control variables are discussed below. All values denominated in non-US currencies were converted to US dollars using the exchange rate on the day of the 10-K filing. The Biomedical R&D Price Deflator from the National Institutes of 4. According to one estimate, the administration component of SG&A amounts to just 5 percent of revenues (Angell 2004: 119–20).



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Health was used to convert R&D expenditures converted to 2009 dollars. All other values from the 10-K filings were converted to 2009 dollars using the gross domestic product deflator. The analysis was limited to firms with (1) publicly reported financial data in the year of the NDA and up to nine years prior to the NDA approval year and (2) separately reported measures of SG&A and R&D. This resulted in an analysis sample of sixty firms, which were responsible for 435 approved NDAs (49.7 percent of the total NDAs) in the period examined.5 The optimal number of lagged values of the variables in the models was either eight or nine, as discussed below. In some cases, an approved NDA from the FDA was designated for a firm that did not have a 10-K filing but that either (1) was a subsidiary of a firm with a 10-K filing or (2) had partnered with a firm with a 10-K filing in the case of that particular drug. In both instances, the values from the 10-K filing for the publicly traded parent or partner firm were used. We also estimated the models excluding NDA approvals for firms that did not have a 10-K filing. The results were qualitatively similar. Merger and acquisition data from company websites, press releases, and web searches were used to ensure that drugs from subsidiaries were appropriately matched to parent firms. First, we examined the frequency of NDA approvals from the three categories over time in the full data set and in the subset used for analysis. We also considered the trends in R&D expenditures and SG&A expenditures and mean values for the financial variables used in the analysis. Second, as noted above, our key objective was to consider the influence of both R&D expenditures and SG&A expenditures on the three categories of NDAs. Each of the three measures of NDAs discussed above were modeled separately as a function of current and prior (1) R&D for a firm in a year, (2) SG&A for a firm in a year, and (3) control variables, where the unit of analysis was a firm in a particular year from 1999 to 2009. 5. The sixty firms were Abbott Laboratories, Adolor Pharmaceuticals, Akorn, Alkermes, Allergan, Amylin Pharmaceuticals, APP Pharmaceuticals, Astellas Pharma, Axcan Pharma, Barr Pharmaceuticals, Bausch and Lomb, Bristol-Myers-Squibb, Celgene, Cephalon, Cubist Pharmaceuticals, Daiichi Sankyo, Depomed, Draxis Specialty, DUSA Pharmaceuticals, Eisai, Elan, Eli Lilly, Endo Health, Forest Laboratories—CL A, Genentech, GlaxoSmithKline, H. Lundbeck, Inspire Pharmaceuticals, ISTA Pharmaceuticals, King Pharmaceuticals, Meda AB, Medicines Company, Medicis Pharmaceutical, Medigene, Merck and Co., Merck KGaA, Mylan, Novartis, Noven Pharmaceuticals, Novo Nordisk, Par Pharmaceuticals, Perrigo Company, Pfizer, Recordati-Industria, Regeneron Pharmaceuticals, Roche Holdings, Salix Pharmaceuticals, SanofiAventis, Schering-Plough, Schwarz Pharma, Sepracor, Shire, Skye Pharma, Spectrum Pharmaceuticals, Taro Pharmaceutical Industries, Teva Pharmaceuticals, United Therapeutics, Valeant Pharmaceuticals, Watson Pharmaceuticals, and Wyeth. Among the organizations excluded from our study were government research centers, universities, nonprofit research centers, and privately held biotech firms.



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Included among our control variables were current and past firm-level annual measures of technological spillovers facing the firm, total revenue, and net income; we also include binary indicators for each year. Technological spillovers facing a given firm in a year were represented by the R&D expenditures of all other publicly traded pharmaceutical firms in the sample in a given year that had at least one NDA approval in the 1999–2009 period. In theory, technological spillovers may have a negative effect on innovation at a firm since more R&D by rivals decreases the probability that the firm invents an innovative new drug. Alternatively, higher technological spillovers may have a positive effect on innovation by a given firm if some of the R&D activity by rivals ends up benefiting that firm. This may happen if scientists move among firms, publish their findings, or discuss their findings. Technological spillovers in the pharmaceutical industry have been the subject of a number of articles, where the direction of the effect of spillovers has been mixed (Cincera 1997; Furman et al. 2006; Henderson and Cockburn 1996; Penner-Hahn and Shaver 2005). Our inclusion of current and lagged values of total revenue allows us to control for firm size, while current and lagged values of net income are indicators of the firm’s current and past financial health. By including current and lagged values of these financial measures, we are better able to isolate the independent effects of both SG&A expenditures and R&D expenditures. To estimate the models, a conditional fixed-effects Poisson model with panel bootstrapped standard errors was used. We used a Poisson model due to the discrete nonnegative nature of the dependent variables, which were counts of NDA approvals in a year, and estimated all models using Stata 12.6 The fixed-effects specification allows us to control for unmeasured characteristics that are constant at the firm level over the 1999–2009 period considered, including factors such as leadership position in the industry or the quality of the scientific staff. Given the lengthy drug development process, past (i.e., lagged) values of all financial variables are used to predict current NDA approvals. We tested for the optimal number of lagged values for the explanatory variables by estimating the models with one 6. The conditional fixed-effects Poisson model was chosen over the conditional fixed-effects negative binomial model. This decision was based on the fact that the conditional fixed-effects negative binomial model proposed by Jerry Hausman, Bronwyn H. Hall, and Zvi Griliches (1984) is not a true fixed-effects method, because it does not control for all stable covariates (Allison and Waterman 2002). We did consider the issue of overdispersion by examining the relationship between the mean and the variance of the NDA measures. For pioneering drug approvals, the variance was 1.2 times the mean, and for the moderately innovation drug approvals the variance was 1.3 times the mean. In both cases, the small amount of overdispersion is likely to be of little consequence. For weakly innovative drug approvals, the variance was approximately four times the mean, suggesting that any estimated errors are too small.



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through nine lags and conducting a series of likelihood ratio tests to determine the optimal lag length. Third, using the models with the optimal number of lagged explanatory variables, we considered the cumulative marginal effect of current and past R&D or SG&A spending on NDAs during the year. To find the cumulative marginal effect of R&D, for instance, we summed the marginal effects for all current and past values of R&D in the model and then tested for whether all of the current and past R&D activity had a significant effect on NDA approvals of a particular type. We use the results to consider the impact of additional R&D spending and SG&A spending on the generation of NDA approvals for each of the three categories. Finally, following Richard H. Browne (1979), we considered whether the effect of R&D spending on the volume of NDA approvals was higher for priority NMEs or for priority non-NMEs plus standard NMEs, using standard non-NMEs, the least innovative drugs, as the reference group. Similarly, we also considered whether the effect of SG&A spending on the volume of NDA approvals was lower for priority NMEs or for priority non-NMEs plus standard NMEs, when compared with standard non-NMEs. Results

Figure 1 shows the trend in NDA approvals by year by the FDA from 1999 to 2009 for each of the three innovation categories in the full set of publicly traded firms, as described above. Simple linear regression models of the trend indicate no significant trend in any of three individual measures or the overall total number of NDA approvals over the 1999–2009 period. A total of 876 new priority or standard review drugs were approved over the period, with nearly two-thirds (n = 591, or 65 percent) falling into the weakly innovative (standard non-NME) category. For the other categories, the total number of drugs approved was 87 (9.9 percent) for the pioneering (priority NME) category and 198 (22.6 percent) for the moderately innovative (priority non-NME plus standard NME) drug categories. While figure 1 contains all NDA approvals, it is important to note that the trends in NDA approvals and the percentage of drugs in the three categories in the analysis sample of publicly traded firms with more than 50 percent of revenue from pharmaceutical preparation manufacturing with complete financial information follow a similar pattern for all three categories. As discussed above, our analysis sample, which includes sixty distinct firms with at least one NDA approval over the 1999–2009 period, includes 435



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Figure 1 Trends in NDA Approvals for Publicly Traded Firms, 1999–2009 Source: Authors’ analyses of data from Drugs@FDA for publicly traded firms. Complete description in “Data” section. Notes: NDAs = new drug applications; NME = new molecular entity

(49.7 percent) of all NDA approvals over the period. In the sample, 66.2 percent of NDA approvals were for weakly innovative (standard nonNME) drugs over the period examined; 10.8 percent of the total number of drugs approved were in the pioneering (priority NME) category, and 23 percent were in the moderately innovative (priority non-NME plus standard NME) drug category. Figure 2 shows the trends in R&D expenditures and SG&A expenditures for the average publicly traded firm in our analysis sample. Simple linear trends reveal that average firm-level SG&A spending increased at a real rate of $63.2 million per year, while average firm-level R&D spending increased at a rate of $60.24 million per year. By 2009, the average firm in our sample was spending nearly $2.6 billion on SG&A and $1.4 billion on R&D. It is also interesting to note that average SG&A spending over the



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Figure 2 Trends in Average Firm R&D and SG&A Expenditures (in Millions of Dollars), 1999–2009 Source: Authors’ analyses of data from firms’ 10-K filings with the Securities and Exchange Commission, available in Mergent or Compustat, for firms with at least one NDA approval from the FDA from 1999 to 2009. Notes: R&D = research and development; SG&A = selling, general, and administrative; NDA = new drug application

period was approximately double average spending on R&D for the firms in the analysis sample. Data on average annual firm-level drug approval and financial measures used in the analysis are contained in table 2. Most firms had relatively low annual innovation rates, especially for the priority drug category. Key results from the four models of NDA approvals are contained in table 3. The first two lines of numerical results provide the marginal effects of the sum of SG&A and R&D, respectively, over all periods of financial data used in the model on NDA approvals. The p-values indicate whether the sum of SG&A or R&D over all periods included in the model has a significant effect on new approvals. Using a 5 percent significance level, SG&A spending has a positive but not statistically significant effect on the volume of new standard non-NME drug approvals, new standard NME



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Table 2 Characteristics of Firm-Level Annual Measures of NDA Approvals and Explanatory Variables

NDA Approvals: Pioneering (priority NMEs) Moderately innovative (priority non-NMEs + standard NMEs) Weakly innovative (standard non-NMEs) Key explanatory variables: SG&A $ (millions) R&D $ (millions) Control variables $ (millions): Net income Total revenue Technological spillovers

Mean

Standard Error

Minimum

Maximum

0.1066 0.2063

0.3567 0.5227

0 0

3 3

0.6735

1.6740

0

25

2,424.22 1,224.72

3,975.66 2,037.05

3.08 1.85

19,128.48 9,586.45

1,345.80 7,811.75 85,196.93

2,842.25 13,154.47 18,608.25

- 3,462.10 0 48,523.24

20,516.73 61,526.96 107,948.40

Notes: NMEs = new molecular entities; SG&A = selling, general, and administrative; R&D = research and development. The values for the key explanatory variables and control variables are based on firms with at least one NDA approval from 1999 to 2009, with > 50% of revenue from pharmaceutical preparation manufacturing and with complete financial data for at least eight years prior to the observation year.

drug approvals, and priority non-NME drug approvals. In contrast, SG&A expenditures have a negative and significant effect on priority NME drug approval volume. The effect of the sum of R&D expenditures on NDA approvals is only statistically significantly different from zero in the model for new priority NME drug approvals, where the effect is positive. For the priority NME and standard non-NME models, the optimal lag length for the financial explanatory variables was nine; for the middle category, the optimal lag length was eight per firm. Data from the multivariate analysis and mean values from the subsamples for the explanatory variables were used to construct the estimates of the impact on NDA approvals in each of the three categories of a permanent 1 percent increase in SG&A and R&D. As shown in figure 3, a permanent increase in SG&A over ten years of 1 percent each year results in a reduction in NDA approvals of 1.25 priority NMEs on average per firm. In contrast, the same permanent 1 percent increase in SG&A over ten years (standard non-NME) or nine years (priority non-NME plus standard NME) results in 0.2 more new standard non-NME drug approvals and 0.08 NDA



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Table 3 Estimates of the Effect of SG&A and R&D on NDA Approvals and Tests for Differences Moderately Innovative Weakly (Priority Innovative Non-NME (Standard and Pioneering NonStandard (Priority NME) p-value NME) p-value NME) p-value Sum of effect of - 0.0066 0.010 0.0004 0.463 0.0011 0.165 SG&A all periods Sum of effect of 0.0106 0.006 - 0.0020 0.167 - 0.0089 0.343 R&D all periods 9 8 9 Optimal number of lagged values for explanatory variables Number of firms 20 32 42 Number of 186 287 346 observations Test for Significant Difference Between Effect for Standard Non-NME and NDA Approval Category Difference in effect Yes No NA of SG&A? Difference in effect Yes No NA of R&D? Source: Authors’ analyses of data for publicly traded firms with complete financial data, as described in the “Data” section. Notes: SG&A = selling, general, and administrative; R&D = research and development; NDA = new drug application. All estimated models include the control variables and lags of the control variables indicated in the Methods section, as well as firm and year fixed effects.

approvals in the middle innovation category. The effects of increased spending on R&D are also large for priority NMEs and standard nonNMEs. For priority NMEs, increasing permanent spending by 1 percent results in an additional 0.95 NDA approvals per firm over the ten years. However, the same 1 percent increase in R&D over the ten years reduces the number of NDA approvals in the standard non-NME category by 0.8. The final set of results in table 3 are tests for significant differences between the effect of SG&A or R&D for standard non-NMEs and for each of the two more innovative drug approval categories. We find that the negative effect of increased SG&A expenditures on priority NME drug



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Figure 3 Estimated Impact of Increased Lagged and Current SG&A and R&D on NDA Approvals Source: Authors’ analyses of data for publicly traded firms with complete financial data, as described in the “Data” section. Notes: R&D = research and development; SG&A = selling, general, and administrative; NME = new molecular entity

approvals is statistically significantly different from the positive effect of increased SG&A expenditures for standard non-NME drug approvals. Similarly, the positive effect of increased R&D expenditures on priority NME drug approvals is statistically significantly different from the negative effect of increased R&D expenditures for standard non-NME drug approvals. However, we do not find a statistically significant difference between the moderately innovative category and the weakly innovative category in the effects of both SG&A and R&D. In the 1999–2009 period covered by our data, only 9.9 percent of all NDA approvals for publicly traded firms were pioneering, priority NMEs, and 67 percent were weakly innovative, standard non-NMEs, with 22.6 percent in the combined moderately innovative category of standard NMEs and priority non-NMEs. This indicates a trend away from the generation of the most innovative drugs toward a focus on increased production in the



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less innovative FDA drug categories based on a comparison with the study by the GAO (2006: 23) discussed above. Financial values from eight to nine years before a drug is approved by the FDA were influential in predicting NDA approvals. This result is consistent with Michael Dickson and Jean Paul Gagnon’s (2004) finding that the average drug development time is 8.5 years. The negative impact of increased marketing expenditures on drug approvals is significant for the pioneering and moderately innovative categories, while there is a positive impact of SG&A spending on weakly innovative drug approvals. These effects are quite large. For instance, in our sample, the average publicly traded firm produced only one pioneering drug (priority NME) over the 1999–2009 period. For the sample of firms with at least one priority NME over the 1999–2009 period, the average was 2.44 drugs over the eleven-year period. Our results indicate that a permanent 1 percent increase in SG&A spending would have been associated with an average firm-level reduction in pioneering NDA approvals of approximately one drug. Limitations

This study and associated findings are limited in several respects. First, we limit our analysis to a relatively homogeneous set of pharmaceutical drug manufacturers that are publicly traded and for which we have data for nine or more years. We do not examine firms that have much more diverse portfolios of products, where drug production plays a comparatively minor role; therefore our results are limited to firms with a focus in pharmaceutical development and production. Data on privately held firms are not available, and these firms may behave differently than firms that have been publicly traded for nine or more years. Second, while we take care to control for potential confounders, we recognize that the negative association between marketing expenditures and innovative drug approvals may not be causal in nature. For instance, firm-level leadership may be a variable that affects both drug innovation and marketing expenditures. If this is the case, the seemingly direct relationship between marketing expenditures and innovative drug approvals may be a consequence of a particular leadership type that promotes the former and de-emphasizes the latter. While it is impossible to rule out these types of relationships, we argue that our fixed-effects estimation approach and control variables rule out most threats to internal validity. Third, we use FDA priority review NME status as our indicator of the most innovative NDA approvals and standard review, non-NMEs drugs



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as our indicator of the least innovative NDA approvals. There may be other measures of innovation that other authors may wish to consider. Discussion

When we compare the effect of increased marketing expenditures on approvals of weakly innovative standard non-NME drugs, we find that the effect is significantly different from the effect for pioneering, priority NME drugs but is not significantly different from the effect for the middle innovation categories (priority non-NME and standard NME). This evidence supports the notion that marketing expenditures encourage less innovative drug production while inhibiting more innovative drug discovery. In examining R&D spending, we see that increased spending on R&D has a bigger effect on the volume of NDA approvals for pioneering, priority NME drugs than for standard non-NME drugs.7 However, there is no difference between the effect of R&D on the volume of weakly innovative, standard non-NME drug approvals and the moderately innovative, priority non-NME or standard NME drugs. This suggests that higher R&D spending levels produce significantly more pioneering priority NME drug approvals than all less innovative drugs as expected. Policy Recommendations

Policy makers interested in altering incentive structures for pharmaceutical companies to encourage the development of more pioneering drugs have numerous instruments at their disposal. Here we review five options. First, differential patent lengths may be introduced both in the United States and in other jurisdictions such as the European Union. Alastair J. J. Wood (2006) has previously proposed this change for “first in class” drugs. A practicable way to implement this strategy would be to differentiate the lengths of patents or patent extensions for pioneering drugs (priority NMEs), moderately innovative drugs (standard NMEs and priority nonNMEs), and weakly innovative (standard non-NME) drugs, with pioneering 7. Daniel Carpenter (2014) finds that firms with more NME submissions (whether standard or priority review) are more likely to receive priority rating for future drugs. He takes this to imply that the “ratings have served to reflect the Administration’s judgments about likely product quality and safety, uncertainty over which is reduced by solid firm reputations” (Carpenter (2014: 684). Alternatively, this result is consistent with an organizational learning model whereby firms gain valuable experience from prior attempts and are thereby more successful in future attempts. While firm reputation or organizational learning may be factors in the attainment of pioneering innovation, our results show that firm strategy is clearly significant, as reflected in comparatively high firm R&D expenditures versus marketing expenditures.



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drugs granted the longest patent lengths, moderately innovative drugs given a shorter patent length, and weakly innovative drugs given the shortest patent lengths. Second, exclusivity for nonorphan priority NMEs might be increased to six years from the current five-year period and exclusivity for standard NMEs decreased to four years from the current five-year period, thereby providing greater incentives for the development of pioneering drugs. Third, currently most marketing expenditures are tax deductible. Amending the Internal Revenue Code to prohibit the deduction of all drug marketing expenditures would reduce company incentives for developing and aggressively marketing weakly innovative drugs at the expense of more innovative drugs. This is consistent with the Say No to Drug Ads Act (H.R. 722, 112th Cong. (1st Sess. 2011); H.R. 923, 113th Cong. (1st Sess. 2013)), which would eliminate the deduction for DTCA. An expanded act that targeted all marketing deductions for elimination would encourage innovation and better facilitate competition among drugs based on therapeutic merit and cost. In addition to removing the tax deduction for pharmaceutical marketing, some have called for a tax on marketing expenditures similar to the Italian model of a 5 percent tax on promotions to health care professionals that is used to fund independent research (Gagnon 2013). A more comprehensive tax on all pharmaceutical marketing expenditures (including physician detailing, medical journal advertising, continuing medical education, and product claim DTCA), in addition to removing the tax deduction for such expenditures, would provide an additional disincentive for marketing and a greater incentive for industry R&D of more innovative drugs.8 Fourth, recent studies have documented the significant increase in enforcement of existing regulations regarding the pharmaceutical industry, especially regulations concerning drug marketing (Donohue, Cevasco, and Rosenthal 2007; Qureshi et al. 2011: 1503). From 1991 to 2002 there were no more than three settlements per year in the United States, whereas 2009 saw thirty-seven settlements, 2010 forty-three settlements, and 2011 fortyfour settlements (Almashat et al. 2010). This increase is attributable in part to increased enforcement efforts by state and federal authorities. As noted in the introduction, most of this illegal activity has involved marketing. The 8. The deceptive and manipulative nature of such advertising is well documented (Almashat et al. 2010; Almashat and Wolfe 2012; Angell 2004; Applbaum 2006, 2009; Arnold and Oakley 2013; Avorn 2004; Brody 2007; Gagnon 2013). However, it has been argued that “help seeking” advertisements do not have the same potential for manipulation and, if utilized in an appropriate manner, could have potential health care benefits (Arnold 2009). For this reason, we do not include them among the types of DTCA to be taxed.



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growth in illegal marketing that places patient welfare at risk is one indication of the perceived value of a marketing-driven firm strategy. Channeling pharmaceutical marketing tax resources into increased FDA oversight and US Department of Justice enforcement of existing marketing regulations is one potential way to curb marketing expenditures. Curbing deceptive marketing is important to the development of pioneering drugs because sales of weakly and moderately innovative drugs are increased by manipulating physicians and consumers into wrongly believing that such drugs are more beneficial than other therapies, thereby enhancing firm revenues from less innovative drugs. If firm revenues from less innovative drugs are reduced, firms will have a greater incentive to focus on the development of pioneering drugs. More vigorous enforcement might be accomplished via higher settlement amounts, the criminal prosecution of individual executives, the loss of patent exclusivity for fraudulently marketed drugs (Lichtenberg 2005), and increased use of corporate integrity agreements. Finally, regulators should consider mandating transparent disclosure of all drug company marketing expenditures. Any company submitting NDAs could be required to provide detailed information on an annual basis regarding all marketing expenditures including detailing, product samples, DTCA, journal advertising, continuing education and promotion, and the retention of physicians as paid advocates or “thought leaders.” This information would allow policy makers and scholars to better assess corporate marketing expenditures in relation to R&D expenditures and innovation in the future.

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Denis G. Arnold is the Surtman Distinguished Professor of Business Ethics and professor of management in the Belk College of Business, University of North Carolina at Charlotte. His publications include over forty articles and chapters and six books, including Ethics and the Business of Biomedicine (2009). One of his primary research streams focuses on ethics, compliance, and public policy in the pharmaceutical industry. He coauthored a recent study published in the Journal of Health Politics, Policy and Law (2013) documenting widespread deceptive marketing by pharmaceutical firms and providing policy solutions. Currently, he is collaborating with a team of investigators on a study that seeks to understand organizational and governance attributes that differentiate firms with high integrity from firms with low integrity. He serves as editor in chief of the academic journal Business Ethics Quarterly.



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Jennifer L. Troyer is professor of economics, adjunct professor of public health sciences and public policy, and associate dean for research and graduate programs at the University of North Carolina at Charlotte’s Belk College of Business. She has taught courses in health economics and econometrics, and her work focuses primarily on policy relevant issues concerning health care costs and quality. Currently, she is coinvestigator on a project funded by the Agency for Healthcare Research and Quality that examines costs and outcomes of a technology-based colorectal cancer screening intervention for primary care practices. She holds a PhD and an MS in economics from Florida State University. Her publications include articles in Health Services Research; Medical Care; Journal of Health Politics, Policy and Law; Gerontologist; Academic Emergency Medicine; Circulation: Cardiovascular Imaging; Journal of Bone and Joint Surgery; and Health Care Management Science.

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