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  1. 1. Stefan Stremersch & Walter Van Dyck Marketing of the Life Sciences: A New Framework and Research Agenda for a Nascent Field Although marketing scholars often seek to contribute new knowledge that is applicable across industries, some industries have unique characteristics that require industry-specific knowledge development. The authors argue that this requirement applies to the life sciences industry, defined as companies in pharmaceuticals, biotechnology, and therapeutic medical devices. Marketers in the life sciences industry face novel and unique challenges along eight decision areas in therapy creation, therapy launch, and therapy promotion. In therapy creation, they face therapy pipeline optimization, innovation alliance formation, and therapy positioning decisions. In therapy launch, they face global market entry timing and key opinion leader selection decisions. Therapy promotion mostly revolves around sales force management, communication management, and stimulating patient compliance. The authors qualify these decision areas according to their practical importance and academic potential. The article derives preliminary generalizations and propositions from prior research and practice and steers further research in specific directions. The authors believe that marketing of the life sciences offers a fertile area for further research because, among other things, its potential impact transcends any problems typically investigated by marketing scholars. Keywords: life sciences, marketing theory, research agenda, pharmaceutical, biotechnology, medical device, marketing, sales A lthough marketing scholars often seek to contribute industry spans companies in pharmaceuticals, biotechnol- new knowledge that is applicable across industries ogy, and therapeutic medical devices, and it forms the inno- (Stewart 2002), some industries have unique charac- vative producer side of the health care industry. Two funda- teristics that require industry-specific knowledge develop- mental dimensions underlie the life sciences industry: ment (Eliashberg, Elberse, and Leenders 2006). Examples science-based knowledge (know-why) and quality of life. include the services industry (Parasuraman, Zeithaml, and Life sciences companies are significantly more linked to Berry 1985; Rust and Chung 2006; Vargo and Lusch 2004), science than any other industry and convert the know-why the entertainment industry (Eliashberg, Elberse, and Leen- they develop into new therapies (therapy creation). The ders 2006; Eliashberg and Shugan 1997), and the high-tech resultant therapy is launched into society only after scien- industry (Bourgeois and Eisenhardt 1988; Glazer and Weiss tific review of its impact on people’s quality of life through 1993; Heide and Weiss 1995; John, Weiss, and Dutta 1999; examination of the therapy’s safety, efficacy, and incremen- Stremersch et al. 2007; Weiss and Heide 1993). tal cost effectiveness (therapy launch). Life sciences firms In this article, we argue that this requirement also promote their life sciences therapies to both health care applies to the life sciences industry. In our definition, this providers and patients within the regulatory framework designed by society (therapy promotion). Marketers face unique challenges in therapy creation, therapy launch, and Stefan Stremersch is Chaired Professor of Marketing and Desiderius Erasmus Distinguished Chair of Economics, Erasmus School of Econom- therapy promotion decisions (see Figure 1). ics, Erasmus University Rotterdam, and Visiting Professor of Marketing, The scant survival probability of newly created thera- IESE Business School, Universidad de Navarra, Barcelona (e-mail: peutic inventions—only 1 in 5000–10,000 new inventions stremersch@few.eur.nl). Walter Van Dyck is Associate Professor of Tech- eventually makes it to market—leads to life sciences devel- nology and Innovation Management, TiasNimbas Business School, opment portfolios being uniquely shaped as funnels (Ding Tilburg University and Eindhoven University of Technology (e-mail: and Eliashberg 2002). Life sciences marketers decide on w.vandyck@tiasnimbas.edu). The article was written when the second therapy positioning—the match between indication and new author was on the faculty at Erasmus University, and both authors con- tributed equally to this article. The authors acknowledge the research therapy—many years before market entry. Market entry for assistance of Christiaan Bakker, Christian Van Someren, and Jo Sinjorgo. new therapies is strictly regulated, differentially so across They also thank Jacco Keja from Quintiles and Servaas Buijs from IMS countries. If market access is granted, manufacturers get a Health, both business partners of the Institute for Life Sciences Business limited time—in most cases, 20 years as of initial applica- Economics at Erasmus University Rotterdam, for their support. They are tion filing, 10–12 of which are typically spent in clinical grateful for the comments on preliminary versions of this article by their development—of market exclusivity, after which generic colleagues Nuno Camacho, Eelco Kappe, Vardit Landsman-Schwartz, therapies can enter the market. Life sciences firms’ market- Isabel Verniers, Sonja Wendel, and Stefan Wuyts. Finally, they thank sur- vey respondents in the business and academic communities, as well as ing efforts are typically capped (e.g., in many European the anonymous JM review team, for their valuable suggestions. countries) and/or regulated (e.g., some states in the United States require medical sales representatives to undergo a © 2009, American Marketing Association Journal of Marketing ISSN: 0022-2429 (print), 1547-7185 (electronic) 4 Vol. 73 (July 2009), 4–30
  2. 2. FIGURE 1 Key Marketing Decision Areas in Life Sciences Firms Therapy Creation Therapy Launch Therapy Promotion •Therapy pipeline •Sales force optimization •Global market entry management timing •Innovation alliance •Communication formation •Key opinion leader management selection •Therapy positioning •Stimulating patient compliance certification process). Life sciences is also one of the few ing why a certain therapy affects the human body in a cer- industries in which manufacturers are legally prohibited tain way. Science represents “know-why” (Kogut and Zan- from communicating directly with their end customer (with der 1992), in contrast to technology, which represents the exception of New Zealand and the United States). “know-how” (Quinn, Baruch, and Zien 1997). The average The life sciences industry constitutes an important and number of scientific studies a firm cites when applying for a growing part of the economy; for example, the U.S. life sci- patent for its inventions (science linkage), rather than other ences industry represented $271 billion of global sales in prior patents (know-how development), can be used as a 2007 (Pharmaceutical Research and Manufacturers of measure of the extent to which the firm is science based America 2008). In the United States, prescription drug (Narin 2001). spending—the life sciences industry’s largest component— A second constitutive characteristic of the life sciences is expected to accelerate through 2017 (Centers for industry is that the preventive or curative therapies it creates Medicare & Medicaid Services, Office of the Actuary are scientifically reviewed regarding their effect on people’s 2008). quality of life, after which they are promoted to patients and Because of its vast importance and unique challenges, providers to convince them of the acclaimed effects. the marketing literature has recently turned to the life Improvement in quality of life is expressed as an increase in sciences industry to study sales force effectiveness (Man- “quality-adjusted life years” (often referred to as QALYs) chanda and Chintagunta 2004; Manchanda and Honka and can lie in enhanced effectiveness, reduced side effects, 2005; Manchanda, Rossi, and Chintagunta 2004; Mizik and and improved convenience (Garber and Phelps 1997). It is Jacobson 2004; Venkataraman and Stremersch 2007), ther- based on both quantity and quality of life years generated apy compliance (Bowman, Heilman, and Seetharaman by the medical interventions. 2004; Wosinska 2005), communication effectiveness (Cleanthous 2004; Iizuka and Jin 2005; Macias and Lewis The Components of the Life Sciences Industry 2003; Mukherji, Dutta, and Rajiv 2004; Wosinska 2006), We discern three components within the life sciences indus- and innovation (Chandy et al. 2006; Ding and Eliashberg try: pharmaceutical, biotechnological, and therapeutic 2002; Prabhu, Chandy, and Ellis 2005; Sorescu, Chandy, medical devices. These three industries are science based and Prabhu 2003, 2007; Wuyts, Dutta, and Stremersch because their patents typically refer to more scientific stud- 2004), among other areas. ies than any other industry. For example, Narin (2001) The objectives of the current research are to evaluate shows that pharmaceutical and biotechnology firms, respec- prior research, suggest new directions for further research, tively, cited 7.3 and 14.4 scientific references per patent, and ignite life sciences marketing as an important area for which were the two highest science linkages of all technol- scholarly research. We achieve these objectives by defining ogy areas. Though not separately identified in Narin’s the life sciences industry and discerning its boundaries, study, therapeutic medical devices are also science based. deriving the key marketing decision areas in this industry, First, the average science linkage of all medical devices and formulating generalizations and propositions derived from equipment companies, which includes therapeutic medical prior research and state-of-the-art practice, and steering fur- devices, is more than twice the average of the high-tech ther research in specific directions. industry, such as aerospace or information and communica- tion technologies (Narin 2001). Second, therapeutic medi- cal devices companies, such as Nektar Therapeutics or Defining the Life Sciences Industry ArthroCare, belong to the most science-based companies in and Its Boundaries the economy.1 Underlying Dimensions of the Life Sciences Industry 1Nektar Therapeutics offers noninvasive deep-long delivery sys- A first constitutive characteristic of the life sciences indus- tems. ArthroCare offers minimally invasive surgical procedures try is that this industry creates scientific knowledge regard- involving tissue removal and treatment. Marketing of the Life Sciences / 5
  3. 3. These three industries also market products that aim to cure diseases, mostly of the skin. Therefore, they are dis- improve the quality of life. They market inorganic com- tinct from mere cosmetics, which aim to alter appearance of pounds (pharmaceutical), organic compounds (biotechnol- the skin, eyes, hair, nails, and so forth. Some cosmeceuti- ogy), or therapeutic devices that affect the (diseased) human cals (i.e., cosmetics-based therapies) are science based (e.g., body. Take breast cancer as an example. Pharmaceutical acne care products with therapeutic antiseptics). firms aim to improve breast cancer patients’ condition Medical devices and equipment vary from wheelchairs through chemotherapy, and biotechnology firms may offer to imaging devices (e.g., magnetic resonance imaging) to targeted therapies in well-identified patient types (e.g., Her- stents. Equipment such as wheelchairs improve the patient’s ceptin by Genentech). Device-based therapies are also often quality of life (e.g., through mobility), but they are not sci- used with the same objective of increasing quality-adjusted ence based. In contrast, medical imaging devices do not life years (e.g., through radiotherapy). therapeutically improve humans’ quality of life but repre- Discerning the Boundaries of the Life Sciences sent considerable know-why (science). Some devices (i.e., Industry device-based therapies), such as stents, implants, and pace- makers, enhance the quality of life and are science based; Our definition of the life sciences industry enables us to dis- thus, they belong to the life sciences industry. cern life sciences boundary industries (see Figure 2)— Nutraceuticals refer to products such as nutritional sup- namely, cosmeceuticals, medical devices and equipment, plements, vitamin- or calcium-enriched foods, and polyun- and nutraceuticals. Each of these industries contains a small saturated fatty acids. Nutraceuticals may improve quality of segment that belongs to the life sciences industry because it life beyond merely feeding the body (foods). However, only produces therapies that are science based and improve qual- a subset of these products (i.e., food-based therapies) is sci- ity of life. ence based and, thus, part of the life sciences industry. An Typical cosmeceuticals are antiwrinkle agents or balms example is sterol-derived, cholesterol-lowering BENECOL. to treat eczema or burning wounds. They prevent, treat, or Therapies exist that include both a device and a cosme- ceutical or nutraceutical component. Examples include breast implants (cosmeceuticals and devices) and nutri- FIGURE 2 genomics, that is, personalized diet recommendations based The Life Sciences Industry and Its Boundaries on diagnostics of bodily fluids (nutraceuticals and devices). Figure 3 positions the life sciences industry in the health care market (adapted from Burns 2005). Payment flows from left to right, from payers to providers, over financial Life Sciences intermediaries. Products flow from right to left, from pro- ducers to providers, over product intermediaries. The life C ba rap ie ed os s ie sciences industry is the producer side of the health care ap s m ed s er ba s et th th od- market. C ic e s os al s- Fo ic Device-based m ut ec ce therapies eu Key Marketing Decision Areas in ra tic ut al N the Life Sciences Industry s Medical devices and equipment Next, we derive the key decision areas for marketers in the life sciences industry. We first discuss our methodology, Boundary Industries after which we identify and qualify the key marketing deci- sion areas on managerial relevance and scholarly potential. FIGURE 3 The Life Sciences Industry in the Health Care Market Financial Product Payers Intermediaries Providers Intermediaries Producers Government Insurers Hospitals Pharmacies The life sciences Industry and its Patients Health Physicians Wholesalers boundary maintenance industries Employers organizations Integrated Group purchasing delivery organizations networks Source: Adapted from Burns (2005). 6 / Journal of Marketing, July 2009
  4. 4. Methodology Research, and Marketing Science, which have been used in Figure 4 graphically depicts our methodology. We first prior research as a good representation of the major journals identified marketing decision areas in life sciences from a in marketing (Stremersch and Verhoef 2005; Stremersch, literature study (Step 1).2 Appendix A provides an overview Verniers, and Verhoef 2007). of the major publications in life sciences marketing accord- Given its relatedness in the health care value chain, ing to the three areas we defined—therapy creation, launch, Appendix B provides an overview of the health psychology and promotion. These publications include International literature in the same major marketing journals. It discerns Journal of Research in Marketing, Journal of Consumer three frameworks in this literature: health-related behavior, Research, Journal of Marketing, Journal of Marketing health risk perception, and health communication. Two early schools of thought underlie these frameworks: protec- tion motivation theory and the health belief model. Protec- 2Our sample of academic literature included (1) marketing jour- tion motivation theory predicts protection intentions as a nals, such as Journal of Marketing; (2) journals on the boundaries function of severity, vulnerability, response efficacy, and of the marketing discipline, such as Management Science; (3) spe- self-efficacy and is used to test the effectiveness of health cialized journals in life sciences and health economics, such as communication (Maddux and Rogers 1983; Rogers 1975; Journal of Health Economics; (4) recent proceedings of confer- see also Keller and Lehmann 2008). The health belief ences, such as the INFORMS Marketing Science Conference model (Becker 1974; Rosenstock 1974) proposes that (2000–2008) and the Association for Consumer Research confer- increasing risk perceptions should lead to precautionary ence (2000–2008); and (5) unpublished working papers. In the study of the industry literature, we included Journal of Medical behavior (see Menon, Raghubir, and Agrawal 2008). Marketing, Life Sciences, Medical Device Technology, Medical Though more distant to the life sciences marketing Marketing & Media, Pharmaceutical Executive, and Pharma Mar- field, we also reviewed the health economics literature. The keting News, among others. literature provides good reviews on the cost of innovation FIGURE 4 Methodology Practitioner Academic Literature Review Literature Review Step 1 Preidentified Life Sciences Marketing Decision Areas Identifying Marketing Decision Areas and Domains Life Sciences Marketing Practitioners Step 2 Personal Interviews Identified Life Sciences Marketing Decision Areas Life Sciences Marketing Healthcare Payer and Practitioner Telephone Provider Telephone Marketing Academics Survey Survey Online Survey Step 3a Step 3b Step 3c Life Sciences Marketing Decision Areas Importance Rating Low High Life Sciences Marketing Decision Areas Future Health- Research Need Critical enhancing High decision decision Low High areas areas Step 4 Practice- High- Performance- Ancillary High enhancing impact enhancing Low decision research research decision areas Step 5 areas Knowledge- Incremental Qualifying Low enhancing research Further research Research Marketing of the Life Sciences / 7
  5. 5. (see DiMasi, Hansen, and Grabowski 2003), price competi- we asked the academics to assess (on a 1–7 scale) the extent tion among pharmaceutical firms (see Bhattacharya and to which (1) they are covered by current marketing research Vogt 2003; Scherer 1993), the effect of generic entry on in progress, (2) they deserve more scholarly attention in the branded drug prices (see Frank and Salkever 1997; future, and (3) they are perceived by academics as impor- Grabowski and Vernon 1992), health care policy (see Drum- tant for life sciences marketers in practice. mond, Jönsson, and Rutten 1997; Scherer 2004), and refer- Step 4 yields the practical impact of life sciences mar- ence pricing (see López-Casasnovas and Puig-Junoy 2000). keting decision areas from both a firm profit perspective In Step 2, we conducted two-hour personal interviews and a patient welfare perspective. Step 5 consists of map- with nine marketing experts in life sciences companies, ping the need for academic research, as perceived by acade- such as Amgen, GlaxoSmithKline, Novartis, Novo Nordisk, mics, onto decision area importance, as perceived by practi- and Philips Medical Systems. To have sufficient confidence tioners (combining the input of both marketing managers in our findings and to qualify the marketing decision areas and health care providers and payers). we identified in terms of importance, we conducted quanti- tative telephone surveys with marketing managers at life Identification of Key Marketing Decision Areas sciences firms and with health care payers and providers, Figure 1 contains the marketing decision areas we retained and we conducted an online survey of marketing academics. as key areas, grouped into three higher-level decision We sampled marketing managers (Step 3a) using a domains: therapy creation, therapy launch, and therapy pro- snowballing technique, first contacting respondents we motion. In therapy creation, the key decision areas are ther- knew personally, then contacting executives the first apy pipeline optimization, innovation alliance formation, respondents identified as useful respondents, and so on. In and therapy positioning. The key decision areas in therapy total, we contacted 110 executives, 96 of whom agreed to launch are global market entry timing and key opinion participate in the telephone interview (for a response rate of leader selection. The key decision areas in therapy promo- 87%): 40 managers of pharmaceutical firms (e.g., Astellas tion are sales force management, communication manage- Pharma, AstraZeneca, Bristol-Myers Squibb, Glaxo- ment, and stimulating patient compliance. Table 1 describes SmithKline, Johnson & Johnson, MSD, Novartis, Novo each decision area. The second column presents the clarifi- Nordisk, Organon, Pfizer, Roche, Sanofi-Aventis, Schering- cation we provided to respondents when we asked them to Plough, Wyeth), 28 managers of biotech firms (e.g., Amgen, rate the decision area’s importance. The third column con- Biogen Idec, Galapagos, Genzyme, Novo Nordisk, tains the associations respondents made for each decision Organon), and 28 managers of medical devices companies area during our interviews. (e.g., 3M Medical Specialties, AGFA HealthCare, B. Braun, Coloplast, Johnson & Johnson, Philips Medical Systems, Qualifying Key Marketing Decision Areas in Terms Siemens Medical Solutions). We overweighted the pharma- of Research Potential ceutical industry, given its larger size compared with the In Step 4 (for more details, see Figure 5), we join relevance others. From these managers, we inventoried key decision in terms of business performance (averaged over all life sci- areas (open question) and the importance of each previously ences firms we surveyed) and relevance in terms of patient identified (Steps 1 and 2) decision area for the firm on a 1– welfare (average of the averages over all surveyed payers on 7 scale. the one hand and all surveyed providers on the other hand3). We sampled health care payers and providers (Step 3b) Average importance to business performance ranged from from contact lists provided by IMS Health. From a sample 4.8 (innovation alliance formation) to 5.6 (sales force man- of 545 payers and providers, 112 respondents participated agement), while average importance ratings to patient wel- (for a response rate of 21%), 81 of whom were physicians fare ranged from 3.6 (therapy positioning) to 5.2 (commu- (health care providers) and 31 of whom were representa- nication management), all on a scale ranging from 1 to 7. tives of health care government and health management In Figure 4, we qualify the different cells as follows: (1) organizations (health care payers). From this sample, we “Critical decision areas” are of above-median importance assessed the impact of the previously identified (Steps 1– to both business performance and patient welfare, (2) 3a) marketing decision areas on patient welfare on a 1–7 performance-enhancing decision areas are of above-median scale. importance to business performance and of below-median We sampled academics (Step 3c) using two criteria: (1) importance to patient welfare, (3) health-enhancing deci- They had a position in marketing, and (2) they had knowl- sion areas are of below-median importance to business per- edge relevant to the life sciences industry through their aca- formance and of above-median importance to patient wel- demic research. From a sample of 78, the following 29 aca- fare, and (4) ancillary decision areas are of below-median demics eventually participated (for a response rate of 37%): importance to both business performance and patient N. Agrawal, M. Ahearne, R. Bezawada, L. Bolton, D. Bow- welfare. man, R. Chandy, A. Ching, M. Dekimpe, M. Ding, X. Communication management and key opinion leader Dong, J. Eliashberg, P.A. Keller, L. Krishnamurthi, M.F. selection appear to be critical decision areas. Global market Luce, P. Manchanda, M.K. Mantrala, N. Mizik, C. Moor- man, H. Nair, J.C. Prabhu, V. Shankar, C. Sismeiro, A. 3The responses of payers were similar to the responses of Sorescu, E.R. Spangenberg, P. Stern, D. Vakratsas, C. Van providers. The correlation between the average ratings across both den Bulte, S. Venkataraman, and S. Wuyts. For each of the groups of respondents was .90, yielding a similar ranking on previously identified marketing decision areas (Steps 1–3a), importance of decision areas. 8 / Journal of Marketing, July 2009
  6. 6. TABLE 1 Description of Key Decision Areas in Our Survey Decision Area Clarification Provided to Respondents Associations That Respondents Made Therapy Creation Therapy pipeline Includes premarket decisions on portfolio or “Our pipelines of the future will have to optimizations pipeline optimization. contain more targeted therapy-diagnostic combination projects.” (Johnson & Johnson) Innovation alliance Includes decisions regarding alliances “How do we get synergy amongst alliance formation during product development. partners?” (Philips Medical Systems) Therapy positioning Includes premarket decisions on “Instead of being product-minded, we should competitive positioning (including become more solution-minded.” (Philips segmentation, targeting) of the product. Medical Systems) Therapy Launch Global market entry timing Includes decisions regarding optimal market “At present, marketing and pricing is too entry timing, pioneer versus follower country specific. How do we make a good advantages, international launch strategy, trade-off between local and global market and new product market potential entry?” (Johnson & Johnson) forecasting. Key opinion leader Includes the structuring of the company’s “We assured fast product uptake in a socially selection key opinion leader network for maximum retarded area by convincing the members of effectiveness. a local fertility control council exerting high impact on the local doctors.” (Organon) Therapy Promotion Sales force management Includes decisions on optimal sizing and “It is absolutely necessary for sales people to targeting of the sales force, decisions that have the level necessary to build optimize sales call quality, and the optimal relationships with healthcare providers.” use of product samples, including sales (B. Braun) response models. Communication Includes the design of optimal “How to reach patients with the present management communication strategies, including the use regulatory restrictions?” (Roche) of medical publications, DTCA, and Internet-based communications that reach patient and physician disease communities. Stimulating patient Includes the design of optimal patient “There’s a gamut of new technologies, like compliance compliance programs. smart pill bottles, coming available now to support compliance. We should consider them in our product delivery designs.” (Johnson & Johnson) entry timing and sales force management are performance- FIGURE 5 enhancing decision areas. The low relevance of sales force Importance of Decision Areas to Firm management to patient welfare may explain why many Performance and Patient Welfare hospitals and physicians have begun to deny access to phar- maceutical sales representatives. Therapy pipeline opti- Importance to Life Sciences mization and stimulating patient compliance are health- Business Performance enhancing decision areas. Innovation alliance formation and Below Median Above Median therapy positioning decisions are ancillary, probably to ther- •Therapy pipeline •Communication apy pipeline optimization. optimization management Patient Welfare Above Importance to In Step 5 (for more details, see Figure 6), we confront Median •Stimulating patient •Key opinion leader the practical importance of decision areas (taken to be the compliance selection highest of importance in terms of business performance and •Innovation alliance •Global market patient welfare) with the need for academic research, as Below formation entry timing perceived by academics. The average need for further acad- Median •Therapy •Sales force emic research ranges from 5.0 (sales force management) to positioning management 5.8 (stimulating patient compliance) on a scale ranging Marketing of the Life Sciences / 9
  7. 7. FIGURE 6 provide direction for further research. Preliminary generali- Research Agenda zations are already supported by the existing literature, but they may benefit from additional testing through techniques Future Research Need such as meta-analyses. Propositions are exploratory and at Below Median Above Median least partly supported by verbal logic, mathematical proof, or empirical evidence (Stremersch and Tellis 2002). •Communication •Therapy pipeline Importance to Life Sciences Business Performance and management optimization •Sales force •Global market Therapy Creation management entry timing Therapy pipeline optimization. In life sciences firms, Patient Welfare Above •Key opinion therapy pipelines contain all innovation projects along the Median leader selection following temporal stages: During discovery, therapy candi- •Stimulating patient dates are screened for maximum activity on the biological compliance target. Preclinical development and clinical development •Therapy •Innovation entail further development, using in vitro or animal experi- Below positioning alliance ments and human experiments, respectively. Median formation Prior research on therapy pipelines aimed to determine the optimal number and sequencing of innovation projects that a firm’s resource base could support and that served its goal to maximize the number of commercially launched from 1 to 7. In Figure 4, we qualify the cells as follows: (1) innovations (see Blau et al. 2004; Chandy et al. 2006; Ding High-impact research is research that promises to be an and Eliashberg 2002; Loch and Kavadias 2002). This important contribution to academic knowledge and of high, research found that there is an inverted U-shaped relation- immediate, practical relevance to business performance ship between the number of innovation projects undertaken and/or patient welfare; (2) knowledge-enhancing research is and the number of innovations commercially launched. research that promises to be an important contribution to However, scholars in this literature stream did not discern academic knowledge but is not necessarily of immediate, the different temporal stages in the therapy pipeline. practical relevance; (3) practice-enhancing research is Although companies’ ability to convert innovation projects research of high, immediate, practical relevance to business in commercially launched products may suffer from taking performance and/or patient welfare but is not necessarily of on too many projects in development, this may not be the immediate academic importance; and (4) incremental case in discovery, in which more exploration leads to more research is research that is neither of high, immediate, prac- effective knowledge on biological targets, resulting in more tical relevance nor necessarily an important contribution to new therapy opportunities. Thus: academic knowledge. P1a: There is a positive relationship between the number of Although all four types of research are valuable in their innovation discovery projects initiated and the number of own right, the chance of gaining a breakthrough insight is patented inventions of a firm. the highest in the “high-impact” (top-right) quadrant of P1b: There is an inverted U-shaped relationship between the Step 5 in Figure 4 (for more details, see Figure 6). Such number of innovation development projects initiated and decision areas are therapy pipeline optimization, global the number of commercially launched innovations of a market entry timing, key opinion leader selection, and firm. stimulating patient compliance. Further research on innova- The optimal number of innovation development projects tion alliance formation is qualified as knowledge-enhancing a firm should undertake may also be contingent on the type research. The academic knowledge generated can be ancil- of innovation project. Targeted (specific for certain patient lary to decision areas such as therapy pipeline optimization. types) therapy innovation projects require fewer resources Communication and sales force management are practice- in development and feature higher probabilities of ultimate enhancing areas. Research on therapy positioning is likely regulatory approval (Vernon and Hughen 2005). Thus: to be incremental. Academics assessed the need for further research on P2: Innovation development projects on targeted therapies lead therapy positioning as low because they considered this to more commercially launched innovations than the same decision area of low practical relevance, while they assessed number of innovation development projects on nontar- geted therapies. the need for further research on sales force and communica- tion management as low because it is already largely Scholars might also study other types of innovation pro- addressed in prior and ongoing research, even though its jects as contingency factors beyond targeted or nontargeted relevance remains high. projects, such as radical versus incremental projects. Study- ing the therapy pipeline in the context of patent expiry might also be fruitful. Firms may anticipate expiry in multi- Generalizations, Propositions, and ple ways, such as the development of combination drugs, Directions for Further Research more convenient administration and dosage methods, and Drawing on prior research and practice, we formulate pre- reengineered variants with higher effectiveness or less seri- liminary generalizations (G) to evaluate early streams of ous side effects. To develop and test such a contingency research in this area, and we develop propositions (P) that framework, scholars could analyze databases, such as the 10 / Journal of Marketing, July 2009
  8. 8. Pharmaprojects database, the R&D Focus Database that areas of social networks and the balance between internal IMS Health maintains, and the Food and Drug Administra- and external innovation. tion’s (FDA’s) Orange Book, all of which contain detailed Therapy positioning. Therapy positioning refers to pipeline information. As outcome variables, scholars could research-and-development (R&D) decisions on the envi- gather information on the number of approved new patents sioned therapy toward specific indications. The practition- (U.S. Patent and Trademark Office) and new therapies (the ers we surveyed considered therapy positioning an ancillary FDA’s Orange Book). Beyond direct innovation measures, decision area, while academics did not foresee a strong they could also examine the impact of therapy pipeline need for further research. Therefore, we do not derive theo- decisions on sales, profits, or stock market returns. retical generalizations or propositions. Decision makers Innovation alliance formation. As we noted previously, need to balance three key dimensions: (1) the likelihood practitioners consider decisions on innovation alliances that the therapy will be approved for the respective indica- ancillary decisions. At the same time, this decision area has tion, (2) the price they will obtain from the therapy, and (3) provided an ideal and often-used testing ground for theory the market size for the respective indication over time. development on interfirm cooperation. The reason is that If positioned for a mild indication, a therapy may reach the life sciences industry provides possibly the richest docu- a large market, but at relatively low prices and with possible mentation on such alliances (e.g., Recap’s database on denial of approval. Consider Elidel (pimecrolimus), a ther- interfirm agreements) and their outcomes (e.g., patents, new apy for eczema by Novartis. Novartis introduced Elidel for products, profits, sales, share price). a mild to moderate indication of eczema—that is, for first- Similarity between parties in an alliance is probably line use. Competitor Fujisawa introduced a variant of this most often studied. Dissimilarity between partners yields molecule, Prograf (tacrolimus), which was targeted at mod- greater learning opportunity because there is less knowl- erate to severe indications of eczema—that is, for second- edge redundancy, while similarity between partners makes line use. Although both products showed scientific evi- it easier to understand each other and share information. dence, only tacrolimus was endorsed by the U.K. The tension between both arguments has led many government, because the former could not show that it rep- researchers (Cloodt, Hagedoorn, and Van Kranenburg 2006; resented a good value for the money (Gregson et al. 2005) Prabhu, Chandy, and Ellis 2005; Wuyts et al. 2005) to find a for the moderate indication. It was subsequently endorsed curvilinear relationship between knowledge similarity after resubmission, but then also for the severe indication. If between alliance partners and the innovative outcome that positioned for a severe indication, a therapy may have a the alliance yields. This leads us to the following prelimi- higher likelihood of being approved at a high price, but it nary generalization: may pertain to a relatively small market. For example, Sym- G1: There is an inverted U-shaped relationship between bicort by AstraZeneca was first approved for severe asthma, knowledge similarity between alliance partners and the after which AstraZeneca enlarged the market for Symbicort number of new therapies the alliance yields. to chronic obstructive pulmonary disease (COPD). Because there are many possible indications, all with Scholars have also studied the differential effect of different levels of uncertainty for the respective therapy to alliances on radical versus incremental innovation (Wuyts, be approved and varying price expectations, further Dutta, and Stremersch 2004). For radical innovation, it is research should aim to specify decision support models that instrumental that alliance partners repeatedly cooperate to simulate market size using patient flow dynamics (first use, stimulate knowledge transfer through the development of reuse, switching from competition) at various price expecta- relationship-specific heuristics and the sharing of mental tions and approval likelihoods. models, among other things (Madhaven and Grover 1998; Uzzi 1997). Genentech and Roche provide a successful Therapy Launch example of such repeated collaboration. For incremental Global market entry timing. Previous research has innovation, large portfolios may be beneficial because of shown that pioneers do not have long-lasting market advan- scale effects in development (Ahuja 2000; Wuyts, Dutta, tages (Golder and Tellis 1993; Shankar, Carpenter, and and Stremersch 2004). We offer the following preliminary Krishnamurthi 1999). In the life sciences industry, an generalizations: important moderator of the market return on a pioneering G2: As the level of repeated partnering in a firm’s innovation therapy may be whether it pertains to generic or branded alliances portfolio increases, its radical innovation output therapies. In the case of branded therapies, pioneers are the increases. first entrants in a therapeutic category (e.g., Mevacor [1987] G3: As the number of alliance partners in a firm’s innovation for statins). In the case of generic therapies, pioneers are the alliances portfolio increases, its incremental innovation first generic available for a specific therapy (e.g., the first output increases. generic Simvastatin, the statin introduced by Merck as Further research on interfirm cooperation will likely Zocor). continue to use the life sciences industry as a testing ground There are many cases of late branded entrants that took for theory development, with continued use of databases over pioneers through increased effectiveness, higher con- (e.g., Pharmaprojects, Recap), newspapers and magazines, venience, or weaker side effects. Examples include Zocor and surveys. Novel breakthroughs are likely to be in the and Lipitor in statins (increased effectiveness), Symbicort Marketing of the Life Sciences / 11
  9. 9. in asthma/COPD (higher convenience), and Xyzal in anti- referencing country late relative to the set of referent histamines (weaker side effects). countries. Contrary to common wisdom in other industries and To test this proposition, regulatory data can be gathered contrary to branded variants in life sciences, generics may from Urch Publishing and the Organisation for Economic yield strong pioneering advantages. The first generic variant Co-operation and Development, both of which track inter- for a specific therapy (“the pioneer”) may attract and main- national regulatory health systems (including identification tain a disproportionately large market share. The reasons for of the set of referent countries for each referencing coun- this are multifold. It takes substantial effort from physicians try), and integrated with IMS Health data on international and pharmacists to explain bioequivalence between differ- prices and introduction dates. It is also possible to include ent variants (Gupta, Yu, and Guha 2006). At the same time, firm effects (firms may have differential policies, depending only the pioneering generic therapy benefits from the large on their home market or size) or therapy effects (payers price differential with the alternative (the branded variant). across countries may have differential price and market Generics that subsequently enter do not show as large of a access policies for different therapy classes). In addition, price differential anymore, and when they do, the generic diffusion studies can deliver valuable and complementary pioneer may readily match the lower price, with market insights into launch decisions. Examples of such valuable shares remaining stable (Hollis 2002). The first generic inquiries that may inform launch decisions are improved entrant also typically makes supranormal profits before the models of physician learning and international diffusion entry of a second generic because it provides the only studies. (cheap) alternative for an expensive branded variant (Gupta, Key opinion leader selection. Life sciences firms often Yu, and Guha 2006). Thus: stimulate reviews of their therapy by select key opinion P3: Pioneering yields market share advantages for generic leaders because such leaders may serve as product champi- therapies. ons to their peers. The effect of such opinion leaders on other physicians’ prescriptions can be large when consider- The life sciences industry lends itself well to the exami- able uncertainty exists (e.g., a change in the regulation or nation of order-of-entry effects because entry is well docu- the introduction of a new therapy) or when physicians mented (e.g., with the FDA Drugs@FDA for the United experience normative pressures (e.g., there is strong formu- States). These entry dates can be complemented with IMS lary adherence) (Coleman, Katz, and Menzel 1966; Iyengar, Health’s dollar sales estimates. Moderators that could be Valente, and Van den Bulte 2008). For example, Nair, Man- considered in such research effort are clinical profile of the chanda, and Bhatia (2006) show that the effect of opinion treatment (e.g., from National Institute for Health and Clin- leader prescriptions is 100 times larger than the detailing ical Excellence or published meta-analyses in scientific effect on regular physicians after the market underwent a journals) and marketing support (commonly available from change in National Institutes of Health guidelines. firms such as IMS Health, Kluwer, or Verispan). However, we cannot take the positive role of opinion Firms typically do not launch a new treatment simulta- leaders for granted (e.g., Van den Bulte and Lilien 2001), neously across the globe. Rather, they use specific launch and further research should inventory the contingencies that sequences, often driven by a country’s regulatory system, affect the role of opinion leaders. In such research, it is economic wealth, and size (Danzon, Wang, and Wang 2005; worthwhile to consider two types of key opinion leaders Kyle 2007; Verniers, Stremersch, and Croux 2008). Differ- with potentially differential effectiveness: clinical and mar- ential launch timing across countries has been shown not to ket leaders. Clinical leaders are experts within the respec- affect unit sales (Stremersch and Lemmens 2009), though it tive disease and therapy class with a strong reputation, as has been shown to affect launch price (Verniers, Strem- evidenced by their publication records in top-ranked medi- ersch, and Croux 2008). In the life sciences industry, launch cal journals. They are typically involved in premarket prod- price is rarely a market price; rather, it is often an agreed-on uct testing and have cooperated with the firm to reduce clin- price between the supplier and the government or insurance ical uncertainty of the therapy. In contrast, market leaders firm, which acts as a (co)payer. In such negotiations, entry are tightly connected to the local patient and physician timing may be used by both the payer and the firm as an communities. They are typically general practitioners with instrument to affect the agreed-on price. large practices who gain recognition by the satisfaction and An important contingency factor that has not received loyalty of their patients. They deliver key experiential mes- any attention is the role of cross-country influence in launch sages on the therapy to their peers. sequencing. Often, this cross-country influence is institu- For example, as a contingency factor, consider whether tionalized because payers will use the price of a therapy in a uncertainty manifests in terms of effectiveness or side defined set of other countries (the “referent” countries), if effects of a life sciences therapy. The impact of uncertainty available, as a reference price for the negotiations in their on effectiveness can be reduced through quantitative assess- own country (the “referencing” country). Such regulation ments without much detail on specific physician practices incentivizes companies to avoid spillover effects (Hunter (i.e., large scale, study based). Conversely, the impact of 2005). Thus: side effects information is more qualitative and dependent P4: Firms that launch a new therapy in a referencing country on the specific composition of a practice (i.e., case based). early relative to the set of referent countries obtain a Because clinical leaders support quantitative assessments of higher price than firms that launch a new therapy in a effectiveness and market leaders share case detail on side 12 / Journal of Marketing, July 2009
  10. 10. effects from practices similar to other physicians, we pro- through meta-analysis. Kremer and colleagues (2008) offer pose the following: a first attempt at such generalization, but they provide only P5a: The greater the uncertainty on therapy effectiveness, the a limited number of significant moderators and omit drugs’ higher is the impact of clinical leaders, compared with clinical profile. A second opportunity lies in the develop- market leaders, on other physicians’ prescription ment of models that allow for policy experiments. Although behavior. we have reliable estimates of the mean effect of detailing, P5b: The greater the uncertainty on therapy side effects, the all models are estimated on data that show relatively little higher is the impact of market leaders, compared with policy variance, which inhibits any extrapolation to policy clinical leaders, on other physicians’ prescription shifts in detailing, either by the manufacturer (many firms behavior. are now considering drastically reducing their detailing Another contingency factor to consider is the physi- efforts) or by the regulator (several European countries are cian’s institutional setting. Hospitals have formal ethical considering curtailing detailing). The third opportunity lies guidelines (Gallego, Taylor, and Brien 2007) to which an in developing physician targeting models based on volume, individual practitioner must adhere, which increases the physician responsiveness to detailing, and competitive return on legitimacy compared with general practitioners. detailing patterns (for working papers in this tradition, see Clinical leaders enhance legitimacy to a greater degree than Dong, Manchanda, and Chintagunta 2008; Kappe, Strem- market leaders, which fits with their high impact on formu- ersch, and Venkataraman 2008). lary decisions. At the same time, market leaders achieve By far, the most room for novel research seems to be in their influence through similarity of practice. In general, the the content of detailing visits. Past and, for most companies, practice of a market leader is more similar to a general prac- present detailing calls present only favorable information titioner practice than to a hospital-based practice. Thus: using positively biased information sets—that is, only stud- P6a: Clinical leaders have a greater impact on hospital-based ies favorable to the brand are presented, or side effects are physicians’ prescription behavior than market leaders. omitted. This sales model seems increasingly dysfunctional, P6b: Market leaders have a greater impact on general practi- with hospitals and physicians reacting adversely to detail- tioners’ prescription behavior than clinical leaders. ing, even rejecting it altogether, which is symptomatic for the conflicting logics between life sciences firms and the Researching these propositions can include surveying all rest of the health care value chain (Singh, Jayanti, and Gan- physicians of a certain area to inventory their opinion lead- non 2008). ers, including Likert-type scales on each of the identified leaders regarding the extent to which they are clinical and/ We propose that life sciences firms can gain substantial or market leaders. returns from communicating unfavorable information in their detailing calls, for two main reasons (Leffler 1981). Therapy Promotion First, in view of their ethical, gatekeeping function to patients, physicians prefer more complete information, even Sales force management. A first decision area in therapy if unfavorable, over ambiguity. Second, communicating promotion is sales force management. Visits by the sales unfavorable information may enhance the legitimacy of the force of life sciences firms to physicians are referred to as sales representative and the firm (Singh, Jayanti, and Gan- “detailing.” Much academic research has emerged on the non 2008). In turn, this enhanced legitimacy may deliver effectiveness (return on investment) of detailing (Azoulay sustained physician access and increased trust in the firm’s 2002; Berndt et al. 1995; Leeflang, Wieringa, and Wittink messages. Both will strengthen long-term return on invest- 2004; Manchanda and Chintagunta 2004; Manchanda, ment from detailing. Thus: Dong, and Chintagunta 2004; Manchanda and Honka 2005; Manchanda, Rossi, and Chintagunta 2004; Mantrala, Sinha, P7a: Communication of complete (including both favorable and Zoltners 1994; Mizik and Jacobson 2004; Narayanan, and unfavorable) therapy information in sales calls may affect more positively the firm’s long-term return on Desiraju, and Chintagunta 2004; Narayanan, Manchanda, investment from detailing than just communicating favor- and Chintagunta 2005; Parsons and Vanden Abeele 1981; able therapy information. Venkataraman and Stremersch 2007). We derive the follow- P7b: The effect postulated in P7a is larger in the case of thera- ing generalization from this literature: pies for life-threatening illnesses than in the case of non- G4: The mean effect of detailing on brand prescriptions is (a) life-threatening illnesses. positive but (b) small. P7c: The relationship postulated in P7a is larger in hospital environments than in outpatient environments. “Mean” in G4 refers to the mean across brands and physicians. Prior literature has shown high physician- and In P7b and P7c, we conjecture that the effect of disclo- drug-level heterogeneity, including some brands and physi- sure of complete information may be contingent on whether cians showing a negative return on detailing (Leeflang, the disease is life threatening and on the physician’s institu- Wieringa, and Wittink 2004), and has investigated specific tional setting. Agents confronted with a decision of high contingency factors, such as drug characteristics (e.g., side importance attach a greater value to information (Celsi and effects, effectiveness [Venkataraman and Stremersch 2007], Olson 1988). Therefore, physicians’ preference for more and physician traits [e.g., Gönül et al. 2001]). complete information, even if unfavorable, over ambiguity There is room for further study. A first opportunity is to will be higher in the case of life-threatening diseases than in increase the reliability of this preliminary generalization the case of non-life-threatening diseases. For example, there Marketing of the Life Sciences / 13
  11. 11. is more value in reducing ambiguity about the side effects The process involves DTCA triggering a patient’s request of chemotherapy, even if it concerns an increased probabil- for a therapy at the physician’s office, which the physician ity of pneumonia versus an increased probability of insom- can accommodate or not. The role of patient requests and nia caused by antihistamines. As we argued previously, the factors that affect the degree to which the physician practitioners in hospitals may have a higher return on legiti- accommodates them are not addressed in the academic lit- macy than general practitioners in the outpatient environ- erature at this point (for an exception, see Venkataraman ment. Revealing unfavorable information together with and Stremersch 2007). Developing such a process view may favorable information enhances a sales representative’s yield relevant insights for managers (e.g., on audience tar- legitimacy. geting). As an example, consider audience gender. Prior There are several possible tests of P7a–P7c. IMS research has shown that women are more concerned about Health’s U.S. panel data include data on which attributes of their health (Verbrugge 1985) and interact more assertively a drug were discussed in a sales call. Adding information on in health care settings (Kaplan et al. 1995) than men and how drugs in a category compare on each of these attributes that physicians are more empathic to female than male may reveal whether favorable rather than unfavorable attrib- patients (Hooper et al. 1982). Consequently, DTCA may utes were discussed. Several individual firms have records more easily trigger requests among women, and female on which studies were covered in sales calls, which can requests may be more easily accommodated by physicians reveal whether unfavorable studies were covered. The than male requests. Thus: return on investment from long-term detailing can be P9: The effect of DTCA on brand-level demand is higher regressed on both types of data to test the propositions. among female viewers than among male viewers. Longitudinal experiments can also be conducted to test the propositions, in which physicians or medical school stu- Many other boundary conditions can be formulated on dents are detailed within a simulation. aspects such as the type of disease and patient–physician Communication management. Although communication relationships, all of which may inform ad content and target efforts of life sciences firms may target both consumers and audience decisions of firms. Data availability on DTCA is physicians, the budgets dedicated to the former group are high. Secondary data sources include ACNielsen and TNS more than ten times larger than the budgets dedicated to the Media. Both data types can be connected with aggregate- latter (Kremer et al. 2008), and from the interviews we held level sales data (e.g., from IMS Health) or panel-level data with practitioners, direct-to-consumer advertising (DTCA) (e.g., from IMS Health or Verispan). In addition, experi- is also the most challenging. The academic literature on mental studies may have high potential because they may DTCA (Berndt et al. 1995; Bowman, Heilman, and reveal underlying psychological processes. Seetharaman 2004; Iizuka and Jin 2005; Narayanan, Desir- Stimulating patient compliance. As our survey results aju, and Chintagunta 2004; Wosinka 2005) mostly exam- show, life sciences firms undervalue the importance of ines overall effectiveness of DTCA and yields the following stimulating patient compliance, from both a patient welfare preliminary generalization: and a profit perspective. Our interviews with managers G5: DTCA has a positive effect on (a) the number of patients revealed that they consider their impact on patient compli- seeing a physician for the respective disease for which a ance minimal, though they believe that it is mostly affected therapy is advertised and (b) total category-level demand by the provider in his or her interaction with the patient. In in the category of the therapy that is advertised. contrast, our survey among providers and payers shows that Further research on other potential outcomes of DTCA, they believe that life sciences firms’ efforts to stimulate such as its effect on brand choice, would be fruitful because patient compliance may have important effects on patient it is fraught with debate. Iizuka and Jin (2005) and Wosin- welfare. ska (2005) find that DTCA does not affect drug brand Despite its high relevance, academic research has not choice, while Berndt and colleagues (1995) and Narayanan, studied the role of the life sciences firm in patient compli- Desiraju, and Chintagunta (2004) find a positive effect of ance in depth. Prior research has found that provider exper- DTCA on drug brand choice. Such research could involve tise (Dellande, Gilly, and Graham 2004), the attitudinal meta-analysis or the analysis of contingency frameworks. homophily between patient and provider (Dellande, Gilly, An example of a contingency factor is the degree to and Graham 2004), the frequency of contact between which DTCA messages include favorable and unfavorable patient and provider (Bowman, Heilman, and Seetharaman information. Although unfavorable information (e.g., infor- 2004), reminder messages (Becker and Rosenstock 1984; mation on serious side effects of therapy) may arouse con- Rosenstock 1985), and the burden of therapy (Kahn et al. sumers (Moorman 1990), it may also yield negative emo- 1997; Kahn and Luce 2003, 2006) all affect patient compli- tions that hinder information processing (Agrawal, Menon, ance. The only research that exists on how life sciences and Aaker 2007; Keller 1999). Thus: firms may affect patient compliance examines warning labels. For example, Ferguson, Discenza, and Miller (1987) P8: The effect of DTCA on brand-level demand is higher the find that warning labels that include information on the con- more the advertisement depicts favorable, rather than unfa- sequences of poor compliance are effective. vorable, therapy information. Today, life sciences firms sporadically institute new At the same time, no study develops a process view on types of compliance programs, the effectiveness of which the effects of DTCA on the demand for a specific therapy. remains void of academic scrutiny. We categorize such 14 / Journal of Marketing, July 2009
  12. 12. compliance programs in technology-enabled and customer cute. Relatively few firms have instituted a compliance pro- relationship management– (CRM-) enabled programs. gram, patient-level data are difficult to obtain, and patients Such CRM-enabled programs typically used in practice self-select into a program (which may cause sample selec- are direct mail or call campaigns. Pfizer has developed a tion issues). One method may be to conduct a conjoint “Staying on Track” CRM program for its statin drug Lipitor experiment using physicians as informants on patient (Arnold 2004). Such programs monitor patients’ disease behavior. In such a conjoint experiment, program design and refill status, motivate patients to stay on therapy regi- factors could be manipulated, and their effect on patient men, and provide patients with therapy risk–related infor- compliance (as informed by the physician) could be esti- mation tailored to the stage of therapy with their specific mated. Test–retest reliability and comparison with actual symptoms and motivations (Hopfield, Linden, and Tevelow cases could further support the validity of such an approach. 2006). A more demanding alternative is cooperation with a life sci- Technology-enabled programs include a technological ences firm that is open to a field experiment, including a device to remind patients to take their pills. Bang & Olufsen longitudinal survey to the compliance program participants. Medicon’s blister card–based “The Helping Hand” gives a More generally, the field of compliance would benefit from visual indication of therapy compliance through red or extensive survey research across patient–physician relation- green LEDs (light-emitting diodes) as soon as a blister is ships because compliance is intrinsically embedded in this inserted into the device. Another example is “SIMPill,” a relationship. smart pill bottle that reminds patients through SMS (short message service) that they have forgotten to take their medicine. Conclusion Both types of programs connect to different behavioral Some industries require industry-specific knowledge devel- rationales for poor compliance: a patient’s belief in self- opment because they have unique characteristics that yield efficacy and mindfulness. A patient’s belief in self-efficacy specific challenges for marketers. In this research, we aim refers to the belief of being capable of carrying through the to advocate such knowledge development for life sciences prescribed therapy, and mindfulness refers to awareness of marketing. This article has implications for both life sci- actions to be taken (Keller 2006). Customer relationship ences marketing practice and academia. management–enabled programs promote a patient’s belief in self-efficacy, and technology-enabled programs promote Life Sciences Marketing Practice mindfulness. The potential of CRM programs to promote Defining life sciences—to our surprise, no useful definition mindfulness is limited because the reminder frequency existed in the literature—proved to be challenging but, at within a CRM program is unable to match therapy fre- the same time, eye-opening. Discerning clear boundaries quency (one or multiple therapy occurrences a day). Con- to the domain enabled us to demarcate boundary areas, versely, technology programs cannot offer the patient inter- such as cosmetics-, device-, and food-based therapies, while personal coaching (e.g., Bandura 1982) to stay on therapy. integrating pharmaceuticals, biotechnology, and medical Given their differential behavioral rationales, the effec- devices. With an increasing patient-centered view on health tiveness of both programs is likely to depend on factors and personalization in medicine (see Camacho, Landsman, such as disease complexity and symptom salience. First, the and Stremersch 2009), life sciences companies that develop more complex a disease, the higher is the likelihood that an integrated view on patients’ health—rather than consid- poor compliance is driven by disbelief in self-efficacy. As ering themselves a pharmaceutical, biotech, or medical such, CRM-enabled programs can effectively reduce such devices company—will be best equipped for the future. uncertainty, but technology-enabled programs cannot. Sec- Such integration is challenging. For example, with its his- ond, the less salient the symptoms of a disease (e.g., the flu torical structure along product divisions, Philips is chal- is a disease with salient symptoms and high cholesterol is a lenged to develop an integrated view on opportunities in disease with low salience), the more compliance will be dri- personalized medicine because such opportunities often ven by mindfulness. When salience is low, technology- stretch across the firm’s personal care, medical devices, and enabled programs will be more effective in stimulating consumer electronics divisions. Another related challenge compliance than CRM-enabled programs. for life sciences firms is to enhance their typical curative P10a: As disease complexity increases, CRM-enabled compli- offering to include prevention, patient monitoring, and ance programs increase in effectiveness to stimulate patient wellness. For example, firms with a diabetes fran- patient compliance, compared with technology-enabled chise have moved historically from providing therapies compliance programs. (e.g., glucose) to providing monitoring devices (e.g., blood P10b: As symptom salience decreases, technology-enabled monitoring personal digital assistants) and, more recently, compliance programs increase in effectiveness to stimu- have faced the challenge to move into comprehensive care, late patient compliance, compared with CRM-enabled which extends toward patient wellness (e.g., prevention and compliance programs. awareness on probable consequences of diabetes, such as Further research might consider a broader array of con- blindness and wound care). tingency factors than those developed in these propositions. We also found substantial divergence in the evaluation Such research promises to be impactful for both academia of the importance of certain decision areas between life sci- and practice, but at the same time, it is challenging to exe- ences marketers and health care payers and providers or, Marketing of the Life Sciences / 15
  13. 13. alternatively worded, between profits and patient welfare. Life Sciences Marketing Academia While marketing managers emphasize the profit implica- This article shows that a bright future for this nascent field tions of sales force management, health care payers and within marketing is imminent (Stremersch 2008). Among providers emphasize patient welfare implications of life sci- the many reasons are that (1) this context presents unique ences firms’ actions to stimulate patient compliance. Such and often challenging problems, (2) for which high-quality divergence gives rise to potential conflict in the health care data are available and (3) that have an impact that tran- value chain. As Singh, Jayanti, and Gannon (2008) argue, scends the problems typically investigated by marketing there is a strong need for the life sciences industry to escape scholars. On the supply side, universities are likely to invest such conflicting logic in the short run and increasingly considerable research funds in life sciences marketing as a adopt a partnership model, which could lead to enhanced research program that transcends various schools (business, legitimacy in the long run for life sciences firms. medicine, economics), creates vast societal influence Although further testing is needed, the generalizations (regarding public policy, firms, the press, and the public at large), and does not have a pure for-profit nature (compared and propositions we derive may provoke some firms to alter with other business school research). their marketing approach. For example, our propositions on We have demarcated the boundaries of this new domain; opinion leaders encourage a dual-layer strategy of firms, categorized the main decisions of life sciences marketers; such that at launch, they may rely on clinical leaders and provided generalizations, propositions, and research (mostly through research cooperation), and as experience directions to stimulate and steer research in this nascent with the therapy’s side effects grows, market leaders may field. As with the advent of any new field, there are as many be actively involved (e.g., through specialized detailing). cynics who claim that nothing is fundamentally different Although some firms already have such a dual-layer strat- about life sciences marketing and that conventional insights egy, this is not (yet) common practice among life sciences can easily be extended to such markets without adaptation firms. Another example is the differentiation between as there are enthusiasts who embrace these markets as being CRM-enabled and technology-enabled compliance pro- as different as the moon is from the earth. The former group grams. As the quotation from a Johnson & Johnson mar- often finds a dominant argument in the data-driven nature of keter in Table 1 shows, most life sciences firms are just the original contributions to life sciences marketing. How- beginning to consider compliance programs. Our proposi- ever, in itself, this is not a reason an industry cannot be guided by different principles, thus leading to unique chal- tions on compliance should encourage them to analyze the lenges. The same applies to the argument that some chal- underlying characteristics of the disease and the patients to lenges are also present in other industries, in a slightly mod- steer them to a suitable type of program. The review of ified form. In the dialectic tradition, we try to build the case prior research and the generalizations we derive from it may for the enthusiasts. Early interest at conferences, in jour- also inform practice. The positive expectations of many nals, and in MBA program offices seems to favor the enthu- firms regarding the effect of DTCA on brand sales (note the siasts. The least we have hopefully achieved with this arti- high spending on DTCA among life sciences firms) are cle is to define the playing field on which cynics and unrealistic in light of prior research findings. enthusiasts will interact, both in research and in teaching. 16 / Journal of Marketing, July 2009
  14. 14. APPENDIX A Overview of Life Sciences Marketing Literature Decision Conceptual Method Authors Areas Main Findings Framework Used Empirical Base Therapy Creation Sorescu, IAF Pharmaceutical firms with large product capital assets are better Resource- Ordinary least 238 acquisitions in 7 countries Chandy, and at selecting targets with innovation potential and deploying this based view of squares (OLS) (1992–2002) Prabhu (2007) innovation potential. The performance consequences of this the firm regression model superiority in the selection and deployment of target firms manifests itself in long-term financial rewards to the acquiring firm. Chandy et al. TPO Firms that (1) focus on a moderate number of ideas in areas of Problem Discrete choice 322 drug ideas by 38 firms (2006) importance and in which they have expertise and (2) deliberate solving model (1980–1985) for a moderate length of time on promising ideas have the highest conversion ability. Prabhu, Chandy, IAF Innovation outcomes of acquisitions are driven by the Knowledge- Distributed-lag 35 pharmaceutical firms that and Ellis preacquisition knowledge of the acquirer and its similarity with the based view of model acquired 157 targets (2005) target’s knowledge. the firm (1988–1997) Moorman, Du, TP Firms can make strategic use of regulation by thinking about Economics of Random effects Universal Product Codes at and Mela costs and benefits of regulation relative to competition. The information probit on the firm and brand levels for (2005) introduction of the Nutrition Label and Education Act (NLEA) longitudinal quasi- 109 categories from 2186 (Public Law 101-535) led to (1) an increase in small-share firm experimental data firms (Supermarket Review exits and (2) a greater increase in distribution for large-share data) and for 265 categories firms. No concurrent increase in price by large-share firms from 29,374 firms (Infoscan) following the NLEA was observed. per year (1991, 1993, and 1995) Wuyts, Dutta, IAF Alliance portfolio technological diversity has a positive affect on Knowledge- Negative binomial 991 R&D agreements and incremental and radical innovation output but has a negative based view of and OLS (1985–1998) Stremersch direct effect on profitability. Repeated partnering has a positive the firm regression model (2004) effect on radical innovation and a curvilinear effect on profitability. Alliance portfolio size has a positive effect on incremental Marketing of the Life Sciences / 17 innovation output and firm profitability. Sorescu, TPO Firms that provide higher per-product levels of marketing and Risk- and Random effects 255 breakthroughs introduced Chandy, and technology support obtain much greater financial rewards from resource- Poisson model by 66 publicly traded firms Prabhu (2003) their radical innovations than other firms. Firms that have greater based view of (1991–2000) depth and breadth in their product portfolio also gain more from the firm their radical innovations.