BREAST CANCER IS ONE of the most commonly diagnosed cancers and a leading cause of death for women worldwide. Each year, more than 2 million new cases are diagnosed and more than 650,000 women die of breast cancer (Sung et al. 2021). Up until the 1970s, breast cancer could solely be treated with toxic and invasive remedies, i.e., surgery, radiation, and chemotherapy, in regimens that varied little from woman to woman. In the 1970s, hormonal therapies began to be developed to help limit the growth and spread of breast cancer cells. With discovery of the oncogene, a mutated gene that could lead to cancer, and advances of molecular engineering in the 1980s, hopes of patients and industry began to grow that a widely working, nontoxic, and noninvasive treatment for breast cancer could be developed. After twenty-five years of developments, for a limited percentage of breast cancer patients, six of such life-prolonging therapeutics had received regulatory approval, amounting to global sales of more than US$ 6.3 billion (Syed 2015).1
The search for such breakthrough therapeutics for breast cancer, like other quests for drug discovery and development, took many twists and turns. The many human and nonhuman actors who contributed to the development of a market for innovative breast cancer therapeutics—from biotechnology companies and patients to investors and molecules—were facing an unknown future that was nevertheless fraught with hopes and expectations. Which research strategy should biotechs follow when biochemical mechanisms were unknown? On what grounds could they secure funding for their research expenditures? And would the novel product pass through clinical trials and obtain regulatory approval? At the same time, competition between biotechs was intense as each sought to find a successful treatment while also striving to hit a financial jackpot. This search can be seen as a window onto not only the development of cancer therapeutics and the biotech industry at a pivotal time, but also more generally onto how innovations emerge and are transformed amid a nascent market of competitors.
The book traces the evolution of “innovative breast cancer therapeutics,” beginning from the late 1980s until 2010, to better understand how market emergence and transformation occur in dynamic conditions of innovation. At the center of drug discovery, it shows, lie complex innovation processes in which scientists, biotechnology companies, and their funders and investors need to make sense of ambiguous findings and grapple with numerous and unpredictable interdependencies over many years of product development. To do so, they use stories, especially public stories of the future. Applying a combination of qualitative and large-scale text analyses to thousands of press statements, media reports, scientific reports, and financial and industry analyses related to innovative breast cancer therapeutics, Making Sense: Markets from Stories in New Breast Cancer Therapeutics identifies stories as the central mechanism for the emergence of markets and develops a novel methodology for theorizing emergent processes in the economy.
How actors make decisions in situations of uncertainty is central for the research field of economic sociology. In numerous studies it has been convincingly shown that social relations, institutional frameworks, as well as practices contribute to reduce uncertainty in decision-making processes. Actors’ social and institutional embeddedness structure their expectations and actions in market contexts, thus enabling coordination. Typically, such analyses have dealt with existing markets, or they have looked at how markets emerged from an ex post perspective.
Here the inquiry is into a market—the innovative breast cancer therapeutics market—during its emergence and from a perspective as it is emerging. My argument is that in order to understand how actions are coordinated in situations when it is unclear who participates and who will profit and thus to understand market emergence, accounts of structural mechanisms are not sufficient. Instead, I argue for a relational and processual perspective on markets as networks of sociocognitive and sociomaterial actors. Such a theoretic model allows a focus on the narrative and evaluative dimensions in emergent processes. The result is a cultural analysis of market emergence that shows its crucial elements and mechanisms in three phases over time.
This book posits that actors leverage culture to grapple with ambiguities of newness in the emergence of markets. A diversity of actors, such as companies, industry analysts, journalists, and scientists, tell stories in which they evaluate and interpret the present, the past, and a projective future. These stories then serve as cues for other market actors. Therefore, this book also suggests that meaning-making is crucial for market emergence.
An inquiry into the stories of potential members of a new market allows for the tracing of individual and collective interpretations and meaning-making. In turn, collaboratively these actors’ stories participate in category construction on what the new market is about. Such an inquiry sheds light onto both successes and failures in category construction. The collaborative process of category construction will not be friction-free; indeed, rivalries and dissonances are conducive to entrepreneurship (Stark 2009) and, as a by-product, to category construction. Moreover, no individual firm is able to claim to have a worthy product or to be a worthy market participant without receiving recognition by others. Similarly, no product can claim to be a worthy market participant unless tested and proven so over time and unless other market participants recognize its worth. In the ambiguous setting of a nascent market, worth gets negotiated collaboratively in struggles and agreements.2
Through its empirical analyses of economic life from a cultural perspective, the book delineates how the interrelations between multiple network domains of science, biotech companies, and financial and industry analysts collaboratively come to form a market. The analyses build on the theoretical insight that networks are composed of “culturally constituted processes of communicative interactions” (Mische 2003) across heterogeneous actors. Empirically this translates into tracing stories. The stories selected as data for analyses originate from public statements of companies that claim to be involved in breast cancer therapy research, as well as from financial analysts, industry analysts, journalists, and the scientific community as published in specialized media outlets. This selection of data thus purposefully allows for a look at the entangled developments in breast cancer therapy research from different though interrelated perspectives at the time they were happening. Via a combination of qualitative text analysis and novel computational methods of large-scale text analyses, the book captures the dynamics of meaning-making processes over twenty-two years in what is now understood as a period of medical transformation toward targeted or so-called personalized medicine.3
One set of stories examines the state of the art of scientific findings. They provide answers to the questions of what topics research on breast cancer therapeutics has focused on and how that research has evolved. These stories offer many facts, but they also address hopes and expectations. Other sets of stories furnish insights into how actors evaluate their situation and context, and how they act accordingly. Narrated stories establish interpretations that serve as stabilizing forces for actors’ identities. At the same time, actors are in narrative competition with one another about which story counts, how a situation should be interpreted, and what social formation they are part of. Dominant interpretations may come to be confirmed or contested. Moreover, studied over time, such sets of stories also show how interpretations can settle into categories, understood as narrative constructions with real material consequences. To be sure, the perspective taken here does not trace individual stories of individual actors, but rather understands stories and their observations as relational ties of a larger network of cognitive interdependence. As actors tell stories about an uncertain present and a projective future, they share “socially structured imaginaries” about what counts as worthy (Fourcade 2011) and provide interpretations of themselves that are also for others.
Two central findings result from the analyses of these sets of stories and their workings. First, the study finds that economic actors tell stories of the future and thereby create a market of expectations. Prior to the existence of any innovative breast cancer product, biotechs are trading stories on expectations, projections, and imaginings about what the future might hold. These stories provide cognitive guidance for the involved actors amid an ambiguous setting. Moreover, journalists and financial analysts similarly voice their bets about an uncertain future; they too face ambiguities of newness and need to cope with the many unknown unknowns related to how to interpret and evaluate biotechs’ research reports. Hooking on to stories of the future, filled with expectations, promises, and hopes, helps all involved to cope with uncertainties of the situation. Together and with their entangled stories, these actors are creating a market of expectations.
Second, the study finds that the stories temporarily settle into categories that in turn have real-world consequences: they induce changes in the market structure. Biotechs’ research strategies, their funding, and their positioning in the emerging market are influenced by the stories actors tell—and by the observation of their competitors. The study finds that competing actors are involved in collaborative meaning-making processes on how the new market can be categorized. The construction of a new category results from negotiations of newness and from dealing with ambiguities. It helps to, albeit temporarily, stabilize the market. New categories develop as constructs in which to store temporary associations as well as temporary imaginations of what constitutes actors worthy to connect to that category. In turn, categories provide a mechanism for inducing market structure.
These insights go beyond a simple “stories matter” message and instead provide support for the argument that narrative constructions play a fundamental role in the economy (Beckert 2016, 2021). The analyses show that decision-making in situations of great uncertainty, when it is unclear what the outcome will be, and who is competing with whom about what, is guided by stories of the future that the involved actors tell to direct and to justify their actions. Stories in this sense are the cognitive connections between a diversity of actors, which include organizations, people, tools, tests, and also molecules. Stories are the primary devices for contextual, situational meaning-making in markets and are thus microfoundations of decision-making. They are not “only talk.” If they can inspire a belief in a specific future, they can motivate, orientate, and coordinate action. Moreover, stories are also instrumental in establishing categories of what the “new” is about. The analyses thus point to two crucial elements—expectations and categories—that rely on the existence of stories and that are necessary for the emergence of markets.
The study finds three phases in the emergence of this market. In the first phase, it is unclear what the products will be and who will participate. The phase begins in the late 1980s, when the “first biotech era” ends with the centerpiece biotech drug called interferon failing in cancer trials (Kaplan/Murray 2010; Pieters 1998, 2005). At this time, scientific advances suggested that a molecular, noninvasive treatment of breast cancer might be possible. Nevertheless, uncertainty about which research strategy to follow and which molecule to invest resources in characterize the field. The first phase ends when regulatory agencies approve the first product for breast cancer therapy based on molecular engineering in 1998.
A second phase begins after that first product approval. With the approval, market participants have a first product that can be used for comparison. Yet ambiguity about the products’ mechanism and alternative research strategies persists. This is a phase of discursive struggles and contestations. Processes of categorization first move from a description that the market is about “innovatives” to identifying the market to be about “targeted therapies.” This category, increasingly mentioned in self-descriptions and analyses, is able to stick with the heterogeneous actors constituting the market in the early 2000s. At that time, it has become scientifically evident that no blockbuster, no cure for all would be possible to develop for breast cancer. Indeed, the future of cancer research would be targeted treatments moving toward “personalized medicine” (Langreth/Waldholz 1999). The empirical analyses show how the new category targeted therapies stuck.
Once the category was taken for granted and institutionalized after much contestation, and only after the approved product had been collectively labeled to exemplify a new category of therapies, did the market transpose and diversify. This is when the third phase begins, in which more products get approved. Clinically, breast cancer is categorized into three basic therapeutic groups depending on hormonal and other receptors. Beginning with the early 2010, however, research on the molecular structure of breast cancer pointed to a more complex picture: breast cancer can be classified into four genetically distinct types, which with their combinatorial subtypes yield at least forty genetic variations to which targeted therapies may be developed (Cancer Genome Atlas Network 2012; Schnitt/Lakhani 2014; Sinn/Kreipe 2013). Mounting evidence on genetic mutations and results from clinical trials currently suggest that it is not suitable anymore to simply categorize cancers by tissue. Thus, after 2010 new categorization attempts can be found. Overall, the analysis traces the different attempts to make sense of products and scientific developments.
While the empirical focus is on a biomedical field at the overlap of science, commerce, and finance, the book’s contributions fundamentally speak to ongoing discussions in sociology.
First, the book contributes to recent developments in economic sociology toward cultural processes (Beckert 2013, 2016, 2019; Wherry 2012, 2014) when it focuses on the role of stories to explain how markets emerge. It complements a solely structural perspective on the emergence of new social formations (Padgett/Powell 2012a) by taking sociocognitive and sociomaterial actors into account (Stark 2009). Focusing on economic actors, their setting, and their products as well as the stories that create and shape them, the book advances a perspective for a cultural analysis of market emergence.
In doing so, the book contributes to ongoing discussions on meaning-making processes. This contribution has two dimensions. One dimension is a substantive one in that it delineates categorization processes. US and European cultural sociologists and organizational scholars alike have become acutely aware of valuation and evaluation processes as basic social actions at stake when sorting, classifying, and categorizing occurs (e.g., Lamont 2012). In particular, the book focuses on the How of category construction in ambiguous situations.
Another dimension is a methodological one. Building on insights from innovation studies on how to study newness, the book takes a not only relational but also a processual perspective to study dynamics of market actors over time. To do so, the book engages with discussions on how to measure meaning (Mohr 1998) and employs a combination of methods. It combines in-depth qualitative text analyses with novel, computational methods of text analyses, i.e., topic modeling and semantic network analysis, to enable a sociological inquiry into meaning-making over time. Moreover, such a design permits us to overcome the often-faced divide between qualitative and quantitative approaches in cultural analysis and in this quest joins current research (e.g., Bail 2014; Breiger et al. 2018; Karell/Freedman 2019; McFarland et al. 2013; Mohr et al. 2020; Mohr/Bogdanov 2013; Mohr/Rawlings 2015; Mohr et al. 2015; Nelson 2020, 2021).
The content of the book bridges and recombines elements from different fields of academic discussions, including economic sociology, sociological theory, innovation studies, organizational studies, and methods of cultural analysis, to study the complex field of commercial cancer research as an example for the framework of markets that come from stories. Additionally, by describing the scientific developments in cancer research, the book intends to provide a non-expert readership with a basic understanding of the field. Similarly, computational methods used are introduced in nontechnical terms. Their technical details can be found in the Appendix.
In this introductory chapter, I first sketch how the problem of innovating in the field of biotechnology has been analyzed and point to temporal, relational, and cognitive complexity in innovation processes. I then introduce the larger theoretical perspective of the book and how that translates into methodological choices. In the last part, I lay out the organization of the book.
1. To be sure, for hundreds of thousands of breast cancer patients the so-far approved, noninvasive therapeutics remain ineffective, or they develop resistances to the treatments. The search for treatments is ongoing.
2. This is a dynamic much like the interaction preludes of Leifer (1988).
3. See Appendix A for more on data sources used.