Translational Science and the Hidden Research System
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This paper analyses the interactions and dynamics involved in clinical translation for the case of a Canadian network of scientists, clinicians, and clinician-scientists studying the pathogenomics of immunological disorders and innate immunity. We see clinical translation as similar to the chain-linked model of innovation described by Kline and Rosenberg (1986), an iterative process through which problems, novel discoveries, information and artefacts navigate from the clinic to the research lab and back again. Within clinical translation, high levels of interactivity are crucial (Atkinson-Grosjean, 2006) with interactions between scientists and clinicians playing a pivotal role (Gelijns et al., 2001; Hopkins, 2006; Swan et al., 2007). This paper follows the movement of problems, discoveries, information and artefacts during clinical translation within this Canadian research network, explores the role of interaction and collaboration between the network's members, and analyses the motivations of its members to become involved in clinical translation. Biomedical research has always been closely connected to practical applications. Although policy and funding incentives have consistently promoted clinical translation of biomedical science, the processes involved in translation remain less studied (Hopkins, 2006). Existing research tends to focus on interactions between firms and universities rather than on interactions between clinicians and scientists or the role of academic health centres in fostering clinical translation (Hopkins, 2006), an innovation system that remains hidden in these analyses. To gain a more comprehensive, nuanced, and empirically based understanding of the processes of clinical translation more emphasis must be placed on these "hidden research systems" (Hicks and Katz, 1996) in which clinicians, scientists, and hospitals interact. Data collection for this project began in summer 2006 and is ongoing. Methods include site visits, surveys and semi-structured interviews with members of the network as well as field observations of the day to day functioning of the network's research labs. Surveys were administered face-to-face and results were statistically analyzed using SPSS software. Interviews were digitally recorded, transcribed and coded for analysis with Atlas.ti software using a grounded-theory approach. Empirical results from these analyses were subsequently situated in the wider literatures. Much of the activity observed within this network moved in the opposite direction from the stereotypical linear conception of innovation where new knowledge developed by scientists is transferred to application. Within this network we found that most clinical translation observed moved from the clinic to the research lab by taking previously undiagnosed or understudied clinical problems (dubbed 'experiments of nature') and moving them towards more basic research. By beginning in the clinic, these research initiatives originated with a medical problem as opposed to a scientific question. Clinician-scientists embedded within larger formal and informal networks of practitioners and researchers acted as crucial mediators in this process. In their role as hospital-based medical specialists, interacting with patients, they were able to identify important clinical problems. Drawing on related patient data, these clinical problems were researched and analysed within the research labs of the clinician-scientists and those of their university-based collaborators. As one clinician researcher described his research, "I start from the patient, and start from what I see as important clinical questions where I can offer some insight...and then I try as much as possible to use samples from the patient, blood, DNA, other information." As research progressed, relevant findings affecting patient treatment were locally adopted into clinical practice and published in both the clinical and research literatures. More basic research findings about underlying biological mechanisms moved increasingly into the university lab over time and from patient-based to system-based analysis. These processes underscore the iterative nature of clinical translation. Although firms are the traditional focus of innovation analysis, they played no role in this clinical translation process and the motivation for engaging in clinical translational innovations seems to have little connection to conventional perceptions of technical competition fuelled by profit and the association of innovation with firm survival. Rather, engagement in clinical translation appears to be motivated by perceived clinical need on the one hand, and personal career advancement on the other. Confronted by a clinical problem they were unable to solve, practitioners and clinician-scientists, as medical doctors, used their tools and abilities to try to help the patient. Hopkins (2006) similarly found that the evolution of cytogenetic testing in the UK was primarily based on clinical utility, not profit. Regarding career advancement, clinician-scientists qua scientists appear to have a competitive edge with Canadian funding agencies because of their clinical relevance and access to patient data. Their patient-based connection to the clinic fuels their research and acts as an asset in their collaborations with academic scientists who otherwise rely on anonymous tissue cultures and cell samples. This paper explores the role of clinicians, scientists, and academic health centres in fostering clinical translation using a Canadian network involved in the pathogenomics of immune disorders and innate immunity as a case study. In doing so, it expands innovation analysis beyond firm-industry-research institute analyses and explores motivations for engaging in clinical translational activities. References Atkinson-Grosjean, Janet (2006) Public science, private interests: culture and commerce in Canada's networks of centres of excellence. Toronto: University of Toronto Press Gelijns, A. C., et. al. (2001). Journal of Health Politics, Policy and Law, 25(5), 913-924. Hopkins, M. (2006). Science as Culture, 15(3), 253-276. Hicks, D., & Katz, J. S. (1996). Science and Public Policy, 23(5), 297-304. Kline, S., & Rosenberg, N. (1986). An overview of innovation. In R. Landau, & N. Rosenberg (Eds.), The positive sum strategy: Harnessing technology for economic growth (). Washington, D.C.: National Academies Press. Swan, J., et. al. (2007). Research Policy, 36, 529-547.