Perceptions of risk in tissue engineering R&D: a classification

(see for useful overviews: Horlick-Jones and Sime 2004; Renn 1992; Slovic 2000). Categorisation of risk is not novel either (see for one attempt: Sarangi and Candlin 2003).

From expert interviews (see later) different notions emerged of ‘the risks’ of tissue engineering, and more particular articulation and differentiation of these risks over specific spheres. I have called these risk domains. As such, a rather grounded approach was adopted where dynamic and varying interpretations of risk seemed to emerge as an important theme during the fieldwork. Initial inspiration to analytically engage with this variation came from a risk typology developed by Douglas and Wildavsky in their work ‘Risk and Culture’ (Douglas and Wildavsky 1982). This model is concerned with risk perception, and

classifies how different social groups select risk based on their cultural characteristics. The authors define three general areas of concern with risk:

Socio-political risks include dangers to social structure, usually stemming from human violence such as crime or war; economic risks are threats to the

economy or risks of economic failure; and what they label natural risks includes ecological threats to nature and the body, which covers risk from technology (Lash 2000).

Douglas and Wildavsky use this typology not to provide a classification of ‘real’

risk but as a tool to link particular risk perceptions with separate risk cultures.

This provided a good starting point for discriminating between different risk perceptions in tissue engineering. In my research I translate this model to different stages of the innovation process of biomedical technology, and as

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such have a narrow take on risk perception as defined by actors in research and development (R&D) of this technology. The structure of this underlying innovation framework is discussed next.

My classification of risk perceptions follows the early stages of the innovation cycle of (biomedical) technologies, where innovation is simply considered as

‘introducing something new’ (Loughlin 2002). The innovation development process has typically been described as a linear model consisting of six

phases, starting with problem or need definition which stimulates research and development, towards commercialisation, diffusion and adoption of the

innovation by users to finally its consequences (Rogers 1995). My model for categorising risk perceptions is only concerned with a fraction of this process, namely the R&D and commercialisation phase, where scientific knowledge and insights of basic and applied research are further developed and converted into products or services for sale in the marketplace. Commercialisation, then, is the final station of interest in my study, where innovations are conversed into

production, manufacturing, marketing and distribution of products. With respect to domains of innovation, this research speaks in simplified terms of lab, clinic and marketplace, which are each connected to certain practices and value systems. Perceptions of risk of tissue engineering technology are discussed in relation to these three domains. This leads to the following alternative risk typology:

A taxonomy o f risk:

Risk domains and a safety bar based on cell source

Cell source

Clinical Technoloc

Autologous

Allogeneic

Xenogeneic

In this model the three social worlds of lab, clinic and marketplace are visible as main domains, corresponding with the following categories of risk:

• Technological risk (safety)

• Clinical risk (efficacy)

• Commercial risk (marketability)

Technological risk covers concerns related to the processing and

manufacturing of human tissue and cells, and reflects an overall concern with safety. Clinical risk is about perceptions of risk related to clinical evidence available for these products, with efficacy as key word. Commercial risk refers to concerns about the market and business climate for tissue engineering, and includes factors to do with cost and marketability of tissue engineered products.

Thus this typology is a reflection of the innovation process from lab to clinic to market. It covers the different phases in the R&D process with a focus on primary scientific work and basic research in the lab (technological risk, discussed in chapter 4), to the clinical phase in which the constructs are

translated into initial clinical testing in humans (clinical risk, chapter 5), as a first transition into the market place, where the products enter the commercial cycle (commercial risk, chapter 6).

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It should be noted though that these phases of innovation do not necessarily take place in a linear sequence, nor that these are distinct (a more dynamic stance is provided by: Blume 1992). The proclaimed ‘biotech revolution’ is one example. Instead of bringing revolutionary changes biotech has followed a well- established pattern of slow and incremental technology diffusion, where the translation of basic knowledge into new technology has been argued to be more difficult, costly and time-consuming. In other words the linear model of innovation is being questioned, and policymakers need to take into account the

‘uncertain, systemic nature of technical change and the very long time scales between advances in basic knowledge and productivity improvements’

(Nightingale and Martin 2004: 568).

This uncertainty has been described as notable characteristic of medical innovation. Policy debates are often based on the assumption of innovation as a homogeneous activity that follows the linear model as discussed above. But processes of innovation differ per sector and per economy, with extreme diversity of background conditions underlying the innovation process (Gelijns and Rosenberg 1995). For example technological innovation in the

semiconductor industry does not resemble the process as found in fields such as tissue engineering. Even within the medical domain the conditions for successful innovation differ substantially per sector and sub-sector (e.g.

compare pharmaceuticals and medical devices). In the case of tissue engineering this could be extended to even larger diversity because of the broad range of clinical applications, from relatively simple woundcare products to highly manipulated and complex constructions for whole organ replacement - that also constitute different risks.

Highlighting these limitations serves to illustrate the danger of crude

reductionism in my classification of risk across three domains of lab, clinic and market. Therefore I also demonstrate the dynamic interactions between

inhabitants of these domains, and the ways in which risk perceptions serve as boundary objects in negotiating what belongs to the social worlds of risk and/or regulation, and how the conditions of these boundaries are contested and negotiated. Here I rely on social constructivist notions of how ‘relevant social

groups’ help to shape technological innovation, acknowledging the relevance of interest groups and networks of social interaction around technical, scientific and medical innovation (Pinch and Bijker 1987). With this approach the distinct linear stage model of technological development is questioned, adopting a more dynamic view on the spread of innovative technologies (see also:

Nicholson 2002). Eliciting different risk perceptions in transcending boundaries (rather than assuming these are fixed) is one way of illustrating this point.

Furthermore, the model also contains a ‘safety bar’ which runs across the different risk domains. This bar is based on interviewees’ perceptions of the

‘riskyness’ of the different biological materials which form the starting materials for tissue engineered applications. Here it becomes clear how many of these risks are related to each other, but also constitute different values across risk domains. Therefore, in chapter 7 alternative dimensions are discussed in the perception of risk. One of those I have labelled the ‘risk hierarchy’, which is a reclassification of risk in terms of the particular source material used for tissue engineered construct. Autologous applications are generally considered ‘less risky’ than products based on allogeneic material. As demonstrated though, this perception clashes with another concern high on the risk list, namely the use of xenogeneic material in the cell culturing process for both the autologous and allogeneic engineering routes. Furthermore I argue how the particular cell source determines not only scientific endeavours but also drives clinical

concerns and commercial strategies. It is here that the risk hierarchy becomes a more dynamic model, where risk in techno-scientific terms takes on a

different meaning and value in clinical and commercial domains.

Another dimension of risk described in this chapter is what I have called the

‘risk balance’, which is about acceptability of risk, where perceived risks of tissue engineering are differentiated into levels and degrees of risk for

particular applications (life-saving versus cosmetic, availability of alternatives), subsets of populations (e.g. children), and overtime (‘intergenerational risk’).

The content of the balance of risk and the hierarchy of risk provide the context for risk management approaches, making the transition to the social world of regulation as discussed in subsequent chapters. The next section discusses the implications and limitations of this research.