PGx in both drug development and clinical practice is still largely in the developmental stages. In some clinical practices, genetic factors affecting drug efficacy are tested for as a matter of routine (for example, HER2 testing in breast cancer and KRAS testing in colorectal cancer) but in the majority, PGx remains more of a promise than a reality. Within this, PGx tests are most commonly carried out in hospital settings and in medical specialisms (namely Oncology) where the risk and severity of ADRs are increased. Given this, PGx has made almost no impact on clinical practice outside of hospital settings although Grice et al. (2006) identify the potential application of PGx principles to a number of primary care drugs arguing that at least one in four primary care patients takes a drug which causes ADRs. Moreover, elsewhere Warfarin, which is most commonly administered in primary care, is discursively framed as a key area of the application of the principles of PGx (see Rajanayagam, 2009; Wadelius and Pirmohamed, 2006).
Given this relatively limited impact to date, the translation of PGx from ‘bench to bedside’ (Erlich et al., 2003; Weinshilboum and Wang, 2006) is subject to much debate and these debates can often raise more questions than they answer. At the development side of the process, Weinshilboum and Wang (2006) identify four challenges to be overcome to successfully translate PGx technologies into beneficial outcomes for patients. Firstly, they argue, genomic science will need continual optimisation in order to produce cost effective and clinically applicable results. This necessitates collaboration between practitioners and researchers from a diversity of fields and is, thus, echoed by the PriceWaterHouseCoopers’ (2009) report which saw private and public sector scientific collaboration as a necessary future mode. Secondly, they argue that incentives will need to be created in order for drug
74
development companies to mobilise PGx techniques rather than the traditional blockbuster model. Thirdly, healthcare practitioners will need to be educated in genomic principles in order to provide the best service and advice to patients. This is also echoed in UK policy where the Human Genetics Commission (2003) asserted that the successful integration of genetic principles into routine medical practice would rely on, and necessitate, the cultivation of a ‘genetically literate’ primary care workforce. In addition, the White Paper Our Inheritance, Our Future (2003a) also proposed the need for increased genetic education amongst healthcare practitioners and was followed, in 2004, by the establishment of the National Genetics Education and Development Centre (NGEDC), which offers genetic training to a variety of practitioner groups, including pharmacists. Finally, Weinshilboum and Wang (2006) argue that this education needs to be expanded to include patients in order for them to understand how any why PGx principles are applied to their treatment. For Condit (2010), this incorporates both patients’ understanding of the testing process and their ability to make sense of genetics-based risk information. Elsewhere, the limited understanding of, and value invested in, statistical risk-based information has been highlighted by social scientists (Gross and Shuval, 2008). Within this, Gross and Shuval (2008) highlight the rejection of this construction of risk as a rejection of the biomedicalisation of illness, disease and, in this particular case, pregnancy.
In addition to these challenges presented by Weinshilboum and Wang (2006), Erlich et al. (2003) pose a number of questions about PGx as part of everyday work actitivies which, they argue, will need to adequately answered in order for PGx to be successfully integrated. They ask, then, who should perform PGx tests? When should a PGx test be done? What actions should be taken based on a test result? And what is the cost-benefit ratio of PGx testing? This final question is particularly pertinent to the public sector interest in PGx highlighted above. Within this, the promises of PGx to reduce the financial burden of ADRs and non-responsive patients only become relevant where pre-prescription testing is cost effective when compared with trial and error approaches to prescribing. Since different PGx tests require different scientific products and expertise and, moreover there can be a number of other non-genetic factors affecting drug response, the extent to which the cost effectiveness of PGx as a whole can be analysed is limited. For example, whilst Rosove and Grody (2009) argue that PGx testing for Warfarin treatment is not cost
75
effective given the inability of pre-prescription testing to identify all response variation, Vijayaraghavan et al. (2011) identify KRAS testing for colorectal cancer patients as being cost effective to the tune of $7,500-$12,400 for each US patient. Elsewhere, however, Payne et al. (2009) question the parameters of PGx economic evaluation models and suggest a cautious approach to their conclusions. Moreover, as mentioned above, the decreasing cost of genotyping technologies is likely to further shift these economic evaluations.
What this shows is that the process of putting PGx into routine clinical practice is challenging on a number levels from the everyday organisation of healthcare work to the economic evaluations which are used to assess PGx’s cost- effectiveness for the NHS. A future question also arises here which is related to the
integration of PGx into routine clinical work. Here, the internal structures of
different medical practices and the social and political implications of different PGx tests come into play.