Furthermore, advances in personalised medicine could also improve the cost-effectiveness of existing treatments by tailoring medications to an individual’s genotype. This is important as often major drugs will be ineffective in more than half of some patient populations (Spear, Heath-Chiozzi, & Huff, 2001). Using personalised medicine to inform the treatment of treatment-resistant depression is one example of how genomically guided therapies may reduce the costs of high rates of trial and error and reduced quality of life (Mrazek, Hornberger, Altar, & Degtiar, 2014). Additionally treatment resistant depression is associated in the United States with financial costs of treatment approximately $5,481 higher than for patients with treatment-responsive
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Frequently it is difficult to find information regarding the economic benefits and the evidence supporting the efficacy of personalised medicine (Phillips et al., 2013). This uncertainty can be viewed broadly as the result of two significant factors. The first is the lack of economic incentive for pharmaceutical companies to create genomically targeted therapies. As while identifying those who respond better to a specific therapy may allow for higher pricing, overall targeted therapies generally reduce the number of potential customers for a product (Lunshof, 2005). The second is that from both an economic and logistical standpoint it is frequently highly impractical to conduct the randomised double-blinded clinical trials that would provide the evidence necessary to develop these therapies (Lunshof, 2005). As the strength of the supporting evidence is key to having these therapies reimbursed by payers, this may effect whether or not these therapies are assessed to be cost-effective (Meckley & Neumann, 2010). From a payer perspective, the uncertain nature of preliminary clinical trials makes it more economical to delay reimbursements for personalised medicines as it becomes easier to identify over time which therapies have the potential to be cost-effective (Davis et al., …show more content…
This is reflected in the analysis 59 cost–utility studies by Phillips et al. (2013) which found that 72% of the tests analysed would improve health but at a higher cost than current treatments. The funding of these more expensive genomically targeted personalised medicine could thus have significant implications for current funding models as the financial cot of helping these smaller populations of patients may conflict with the fair allocation of resources (Lewis, Lipworth, & Kerridge, 2014). In these instances, the problem of “Just Caring” arises which results from the limited financial resources of most societies which have to be allocated to meet ‘virtually unlimited healthcare needs’ (Fleck, 2014, p. 202). This is a key issue because as personalised medicine advances, as any new technology does, it will increased the number of these healthcare needs (Callahan, 1995). Traditionally this has been distributed by calculating measures such as the cost per QALY (Goldsmith, 2015). As the public reaction to the recommendation by the Pharmaceutical Benefits Advisory Committee to exclude Herceptin from the Pharmaceutical benefits scheme, highlights however economic costs alone are frequently insufficient to meet community expectations (Lewis et al.,
Frequently it is difficult to find information regarding the economic benefits and the evidence supporting the efficacy of personalised medicine (Phillips et al., 2013). This uncertainty can be viewed broadly as the result of two significant factors. The first is the lack of economic incentive for pharmaceutical companies to create genomically targeted therapies. As while identifying those who respond better to a specific therapy may allow for higher pricing, overall targeted therapies generally reduce the number of potential customers for a product (Lunshof, 2005). The second is that from both an economic and logistical standpoint it is frequently highly impractical to conduct the randomised double-blinded clinical trials that would provide the evidence necessary to develop these therapies (Lunshof, 2005). As the strength of the supporting evidence is key to having these therapies reimbursed by payers, this may effect whether or not these therapies are assessed to be cost-effective (Meckley & Neumann, 2010). From a payer perspective, the uncertain nature of preliminary clinical trials makes it more economical to delay reimbursements for personalised medicines as it becomes easier to identify over time which therapies have the potential to be cost-effective (Davis et al., …show more content…
This is reflected in the analysis 59 cost–utility studies by Phillips et al. (2013) which found that 72% of the tests analysed would improve health but at a higher cost than current treatments. The funding of these more expensive genomically targeted personalised medicine could thus have significant implications for current funding models as the financial cot of helping these smaller populations of patients may conflict with the fair allocation of resources (Lewis, Lipworth, & Kerridge, 2014). In these instances, the problem of “Just Caring” arises which results from the limited financial resources of most societies which have to be allocated to meet ‘virtually unlimited healthcare needs’ (Fleck, 2014, p. 202). This is a key issue because as personalised medicine advances, as any new technology does, it will increased the number of these healthcare needs (Callahan, 1995). Traditionally this has been distributed by calculating measures such as the cost per QALY (Goldsmith, 2015). As the public reaction to the recommendation by the Pharmaceutical Benefits Advisory Committee to exclude Herceptin from the Pharmaceutical benefits scheme, highlights however economic costs alone are frequently insufficient to meet community expectations (Lewis et al.,