By Cristina Piñel Neparidze
A fundamental aspect of service delivery in the current age is that of personalisation. When employed as an AI-based marketing approach, it delves into the internet footprints of a customer’s patterns of interest to escalate engagement and sales. Though eventually spotting an attractive and suiting product for a customer, personalisation is ultimately a very skilful mechanism of increasing profit.
Of course, the concept of service is diversiform, and thus personalisation can be applied beyond the identification of trivial products on the internet, such as a potentially favoured nail polish tone. A suitable example is that of the ever-increasing enthusiasm for the personalisation of an imperative service: healthcare. The term personalised medicine or “precision” medicine is nowadays flourishing as a promising medical model that moves away from “one-size-fits-all” treatment approaches implementing, instead, patient stratification based on genomic data to provide a more personal, tailored therapy.
For instance, the development of the drug tamoxifen, a competitive inhibitor of the oestrogen receptor, has particularly made steroid-receptor-positive breast cancer patients stand to benefit from healthcare personalisation: the efficacy of this drug fluctuates depending on expression of the gene CYP2D6, and thus genetic screening for CYP2D6 levels in cancer patients has enabled clinicians to successfully adjust quantity and frequency of drug delivery, therefore optimising treatment outcome (Ruddy et. al., 2013).
Unarguably, the genetic stratification applied to fine-tune tamoxifen treatment dose has revolutionised breast cancer treatment, sparking enthusiasm for the idea of precise delivery therapy. However, since precision is often synonym of expensiveness, one cannot help but wonder whether such upscale personalised molecular profiling can be systematically sustained by current healthcare. As an example to justify such scepticism, commercialisation of drug Ivacaftor in the United States, designed to treat only 5% of cystic fibrosis patients with a unique G551D mutation in the CFTR gene, costs $300,000 per patient per year (Ferkol et. al., 2015), robustly arguing against the economic feasibility of such systematic sustainment.
How can one advocate for the personalisation of healthcare, a highly priced effort with heavy time and resource demands, when millions of patients still require decent healthcare coverage? Akin to personalised marketing, is precision medicine just a sugar-coated strategy coupled with a benevolent justification snakingly seeking to allow big pharma to feather its nest?
Thus, as personalised medicine develops and similar dilemmas rise, it is imperative to examine and meet its moral implications whilst proceeding with caution and healthy scrutiny. This would not only involve an exhaustive assessment of the potentially self-interested modus operandi of pharmaceutical companies as mentioned above, but also a careful ethical consideration of the nature of personalised healthcare itself.
As an example, one must acknowledge that precision medicine is robustly information-intensive. This means that the perks of personalising healthcare go hand in hand with an ever-increasing personal information availability as a result of heavy genetic profiling (Yuan, 2018). Under the NHS Confidentiality Code of Practice, clinicians are under duty not to disclose health records without patient consent but, as exhaustive genetic profiling and other data-heavy analytics are required for a more precise diagnosis and treatment, it is not hard to envision a future where certain information may fall under a grey area, being disclosed to third parties and hence seriously posing health confidentiality under question.
From a bioethical standpoint, such disclosures can be classified under two potentially harmful threats: lack of privacy and genotype-based discrimination (Brothers et. al., 2015). The former, intuitively, may compromise a patient’s quality of healthcare if health information policies evolve to be more malleable, leading to medical avoidance out of fear of improper sensitive information disclosure. The latter, has the potential to highlight privilege differences among individuals in a healthcare system with existing disparities: genomic information could indicate that a certain individual is prone to develop an illness in the near future, and storage of such information could generate unfair distinctions if compelled disclosures come into play. Consequently, if data density overtakes the strictness of health information law, a future where insurance companies are entitled to decide an individual’s insurance policy according to their genetic variants is arguably realistic. It is therefore essential that future policies proceed with caution as personalised medicine and its accompanying data density establish themselves in healthcare.
Of course, one might consider that, as long as health law remains robust, lack of privacy and genotype-based discrimination will fail to materialise. However, according to a number of critics, the ethical dilemmas raised by the nature of personalised medicine expand beyond its information density. Consequently, disparities as a result of its implementation not only can arise as third parties such as insurance policy companies manage sensitive information, but also because normalising such costly, specialised medical model may also exacerbate existing ethnic, social and economic disparities in healthcare (Brothers et. al., 2015).
This can be regarded as paradoxical, because the elimination of health disparities is one of the most glorified aspects of precision healthcare (for instance, through the discovery of a particularly over-represented phenotype within a certain ethnic group as an indicator of an underlying genotype-phenotype association, allowing for the development of targeted therapies). However, eagle-eyed critics cannot help but wonder whether such associations may reinforce the mistaken notion that racial categories can be directly translated onto biological realities, therefore overshadowing the role social, cultural and economic aspects that may influence health.
Additionally, from an economic standpoint, the personalisation of healthcare may also emphasise the economic barriers that both limit access to healthcare and reduce the benefit patients are able to derive from it: as previously mentioned, precision medicine relies on complex and costly state-of-the-art machinery (e.g. next generation sequencing) and thus, patients unable to cover the cost of such novel, personalised technology, will not benefit from it (Muzur et. al., 2019). While it is certainly true that laboratory tests that inform personalisation are expected to become more accessible as genome sequencing technology shifts towards more affordable prices, such technological improvement does not account for labour costs, analytical costs as well as commercial mark-up (Brothers et. al., 2015).
Moreover, when considering the economic impact of new medical philosophies, it is also essential to contemplate their influence on the breach between public and private healthcare systems. Considering personalised medicine and its potential impact as a novel medical model, experts fear for its possible role in accentuating existing disparities between both systems: in countries with private insurance systems, patients with extensive health coverage or the ability to cover such costs out-of-pocket may be able to take new tests and obtain benefits from personalised medicine. Conversely, patients benefiting solely from nationalised healthcare may take longer to profit from such innovations, thus creating a considerable healthcare benefit breach (Garber et. al., 2009).
Regardless of health insurance system kind, it is also worth considering the potential impact of healthcare personalisation on the dichotomy between developed and third world nations: analogously to the predicted contrasts between private and public healthcare systems, patients from developed nations are expected to profit from the benefits of personalised medicine far more than those who live in developing countries, mainly because the cost of novel diagnostic analyses and alternative treatments are likely to limit their availability in the third world (Brothers et. al., 2015).
To conclude, having considered the mentioned potential implications of implementing personalised medicine within the current world healthcare system, it is undeniable that the scope of work on the ethical, legal, social and economic challenges raised by this exciting new model of care need to be expanded. Personalised medicine is evidently an intelligent new approach to healthcare that empowers patients to take responsibility for their health, but with it come the tangle of legal rights between patients and insurance policy companies, the shift in R&D incentive of pharma companies, potential economic, ethnic and social disparities and, of course, the ethical dilemmas coupled to genomic information density (Yuan, 2018). Fortunately, the field of bioethics has a rich tradition of devoting effort to carefully contemplate such matters which, complemented with collaborative, proactive work between quality experts, implementation scientists and health economists can lead to a future with an extraordinarily productive improvement of patient care in a legal, ethical and responsible manner.
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Ferkol, T. & Quinton, P. (2015) Precision Medicine: At What Price? American Journal of Respiratory and Critical Care Medicine. 192 (6), 658-659. Available from: doi: 10.1164/rccm.201507-1428ed.
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Hazin, R., Brothers, K. B., Malin, B. A., Koenig, B. A., Sanderson, S. C., Rothstein, M. A., Williams, M. S., Clayton, E. W. & Kullo, I. J. (2013) Ethical, legal, and social implications of incorporating genomic information into electronic health records. Genetics in Medicine. 15 (10), 810-816. Available from: doi: 10.1038/gim.2013.117.
Muzur, A. & Rinčić, I. (Bio)ethical Aspects of Personalised Medicine: Revealing an “Inconvenient Truth”? Available from: https://link.springer.com/chapter/10.1007/978-3-030-16465-2_17.
Garber, A. M. & Tunis, S. R. (2009) Does Comparative-Effectiveness Research Threaten Personalized Medicine? The New England Journal of Medicine. 360 (19), 1925-1927. Available from: doi: 10.1056/NEJMp0901355.