{"id":15448,"date":"2024-02-03T13:18:57","date_gmt":"2024-02-03T12:18:57","guid":{"rendered":"https:\/\/dataethics.eu\/?p=15448"},"modified":"2024-02-07T13:39:21","modified_gmt":"2024-02-07T12:39:21","slug":"the-ethical-aspects-of-personalised-medicine","status":"publish","type":"post","link":"https:\/\/dataethics.eu\/da\/the-ethical-aspects-of-personalised-medicine\/","title":{"rendered":"The Ethical Aspects of Personalised Medicine"},"content":{"rendered":"\n

Who has the final word? What about privacy, confidentially, data storage? And do you want to know the risk of getting cancer? These are just a few of many ethical issues when we deploy personalised \u2013 or precision \u2013 medicine<\/strong><\/p>\n\n\n\n

There’s no doubt that moving away from the one-size-fits-all approach in medicine will benefit most patients in the long run. Today, doctors are \u2013 even when considering the individual clinical picture \u2013 mainly treating patients based on knowledge that is effective for the majority of patients with a given condition. Yet, the rise of personalised medicine promises a shift to a more tailored and individualised way of treating \u2013 and also preventing<\/em>and even predicting <\/em>\u2013 diseases. <\/p>\n\n\n\n

With personalised medicine, otherwise known as precision medicine, patients can get much more targeted medicine which takes into account their genetic profile, lifestyle, and environment. It recognises that each person is different, and what works for one individual may not work for another. Ultimately, it may be hoped that personalised medicine will be efficient and cost-effective.<\/p>\n\n\n\n

The goal of personalised medicine is to provide the right treatment to the right patient at the right time.<\/em><\/em><\/strong><\/p>\n\n\n\n

We already see some level of personalisation in the treatment of various chronic patients, for example for patients with type 1 Diabetes. Based on measurements of the patient\u2019s blood sugar level, their level of exercise, and what they eat, the level of insulin they need can be determined. <\/p>\n\n\n\n

Among the benefits of personalised medicine are more effective treatments with fewer side effects and fewer disease risks with early interventions. But there is also a long list of ethical issues that need to be considered. <\/p>\n\n\n\n

“While personali<\/em>s<\/em>ed medicine is touted as an innovative solution to the one-size-fits-all approach, it is important that we separate reality from hype. Like all medical methods, it is imperative that we continue to reflect on, and manage, the ethical risks that might be introduced with emerging tools and interventions<\/em>, <\/em>says Ji-Young Lee, Assistant Professor at Copenhagen University, and PI at the MG-PerMed project responsible for the ethical, legal and social aspects. “<\/em>I am particularly interested to explore how personali<\/em>s<\/em>ed medicine will affect groups and communities that are already marginali<\/em>s<\/em>ed or discriminated in healthcare settings”<\/em>.<\/em><\/em><\/strong><\/p>\n\n\n\n

We will go through the ethical aspects of personal or precision medicine below and go deeper into some of them in later interviews with the different scientists in the MG-PerMed project later on. <\/p>\n\n\n\n

Decision-Making.<\/strong> Who has the final word? The doctor(s) or the machine? And is the doctor ‘strong’ enough to insist that his or her intuition must be part of decision-making? The general idea is that it is okay for computers toassist<\/em> doctors in making decisions, but it’s not okay for decision-making about health to be entirely left to the quantifications made by computers. . If the doctor always has the last word, we also know where the responsibility lies. <\/p>\n\n\n\n

Philosopher Thomas Telving points out in this article<\/a>, that it is not easy to hold on to the idea that machines should only be supportive:
\u201cOne issue is that it’s only a matter of time before it can be considered downright risky to disregard the recommendation of an AI model.<\/em>
There are already algorithms that are more accurate than doctors. For example, based on MRI scans, an algorithm has predicted how physical and cognitive symptoms of multiple sclerosis (MS) will develop over the next two years significantly better than doctors. While doctors got it right 70 per cent of the time, the algorithm got it right 86 per cent of the time. This example is far from unique.<\/em>
The obvious thing to do is probably to stick to the idea that this is decision support and that machine and human complement each other to increase the total number of correct judgements. But does this hold true in a practical reality? Under constant time pressure and confronted with the industry’s best and most recognised software, does a doctor want to go in a different direction than the algorithm?\u201d<\/em><\/p>\n\n\n\n

Privacy and Confidentiality<\/strong>: Personalised medicine involves collecting and analysing health and genetic data, which raises concerns about the privacy and confidentiality. There’s a risk of sensitive data being accessed or used inappropriately. Many justifiably fear that the data can end up in the hands of insurance companies which could lead to discrimination by insurance companies, potentially affecting coverage and premiums.<\/p>\n\n\n\n

Informed Consent and Psychological Impact<\/strong>: Ensuring that patients fully understand the implications of genetic testing and personalised treatments is crucial. Of course, the patient must consent to the treatment, or the predictions personalised medicine might make of him or her. But does she understand the consent, and does she really want to know her risk of getting cancer in 30 years? Or that she has a 70% probability of dying before she turns 70? Further, receiving detailed genetic information can have psychological impacts on patients and their relatives, particularly if it reveals high risks of certain genetic disorders. <\/p>\n\n\n\n

Impact on Doctor-Patient Relationship<\/strong>: Personalised medicine could alter the doctor-patient relationship when it comes to decision-making, trust, and communication. Should a doctor tell a patient that she’ll likely get cancer within a few years? How should the doctor react if she is sitting on relevant knowledge about a patient without knowing if the patient wants this information? When it is only a risk factor and not a fact, should the doctor then attempt to treat the patient preventatively, or should the patient be left alone to live her normal life without this predictive interference?<\/p>\n\n\n\n

Incidental Findings, Anxiety, and Unnecessary Treatment<\/strong>: Genetic testing might reveal unintended information, such as unknown paternity or predisposition to unrelated diseases. Are patients – and sometimes their relatives – prepared for this possibility, and do they want to know? Further, there’s a challenge in ensuring that the genetic information is clinically relevant and doesn’t lead to unnecessary anxiety or overtreatment.<\/p>\n\n\n\n

Discrimination and Bias.<\/strong> For any projects using data, including DNA, the data might be biased \u2013 because it is unrepresentative, missing or mistaken \u2013 in favor or against certain groups of people. This thereby risks entrenching discrimination based on one\u2019s e.g. gender, nationality, or race. This risk is also embedded in any predictive measures. <\/p>\n\n\n\n

Economic Inequality.<\/strong> From a societal point of view, personalised medicine could exacerbate healthcare disparities. Some treatments may be more expensive and less accessible to underprivileged populations, aggravating existing inequalities in healthcare access across different groups. Deciding how to allocate limited healthcare resources between personalised and traditional approaches can also pose various challenges. <\/p>\n\n\n\n

Data Management and Sharing<\/strong>: There are ethical considerations regarding how patient data is stored, who has access to it, and under what circumstances it can be shared for research or other purposes. Of course, there are legal requirements that must be complied with, but there are still data sharing and storage issues from an ethical standpoint. Even though it might be legal to store data in the US, many Europeans might feel uneasy about the fact and would prefer their sensitive data to be stored in Europe. <\/p>\n\n\n\n

Use of Third-Party Services. <\/strong>In every healthcare project, any use of services and apps needs to be evaluated before use to be sure it is not only legal but also ethical. This is also the case for the implementation of telemedicine services. Regulation in e.g. the US and EU differ a lot – also on health data – and therefore additional attention is needed when evaluating the US services. <\/p>\n\n\n\n

Regulatory and Oversight Challenges<\/strong>: Establishing appropriate regulations and oversight mechanisms for personalised medicine, which is rapidly evolving, is necessary to prove that you are actually doing what you are claiming. <\/p>\n\n\n\n

For the EU-financed project, MG-PerMed, philosopher Ji-Young Lee is taking the lead in the ethical aspects of the project supported by professor Ezio Di Nucci and Pernille Tranberg (the author of the articles series) from DataEthics.eu.<\/p>\n\n\n\n

“The MG-PerMed Project is an exciting opportunity for dedicated researchers to construct a personali<\/em>s<\/em>ed medical application from scratch. This will allow for critical ethical reflections to be embedded and addressed at every stage of app-building and user experience: from the design and modelling of the app to its deployment. It is essential, and hopefully obvious, that any project which proposes to make a profound impact on human health and welfare is conceived with ethics at its very core. This goal is of course also aligned with the EU\u2019s vision of artificial intelligence to advance research and innovation whilst prioriti<\/em>s<\/em>ing safety and respect for fundamental citizen rights.”, <\/em>says Ji-Young Lee.<\/strong><\/p>\n\n\n\n

Addressing the ethical challenges requires careful consideration and a balance between the benefits of personalised medicine and the protection of individual rights and societal values. <\/p>\n\n\n\n

Photo by Ksenia Yakovleva<\/a> on Unsplash<\/a><\/em><\/p>\n\n\n\n

Personalised Medicine and the MG-PerMed Project<\/strong> This articles series focus on the ethical aspects of personalised medicine. We use Myasthenia Gravis (MG) as a case, as we follow the EU-financed project (MG-PerMed) dealing with personalised medicine for MG patients. However, the same ethical aspects of personal medicine exist in the personal treatment of all other deceases. MG makes muscles weak because the body’s immune system attacks them. People with MG often need medicines that weaken their immune system to control the disease. But it varies a lot from person to person, what medicines they need. This project, Prevention in Personalised Medicine, aims to tailor treatments to each person’s unique needs instead of a one-size-fits-all approach. <\/p>\n","protected":false},"excerpt":{"rendered":"

Who has the final word? What about privacy, confidentially, data storage? 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