Personalised medicine (PM) is changing healthcare but presents its own challenges. This article talks about the three challenges namely, data collection, accessibility and physician liability posed by personalised medicine. 

The healthcare landscape is expected to transform in the next few years, largely due to the development of personalised medicine PM. PM has great potential to effectively treat and prevent disease through individualised healthcare methods, according to an article published by the Journal of Translational Medicine.

But with innovation comes new challenges related to data collection issues, accessibility concerns, and physician liability. Doctors can address these by considering patients’ quality of life, embracing the digitisation of AI, and learning about liability risks associated with PM.

1. Data collection

The success of PM relies not only on data collection from patients but also on effective collection approaches and corresponding databases.

An article published by Frontiers in Digital Health stated that molecular profiling is one way to formulate comprehensive databases. These can be used to predict how treatments will affect a patient, and to recommend adjustments as needed.

Gathering patient-driven xenograft samples, however, often requires patients to undergo biopsies or have tumours surgically removed. Both methods are invasive.

Similarly, obtaining patient-derived organoid samples requires invasive extraction of adult stem cells located in bone marrow or blood circulations. While both approaches are increasingly prevalent in clinically relevant settings to actualise the most effective treatment strategies for each patient, doctors must consider what quality of life the patient presents before taking invasive measures.

If circumstances call for it, doctors can consider other non-invasive or minimally invasive approaches. The frequency at which data need to be collected is another consideration. For example, patient sample-driven regimens require a one-time collection, whereas artificial intelligence AI approaches entail more longitudinal collections.

2. Accessibility

In addition to data collection challenges, doctors must reckon with patient accessibility to PM. According to the Frontiers in Digital Health article, harnessing digital platforms is one pathway to deploying PM. Digitised strategies have already been used, and further bridging the gap between PM and digital medicine will expand patient access to this increasingly effective method of care.

CURATE.AI is an AI program that can be digitised to offer rapid optimisation of treatment plans with the use of the patient’s clinical data. The Frontiers in Digital Health authors cite its use in a patient with prostate cancer, who was able to return to his desired lifestyle.

The authors also discussed real-world uses of digital medicine in PM, writing, “Digitising platforms like QPOP can potentially provide more tailored, personalised treatments to patients who are not responding to the standard of care. Therefore, digitising personalised medicine strategies for deployment in clinical settings is one critical step forward to integrate them into established clinical workflows.”

3. Physician liability

Aside from the challenge of harnessing accessible, PM-friendly technology, doctors who practice PM may struggle with liability concerns.

Consultations with the patient and the family can become problematic in PM, as the physician’s responsibilities are not clear-cut at present. The authors of an article published by Frontiers in Medicine raise the following questions:

1. What bearing does the infrequent application of genetic knowledge have on a physician's duty to warn a patient's children and family members?
2. When test results show a multitude of “variants of unknown significance,” what guidance should be provided to physicians as to how to proceed?
3. When does a physician have a duty to recommend genetic testing for a patient who has a history of disease generally associated with a genetic mutation?

What this means for you

Personalised medicine PM presents its own challenges. It relies on data collection from patients, who may not fare well with invasive collection methods. Doctors should consider a patient’s quality of life and then determine the best approach. Accessibility of PM is another concern, that doctors can address by embracing the digitisation of AI, which paves the way for optimal patient treatment and can increase the integration of PM into clinical workflow. Liability is also a growing concern as PM develops, so doctors must assess the risks associated with such methods.

Disclaimer: This story is contributed by Jules Murthah and is a part of our Global Content Initiative, where we feature selected stories from our Global network which we believe would be most useful and informative to our doctor members.