So much progress has been made towards fulfilling the promise of personalized medicine.
Personalised medicine refers to the application of individual (genetic and other) characteristics for understanding susceptibility to disease, prognosis or response to treatment and ultimately enhancing health outcomes.
They involve companion diagnostics, which predict what medicines will work best on an individual basis, along with highly targeted treatments – such as that used to successfully treat Mila – which make a beeline for the molecular target of the drug.
Better Outcomes for Patients
Until recently, the doctors treating them used a one-size-fits-all strategy. When prescribing medications for similar diseases, a physician who saw one trial worked might use that same treatment for all of his or her patients. That strategy ignores the diversity in ways that patients may be built – from genetics to environmental and behavioural influences on health.
Now that completion of the Human Genome Project is making genome sequencing a routine event and as gene-splicing practices are facilitated by increasingly sophisticated molecular biology techniques, personalised medicine is a truer reality. What this means is that provider and patient can use data, specific to the individual, in deciding on the best possible approach to care based on the genetic makeup of a patient. It would help a physician decide what approach would be most appropriate for that person, and how to develop the plan for her.
Personalised medicine has lots of advantages – from accelerating diagnosis and decision-making to reducing unnecessary drug treatment and side effects that are predictable in certain patients. But there are major obstacles to overcome before any of it becomes available to any of us.
Less Expensive
But the more options are evaluated on a case-by-case basis, the more opportunities for cost reduction will be realised. The costs of genomic information have already plummeted and are expected to continue to do so; complementary technologies, such as routine blood-based clinical chemistry panels, radiology imaging protocols, and wireless health monitoring devices are being developed to capture individual patient data.
These approaches give clinicians an opportunity to tailor practices, treatments and products to the patient in order to maximise outcomes for an individual. There are, however, some important caveats to consider to maximise the benefit of personalised medicine.
There are several different definitions already available for personalised medicine, some of which look at the genomic or genetic element while others essentially mean ‘drugs’ (see Fig. 1) while others include other medical decisions such as surgery as part of personalised medicine. The lack of agreement demonstrates the need to improve its predictive capacity to help it become more viable and applicable.
More Involved Patients
Such problems bedevil health care today, because physicians can’t be any more specific about whether a treatment will or won’t work – all they can proffer are cautious generalities, such as ‘In this study, X per cent of patients experienced Y range of outcomes.
The most obvious benefit of personalised medicine is that it enables doctors to tailor treatments to their patients’ individual needs, and can eventually lead to better outcomes and fewer side effects. Furthermore, it helps doctors avoid prescribing drugs known to cause predictable side-effects in some people.
Among those who were prompted to think about examples of personalised medicine, many mentioned companion diagnostic tests such as the HER2/neu test to determine which drug a particular woman with breast cancer might respond best to, while others gave examples of prognostic tests such as Oncotype Dx or Mammaprint as examples of such medicine. There are many sorts of personalised medicine and the definition is likely to continue moving forward as new discoveries and technologies come to light.
Power Back in the Hands of Patients
Advances in genomics, diagnostic testing and targeted therapies (medications that address specific cancer genes or proteins) are all allowing physicians and patients to develop an increasingly proactive stance towards health care. Likewise, research demonstrates that preventive measures, such as diet and exercise, can also serve as tools against risk factors such as smoking and obesity.
The tools of personalised medicine contribute genomic, tissue biomarker, imaging-based and radiology data, plus the newly emerging wireless device monitoring data into predictive decision environments. Added to this are extensive tools of artificial intelligence and big data.
And as what’s been dubbed ‘personalised medicine’ gallops ahead, researchers insist that it can’t be realised without fairness and equity – as illustrated recently when Black women were less likely than White women to receive BRCA1/2 testing referrals.
