Emerging technologies, and artificial intelligence in particular, are set to bring about a sea-change in the healthcare industry. Emerging trends like telemedicine and AI-assisted patient diagnosis promise to help enable better, and more effective patient care.
One of the most exciting of these emerging trends is precision medicine, which in the future could power disease treatment and prevention tailored to specific groups of patients. Indeed, the precision medicine software market is now predicted to be worth $2.8 billion in the next seven years.
In this article we’re exploring how technology is helping make precision medicine, which up until recently was little more than a hope for the future, feel like a reality within reach.
Defining precision medicine
The terms precision medicine and personalized medicine are often used interchangeably to signify the same thing: namely, medical treatments that are tailored to specific populations of patients based on factors like genetics, lifestyle, and environment. Because the term personalized medicine risks implying that treatments will be developed for each individual patient, which is not the case, the term precision medicine is generally preferred.
The problem with disease prevention and treatment currently
Precision medicine is still an emerging approach to treating and preventing disease, where the hope is that it will make treatment more effective than it has been historically. The issue with the current approach to treatments and prevention is that they are designed with an average patient in mind. However, because we are all unique individuals with diverse backgrounds and genetic makeups, this one-size fits all approach inevitably fails to meet the needs of many patients.
Naturally, healthcare providers always strive to provide the most individually-effective treatments to their patients. Physicians factor in a patient’s age, known genetic predispositions, and lifestyle when recommending courses of treatment. They will also vary treatment based on an individual patient’s response, but in practice this requires a tremendous amount of trial and error that may take months and years to generate results.
Precision medicine would enable physicians to prescribe more effective treatments from the outset and even potentially to predict disease susceptibility and preempt disease progression.
A wealth of patient data is the engine that will power precision medicine
Whereas even as recently as 30 years ago medical information was stored on paper, siloed and incredibly difficult to access, collate, and analyze, today the medical community has access to a glut of data just begging to be put to use.
A wealth of data in the form of electronic health records, genomic sequencing, large-scale research studies, and outputs from wearables and smart devices can be used in service of developing more precise treatments and enabling us to become more prevention- rather than reaction-focused.
How technology fills the gap
Though huge troves of data about patient outcomes are being collected, the challenge of generating useful insights from that data remains. The rise of artificial intelligence means that we may soon be able to surmount that challenge. Machine learning algorithms can draw insights from large data sets, connecting dots that aren’t readily apparent to human researchers. This, in turn, enables clinicians to better understand how certain treatments affect specific populations.
Pharmaceutical companies are increasingly looking for ways to develop precise therapies for specific patient groups, rather than continuing to rely solely on a one-size fits all approach to drug development. Whereas previously such efforts would have been cost-prohibitive, machine learning can significantly reduce the time and expense required to develop such therapies.
Precision medicine is an emerging field and its the full extent of its promise hasn’t yet come to fruition. However, AI and big data are bringing it steadily closer within our reach.
