Research shows that nearly 40 percent of people taking antidepressants experience adverse side effects, including suicidal ideation. Unfortunately, finding the right medication is often a matter of trial and error that can take months or even years – time that some people with severe depression can’t afford.
But what if your doctor could know which medications were most likely to give you those side effects, and which weren’t before you ever took them? This is the promise of genomics in everyday healthcare, and its potential reaches far beyond just this one application: genomics has implications for everything from prescribing to disease screening and so much more.
That being said, the technology’s applications are still in the early stages of development. Here’s what those in healthcare need to know about genomics, the strides that have been made, where potential lies, as well as the technology’s current limitations:
As healthcare stands right now, when a patient visits a new doctor or takes a trip to the ER, they will be treated as an “average” adult. Their medical or family history will likely be a factor, but clinicians are often very limited in the amount of biological information they have access to. However, genomics plays a major role in a patient’s holistic health profile, and knowing their genetic information can open the door to a much more individualized care process.
Take blood pressure as an example. Blood pressure for the “average” American adult is somewhere in the range of 120/80, and doctors will often operate under the assumption that this should be the goal for nearly every person in that age range. Of course, that’s not always the case – based on a person’s genomics (among other factors), 120/80 may not be healthy. Or, a range outside of the norm could be perfectly fine for that patient, and wouldn’t require treatment such as blood pressure medication that may otherwise be prescribed. Ultimately, being armed with genomic data could help clinicians better understand the individual care that any given patient needs, and offer up the best treatment plan accordingly.
In addition, genomics can tell us which conditions, like certain types of cancer, a patient may be predisposed to – beyond what family history alone can tell us. With this information, clinicians can begin screening for those predisposed conditions early on, perhaps before the recommended ages they might typically suggest for a healthy patient. With earlier screening, these diseases can be detected sooner, often with a much higher treatment success rate.
Medication and Prescribing
Genomics can also improve patient outcomes by streamlining the prescribing process. Typically, a clinician may have a certain go-to drug they recommend first for everyone, based on a range of factors including medical guidelines, as well as what anecdotally seems to work best for most of their patients. That first “recommended” drug won’t work for all patients, however, and finding the right prescription can be a months-long battle of trial and error. For birth control, for example, the side effects can be severe, and the process of finding the right medication can be time-consuming, expensive, and sometimes even dangerous to the patient’s health. However, with genomic data, clinicians can begin to gather a clearer picture of what medications may cause adverse side effects in some individuals right off the bat – eliminating the need for trial and error.
Genomics prescribing potential is particularly powerful when combined with telehealth. When leveraging a telehealth platform, patients will input a wealth of self-reported health data, drug response data, and more – all available in an anonymized, standardized format. When combined with genomics, all of this data can be an incredible tool for clinicians and researchers alike to lean on to better determine how to best treat patients with different genomic profiles, what treatments they best respond to, what side effects are most common, and more.
This, in turn, creates a flywheel effect: as more drug response and genomics data are collected using a standardized format, the more fine-tuned drugs – and how we prescribe them – can become. For example, data collected from these telehealth platforms can be used to inform how pharma manufacturers make their drugs to avoid certain side effects. Likewise, pharmacists can have a better understanding of drug interactions and combinations that may be dangerous for certain individuals.
Limitations and Roadblocks
While there’s a lot of promise in genomics, the application of this technology in everyday healthcare is still in its infancy. First and foremost, there’s still a steep learning curve when it comes to integrating genomic data with existing clinical practices. Widespread implementation of genomics in everyday healthcare will require increased education for clinicians and patients, as well as significant investment in research and development.
Access to testing among diverse populations is another concern. At present, insurance coverage for genomic testing is limited, and we will need to see increased insurance coverage for a greater number of genes sequenced. Without doing so, only patients with adequate resources to get genetic testing will have access to this individualized care – an issue that could further exacerbate health inequities.
Despite the challenges ahead, the potential of genomics in everyday healthcare is undeniable. From personalized medicine to improved medication prescribing and beyond, this technology has the power to revolutionize healthcare and provide better outcomes for patients. Ultimately, the integration of genomics in everyday healthcare will require a collaborative effort from all players in the healthcare ecosystem, from providers and payers to patients and pharmaceutical companies. With the right investment and approach, we can work towards a future where personalized, genomic-based medicine is the norm, and where all patients receive the care that is best suited to their unique biology and needs.
Cathy Tie is the founder and CEO of Locke Bio, a digital health platform company that streamlines the launch of fully integrated, branded telehealth services. Cathy is recognized in Silicon Valley as the youngest founder to raise venture capital in biotech, is a Thiel Fellow, and has been recognized by Forbes in their annual 30 under 30 listing. She founded her first company, Ranomics, a genomics testing company, at the age of 18.