Clinical trials offer a slew of benefits: optimal dosage ranges, identified potential side effects, and efficacy data. If approved by the FDA, clinicians leverage the insights from Phase III trials to support their patient populations. Yet not all medicines help people equally.
Imagine a set of twins who have a family history of migraines. They both go to the pharmacy and pick up the migraine medication prescribed by the doctor. The prescription works for one twin, but the second still has a migraine. A variety of factors drive such a phenomenon: how quickly the person metabolizes the drug, if the twin has a sensitivity to that medication, and other factors.
With the Rise of AI, What IP Disputes in Healthcare Are Likely to Emerge?
Munck Wilson Mandala Partner Greg Howison shared his perspective on some of the legal ramifications around AI, IP, connected devices and the data they generate, in response to emailed questions.
Such differences happen because the recommended dosages are derived from clinical trials. Said clinical trials work on a population level, where they focus on preventing complications and improving health outcomes for the specific patient populations in the studies. This format results in effective dosages for medications, while minimizing side effects. However, such large trials do not account for individual variability within the study population.
Precision medicine has begun addressing part of this issue by examining an individual’s genetics. For example, genetic testing looks at a patient’s individual genes to flag the patient’s potential risks for a variety of disease states, ranging from cardiovascular disease to hypertension to colon cancer. Genetic testing companies – like 23andMe and Ancestry — look at particular genes in a person’s DNA to determine one’s risks for developing diseases. To accomplish this, companies use various testing methodologies, most commonly PCR tests, which look for specific genes known to correlate with particular diseases.
Additionally delivering on precision medicine, the field of pharmacogenomics takes this one step further. Pharmacogenomics looks at how a person’s body metabolizes a particular medication, if the medication will work for that patient, and the potential side effects the patient could face. For instance, pharmacogenomics explores if a patient has the receptors needed for a given drug to work or if the patient will have an increased or decreased uptake of the drug, correlating to the drug’s efficacy. Further, pharmacogenomics can determine how quickly a body can break down a particular drug. For example, in patients with depression being treated with amitriptyline, doctors can screen for two genes – CYP2C19 and CYP2D6 – and adjust the dosage needed for maximized efficacy accordingly, since those genes correlate with different breakdown rates of the drug. The benefits extend beyond just efficacy: improved dosing based on a patient’s pharmacogenomics can mean less risk for adverse side effects – such as with chemotherapy – and avoiding overdoses.
Here’s where whole genome sequencing and pharmacogenomics can really move the field of precision medicine forward. Within a person’s genome lies all the data needed to understand how any given medication will impact that person. And the technology needed to do such analysis is finally under development, so it can work in practice, rather than just in theory.
A Personalized Approach to Medication Nonadherence
At the Abarca Forward conference earlier this year, George Van Antwerp, managing director at Deloitte, discussed how social determinants of health and a personalized member experience can improve medication adherence and health outcomes.
The current pharmacogenomic products on the market look at specific genes known to correlate to how a person responds to medications. The next frontier is leveraging available technology to utilize a person’s entire genome to understand and predict the person’s response to medications.
Looking at the entire genome to gather pharmacogenomic data has the potential to fill in gaps that can be missed by only looking at the interplay of known pharmacogenes.
As companies explore and implement viable technologies to leverage pharmacogenomics for their patients, they can consider the following four points:
- Not just genetic testing: the technology should go beyond merely assessing risk factors for potentially developing a disease. Patients can benefit additionally from genetic information about how they might respond to particular medications, not just the risk factors for diseases.
- Beyond PCR: PCR tests are limited in that they only look for the particular genes indicated in the test, leaving other genetic information out. A more comprehensive view can support truly personalized medicine to help patients.
- Whole genome sequencing: the technology that analyzes the entire genome, not just a portion, will offer the most complete picture and can help optimize patients’ treatment options.
- Clinical decision support: to make the technology useful in practice, it should not only explore pharmacogenomic information about a patient, but also should offer targeted clinical recommendations for the patient. For example, dosing recommendations based on the pharmacogenomic profile or alternative medications if one is not suitable based on the pharmacogenomics.
As the industry moves towards more personalized medicine, pharmacogenomics could play a key role in keeping patients healthier longer and in getting them viable treatments for their unique genetic profile.
Photo: Getty Images, 4X-image
Jayden Lee, PharmD is Clinical Pharmacogenomics Director at UGenome AI, a bioinformatics company offering analytical solutions for businesses in any stage of therapeutic development.
Zachary S. Brooks, PhD is the CEO of UGenome AI, a bioinformatics company offering analytical solutions for businesses in any stage of therapeutic development.
