This week we’re talking about one of the pillars of personalised healthcare - pharmacogenomics. Let’s dive in.
🤷♂️ Problem
Adverse drug reactions (ADRs) account for 6.5% of acute hospital admissions in the UK and are in the top 10 causes of in-hospital mortality in the US.
Prescribing a medication can be a shot in the dark. We don’t always know which patients will benefit from a given drug and many will have to endure ‘therapeutic trials’ to find something that works for them.
More than 90% of the US population has at least one genetic variation that may affect their response to medications.
💡 Solution
Deploy pharmacogenomic tests and tailor drug treatments to a patient’s genetic makeup. How will this help?
Improve drug effectiveness
Reduce side-effects
📖 Terms
Pharmacogenomics is often used interchangeably with pharmacogenetics, but there is a subtle distinction…
Pharmacogenetics. The study of how variation in one single gene influences the response to a single drug.
Pharmacogenomics. The study of how all the genes that make up the genome can influence responses to drugs.
Pharmacokinetics. What the body ‘does’ to a drug. Focuses on the drug’s absorption, distribution, metabolism and excretion within the body.
Pharmacodynamics. What the drugs ‘do’ to the body. Includes receptor binding, post receptor effects and other chemical interactions.
📚 History
As with most notable historical tales, this one also starts with your favourite Greek philosopher…
510 BC. Pythagoras documents the first observation of pharmacogenomics in action when he observes that a subset of people ingesting fava beans experience potentially fatal haemolytic anaemia. (Much much later, this is found to be due to an inherited mutation in a specific enzyme - G6PD).
Many years later…
1957. American geneticist Arno Moltulsky first proposes the concept of pharmacogenetics at a time when variation in drug response was thought to be in some way influenced by genetic inheritance.
1960s/70s/80s. Subsequent research mainly focusses on pharmacokinetics and how genetic variation in certain drug metabolising enzymes can influence drug concentration in the bloodstream. But all of this takes place before genes are being routinely cloned and sequenced. Progress is slow.
Late 1980s/90s. Pharmacogenomic research begins cloning and sequencing genes encoding proteins that might contribute to variation in drug responses. The research demonstrates that much of the genetic variation in drug response that had been reported previously results from common sequence variation within or near genes that encode metabolising enzymes.
1990. Perhaps the greatest collaborative scientific project - The Human Genome Project (HGP) - officially kicks off in October, aiming to discover all the estimated 20,000-25,000 human genes, make them accessible for further biological study and determine the complete sequence of the 3 billion DNA subunits.
2003. The HGP finishes in April (finally!), setting the stage for more rapid pharmacogenomic discovery and pharmacogenomic clinical implementation. Researchers role up their sleeves…
2016. By May 2016, 30 published gene–drug pair guidelines, in which a particular gene variation has implications for how a patient will respond to a given drug, have been documented, along with clinical dosing guidelines. Translational pharmacogenomic research has truly arrived!
💼 Use cases
The FDA maintains a list of drugs for which there are pharmacogenomic biomarkers with demonstrated clinical utility. Here are some notable examples.
Warfarin. The common ‘blood thinner’ has four genomic biomarkers that guide dosing, highlight possible drug interactions, or highlight the risk of specific adverse drug events.
Escitalopram. The common SSRI for depression and anxiety has several genomic biomarkers that influence dosing and the risk of potentially dangerous changes to the heart rhythm (QTc prolongation).
👥 Players
In 2018, the global pharmacogenomic market size was a cool $4.5B. This is expected to double by 2028. Here are some (but not all) of the movers and shakers in the industry:
Genelex*. US-based company providing pharmacogenetic testing solutions including decision support tools for clinicians
YouScript*. Technology solution combining pharmacogenomic data with other drug/patient data to support prescribing decisions. Integrated into several EHRs.
Myogenes. UK-based molecular diagnostic company. Distributes genetic tests either through clinics or direct to consumers. Provide different testing panels for several clinical specialties.
Sonic Genetics. Australian-based genetic testing company. Provide access to pharmacogenomic screens.
OneOme. A Mayo Clinic startup. Provides the pharmacogenomic ‘RightMed’ test and report to facilitate personalised prescribing.
2bPrecise. EHR integration solution that ensures pharmacogenomic results are available to clinicians when prescribing.
Geneticure. Another pharmacogenomic test provider in the US. Distributes to patients, care providers and employers.
PharmGKB. (A researchers dream!). NIH-funded comprehensive resource that curates knowledge about the impact of genetic variation on drug response for clinicians and researchers.
*Companies that have been acquired by Invitae - a US-listed genetic testing company
👊 Impact
To demonstrate the impact pharmacogenomics can have on clinical care, the HIV drug ‘abacavir’ serves as a great example.
Millions of people worldwide live with HIV. Combination antiretroviral treatment is the most effective therapy and helps avoid the development of resistance.
Abacavir is one such medication, but it can cause a severe hypersensitivity reactions in some individuals which can be serious and life threatening.
This adverse reaction is associated with a specific genetic variant - ‘HLA-B*5701’. Screening for this prior to treatment can ensure patients avoid a potentially risky medication.
Minimising adverse effects of antiretroviral therapy is critical to controlling the infection and maintaining treatment adherence.
🔮 Predictions
More evidence. We have the technology, but does it benefit patients? Expect positive outcomes from credible trials over the next few years (like this one for patients with depression).
Increased affordability. High costs or lack of insurance coverage limits the degree of pharmacogenomic testing that can takes place currently. If the evidence shows population level reductions in acute admissions and ADE-related care, the case for routine testing is made.
Genetic counselling. As pharmacogenomic tests become more widely used, counselling will become integral as testing may uncover issues that impact future health and treatment decisions.
Integration. The increasing use of EHRs to store patient data will make genomic information more accessible and actionable at the point of prescribing.
Test panels. Clinicians will start acquiring genomic profiles for their patients by ordering a panel rather than a single test. These will cover a range of genomic biomarkers that influence common prescription drugs.
Other -omics. Genomics isn’t the only ‘-omic’ to influence drug efficacy and safety. We’ll likely see pharmacometabolomic as well as pharmacogenomic data influencing clinical decisions in the future.
🤔 Challenges
No guarantees. Genomic analysis might suggest a lower likelihood of an adverse drug event but this isn’t a guarantee. Patient expectations need to be managed.
Don’t forget the environment. Better understanding of the human genome doesn’t negate the impact of environmental factors on disease or drug therapies.
Bench to bedside. Research may show an association between a gene variant and a drug response, but a test still has to be developed to make it available and usable in clinical practice.
Adherence. Whether medicines are personalised or not, they can only be effective if patients actually take them. Tackling adherence issues also needs to be addressed.
Ethics. Genomic analysis for personalised therapies might uncover other genetic variants that are problematic. How should this knowledge be shared with patients?
Premiums. Will insurers attempt to adjust premiums based on how ‘risky’ someone’s genome might be? Who pays if pharmacogenomic analysis suggests a more expensive drug is preferable?
Equitable access. As with many emerging health technologies, whether those who would benefit most get appropriate access will also be a challenge for pharmacogenomics.
🌅 Opportunities
Precision medicine. Right drugs for the right patients at the right time. Pharmacogenomics is a step away from generalised treatments informed by population level studies.
Clinical guidelines. Help clinicians interpret genomic testing results so they can appropriately adapt treatments to patients. The current guideline paradigm will need to change significantly to ensure doctors feel they are practicing evidence-based medicine.
GWASes. Genome wide association studies have already identified important pharmacogenomic biomarkers. As ‘omics’ databases become more linked to EHR data, the opportunity to find more drug phenotype - gene variant associations is huge.
🔗 Links
This jargon-less article provides an accessible introduction to pharmacogenomics
This journal article covers the past, present and future of pharmacogenomics
That’s it for this week - catch ya next time 👋