Pharmacogenomics, also known as pharmacogenetics, is a field of research dedicated to investigating how an individual's genetic makeup influences their response to medications.
Most drugs on the current market are "one-size-fits-all," and beyond dosage based on size, don't take into account the differences among people. Because of this, some patients might not benefit from the treatment. And, in some cases, they may experience negative side effects, including serious adverse reactions. These adverse drug reactions are a significant cause of hospitalisations and deaths in both the US and UK, as well as the rest of the world.
Using pharmacogenomics, researchers are able to understand how the differences in genes can affect responses to medications. By creating a link between medication effectiveness and DNA, we can better predict whether a medication will be a good choice for a particular person and which dosage will help prevent negative side effects and adverse reactions. In this blog, we discuss the crucial role genetic variations play in drug responses and why it's so important to consider this in drug development.
Researchers test which variants affect drug responses the same way that they test for variants linked with diseases: By pinpointing genetic sites linked to established drug reactions and subsequently examining individuals with unknown responses. To do this, they use multigene analysis or whole-genome single nucleotide polymorphism (SNP) profiles.
Within pharmacogenomics, there are two main determinants:
Understanding both pharmacokinetics and pharmacodynamics is crucial for tailoring drug treatments to an individual's unique genetic profile, ultimately leading to more personalised and effective medical interventions while minimising the risk of adverse drug reactions.
Researchers are still in the process of understanding exactly how genetic variants affect the body’s response to different medications. Some genetic conditions that significantly impact an individual's response to specific drugs have been extensively studied – for instance, warfarin sensitivity, warfarin resistance, and clopidogrel resistance. Warfarin, a blood-thinning medication, can exhibit varying efficacy and safety profiles in individuals due to their genetic makeup, with some individuals requiring lower or higher doses to achieve the desired anticoagulant effect. In the case of clopidogrel, a medication used to prevent blood clots, genetic factors can influence its effectiveness, potentially leading to variations in how well it inhibits platelet function. These insights into genetic conditions related to drug responses not only enhance our understanding of personalised medicine but also inform clinical practice.
DNA can affect multiple steps in process of determining how a drug works in the body:
Drug receptors: These are proteins on the surface of cells that are essential for certain medications to function effectively. Their presence and quantity are determined by DNA, which is why genetic variation can impact drug response. For instance, some breast cancers make too much HER2, a receptor, and this extra HER2 helps the cancer develop and spread. The drug T-DM1 can be used to treat this type of breast cancer and works by attaching to HER2 on cancerous cells to kill them. A healthcare provider may test a sample of a patient's tumour to check the amount of HER2. If there is a high amount (HER2 positive), their doctor might prescribe T-DM1. However, if there is a low amount (HER2 negative), T-DM1 will not work for the patient.
Drug uptake: Some medications need to be continually taken into the tissues and cells they act on. A person's genetics can affect the uptake of drugs and can mean that a drug doesn't work well and can even cause it to build up in other parts of the body. DNA can also affect the speed at which drugs are removed from the cells they act on, which can drastically affect their efficacy. An example of DNA influencing drug uptake happens with statins, a common type of drug that act in the liver to help lower cholesterol. Statins are transported into the liver by a protein made by the SLCO1B1 gene. But, some people have a mutation in this gene that causes less of a statin called simvastatin to be taken into the liver. For patients with this mutation, the drug can build up in the blood and cause muscle problems. For this reason, it's recommended for healthcare providers to check for the SLCO1B1 gene when treating high cholesterol.
Drug breakdown: Genetics may also determine how quickly a drug is broken down in the body. This can affect dosage as well as which drug may work best for the patient. An example of a medication that is affected by this would be the antidepressant drug amitriptyline, which is influenced by two genes called CYP2D6 and CYP2C19, both of which affect how quickly the body breaks down amitriptyline. A healthcare provider may therefore adjust dosage depending on the DNA of their patient to minimise adverse reactions and to make sure the drug is as effective as possible.
While pharmacogenomics is still a relatively new field, there are many examples of how it has helped create better treatments already. For instance, the Food and Drug Administration (FDA) now includes pharmacogenomic information on the labels of around 200 medications to provide guidance on dosage, side effects, or differences in effectiveness for people with certain gene variants.
A specific real-world example can be seen in cystic fibrosis treatment (CF). Cystic fibrosis is a condition caused by mutations in the CFTR gene, which affects the CFTR protein. For most people, the CFTR protein forms a channel that acts as a passageway to move particles across the cells in the body. When that protein is made correctly, this channel can open and close. However, some individuals living with CF have a mutation that causes this channel to be permanently closed. A treatment for CF called ivacaftor acts on this kind of mutation to keep the channel open. Unfortunately, not all forms of cystic fibrosis are caused by these same mutations, so this medication only works for those with this type. By using genetic testing, doctors can make more informed decisions on CF treatment and offer ivacaftor to those with these specific mutations and know not to prescribe it to patients without.
Expanding the implementation of pharmacogenomics on a broader scale presents numerous advantages for both patients and healthcare providers, while also offering significant potential for advancements in drug development. Nevertheless, there remains substantial groundwork to establish the most effective ways to scale up pharmacogenomic applications.
One promising avenue lies in enhancing data sharing and implementing standardised practices, which have the potential to expedite the seamless integration of pharmacogenomics into healthcare systems.
And, despite being a relatively new field, there is a compelling argument for incorporating pharmacogenomics into the realm of drug design and development more regularly. By tailoring treatments to individual genetic profiles, pharmaceutical companies can not only enhance the efficacy and safety of their therapies but also streamline the development process, reducing associated costs and the risk of adverse drug reactions. Ultimately, this approach has the potential to minimise healthcare expenses and safeguard patient well-being.
Drug responses can vary significantly based on our DNA. Tailoring treatments to account for this is the best way to ensure maximum efficacy, minimise wasted resources, and prioritise patient health. As a science, it brings us closer to personalised medicine and further away from a one-size-fits-all or trial-and-error approach to healthcare.
By considering genetic variations, we can better match medications to individuals, potentially reducing adverse reactions and healthcare costs. While challenges in scaling up exist, standardisation and data sharing can aid in the integration of pharmacogenomics into healthcare systems. And, prioritising this work in drug development and design will allow the field to continue to evolve, paving the way for safer and more efficient drug development.
For more on the use of genomics in drug development, download our whitepaper, "Unravelling the complexities of genomics-driven drug discovery."