What is pharmacogenomics?
The Académie nationale de médecine in France provides a simple and enlightening definition of pharmacogenomics: “Contrary to pharmacogenetics, which studies how genes affect the way a person responds to medications, pharmacogenomics focuses on the effects of the medication on human genes.”
There lies the distinction between the often-confused pharmacogenetics and pharmacogenomics.
Both fields, however, strive to develop safe and effective drugs, as well as dosages that are adjusted for each individual.
Pharmacogenomics, which encompasses pharmacogenetics, is identified with the trend of personalized medicine. Rather than offering a single treatment, it is proactive and tailored to the individual.
Tailor-made benefits with personalized medicine
Typically, medical treatments are focused on treating the average person.
This approach leads to good results for most people who are receiving treatment, but some others will not get the desired results. In certain cases, some treatments can even be harmful.
Personalized medicine takes into account genetic and biological factors, in addition to other factors related to lifestyle, to prevent disease or determine the best approach to treatment.
This approach appears promising for:
- Certain types of cancer
- Cardiovascular and degenerative neurological diseases as well as psychiatric disorders
- Alzheimer’s disease
But there is still a lot of work to be done.
Benefits of pharmacogenomics
Pharmacogenomics allows patients to receive the right treatment and the right medication at the right time.
It allows for a heightened tolerance to medication and, as a result, a better quality of life for patients.
It reduces the risks of complications by minimizing unwanted side effects and toxicity. This in turn reduces hospitalizations and deaths.
Over the long haul, it reduces costs associated with managing our healthcare system.
Lastly in cancer treatment, the introduction of targeted therapies in line with specific and predictive biomarkers allows for more efficient therapy, a higher overall survival rate, significantly higher tolerance and less toxicity than traditional chemotherapy.
Difficulties related to applying pharmacogenomics
1. Consent from individuals to test their genetic code
Some people are concerned that revealing their genetic code to computerized healthcare systems would be more harmful than beneficial.
They fear that if their genetic code reveals that they are at a higher risk for certain types of diseases, and if that information falls in the hands of employers or insurers, they will have trouble finding a job or purchasing insurance.
2. Detecting variants
A person's medical history can help determine whether a particular drug can provoke an adverse reaction. But medical history doesn’t provide many clues.
However, our age, genetics, race, build, the way our kidneys and liver function as well as certain diseases all play a part in how a drug is absorbed, metabolized and eliminated from our body.
Some variants of RNA molecules and the types of proteins in the cells of a person who is ill can also help to predict the effectiveness of a drug or an adverse reaction.
Lastly, certain enzyme deficiencies may cause a drug to accumulate in your body and cause significant toxicity.
And there are many variations. The difficulty therefore lies in detecting the variants, which can take a long time.
3. Mass production of prescription drugs
Even though there are more and more targeted therapies in oncology, smaller drug or vaccine batches need to be produced, but they must be adapted to certain genetic codes.
For pharmaceutical companies, turning to pharmacogenomics could therefore mean an overhaul of their production model.
4. Analysis of genetic variations
Doctors who wish to prescribe drugs based on pharmacogenomics must learn to analyze the genetic variations of each patient to determine the right medication and dosage.
Pharmacogenomics has been drawing interest from researchers. Some are studying the effectiveness of the drugs and the occurrence of side effects based on gender. There is still a long way to go, but the current research results are promising.