How to Identify the Best Antidepressant? Is Genetic Testing Enough?

25 Mar How to Identify the Best Antidepressant? Is Genetic Testing Enough?

Identifying the best antidepressant for patients is not a straightforward process for healthcare providers. This is not ideal and is, unfortunately, a reality. Thankfully there are now techniques to make it more likely to get the best one, the first time.

There is significant variation in therapeutic response, and side effects, to antidepressant drugs. Several antidepressant drugs may need to be tried before an effective one, with no, or tolerable side effects are found for a patient. Between 30% and 50% of patients with the major depressive disorder do not respond to their first antidepressant trial and remission rates are as low as 37.5%. During this drug testing period, patients may experience side effects and their symptoms may not improve or even get worse. Pharmacogenetics has been introduced as a method for reducing that drug testing period.

In this article, our Chief Scientific Officer, Prof. Martin Dawes will discuss the role of pharmacogenetics in treating depression. You’ll also learn about a solution that enables the use of evidence-based pharmacogenetics at the point of care.

Let’s dive right in!

What can a person’s genes tell them about how they might react to antidepressants?

Common variations in a few genes can alter the way some antidepressant drugs are dealt with by your body. People with these genetic variations may need different doses of the drug to gain benefits and avoid harm.

An example of this is one gene called CYP2C19 and its effect on Citalopram, a commonly used antidepressant drug. One common genetic variation of CYP2C19 may lead to Citalopram being inactivated much faster than expected. This individual may need a higher dose, but those doses are unpredictable, so the recommendation is to avoid that drug and use another antidepressant drug. This variation may be present in 5% of Caucasians and 20% of Asians.

Another common genetic variant of CYP2C19 may lead to Citalopram being inactivated more slowly, and in this situation, a lower dose can be suggested. The takeaway message is that pharmacogenetic variants are quite common, have effects on common antidepressant drugs and that this information is not easy nor quick to translate and make usable in a normal clinical encounter.

How can pharmacogenetic information be integrated into drug decisions?

This is an important question. The evidence about the utility of pharmacogenetic tests in certain conditions has been assembled by a couple of international consortiums, one in Europe and one in the USA. The group in the USA, the Clinical Pharmacogenetics Implementation Consortium, CPIC for short, has developed guidelines on the genetic variants and how this information can be used. A companion database, PharmGKB gives detailed information about genetic-drug associations that inform these guidelines. These two sources of information are very useful to clinicians, but also demonstrate the complexity of translating pharmacogenetic information for clinical care.

Clinical decision support tools, or, more specifically, medication decision support tools have been made to assist pharmacists and physicians in this process. They tabulate the genetic variation with the drugs and suggest drug dose modifications. They often include detailed information about the variants and the evidence supporting their information. Drug decision support tools range from paper reports to sophisticated software applications. Individuals receiving pharmacogenetic-guided therapy with decision-support are 1.71 times more likely to achieve symptom remission relative to individuals who received treatment as usual. To put this into perspective this is a similar effect size as comparing an antidepressant with a placebo.

How can pharmacogenetic information be more actionable?

Pharmacogenetics is only one variable that might affect how you react to a drug. Your kidneys, liver, the other drugs you are taking, the diseases you may have, and even whether you smoke can all affect how some drugs work in your body. There are some drugs used to treat depression, for example, Sertraline, that need to have the dose adjusted if you have liver disease. Another commonly used depression treatment, Bupropion, needs the dose adjusted if you have kidney disease. Many drugs used for common conditions such as diabetes or arthritis, interact with drugs used to treat depression.

While a static PDF report is useful at telling the pharmacist or physician about pharmacogenetics it is not possible to integrate these other important variables. This is where interactive medication decision support software comes into play. Advanced software can process every data we have of the patients and generate a list of personalized drug options

For example, the pharmacist or physician wants to know what drugs can be safely prescribed for you, taking into account everything including liver, kidney, drug-drug interactions, and pharmacogenetics. Software programs can do exactly that, taking into consideration thousands of pieces of information and combining this knowledge with all your relevant variables. The list of drug options is displayed with doses adjusted for your variables to maximize the chances of a positive outcome.

(Related Post: Which Antidepressant Does Not Cause Weight Gain? [Interview])

Conclusion

Pharmacogenetics does and will continue to play an essential role in eliminating the testing period of depression treatment. However, back to the key question, is it really enough?

More and more people are recognizing pharmacogenetics as the crucible of personalized and precision medicine. But the adoption is much more complicated than we may realize. Pharmacogenetic information should never replace other variables that are used to make treatment decisions. It should be an addition to those variables, which makes it harder to translate, and include, in a normal clinical encounter.

There is a solution that can process all these crucial data points, a medication decision support tool. It gives healthcare providers the right amount of information to explain to patients the rationale behind selected drugs and the ones that were ruled out. For patients, it enables them to ask more questions and be in control of their own health. Ultimately, having a medication decision support tool allows patients and healthcare providers to focus on shared decision making about drug options which are safe and optimized for success.

Over to you…

To learn even more about how our clinical decision support software works, read this blog. 

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