Which Antidepressant Does Not Cause Weight Gain? [Interview]

Which Antidepressant Does Not Cause Weight Gain? [Interview]


“I don’t like how this antidepressant makes me feel. I want to switch to something else. Which antidepressant doesn’t cause weight gain?”

Perhaps “citalopram” comes to mind first because it has a lower risk of weight gain. However, for a patient who has an ultra-metabolizer of the CYP2C19 gene, citalopram may not work so well. To put patients’ care and safety first, healthcare providers need to consider all variables of prescribing instead of looking at patients’ information in silos. And this provides accuracy, if not precision, in treatment options replacing a trial and error approach. Clinical decision support software, or, more specifically, medication decision support software, like TreatGx, enables just that! 

In this interview with our Algorithm Team Manager, Andrea Paterson, she talks about the exciting updates to our TreatGx software, and how to use it to select the best medication options for patients with depression. 

Let’s get started with the conversation! 

What are the new updates? 

We’ve spent several months enhancing and updating the depression treatment algorithm in the TreatGx software to make it easier for clinicians to treat complex patients with depression. 

We pride ourselves in developing TreatGx, our precision prescribing software (clinical decision support software), with a condition-specific approach. This approach allows us to tailor the medications and doses we include for each condition to take into account effectiveness, safety, and other factors that might influence the selection of one medication over another. In addition to condition, we also take into account genetics, kidney function, liver function, current medications, and many other patient factors.

Previously, our depression algorithm only included initial treatment options. Over the last few months, our team has invested over 500 work hours in adding new features and content to the depression algorithm. It has been a rewarding journey, and to now see the fruits of our labor, enabling efficient and proper care in clinical settings, is super exciting. 

Taking Side Effects Profiles Into Account 

For all of the antidepressants in the algorithm, we added a comprehensive side effects profile, which includes 10 of the most common side effects people experience when taking these medications. Many of these side effects can cause people to stop taking their medications and addressing adherence is a key objective of our solutions, and a topic we have written about before.

The dynamic side effect profiles include the risk of experiencing each of the side effects, rated by low, moderate, or high risk:  

  1. Anticholinergic Effect
  2. Sedation
  3. Insomnia/Agitation
  4. Weight Gain
  5. Sexual Dysfunction
  6. Nausea/Diarrhea
  7. Orthostatic Hypotension
  8. QTc Prolongation
  9. Lethality in Overdose
  10. Discontinuation Syndrome

Crucially, we can now sort all the antidepressants by side effect profiles from low to high risk for a particular side effect. As far as we know, this is the first of a kind in online clinical decision support software and was not unchallenging, given all the other parameters included in our algorithms. We will extend this type of functionality elsewhere based on user feedback.

One of the issues in depression treatment is enabling people to continue their antidepressants long enough to see an improvement. Often this is improved if we can tailor their therapy to avoid side effects they consider unacceptable. Being able to select antidepressants that people can tolerate is an essential feature of depression treatment. The side effects sorting function allows prescribers to choose medications based on the risk of experiencing one of the side effects above, from the lowest risk + to the highest risk +++

Taking Treatment Strategies Into Consideration

We’ve also added two new treatment strategies in the depression algorithm. Prescribers can now easily access information on how to switch antidepressants and augment their current antidepressant therapy. In addition to a tailored list of medication options for each strategy, there are detailed descriptions for switching between antidepressants from sources, including Rxfiles and SwitchRx. These sources provide excellent information on how to change from one medication to another while minimizing the risks of side effects and worsening symptoms. 

For patients who are getting a partial improvement with their antidepressant, the augmentation strategy can be used for augmentation or adjunctive treatment rather than stopping and switching medications, which may lead to a worsening of symptoms. We focus on the ergonomic and clinical workflow design, which both supports and enables advances in health care practitioner efficiencies.

How did your team accomplish these updates?

It involved a lot of teamwork between the algorithm team, the software development team, and our geneticists. Both the genetics team and the software team were integral in supporting us in achieving these updates. 

As part of our update, we added some of the newest medications on the market for depression treatment. We worked with our geneticists to determine if any pharmacogenetic variants affected those drugs. If there were relevant pharmacogenetic variants, they helped us figure out how to utilize genetics in a clinically relevant way. Our software development team also helped us a lot in adding the functionality to sort treatment options by side effect profiles, and making the software more user-friendly. 

To piece the information we needed for the update together, we started with an extensive review of guidelines and literature on depression treatment, from treatment guidelines to individual scientific papers. High-grade evidence is one of our base tenets of development and maintains our exceptional level of clinical credibility. Once we had a better idea of how we wanted to shape the algorithm, we also brought in clinical experts to consult with us. We asked a pharmacist and a renowned psychiatrist to share their input on how to best approach depression treatment and consulted with them throughout the development of the new depression algorithm to get their thoughts and feedback.

What we quickly realized is that there wasn’t a considerable amount of clinical data out there to guide the choice of which antidepressants are the most likely to be effective or to guide the choice of treatment strategy. There were also lots of differing opinions among clinical experts in the field. Therefore, our team had to do a lot of critical appraisal of the studies that were available and spent long hours constructing the treatment algorithms for each treatment strategy. In areas that were lacking in clinical evidence, we used the clinical opinion to rank choices, or we listed all the potential medications to give clinicians as much information as possible for them to select the best medication for their patients.

Why is identifying side effects and treatment strategies so necessary in treating depression? 

One of the most significant issues that patients often have with antidepressants is intolerable side effects. Many antidepressants cause side effects such as insomnia, weight gain, or nausea. And for patients who are older or have other heart issues, they can experience something called QTc prolongation, which can potentially be fatal. Therefore, a lot of these side effects are crucial to take into account when prescribing medications for depression. 

These days, there are so many pieces of information clinicians need to consider when prescribing medications—they might consider things such as genetics, kidney function, liver function, weight, and other medications and conditions. All this information is essential to selecting a safe and effective medication, but patients may not take the medication at all if it causes them to experience certain side effects.  

Bringing all the variables of prescribing together in an easily accessible way, TreatGx gives clinicians everything they need to start a conversation with patients. The shared-decision making not only allows both providers and patients to be aware of the risks but also the benefits of using an antidepressant. We know that no prescription has a benefit without potential side effects.

Most often, patients have a better experience with their medications if they know ahead of time what side effects to expect. They are more likely to continue with the medication if they have been involved in selecting their treatment and are aware of the potential risks. They are also more likely to maintain adherence if the medication choice was optimized and personalized for them.

In TreatGx, we give prescribers two different pieces of information that are essential to treating depression. For all antidepressants, we provide the side effect profiles of the 10 most common side effects and a scale from low risk to high risk. If there’s a particular side effect that the patient wants to avoid, you could then sort the medications by the lowest risk to the highest risk of that side effect. 

For example, if a patient will not take an antidepressant if it causes weight gain, clinicians can use TreatGx to sort the antidepressants by weight gain. Prescribers can see which antidepressants have the lowest risk. Then, they can take a look at the side effect profiles to figure out what other side effects might be shared and avoid other ones that might be less acceptable to patients.

Why are these updates important in supporting healthcare professionals?


For healthcare providers, these updates will be time-saving. As a clinical pharmacist myself, it can take a long time to comb through all the potential drug treatments and find the most appropriate one for my patient, who’s starting a new antidepressant. That’s especially true when the patient has tried the typical SSRI class of medications first, and prescribers are trying to figure out what the next best option is. It can be hard to compare all the antidepressants for a particular side effect at once while also considering other factors like genetics and kidney function. When seeing patients, healthcare providers can tailor the dose based on their kidney function and genetics using TreatGx, without having to look up each medication separately. I think those time-saving opportunities will be a big draw for this. 

I also think patients often stop medication if they’re experiencing something unexpectedly that they think is a dangerous side effect. Our recent updates allow healthcare providers to educate patients about potential side effects and why certain medications are prescribed to them. With the right education and tools, patients will better understand the rationale behind each selected drug. Hence, they’re more likely to persist with the medication and get a benefit. I think patients will be more satisfied with their healthcare providers if they can feel that they are getting better. 

Another benefit is that providers can have a sense of ease because they know that our software includes most medications to treat depression. And our software also takes into consideration the different types of treatment strategies, whether this is an initial treatment, switching between treatment, augmentation, or adjunctive therapy. All the essential information is just right at the providers’ fingertips to ensure they are providing the best quality of care. 

(Related Post: Mental Illness Sucks! Why is Mental Health So Important?)  

How will these updates impact patient experience?

When it comes to healthcare, putting patients first is what matters. Therefore, we developed depression updates with the patients in mind. Ultimately, the goal of our clinical decision support software is to help improve the quality of patient care and experience. 

From the patients’ point of view, they will be more likely to continue with medication if they know what to expect. Our software’s ability to let prescribers sort medications based on side effect profiles enables shared decision-making between patients. The patients decide which side effects are most acceptable to them, and then prescribers select drugs based on that information. The shared decision-making process empowers the patients to take control of their health, be more inclined to follow through with their prescriptions, and eventually get better. 

What we often see in mental health cases is that it can take weeks to months for patients to experience improved depression symptoms. The prolonged symptoms can impair not only patients’ quality of life but also their ability to work, to care for kids and other family members, and their overall quality of life and happiness. Our software can help cut out some of that guesswork by incorporating all the variables of prescribing and the different treatment strategies. Moving from guesswork to personalized treatment options will not only improve patient safety but also decrease their likelihood of experiencing adverse drug events. The feedback from patients, customers, and partners have been overwhelming.

What are your team working on next? 


Next step, we’re working on a new module: the medication review module. We created this module in response to customer feedback.  

Many patients will get a genetic test to see what current medications may need to be changed. And we often tell patients, “if you’re taking medications already, you know how your body is going to respond to them.” In that case, pharmacogenetic information might not tell you any more than what you already knew. But for a depression patient who’s taking an ineffective antidepressant, he/she can find out if genetics may affect their potential to respond to this or other medications. By using the medication review module, providers can obtain this patient’s pharmacogenetic information, along with age, kidney function, liver function, weight, and an entire list of current medications. The medication review module will then generate a list of potential issues with each of their drugs for consideration.

There are three key things that we’re looking at: 

One is the gene-drug issue. For instance, from a pharmacogenetic test, we found out that a patient is a CYP2C19 ultra-rapid metabolizer. In this case, the patient might not respond to citalopram as well as other people will to it. If they’ve been on it for an adequate trial, it is probably better to try to choose a different drug. They can then use TreatGx software to find the best potential medication for them.  

In other cases, there may be a potential dosage adjustment because the patient’s kidney function had worsened since starting the medication.

Lastly, for patients with mental health issues who are experiencing poly-pharmacy, our medication review module looks through all the variables and identifies de-prescribing opportunities. Here, we are looking at medications that might not be necessary anymore. Some of which we can potentially eliminate to help the patient reduce their risk of side effects, drug-drug interactions, and just their pill burden in general. For the payer, it is an opportunity to reduce health care spending while improving the quality of care.

Over to you…

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

And if you’re interested in learning more about the increasing role of pharmacogenetics in treating depression, subscribe to our updates below!

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