AI Rapidly Evaluates Antidepressant Efficacy

The traditional method of trial and error, which often involves enduring adverse side effects, in the quest to find the suitable antidepressant could soon become obsolete for individuals dealing with major depressive disorder. A groundbreaking artificial intelligence model has emerged capable of assessing the effectiveness of a drug for an individual within a mere week.

Liesbeth Reneman, Professor of Neuroradiology at Amsterdam University Medical Center (UMC), emphasized the significance of this development for patients. She noted, “This is crucial information for patients, as typically it takes six to eight weeks to determine if an antidepressant will be effective.”

Revolutionizing Depression Treatment

In the latest clinical application of artificial intelligence, researchers from Amsterdam University Medical Center (UMC) and Radboud UMC have devised an algorithm capable of assessing the long-term effectiveness of a particular antidepressant based on patient MRI scans and other relevant data. Despite approximately 11% of the US population being prescribed medication to manage depression, roughly 60% struggle to find an appropriate medication initially. Due to the time and side effects involved in this process, many individuals may refrain from attempting a second or third medication.

The researchers aimed to determine whether such an AI model could accurately predict the efficacy of the selective serotonin reuptake inhibitor (SSRI) sertraline, commonly known as Zoloft, which is the most frequently prescribed antidepressant in the US.

For this research, the team utilized data from a prior study conducted in the United States involving 229 patients with depression. This data encompassed MRI brain scans and clinical records collected before the administration of either sertraline or a placebo. The AI algorithm analyzed this dataset, focusing specifically on the anterior cingulate cortex and symptom severity.

Eric Ruhé, a psychiatrist at Radboud UMC, explained, “The algorithm indicated that individuals with increased blood flow in the anterior cingulate cortex, a brain region associated with emotion regulation, would benefit from the medication.” He further noted that the severity of symptoms at the second assessment, conducted one week after initiating treatment, confirmed this prediction.

AI Identifies Effective Antidepressant, Mitigating Months of Trial and Side Effects

As a result, the AI determined that sertraline would be effective for only one-third of the participants, sparing the remaining two-thirds from undergoing up to two months of “wait and see” with potential side effects. Although antidepressants may take up to six months to achieve full efficacy, serious side effects can persist for a considerable duration, significantly impacting daily life, often comparable to the disorder itself.

“Through this approach, we can already prevent two-thirds of potentially incorrect prescriptions for sertraline, thereby improving the quality of patient care,” Reneman stated. “This is particularly important considering the drug’s associated side effects.”

Managing major depressive disorder poses challenges due to its multifaceted nature, compounded by the array of medical interventions available, such as SSRIs, SNRIs, atypical antidepressants, tricyclic antidepressants, and MAOIs.

While the algorithm currently focuses on sertraline, the researchers aim to not only personalize it further but also extend its application to a diverse range of depression medications.

Read the original article on: New Atlas

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