Combining AI and genetics for better depression care

By - 2 December 2019

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Finding the right antidepressant can be a frustrating journey…

Depression is one of the most prevalent mental illnesses in the world. According to the World Health Organisation, over 300 million people in the world suffer from depression. On top of this, it can be challenging for a patient and their doctor to find the proper antidepressant treatment. Many individuals who suffer from depression go through a long trial-and-error period, testing numerous antidepressant treatments until they find the right one. It can be a discouraging and lengthy process for both sides.

Digital and tailored solutions for mental health

Historically stigmatised, mental health is a topic that is slowly but surely receiving more attention from the media, governments, businesses and the general public. As such, more information has become available over the years and with it, more awareness of the pervasiveness and factors of mental illness in society. Naturally, startups have also begun developing solutions to help diagnose, manage and treat mental illnesses. 

Several startups have entered the market aiming to provide doctors with the proper tools to make faster, more accurate diagnoses, and provide the right treatment for their patients. The ehealth sector is expected to grow at a 30% CAGR between 2018 and 2025. The growth is even stronger when it comes to the use of artificial intelligence in the ehealth sector (50% CAGR for the same forecast period). The mental health segment has seen numerous startups rise to the occasion and create digital solutions to tackle a variety of illnesses and disorders, including depression.

Startups like Genomind have focused solely on genetic tests to help healthcare professionals treat patients suffering from mental illnesses, including depression. Others have incorporated machine learning, such as Mindstrong Health, which helps diagnose patients through an innovative process known as digital phenotyping. Numerous companies have also tackled online therapy, such as Talkspace, or online medical consultations, such as Babylon Health.

Many of these startups are a part of the current growth observed in personalised healthcare. Healthcare professionals now have the ability to deliver highly personalised treatment to their patients by accessing genetic information alongside other key health data that is increasingly gathered through new technological means, such as the use of wearable devices to monitor a person’s vitals.

Artificial intelligence to tackle antidepressant treatments

The rated startup Taliaz is one of the emerging players addressing tailored treatment options for depression, by leveraging genomics and proprietary artificial intelligence models. The Israeli startup has developed Predictix, a platform meant to help clinicians provide their patients with the right antidepressant treatment. Healthcare professionals using the solution receive a personalised report for each patient that includes predictive information about how they might react to available antidepressant medication. The results are based on the patient’s genetic makeup and health records in addition to data from the STAR*D collaborative study on the treatment of depression.

The process is simple, patients need only provide a saliva sample and fill out a questionnaire. Healthcare professionals, on the other hand, access the relevant reports through the startup’s software. The genetic analysis provided by Taliaz helps doctors make a more confident decision regarding which antidepressant treatment to prescribe, which in turn reduces the time needed to caliber the right treatment and consequently decreases the chances of secondary effects.

Taliaz placed in the top 20% of all startups rated by Early Metrics. One of the key strengths we identified was the expertise behind the project: Dekel Taliaz, the CEO, has a PhD in Neurobiology and Behavior, in addition to experience conducting research on genetic mechanisms in mood disorders. Going forward, the growing number of competitors on the market might become a key challenge for the startup, as it will make it harder to secure market shares over time. However, this innovative player is still well-positioned to grow in the future.

Overall it is great to observe that Taliaz and many other ehealth startups are taking important strides towards more efficient and tailored treatment when it comes to depression. Hopefully, more solutions will also arise from this trend to prevent this mental illness; for instance, with new business and school settings better suited to decrease stress, a major trigger of depressive episodes.

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