Genetika+: precision medicine solutions for mental health

Claudia Albeldas, Niv Cohen, Sari Natan, Nadav Askari, Daphna Laifenfeld & Talia Cohen Solal


Genetika+ is developing a precision medicine tool to optimize the treatment of depression by helping physicians find the best drug therapy for their patients. The tool builds on traditional pharmacogenetics, introducing a ‘brain-in-a-dish’ screening platform for each patient that will overcome the challenge of limited pharmacodynamic knowledge of pharmacogenetics (PGx).

In addition to PGx, our platform integrates patient data with innovative blood-derived patient neurons to test all categories of antidepressants and predict the best drug for each patient. This offers patients optimal drug treatment, allowing a faster response, fewer side effects and lower dosing.

Genetika+ is a fast-growing women-led company founded in 2018 in Israel with the mission of improving patient outcomes in mental health, with the first indication being major depression. Realizing that each patient is unique, Genetika+ has developed a truly personalized medical tool, a simple blood test that predicts which medication an individual will respond to and thus better treat depression and help physicians find the shortest route to healing for their patients. Dr Talia Cohen Solal, the CEO and founder of Genetika+, is an alumnus of Oxford University, University College London and Columbia University, and is bringing her expertise from the bench to this technology, together with her cofounder Dr Daphna Laifenfeld, previously the head of personalized medicine at Teva Pharmaceuticals. Together they lead a team of 17 scientists and professionals dedicated to providing a cutting-edge approach for solving one of the most widespread diseases.

The challenge

Major depressive disorder (MDD) is the largest contributor to the reduced of health-related quality of life [1], with up to 14 life years lost per patient. It is an extremely heterogeneous disease with varied clinical manifestations and treatment responsiveness stemming from complex genetic and environmental factors unique to each individual’s phenotypes [2].

Depression affects 300 million people globally and was the second leading cause of disability by 2020 [3], contributing to 917 accumulated years lost per 100,000 people [4]. Nevertheless, three out of four people suffering from depression do not receive adequate treatment [5].

The lack of information about the unique neuronal properties underlying each patient’s depressive disease has historically resulted in a prescription by the physician from a very broad drug selection, based only on patient clinical observation and a brief interview. As a result, 63% of patients try multiple medications, and a third of patients will not respond even after two rounds of drug testing [6].

With more than 70 antidepressants to choose from and with each antidepressant requiring weeks before response levels can be determined, the patient loses months to testing until the right treatment is found for them and, in the process, suffers the devastating effects of depression and potential side effects of disease comorbidities, job loss and social impacts.

Materials & methods

Ten MDD patient LCLs from the NIH-supported “STAR*D” study were obtained from NIMH Repository and Genomics Resource, a centralized national biorepository for genetic studies of psychiatric disorders. The STAR*D study ( Identifier: NCT00021528) focused on nonpsychotic MDD in adults seen in outpatient settings.

The primary purpose of this research study was to determine which treatments work best if the first treatment with medication does not produce an acceptable response. The study was supported by NIMH Contract #N01MH90003 to the University of Texas Southwestern Medical Center21. All LCLs were derived from MDD patients who did not respond to citalopram on level 1 of the STAR*D study. On level 2, all ten patients were treated with bupropion, to which n = 5 responded and n = 5 did not (Table S1).

Patients were defined as responders if they reached over 50% reduction in their Quick Inventory of Depressive Symptomatology, Self-Report (QIDS-SR) score, and their QIDS score was <7, following the bupropion treatment period.

Cells were thawed and maintained in LCL media composed of RPMI 1640 (Thermo Fisher) supplemented with fetal bovine serum (10%) (Thermo Fisher), 1 mM Glutamax (Thermo Fisher), 50 U/ml penicillin and 50 μg/ml streptomycin (Biological Industries) in T25 cell culture flasks at 37 °C, 5% CO2. Cells were observed daily under a light microscope and passaged once culture media became acidic.

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