Translational approaches in treatment-resistant depression based on animal model

Vol. 59 No. 3, 2018


Ileana Marinescu, Octavian Vasiliu, Daniel Vasile

An intensively researched and yet poorly understood phenomenon, both at clinical and neurobiological level, is the determinism of treatment-resistant depression. Even more controversial are the stages of approaching therapeutically this pathology because there are no evidence-based recommendations stating that a pharmacological agent is superior to another, on medium and long-term. Due to the lack of golden standard approaches, physician s experience, therapeutic alliance and a close monitoring stand as the most useful good practices in the treatment of resistant depression. The neurobiology of this pathology is incompletely characterized, and the current paper will present data derived from single-photon emission computed tomography as arguments for a better understanding of the treatment-resistance in major depression. These data have been compared with the existing data in the literature and arguments in favor of using this investigational method have been formulated. All the three cases presented are patients diagnosed with treatment-resistant major depression, each case with its own psychiatric and somatic background, and therefore with its own therapeutic approach. In all these cases, structured interviews and psychometric scales were applied in order to allow a flexible pharmacological regimen, adjusted to the patient s dynamic needs. Measurements for health-related quality of life were considered necessary for treatment-resistant depression monitoring because low values registered in this domain have important prognostic significance. Translational studies on animal models of depression support the existence of cerebral structural dysfunctions or lesions which can be correlated with clinical and neuroimaging data, allowing for the formulation of neurobiological and psychopharmacological models for treatment-resistant depression.

Corresponding author: Octavian Vasiliu, MD, PhD; e-mail:

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