A review of a recently published guidelines' "strong recommendation" for therapeutic drug monitoring of olanzapine, haloperidol, perphenazine, and fluphenazine

Automated Interlaboratory Comparison of Therapeutic Drug Monitoring Data and Its Use for Evaluation of Published Therapeutic Reference Ranges

Therapeutic drug monitoring is a tool for optimising the pharmacological treatment of diseases where the therapeutic effect is difficult to measure or monitor. Therapeutic reference ranges and dose-effect relation are the main requirements for this drug titration tool. Defining and updating therapeutic reference ranges are difficult, and there is no standardised method for the calculation and clinical qualification of these. The study presents a basic model for validating and selecting routine laboratory data. The programmed algorithm was applied on data sets of antidepressants and antipsychotics from three public hospitals in Denmark. Therapeutic analytical ranges were compared with the published therapeutic reference ranges by the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) and in additional literature. For most of the drugs, the calculated therapeutic analytical ranges showed good concordance between the laboratories and to published therapeutic reference ranges. The exceptions were flupentixol, haloperidol, paroxetine, perphenazine, and venlafaxine + o-desmethyl-venlafaxine (total plasma concentration), where the range was considerably higher for the laboratory data, while the calculated range of desipramine, sertraline, ziprasidone, and zuclopenthixol was considerably lower. In most cases, we identified additional literature supporting our data, highlighting the need of a critical re-examination of current therapeutic reference ranges in Denmark. An automated approach can aid in the evaluation of current and future therapeutic reference ranges by providing additional information based on big data from multiple laboratories.

Striatal functional connectivity in psychosis relapse: A hypothesis generating study

Most individuals with psychotic disorders relapse over their course of illness, yet the neural processes that may lead to symptom worsening are poorly understood. Importantly, such processes could be potentially affected by antipsychotic adherence status upon relapse (i.e., relapse despite ongoing antipsychotic maintenance vs following antipsychotic discontinuation), reflecting distinct mechanisms. As a first foray into this question, we aim to compare the striatal connectivity index (SCI), a biomarker derived from striatal resting state functional connectivity predictive of treatment response, by adherence status upon relapse. In order to confirm adherence status upon relapse, we compared individuals treated with long-acting injectable antipsychotics upon relapse (i.e., breakthrough psychosis) (n = 23), with individuals who had decided to interrupt antipsychotic treatment and then relapsed (n = 27), as well as healthy controls (n = 26). We acquired for each individual >10 min of resting state fMRI, to generate functional connectivity maps. Region of interest (ROI) analyses were conducted to calculate SCI values for each participant. These values were entered as dependent variable in a linear regression adjusted for sex and age for which adherence status was the independent variable. Individuals in the breakthrough psychosis group had significantly lower SCI values than healthy controls (Cohen's d = 0.99, p < 0.001), and non-adherent individuals upon relapse (Cohen's d = 0.58, p = 0.032), whereas non-adherent individuals had also trend level lower SCI values than healthy controls (Cohen's d = 0.44, p = 0.09). These results suggest the hypothesis that striatal functional connectivity may be aberrant in psychosis relapse, and that this dysfunction may be greater among individuals who developed relapse despite ongoing antipsychotic treatment.