Drug-induced depressive symptoms: An update through the WHO pharmacovigilance database.

BACKGROUND: Depression is a highly incident condition and some drugs have been described as inducing or worsening depression. However, literature on this topic is rare and possibly outdated. METHODS: We performed disproportionality analyses using VigiBase®, the largest pharmacovigilance database worldwide to identify drugs associated with depression. Then we excluded drugs already known as depressogenic according to American Summary of Product Characteristics (SPC). We then reviewed drug mechanism of action, scientific literature and European SPC for each drug identified to assess a level of plausibility. We measured Reporting Odds Ratio (ROR) statistically significant and superior to 1, suggesting a significant association between a drug and the reporting of depressive symptoms. RESULTS: Out of the 5237 drugs extracted on VigiBase®, we have retained 89 new drugs associated with depression. More than half of drugs of interest are from nervous system. Opicapone (ROR: 20.66 95 %CI: 15.62-27.33), and gadoversetamide (ROR 18.62, 95 %CI 9.63-35.95) were the drugs with the highest ROR. Among the 89 drugs, 38 were considered already described such as suvorexant or ivacaftor, 20 likely associated such as anti-migraines drugs or new antipsychotic drugs and 31 potentially associated. LIMITATIONS: Pharmacovigilance studies have many inherent limitations, such as under-reporting bias, notoriety effect and protopathic bias. These results are not intended to establish a causal link, only a statistical association. CONCLUSION: We found a strong statistical signal and pharmacological plausibility for 58 new depressogenic drugs. This update list of suspected drugs may prove useful for doctors faced with potential cases of drug-induced depression or to stay aware in case. Other studies are needed to confirm the list.

Will artificial intelligence chatbots replace clinical pharmacologists? An exploratory study in clinical practice.

PURPOSE: Recently, there has been a growing interest in using ChatGPT for various applications in Medicine. We evaluated the interest of OpenAI chatbot (GPT 4.0) for drug information activities at Toulouse Pharmacovigilance Center. METHODS: Based on a series of 50 randomly selected questions sent to our pharmacovigilance center by healthcare professionals or patients, we compared the level of responses from the chatbot GPT 4.0 with those provided by specialists in pharmacovigilance. RESULTS: Chatbot answers were globally not acceptable. Responses to inquiries regarding the assessment of drug causality were not consistently precise or clinically meaningful. CONCLUSION: The interest of chatbot assistance needs to be confirmed or rejected through further studies conducted in other pharmacovigilance centers.

Simultaneous determination of eight ß-lactam antibiotics in human plasma and cerebrospinal fluid by liquid chromatography coupled to tandem mass spectrometry.

Therapeutic drug monitoring of ß-lactam antibiotics is increasingly used for dose optimization in the individual patient to increase efficacy and reduce the risk of toxicity. The objective of this work is to develop and validate a fast and reliable method using liquid chromatography coupled to tandem mass spectrometric detection to quantify simultaneously amoxicillin, cloxacillin, cefazolin, cefotaxime, ceftazidime, cefepime, meropenem and piperacillin in plasma and cerebrospinal fluid (CSF). Sample clean-up included protein precipitation with acetonitrile followed by evaporation of the supernatant and reconstitution of the residue with mobile phase solvents. Eight deuterated ß-lactam antibiotics were used as internal standards. Chromatographic separation was performed on a C18 column (50 mm x 2.1 mm) using a binary gradient elution of water and acetonitrile both containing 0.1% (v/v) formic acid. The total run time was 8 min. The method was then used to perform therapeutic drug monitoring on 2221 patient plasma samples. 32 CSF samples were also analyzed. This method, with its simple sample preparation provides sensitive, accurate and precise quantification of the plasma and cerebrospinal fluid concentration of ß-lactam antibiotics and can be used for therapeutic drug monitoring.