Therapie最新文献

Objective: To describe the clinical characteristics of depressive disorders and suicidality not associated with sexual dysfunction among users of finasteride 1mg/day for androgenetic alopecia.

Methods: A retrospective descriptive analysis was conducted using data from the French National Pharmacovigilance Database (BNPV) from 1985 to May 2024. Cases were selected based on the presence of depressive or suicidal symptoms, classified in Medical Dictionary for Regulatory Activities (MedDRA) high-level group terms, with no co-reported sexual dysfunction.

Results: Forty cases of depression or suicidality were identified in men treated with finasteride, with a median age of 31years. Most cases (62.5%) were classified as serious. In half of the cases, symptoms occurred within 9months of treatment initiation. Suicidality (ideation or attempts) was present in 40% of cases. Among patients who discontinued treatment, 45.2% reported symptom improvement. In unresolved cases (n=10), the median persistence of symptoms after withdrawal was 20.2months. A positive rechallenge was observed in two patients. Only 22.5% had a personal or family psychiatric history, and 17.5% reported a significant impact on quality of life.

Conclusion: While adverse psychiatric drug reactions, including depressive symptoms and suicidality, are often reported in conjunction with sexual dysfunction, this study highlights the severity of depressive effects associated with finasteride, particularly the risk of suicidality even in the absence of associated sexual dysfunction or psychiatric history. The persistence of depressive symptoms sometimes beyond 20months post-discontinuation, underscores the need for adapted management and long-term monitoring. Finally, these findings highlight the need for thorough psychiatric evaluation at the time of prescription and ongoing suicide risk assessment throughout the course of treatment.

In recent years, artificial intelligence (AI) has emerged as a powerful tool in healthcare and is becoming increasingly prevalent across all medical and paramedical disciplines. AI has numerous applications in pharmacology. This narrative review explores the increasing importance of AI in three key areas of pharmacology: pharmacokinetics (PK), pharmacodynamics (PD), and pharmacovigilance (PV), as well as pharmacology education. We conducted a literature review enhanced by the ARTIREV hybrid bibliometric tool to identify and analyze key advances, applications, and challenges with AI integration in this field. In PK, machine learning and hybrid approaches improve the prediction of individualized drug exposure, support model-informed precision dosing and handle irregular and sparse data through architectures such as recurrent neural networks and NeuralODEs. In PD, AI facilitates a shift towards an era of precision and personalized medicine by enabling the development of drug effect models and considering interindividual variability. It also makes it easier to implement adaptive dosing regimens that are tailored to various constraints. Regarding PV, AI enhances the detection of adverse drug reactions, the identification of safety signals at the population level and the assessment of preclinical toxicities through the analysis of unstructured data, particularly from electronic health records. Despite their potential, AI models face several significant limitations. These include the quality of training data, limited explainability due to the "black box" effect and a lack of external validation of the models developed. Altogether, this review emphasizes the role of AI in pharmacology and the necessity of training future professionals to ensure the safe and validated use of AI in personalized medical applications.

Objective: The risk of mucocutaneous ulcerations associated with nicorandil remains a well-described adverse effect (AE). In case of a suspected AE, early diagnosis and immediate discontinuation of nicorandil are recommended. The aim of this study is to update pharmacovigilance data.

Methods: Two sources of data were used for this study over the period from January 2017 to the end of November 2024: pharmacovigilance reports registered in the French PharmacoVigilance Database (FPVD) and data related to this AE and nicorandil extracted from the Toulouse hospital discharge database [programme de médicalisation des systèmes d'information (PMSI)].

Results: We collected a total of 62 cases: 28 cases were registered in the FPVD and 34 additional cases could be identified in PMSI (n=62). None of these cases were reported to the Toulouse Pharmacovigilance Center. Patients were aged 56 to 97 years (sex-ratio 0.94). Nicorandil was discontinued for 36 patients (11 immediately). Six patients died, three of them despite nicorandil discontinuation, mainly due to digestive complications or sepsis. In 61% of FPVD cases (n=17) the AE was classified as severe. The median time to onset of the ulceration was 407 days (IQR: 123 to 1826 days). Cutaneous ulcerations were mainly localized on the lower limbs and mucosal ulcerations mainly affected the oral and digestive mucosa.

Conclusion: Despite a decline in nicorandil sales since 2017 and several communications from the health authorities, our findings indicate the persistence of serious adverse reactions with nicorandil. Delayed discontinuation of the drug results in unnecessary investigations and potentially fatal outcomes. This study has shown that the PMSI and then the Clinical Data Warehouse (CDW), operational at the Toulouse Universitary Hospital Center since 18 June 2025, is a data source that contributes to reducing the under-reporting rate of unknown, albeit "expected" AE and to confirming the persistence of a validated pharmacovigilance signal.