Background: Clozapine is the most effective antipsychotic but requires careful titration to therapeutic blood levels. Methods to predict therapeutic doses are based on population data. Aims: We aimed to construct a model based on genetic variants which accurately predicted plasma levels for clozapine. Method: We measured clozapine plasma levels in patients on a stable dose of clozapine who were known to be fully compliant. Measured plasma levels were adjusted for sampling time and dose. Hepatic enzyme variants were analysed and models were constructed to predict the required dose. These predictions were compared with a standard population-based algorithm. Results: We measured plasma clozapine concentrations in 18 adherent patients on stable doses of clozapine and recorded the exact timing of sampling. For the algorithm-predicted dose, the mean difference was −49.9 mg/day ((SD 155.9), r = 0.36) from the actual dose required to give a plasma concentration of 0.35 ng/ml. The gene variant activity score predicted a dose for which the mean difference was −43.5 mg/day ((SD 140.1), r = 0.55). For the gene variant activity score with omeprazole correction predicted dose, the mean difference was −31.0 mg/day ((SD 140.8), r = 0.54), and with the gene variant CYP1A2 inducibility predicted dose the mean difference was 44.9 mg/day ((SD 160.8), r = 0.32). Conclusion: Our gene variant activity score with omeprazole correction gave the best estimate of the clozapine dose required to achieve a minimum therapeutic plasma concentration. The use of this model will allow safer titration of clozapine and may reduce the need for plasma-level monitoring during titration.

Introduction. Infective endocarditis (IE) is a potentially life-threatening infection, the incidence of which has in creased in recent decades, particularly among elderly patients with comorbidity. The primary objective of this study was to evaluate the effectiveness of dalbavancin in the consolidation therapy of IE in patients with comorbidity six months after the end of treatment (EOT). Material and methods. An observational and retrospective study was conducted on patients with a Charlson Comorbidity Index (CCI) ≥ 3 who were diagnosed with IE and received consolidation therapy with dalbavancin. Results. Forty-eight patients were included, 58.3% were male, mean age of 76.2 years (IQR: 66-88), and a mean age adjusted CCI of 6.5 (IQR: 5-7.5). Definite IE was diagnosed in 77% of cases. The most frequently isolated microorganisms were Staphylococcus aureus (45.8%) followed by Enterococcus spp. (31.3%). Complications of IE were observed in 67.7% of cases, and cardiac surgery was performed in 27% of patients. The primary reason for using dalbavancin was outpatient parenteral antibiotic therapy in 85.4% of cases. The effectiveness at EOT was 93.8%. At six months, six IE-related deaths, four unrelated deaths, and two IE relapses were observed. The effectiveness was 77%. Adverse effects related to DBV were reported in 4.2% of cases, of which 2% were considered serious. Conclusion. Dalbavancin has proven to be an effective alternative as consolidation antibiotherapy for IE in elderly patients with comorbidity. Moreover, a very favorable safety profile with few associated adverse effects has been observed in this population.

Abiraterone acetate is a potent and irreversible inhibitor of cytochrome p450 17A1 that suppresses androgen synthesis. It is approved for chemotherapy-naive and docetaxel-treated patients with metastatic castration-resistant prostate cancer. We describe the protocol for use of abiraterone in metastatic castration-resistant prostate cancer chemotherapy naive patients has been implanted in our centre and we review the cases of those patients whose adverse effects have forced the discontinuation of treatment. The side effects fit the safety profile of abiraterone, speed of their appearance and severity indicate that you should perform a thorough follow-up of these patients especially in the early phases of treatment.

Introduction, the DNA and the Genes Pharmacogenomics (PGx) is the science of understanding the interaction between genes and drugs. The analysis of specific areas of the DNA provides information about a certain drug metabolism and about the expected response to a certain treatment. PGx also aims to reduce the incidence of adverse drug events (ADEs)., Many studies in this area have focused on the identification of genes that predispose to diseases, modulate drug response, affect drug concentration and correlate with [...] Introduction, the DNA and the Genes Pharmacogenomics (PGx) is the science of understanding the interaction between genes and drugs. The analysis of specific areas of the DNA provides information about a certain drug metabolism and about the expected response to a certain treatment. PGx also aims to reduce the incidence of adverse drug events (ADEs)., Many studies in this area have focused on the identification of genes that predispose to diseases, modulate drug response, affect drug concentration and correlate with

Tacrolimus, commonly used after organ transplantation, has a narrow therapeutic index (NTI) and a high risk of dosing errors, with over 50% of patients suffering serious, potentially life-threatening adverse effects. To address this, we developed an interpretable long short-term memory (LSTM) model trained on 14 years of data from 1,774 patients across Spain and the United States. This LSTM predicts tacrolimus levels using clinical data, with approximately 5% mean absolute error, outperforming state-of-the-art models. Addressing data privacy concerns, we demonstrate that synthetic data can replace real data for training without performance loss. Finally, we launched dosetailor.com, a platform providing personalised tacrolimus dosing recommendations for clinicians. Although focused on tacrolimus, this platform forms a foundation for personalising dosage for high-risk, NTI drugs.