Zuclopenthixol acetate 50mg/1ml solution for injection ampoules

OBJECTIVES: Network meta-analysis (NMA) with individual participant data can estimate how treatment effects change with patient characteristics. Yet cost-effectiveness analyses typically use population-average effects. We introduce a framework that incorporates NMA-derived heterogeneous treatment effects into cost-effectiveness analysis using a risk-modelling approach. METHODS: We first derived a baseline risk score for each patient using a prognostic model. This risk score was then used as effect modifier in a network meta-regression to estimate risk-specific treatment effects. These effects were incorporated into the cost-effectiveness model to estimate the incremental cost-effectiveness ratios (ICERs) and net monetary benefits (NMBs) as functions of the baseline risk score. We demonstrated the approach using data from observational and randomized studies in relapsing-remitting multiple sclerosis, comparing dimethyl fumarate, glatiramer acetate, and placebo. RESULTS: Risk-dependent treatment effects from the prediction-NMR framework led to substantial variation in cost-effectiveness across the baseline risk distribution. When these treatment effects were incorporated into the cost-effectiveness model, ICERs increased steadily across baseline risk quintiles, from 48,811 CHF/QALY in the lowest-risk group to 212,870 CHF/QALY in the highest. Dimethyl fumarate has a higher NMB up to a baseline risk of 55%, after which glatiramer acetate becomes the preferred option. CONCLUSIONS: Our findings show that integrating baseline risk modelling with NMA and cost-effectiveness analysis provides more informative decision-making than relying on average effects. Treatment value can vary substantially across the risk spectrum, indicating that optimal therapy selection is strongly dependent on individual patient risk.

Abstract licence: CC BY

INTRODUCTION: Fatigue in multiple sclerosis (MS) is defined as the lack of physical and/or mental energy perceived by the individual that interferes with normal activities. It is the most common symptom in MS, present in up to 90% of people with MS. Fatigue along with disability, depression, cognitive impairment, and disease-modifying therapy (DMT) affect quality of life (QoL). METHOD: We designed a prospective observational study in patients with MS and DMT of moderate efficacy to assess the association between fatigue and the epidemiological, clinical, and pharmacological aspects that influence in the QoL. We analysed variables related to patients, disability, fatigue (MFIS), clinical and radiological activity, depression (BDI), cognitive impairment (SDMT), and QoL (EQ-5D). RESULTS: we included 91 people, 65.9% women, mean age 43.9 years. The DMT were: 27.4% interferon-β, 15.38% glatiramer acetate, 9.89% teriflunomide, and 47.25% dimethyl fumarate. The median of the EDSS was 1.5 points. 40.9% have presented fatigue, 36.3% cognitive deterioration and 30.7% of the patients depression. CONCLUSIONS: Patients with fatigue are older, more disabled, have a higher prevalence of depression and worse QoL. Evolution time, relapses, MRI lesion load, and DMTs are not associated with fatigue. Fatigue is a frequent symptom in patients with MS that influences in the QoL, hence the importance of its diagnosis and treatment.

Abstract licence: CC BY-NC-ND

Multiple sclerosis (MS) is a neuroinflammatory disorder that is characterized by demyelination, neurodegeneration, and immune dysregulation. The experimental autoimmune encephalomyelitis (EAE) model has helped to elucidate MS pathophysiology and test therapies. This review synthesizes current literature on the development, applications, and translational significance of EAE models in MS research. It discusses various EAE induction protocols, including active and passive immunization, and highlights advancements such as humanized mice and induced pluripotent stem cell (iPSC)-derived neuronal models. The review evaluates the role of EAE in identifying immune pathways, validating therapeutic agents like glatiramer acetate and natalizumab, and exploring precision medicine approaches through biomarker discovery. The EAE model replicated the key features of MS, including inflammation, demyelination, and axonal loss, facilitating therapy development. However, its predictive validity faces limitations, such as heterogeneity in disease induction, underrepresentation of chronic progression, and species differences. Innovations, such as humanized mouse models and iPSC-derived neurons, show promise in addressing these challenges. EAE research has advanced biomarker-based personalized treatments, although further validation is required. Despite its widespread use, EAE has limitations in terms of variability in disease induction, incomplete MS feature replication, species-specific responses, and clinical translation. Addressing these limitations remains crucial for therapeutic development, focusing on analyzing model limitations and strategies to overcome translational barriers. This review offers immunologists a comprehensive overview of EAE's contributions of EAE to MS research and its potential to inform the development of novel therapeutic approaches for this debilitating disease.

Abstract licence: CC BY-NC

Abstract Background The present study focused to develop a simple and sensitive HPLC method for resolution and estimation process-related impurities of zuclopenthixol and further assessment of forced degradation behavior of zuclopenthixol. Results The chromatographic separation of drug substance, process-related impurities and its degradation products (DPs) was achieved on KNAUER C18 (250 mm × 4.6 mm, 5µ id) column at that was maintained at 35 °C temperature using 0.1 M sodium acetate buffer at pH 4.3 and methanol in 20:80 (v/v) as mobile phase A, 0.1% formic acid and acetonitrile in 75:25 (v/v) as mobile phase B. Equal volume of mobile phase A and B was pumped in isocratic elution at 0.8 mL/min. Detection wavelength was selected as 257 nm. In the proposed conditions, zuclopenthixol is identified at 6.91 and 1.91 min and 2.89 min, respectively, for impurity B and A min with acceptable system suitability and specificity. The method produces LOD at 0.009 for impurities with calibration range of 30–180 µg/mL for zuclopenthixol and 0.03–0.18 µg/mL for impurities. The other validation parameters were notices to be with in the acceptable levels for zuclopenthixol and its impurities. The drug was exposed to different stressed conditions (acid, base, peroxide, thermal and UV light) according to ICH Q1A (R2) guidelines. The DPs formed during the stress study were identified and characterized by LCMS/MS in ESI positive mode. Conclusion The analysis involved a comparison of collision-induced dissociation mass spectrometry data between the degradation products and zuclopenthixol. As a result, potential structures for six degradation compounds were suggested. The results from additional validation studies were similarly pleasing and demonstrated their suitability for the routine analysis of zuclopenthixol and its associated impurities in both bulk drug and pharmaceutical dosage forms. Additionally, these findings can be extended to assess the mechanism of stress degradation in zuclopenthixol.

Abstract licence: CC BY

Multiple sclerosis (MS) is a clinically and biologically heterogeneous, immune-mediated disease of the central nervous system, with substantial interindividual variability in disease course and response to disease-modifying therapies (DMTs). Over the past three decades, the MS therapeutic landscape has expanded considerably; however, treatment selection and switching remain guided primarily by clinical phenotype and imaging findings rather than molecular predictors of response. Despite extensive clinical trial evidence, prospectively identifying responders and non-responders to specific DMTs remains challenging. Genetic variability appears to influence differences in treatment efficacy, tolerability, and long-term outcomes in people with MS. Numerous candidate pharmacogenomic variants have been reported across interferon-β, glatiramer acetate, oral agents, and monoclonal antibodies; nevertheless, replication has been inconsistent, effect sizes are modest, and no genetic marker has yet been clinically validated for routine use. Consequently, pharmacogenomics is largely absent from current MS treatment algorithms. This review critically evaluates the existing pharmacogenomic literature across approved DMTs, highlighting reproducible findings, methodological limitations, and gaps that hinder clinical translation. We further discuss requirements for integrating pharmacogenomic markers into routine practice, emphasizing the need for large, multiethnic cohorts, standardized response definitions, and functional validation. Overall, these insights underscore both the potential and current limitations of pharmacogenomics in advancing precision medicine for MS.

Abstract licence: CC BY-NC-ND