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Introduction: Pharmacovigilance is essential to monitoring the safety profiles of authorized medicines. Compared with small-molecule drugs, biological drugs are more complex, more susceptible to structural variability due to manufacturing processes, and have the potential to induce immune-related reactions, underscoring the importance of safety monitoring for these products. Although highly similar to reference products, biosimilars are not expected to be structurally identical. For these reasons, proper reporting of potential adverse drug reactions (ADRs) using distinguishable names and batch numbers is essential for accurate tracing of all biological drugs. To address the need for robust pharmacovigilance, the European Parliament and Council of the European Union provided legislation regarding pharmacovigilance of biologics in 2010.

Areas covered: This narrative review examines the current state of pharmacovigilance for biologics in the European Union (EU) and discusses relevant information on pharmacovigilance of biosimilars, the current EU pharmacovigilance system, and areas that could be improved.

Expert opinion: Although steps have been taken to improve pharmacovigilance of biologics in the EU, several enhancements can still be made, including additional training for healthcare professionals on ADR reporting, the use of 2D barcodes that enhance traceability, and an open discussion of potentially missed opportunities in the pharmacovigilance of biosimilars.  相似文献   

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Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).  相似文献   
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