Model-Based Approach for Designing an Efficient Bioequivalence Study for Highly Variable Drugs.
Ontology highlight
ABSTRACT:
SUBMITTER: Song E
PROVIDER: S-EPMC8624447 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:OBJECTIVES: We aim to obtain the intra-subject coefficient of variability of a highly variable antidepressant agomelatine in humans, and propose an adjusted bioequivalence assessment strategy. METHODS: A single-dose, randomized crossover design was conducted in four periods (reference administered thrice, placebo administered once) separated by seven days. A validated LC-MS/MS assay was used to measure drug concentrations in serial blood samples. RESULTS: The intra-subject coefficient of variability was calculated using the residual variance of ANOVA analysis, and the results for Cmax and AUC0-t was 78.34% and 43.52%, respectively, in Chinese healthy subjects. The sample size required for standard BE study were 124(192, 340) if the expected deviation between the reference and generic products was set to 0 (5%, 10%). CONCLUSIONS: Agomelatine meets the criteria for highly variable drug in Chinese healthy male subjects, and the traditional BE criteria for agomelatine needs to be adjusted to alleviate the resource and ethical burden of using a large numbers of subjects in clinical trials. Our clinical data on the intra-subject variability of agomelatine PK in Chinese healthy population enables to adjust bioequivalence (BE) assessment approach for agomelatine based on the RSABE approaches recommended by regulatory agencies. TRIAL REGISTRATION: ChiCTR.org ChiCTR-TTRCC-13003835.
| S-EPMC4203722 | biostudies-literature
Project description:The ability to use structure-based design and engineering to control the molecular shape and reactivity of an immunogen to induce protective responses shows great promise, along with corresponding advancements in vaccine testing and evaluation systems. We describe in this review new paradigms for the development of a B cell-based HCV vaccine. Advances in test systems to measure in vitro and in vivo antibody-mediated virus neutralization include retroviral pseudotype particles expressing HCV E1E2 glycoproteins (HCVpp), infectious cell culture-derived HCV virions (HCVcc), and surrogate animal models mimicking acute HCV infection. Their applications have established the role of broadly neutralizing antibodies to control HCV infection. However, the virus has immunogenic regions in the viral envelope glycoproteins that are associated with viral escape or non-neutralizing antibodies. These regions serve as immunologic decoys that divert the antibody response from less prominent conserved regions mediating virus neutralization. This review outlines the immunogenic regions on E2, which are roughly segregated into the hypervariable region 1 (HVR1), and five clusters of overlapping epitopes designated as antigenic domains A-E. Understanding the molecular architecture of conserved neutralizing epitopes within these antigenic domains, and how other antigenic regions or decoys deflect the immune response from these conserved regions will provide a roadmap for the rational design of an HCV vaccine.
| S-EPMC5775222 | biostudies-literature
Project description:The aim of this study was to apply the reference-scaled average bioequivalence (RSABE) approach to evaluate the bioequivalence of 2 formulations of agomelatine, and to investigate the pharmacokinetic properties of agomelatine in Chinese healthy male subjects. This was performed in a single-dose, randomized-sequence, open-label, four-way crossover study with a one-day washout period between doses. Healthy Chinese males were randomly assigned to receive 25 mg of either the test or reference formulation. The formulations were considered bioequivalent if 90% confidence intervals (CIs) for the log-transformed ratios and ratio of geometric means (GMR) of AUC and C max of agomelatine were within the predetermined bioequivalence range based on RSABE method. Results showed that both of the 90% CIs for the log-transformed ratios of AUC and C max of 7-desmethyl-agomelatine and 3-hydroxy-agomelatine were within the predetermined bioequivalence range. The 90% CIs for natural log-transformed ratios of C max, AUC0-t and AUC0-? of agomelatine (104.42-139.86, 101.33-123.83 and 97.90-117.94) were within the RSABE acceptance limits, and 3-hydroxy-agomelatine (105.55-123.03, 101.95-109.10 and 101.72-108.70) and 7-desmethyl-agomelatine (104.50-125.23, 102.36-111.50 and 101.62-110.64) were within the FDA bioequivalence definition intervals (0.80-1.25 for AUC and 0.75-1.33 for C max). The RSABE approach was successful in evaluating the bioequivalence of these two formulations.
| S-EPMC4724689 | biostudies-literature
Project description:Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g., local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also non-coding regions are examined.
| S-EPMC7886790 | biostudies-literature
Project description:CRISPR-Cas9 technology provides a powerful system for genome engineering. However, variable activity across different single guide RNAs (sgRNAs) remains a significant limitation. We analyzed the molecular features that influence sgRNA stability, activity and loading into Cas9 in vivo. We observed that guanine enrichment and adenine depletion increased sgRNA stability and activity, whereas differential sgRNA loading, nucleosome positioning and Cas9 off-target binding were not major determinants. We also identified sgRNAs truncated by one or two nucleotides and containing 5' mismatches as efficient alternatives to canonical sgRNAs. On the basis of these results, we created a predictive sgRNA-scoring algorithm, CRISPRscan, that effectively captures the sequence features affecting the activity of CRISPR-Cas9 in vivo. Finally, we show that targeting Cas9 to the germ line using a Cas9-nanos 3' UTR led to the generation of maternal-zygotic mutants, as well as increased viability and decreased somatic mutations. These results identify determinants that influence Cas9 activity and provide a framework for the design of highly efficient sgRNAs for genome targeting in vivo.
| S-EPMC4589495 | biostudies-literature
Project description:Nanoporous membranes with two-dimensional materials such as graphene oxide have attracted attention in volatile organic compounds (VOCs) and H2 adsorption because of their unique molecular sieving properties and operational simplicity. However, agglomeration of graphene sheets and low efficiency remain challenging. Therefore, we designed hierarchical nanoporous membranes (HNMs), a class of nanocomposites combined with a carbon sphere and graphene oxide. Hierarchical carbon spheres, prepared following Murray's law using chemical activation incorporating microwave heating, act as spacers and adsorbents. Hierarchical carbon spheres preclude the agglomeration of graphene oxide, while graphene oxide sheets physically disperse, ensuring structural stability. The obtained HNMs contain micropores that are dominated by a combination of ultramicropores and mesopores, resulting in high VOCs/H2 adsorption capacity, up to 235 and 352 mg/g at 200 ppmv and 3.3 weight % (77 K and 1.2 bar), respectively. Our work substantially expands the potential for HNMs applications in the environmental and energy fields.
| S-EPMC7541071 | biostudies-literature
Project description:BackgroundTranslational research in medical education requires the ability to rigorously measure learner performance in actual clinical settings; however, current measurement systems cannot accommodate the variability inherent in many patient care environments. This is especially problematic in emergency medicine, where patients represent a wide spectrum of severity for a single clinical presentation. Our objective is to describe and implement EBAM, an event-based approach to measurement that can be applied to actual emergency medicine clinical events.MethodsWe used a four-step event-based approach to create an emergency department trauma resuscitation patient care measure. We applied the measure to a database of 360 actual trauma resuscitations recorded in a Level I trauma center using trained raters. A subset (n = 50) of videos was independently rated in duplicate to determine inter-rater reliability. Descriptive analyses were performed to describe characteristics of resuscitation events and Cohen's kappa was used to calculate reliability.ResultsThe methodology created a metric containing both universal items that are applied to all trauma resuscitation events and conditional items that only apply in certain situations. For clinical trauma events, injury severity scores ranged from 1 to 75 with a mean (±SD) of 21 (±15) and included both blunt (254/360; 74%) and penetrating (86/360; 25%) traumatic injuries, demonstrating the diverse nature of the clinical encounters. The mean (±SD) Cohen's kappa for patient care items was 0.7 (±0.3).ConclusionWe present an event-based approach to performance assessment that may address a major gap in translational education research. Our work centered on assessment of patient care behaviors during trauma resuscitation. More work is needed to evaluate this approach across a diverse array of clinical events.
| S-EPMC7163198 | biostudies-literature
Project description:In bioinformatics, it is important to build extensible and low-maintenance systems that are able to deal with the new tools and data formats that are constantly being developed. The traditional and simplest implementation of pipelines involves hardcoding the execution steps into programs or scripts. This approach can lead to problems when a pipeline is expanding because the incorporation of new tools is often error prone and time consuming. Current approaches to pipeline development such as workflow management systems focus on analysis tasks that are systematically repeated without significant changes in their course of execution, such as genome annotation. However, more dynamism on the pipeline composition is necessary when each execution requires a different combination of steps.We propose a graph-based approach to implement extensible and low-maintenance pipelines that is suitable for pipeline applications with multiple functionalities that require different combinations of steps in each execution. Here pipelines are composed automatically by compiling a specialised set of tools on demand, depending on the functionality required, instead of specifying every sequence of tools in advance. We represent the connectivity of pipeline components with a directed graph in which components are the graph edges, their inputs and outputs are the graph nodes, and the paths through the graph are pipelines. To that end, we developed special data structures and a pipeline system algorithm. We demonstrate the applicability of our approach by implementing a format conversion pipeline for the fields of population genetics and genetic epidemiology, but our approach is also helpful in other fields where the use of multiple software is necessary to perform comprehensive analyses, such as gene expression and proteomics analyses. The project code, documentation and the Java executables are available under an open source license at http://code.google.com/p/dynamic-pipeline. The system has been tested on Linux and Windows platforms.Our graph-based approach enables the automatic creation of pipelines by compiling a specialised set of tools on demand, depending on the functionality required. It also allows the implementation of extensible and low-maintenance pipelines and contributes towards consolidating openness and collaboration in bioinformatics systems. It is targeted at pipeline developers and is suited for implementing applications with sequential execution steps and combined functionalities. In the format conversion application, the automatic combination of conversion tools increased both the number of possible conversions available to the user and the extensibility of the system to allow for future updates with new file formats.
| S-EPMC3496580 | biostudies-other
Project description:The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.
| S-EPMC4287731 | biostudies-literature
Project description:Paper-based platforms can be a promising choice as portable sensors due to their low-cost and facile fabrication, ease of use, high sensitivity, specificity and flexibility. By combining the qualities of these 3D platforms with the optical properties of gold nanoparticles, it is possible to create efficient nanodevices with desired biosensing functionalities. In this work, we propose a new plasmonic paper-based dual localized surface plasmon resonance?surface-enhanced Raman scattering (LSPR-SERS) nanoplatform with improved detection abilities in terms of high sensitivity, uniformity and reproducibility. Specifically, colloidal gold nanorods (GNRs) with a well-controlled plasmonic response were firstly synthesized and validated as efficient dual LSPR-SERS nanosensors in solution using the p-aminothiophenol (p-ATP) analyte. GNRs were then efficiently immobilized onto the paper via the immersion approach, thus obtaining plasmonic nanoplatforms with a modulated LSPR response. The successful deposition of the nanoparticles onto the cellulose fibers was confirmed by LSPR measurements, which demonstrate the preserved plasmonic response after immobilization, as well as by dark-field microscopy and scanning electron microscopy investigations, which confirm their uniform distribution. Finally, a limit of detection for p-ATP as low as 10-12 M has been achieved by our developed SERS-based paper nanoplatform, proving that our optimized plasmonic paper-based biosensing design could be further considered as an excellent candidate for miniaturized biomedical applications.
| S-EPMC6163559 | biostudies-literature