IN VITRO IN VIVO CORRELATION OF DEXTROMETHORPHAN HYDROBROMIDE MODIFIED RELEASE TABLETS: AN INTERNAL VALIDATION EVALUATION

ABSTRACTObjectives: The purpose of this study was to develop and validate in vitro and in vivo correlation (IVIVC) for newly developed dextromethorphanhydrobromide sustained-release (SR).Methods: During the development of a once-daily SR tablet of dextromethorphan hydrobromide, an extrapolative in vitro drug release method wasdesigned and statistically evaluated using three formulations with varying release rates. The similarity factor (f2) was used to analyze the dissolutiondata. Three-way crossover study design was conducted in six healthy human subjects under fasting condition.Result: The formulations were evaluated by using area under the plasma concentration-time curve, (AUC0-∞), time to reach peak plasma concentration,Tmax, and peak plasma concentration Cmax, while correlation was determined between in-vitro release and in-vivo absorption. A linear correlationwas observed between the absorption and dissolution profiles of the drug. The prediction error (%) was determined to check how well a given modelcan accurately predict a pharmacokinetic parameter of the drug. The predicted Cmax and AUC found to be −6.98 and −8.55 and for AUC was 7.76 and8.82% respectively.Conclusion: In conclusion, a Level A IVIVC explaining the complete time-course of plasma concentrations was developed and validated, internally fordeveloped dextromethorphan hydrobromide SR formulations.Keywords: Dextromethorphan hydrobromide, Dissolution, Bioavailability, Sustained-release, In vitro and in vivo correlation

Self-Organizing Maps for Pattern Recognition in Design of Alloys

A combined experimental\u2013computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasirandom number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as selforganizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process

Algorithms for design optimization of chemistry of hard magnetic alloys using experimental data

A multi-dimensional random number generation algorithm was used to distribute chemical concentrations of each of the alloying elements in the candidate alloys as uniformly as possible while maintaining the prescribed bounds on the minimum and maximum allowable values for the concentration of each of the alloying elements. The generated candidate alloy compositions were then examined for phase equilibria and associated magnetic properties using a thermodynamic database in the desired temperature range. These initial candidate alloys were manufactured, synthesized and tested for desired properties. Then, the experimentally obtained values of the properties were fitted with a multi-dimensional response surface. The desired properties were treated as objectives and were extremized simultaneously by utilizing a multi-objective optimization algorithm that optimized the concentrations of each of the alloying elements. This task was also performed by another conceptually different response surface and optimization algorithm for double-checking the results. A few of the best predicted Pareto optimal alloy compositions were then manufactured, synthesized and tested to evaluate their macroscopic properties. Several of these Pareto optimized alloys outperformed most of the candidate alloys on most of the objectives. This proves the efficacy of the combined meta-modeling and experimental approach in design optimization of the alloys. A sensitivity analysis of each of the alloying elements was also performed to determine which of the alloying elements contributes the least to the desired macroscopic properties of the alloy. These elements can then be replaced with other candidate alloying elements such as not-so-rare earth elements

Report of the ICES\NAFO Joint Working Group on Deep-water Ecology (WGDEC), 11–15 March 2013, Floedevigen, Norway.

On 11 February 2013, the joint ICES/NAFO WGDEC, chaired by Francis Neat (UK) and attended by ten members met at the Institute for Marine Research in Floedevi-gen, Norway to consider the terms of reference (ToR) listed in Section 2. WGDEC was requested to update all records of deep-water vulnerable marine eco-systems (VMEs) in the North Atlantic. New data from a range of sources including multibeam echosounder surveys, fisheries surveys, habitat modelling and seabed imagery surveys was provided. For several areas across the North Atlantic, WGDEC makes recommendations for areas to be closed to bottom fisheries for the purposes of conservation of VMEs

A contemporary dose selection algorithm for stereotactic radiosurgery in the treatment of brain metastases - An initial report.

Indications and treatment goals for SRS have changed since the publication of RTOG 90-05. We present initial retrospective outcomes from a new dose selection algorithm in use at our institution felt to be more contemporary with doses being used in the radiosurgery community today and report our local control and toxicity outcomes. This dose selection algorithm will be subject to a forthcoming prospective phase 2 trial.To evaluate safety and efficacy of an institutional dose selection algorithm in the treatment of brain metastases (BM) with single fraction radio-surgery (SRS).The medical records of 65 patients with ≤10 BM treated with GK at our institution between April 2012 and October 2012 were reviewed retrospectively. The prescription doses used in this study ranged from 16-22Gy and were based upon RTOG 90-05 guideline doses subsequently modified at our institution depending on lesion number, lesion volume, institutional experience and prior history of whole brain radiation therapy (WBRT). Primary endpoint was local recurrence (LR) with additional outcomes measured including distant intracranial recurrence (DIR), death without local recurrence (DWLR) and alive and disease free (ADF). Fine Gray competing risk analysis was used to examine factors affecting local recurrence.Median follow up was 8.9 months (range 1.0-29.6months) and 12 month overall survival was 37% (95% CI 24.9-49.1%). Overall local recurrence rate was 7.7%. On competing risks regression analysis, no variable was significantly associated with local recurrence, including previous whole brain radiotherapy (WBRT), (SHR 1.21 [95%CI 0.13-11.5], p=0.87 and radioresistant versus radiosensitive histology (SHR 0.51 [95% CI 0.06-7.73], p=0.55). No patient developed grade 3 or higher neurotoxicity at 12 months following GK.Initial local control and toxicity results from our institutional dose selection algorithm are reported here. Comparison of our results with RTOG 90-05 is difficult due to significant differences in the patient population and their treatments. The applicability of this algorithm merits further investigation across multiple centers for the purpose of treatment and clinical trial standardization in single fraction SRS and will be the subject of a forthcoming phase 2 prospective study within our own institution

Unbiased yeast screens identify cellular pathways affected in Niemann-Pick disease type C

Niemann–Pick disease type C (NPC) is a rare lysosomal storage disease caused by mutations in either the NPC1 or NPC2 genes. Mutations in the NPC1 gene lead to the majority of clinical cases (95%); however, the function of NPC1 remains unknown. To gain further insights into the biology of NPC1, we took advantage of the homology between the human NPC1 protein and its yeast orthologue, Niemann–Pick C–related protein 1 (Ncr1). We recreated the NCR1 mutant in yeast and performed screens to identify compensatory or redundant pathways that may be involved in NPC pathology, as well as proteins that were mislocalized in NCR1-deficient yeast. We also identified binding partners of the yeast Ncr1 orthologue. These screens identified several processes and pathways that may contribute to NPC pathogenesis. These included alterations in mitochondrial function, cytoskeleton organization, metal ion homeostasis, lipid trafficking, calcium signalling, and nutrient sensing. The mitochondrial and cytoskeletal abnormalities were validated in patient cells carrying mutations in NPC1, confirming their dysfunction in NPC disease

Biochemical Characterization and Evaluation of a Brugia malayi Small Heat Shock Protein as a Vaccine against Lymphatic Filariasis

Filarial nematodes enjoy one of the longest life spans of any human pathogen due to effective immune evasion strategies developed by the parasite. Among the various immune evasion strategies exhibited by the parasite, Interleukin 10 (IL-10) productions and IL-10 mediated immune suppression has significant negative impact on the host immune system. Recently, we identified a small heat shock protein expressed by Brugia malayi (BmHsp12.6) that can bind to soluble human IL-10 receptor alpha (IL-10R) and activate IL-10 mediated effects in cell lines. In this study we show that the IL-10R binding region of BmHsp12.6 is localized to its N-terminal region. This region has significant sequence similarity to the receptor binding region of human IL-10. In vitro studies confirm that the N-terminal region of BmHsp12.6 (N-BmHsp12.6) has IL-10 like activity and the region containing the alpha crystalline domain and C-terminus of BmHsp12.6 (BmHsp12.6αc) has no IL-10 like activity. However, BmHsp12.6αc contains B cell, T cell and CTL epitopes. Members of the sHSP families are excellent vaccine candidates. Evaluation of sera samples from putatively immune endemic normal (EN) subjects showed IgG1 and IgG3 antibodies against BmHsp12.6αc and these antibodies were involved in the ADCC mediated protection. Subsequent vaccination trials with BmHsp12.6αc in a mouse model using a heterologous prime boost approach showed that 83% protection can be achieved against B. malayi L3 challenge. Results presented in this study thus show that the N-BmHsp12.6 subunit of BmHsp12.6 has immunoregulatory function, whereas, the BmHsp12.6αc subunit of BmHsp12.6 has significant vaccine potential

Current provision of simulation in the UK and Republic of Ireland trauma and orthopaedic specialist training: a national survey.

Aims: The primary aim of the survey was to map the current provision of simulation training within UK and Republic of Ireland (RoI) trauma and orthopaedic (T&O) specialist training programmes to inform future design of a simulation based-curriculum. The secondary aims were to characterize; the types of simulation offered to trainees by stage of training, the sources of funding for simulation, the barriers to providing simulation in training, and to measure current research activity assessing the educational impact of simulation. Methods: The development of the survey was a collaborative effort between the authors and the British Orthopaedic Association Simulation Group. The survey items were embedded in the Performance and Opportunity Dashboard, which annually audits quality in training across several domains on behalf of the Speciality Advisory Committee (SAC). The survey was sent via email to the 30 training programme directors in March 2019. Data were retrieved and analyzed at the Warwick Clinical Trials Unit, UK. Results: Overall, 28 of 30 programme directors completed the survey (93%). 82% of programmes had access to high-fidelity simulation facilities such as cadaveric laboratories. More than half (54%) had access to a non-technical skills simulation training. Less than half (43%) received centralized funding for simulation, a third relied on local funding such as the departmental budget, and there was a heavy reliance on industry sponsorship to partly or wholly fund simulation training (64%). Provision was higher in the mid-stages (ST3-5) compared to late-stages (ST6-8) of training, and was formally timetabled in 68% of prostgrammes. There was no assessment of the impact of simulation training using objective behavioural measures or real-world clinical outcomes. Conclusion: There is currently widespread, but variable, provision of simulation in T&O training in the UK and RoI, which is likely to expand further with the new curriculum. It is important that research activity into the impact of simulation training continues, to develop an evidence base to support investment in facilities and provision