Superior Skin Penetration of Diclofenac from Dynapar QPS Plus as Compared to Diclofenac Aerosol Spray

Aamirraza Mansuri,Vivek Kumar Agarwal,Sanjay B Patel,Sohin K Zalavadiya,Ketan R Patel,Kanaiyalal D Prajapati 대한통증연구학회 2023 International Journal of Pain Vol.14 No.2

Background: The currently available topical diclofenac products do not provide effective penetration of diclofenac across the layers of skin. Troikaa Pharmaceuticals Ltd, has developed Dynapar QPS PlusⓇ, a novel, topical formulation of diclofenac and compared its skin penetration with Diclofenac Aerosol Spray. Methods: In this randomized, two way crossover study, healthy human subjects (n = 8) received single dose of either 2 ml of Dynapar QPS Plus or approximately 4 gm of marketed Diclofenac Aerosol Spray. The blood samples were drawn at pre dose and up to 24 hours post dose. The plasma concentrations of Diclofenac was measured using validated LC-MS/MS bioanalytical method. Results: The mean Cmax after administration of Dynapar QPS Plus and Diclofenac Aerosol Spray were 102.945 ± 66.0109 and 15.885 ± 14.7750 ng/ml, respectively. Median Tmax for Dynapar QPS Plus was earlier compared to Diclofenac Aerosol Spray (7 hrs vs. 19 hrs). The mean AUC0-t after administration of Dynapar QPS Plus was significantly higher as compared to Diclofenac Aerosol Spray (AUC0-t: 855.289 ± 494.0262 vs. 149.707 ± 116.6317). Both the products were well tolerated and no adverse event occurred during the study. Conclusions: The results of this study showed that Dynapar QPS Plus is safe and provides faster and more than six times higher skin penetration of diclofenac in comparison to marketed Diclofenac Aerosol Spray. Due to faster and higher penetration of diclofenac, from Dynapar QPS Plus it is best suitable option to treat pain and inflammation related to acute as well chronic musculoskeletal disorders.

Modified meta-heuristicsusingrandommutationfortrusstopology optimization withstaticanddynamicconstraints

Vimal J.Savsani,Ghanshyam G.Tejani,Vivek K.Patel,Poonam Savsani 한국CDE학회 2017 Journal of computational design and engineering Vol.4 No.2

In thispaper,simultaneoussizeandtopologyoptimizationofplanarandspacetrussessubjectedtostaticanddynamicconstraintsareinvestigated. Allthebenchmarktrussesconsiderdiscretecross-sectionalareastoconsiderthepracticalaspectofmanufacturing.Moreover,Trusses areconsideredwithmultipleloadingconditionsandsubjectedtoconstraintsfornaturalfrequencies,elementstresses,nodaldisplacements, Eulerbucklingcriteria,andkinematicstabilityconditions.Trusstopologyoptimization(TTO)canbeaccomplishedbytheremoval ofsuperfluous elementsandnodesfromthehighlyhyperstatictrussalsoknownasthegroundstructureandresultsinthesavingofthemass ofthetruss.Inthismethod,thedifficulties ariseduetothesingularsolutionandunnecessaryanalysis;therefore,FEAmodelisreformedtoresolve thesedifficulties. The staticanddynamicresponsestotheTTOproblemsarechallengingduetoitssearchspace,whichisimplicit,non-convex,non-linear,andoften leadingtodivergence.Modified meta-heuristicsareeffectiveoptimizationmethodstohandlesuchproblemsinactualfact.Inthispaper,modified versionsofTeaching–Learning-Based Optimization(TLBO),HeatTransferSearch(HTS),WaterWaveOptimization(WWO),andPassing VehicleSearch(PVS)areproposedbyintegratingtherandommutation-basedsearchtechniquewiththem.Thispapercomparestheperformance offourmodified andfourbasicmeta-heuristicstosolvediscreteTTOproblems.

An improved heat transfer search algorithm for unconstrained optimization problems

Ghanshyam G. Tejani,Vimal J.Savsani,Vivek K.Patel,Seyedali Mirjalili 한국CDE학회 2019 Journal of computational design and engineering Vol.6 No.1

In this work, an improved heat transfer search (IHTS) algorithm is proposed by incorporating the effect of the simultaneous heat transfer modes and population regeneration in the basic HTS algorithm. The basic HTS algorithm considers only one of the modes of heat transfer (conduction, convection, and radiation) for each generation. In the proposed algorithms, however, the system molecules are considered as the search agents that interact with each other as well as with the surrounding to a state of the thermal equi-librium. Another improvement is the integration of a population regenerator to reduce the probability of local optima stagnation. The population regenerator is applied to the solutions without improvements for a pre-defined number of iterations. The feasibility and effectiveness of the proposed algorithms are investigated by 23 classical benchmark functions and 30 functions extracted from the CEC2014 test suite. Also, two truss design problems are solved to demonstrate the applicability of the proposed algorithms. The results show that the IHTS algorithm is more effective as compared to the HTS algorithm. Moreover, the IHTS algorithm provides very competitive results compared to the existing meta-heuristics in the literature.

Size, shape, and topology optimization of planar and space trusses using mutation-based improved metaheuristics

Tejani, Ghanshyam G.,Savsani, Vimal J.,Patel, Vivek K.,Savsani, Poonam V. Society for Computational Design and Engineering 2018 Journal of computational design and engineering Vol.5 No.2

In this study, simultaneous size, shape, and topology optimization of planar and space trusses are investigated. Moreover, the trusses are subjected to constraints for element stresses, nodal displacements, and kinematic stability conditions. Truss Topology Optimization (TTO) removes the superfluous elements and nodes from the ground structure. In this method, the difficulties arise due to unacceptable and singular topologies; therefore, the Grubler's criterion and the positive definiteness are used to handle such issue. Moreover, the TTO is challenging due to its search space, which is implicit, non-convex, non-linear, and often leading to divergence. Therefore, mutation-based metaheuristics are proposed to investigate them. This study compares the performance of four improved metaheuristics (viz. Improved Teaching-Learning-Based Optimization (ITLBO), Improved Heat Transfer Search (IHTS), Improved Water Wave Optimization (IWWO), and Improved Passing Vehicle Search (IPVS)) and four basic metaheuristics (viz. TLBO, HTS, WWO, and PVS) in order to solve structural optimization problems.

Topology, shape, and size optimization of truss structures using modified teaching-learning based optimization

Tejani, Ghanshyam G.,Savsani, Vimal J.,Patel, Vivek K.,Bureerat, Sujin Techno-Press 2017 Advances in computational design Vol.2 No.4

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization

Tejani, Ghanshyam G.,Savsani, Vimal J.,Patel, Vivek K. Society for Computational Design and Engineering 2016 Journal of computational design and engineering Vol.3 No.3

The symbiotic organisms search (SOS) algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.

Size, shape, and topology optimization of planar and space trusses using mutation-based improved metaheuristics

Ghanshyam G. Tejani,Vimal J.Savsani,Vivek K.Patel,Poonam V. Savsani 한국CDE학회 2018 Journal of computational design and engineering Vol.5 No.2

In this study, simultaneous size, shape, and topology optimization of planar and space trusses are inves-tigated. Moreover, the trusses are subjected to constraints for element stresses, nodal displacements, and kinematic stability conditions. Truss Topology Optimization (TTO) removes the superfluous elements and nodes from the ground structure. In this method, the difficulties arise due to unacceptable and singular topologies; therefore, the Grubler’s criterion and the positive definiteness are used to handle such issue. Moreover, the TTO is challenging due to its search space, which is implicit, non-convex, non-linear, and often leading to divergence. Therefore, mutation-based metaheuristics are proposed to investigate them. This study compares the performance of four improved metaheuristics (viz. Improved Teaching–Learning-Based Optimization (ITLBO), Improved Heat Transfer Search (IHTS), Improved Water Wave Optimization (IWWO), and Improved Passing Vehicle Search (IPVS)) and four basic metaheuristics (viz. TLBO, HTS, WWO, and PVS) in order to solve structural optimization problems.