Design Space Analysis Research Articles

In silico design-space analysis of a novel tablet coating process using advanced modeling

In silico design-space analysis of a novel tablet coating process using advanced modeling

Method operable design region for robust RP-HPLC analysis of pioglitazone hydrochloride and teneligliptin hydrobromide hydrate: incorporating hybrid principles of white analytical chemistry and design of experiments

BackgroundA combination of pioglitazone hydrochloride with teneligliptin hydrobromide hydrate is used to treat type-2 diabetes. Several chromatographic techniques have been described in the literature for determination of each of these medications separately. But these procedures used organic solvents that could be dangerous for humans and animals, not to mention harmful to the environment. It is vital to substitute or reduce the use of these neurotoxic and teratogenic solvents in the chromatographic analysis of these anti-diabetic medications to ensure the safety of life and safeguard the environment. The chromatographic technique used for sample analysis should have characteristics like robustness, eco-friendliness, cost-effectiveness, and user-friendliness following the recently developed idea of white analytical chemistry. Teneligliptin and pioglitazone have not yet been simultaneously estimated using a chromatographic method that has been documented in the literature.MethodsA white analytical chemistry-assisted RP-HPLC method has been developed to fill this gap, using economical and eco-friendly solvents. The design of the experiment approach was used during the development of the RP-HPLC method to reduce organic waste and guarantee that the procedure complied with all applicable regulations. Response surface models were built using the full factorial design approach, and the analytical design space was investigated. This method allowed for the identification of an optimal chromatographic condition within the method's operational design region, allowing reliable RP-HPLC analysis of pioglitazone and teneligliptin.ResultsThe developed RP-HPLC technique underwent validation and was used effectively to assess these drugs in their fixed-dose combinations. Assessments were made of the suggested and published RP-HPLC techniques' validation status, process greenness, cost, and analysis time. For a thorough examination, this review included white analytical chemistry-based RGB models and different green analytical chemistry-based tools.ConclusionIn allowing the simultaneous estimate of teneligliptin and pioglitazone, the devised approach demonstrated robustness, eco-friendliness, and cost-effectiveness.

A multi-objective design tool for decarbonising buildings at the concept stage

To enable the move to carbon-neutral building structures with net-zero operation requires a step change in how buildings are designed. Modern buildings are designed by multidisciplinary design teams each of which has competing performance objectives. Daisy is a flexible performance-based parametric design tool which harnesses computational design workflows to enable designer-led multi-objective optimisation, allowing for the design of buildings which simultaneously achieve high performance across multiple performance objectives. A case study of designs for a 63-storey commercial building is presented that demonstrates how early design space analysis facilitates better-performing buildings across architectural and engineering performance metrics and the potential of multi-objective optimisation for enabling the move towards carbon-neutral building structures. Beyond building structures, the design methodology established for Daisy can be applied to a broad range of civil engineering optimisation problems using a flexible and accessible design space formulation that can be adapted for project-specific design requirements. Designs generated using the Daisy methodology demonstrated that by increasing the spatial daylight autonomy of the benchmark building by 14.7%, the building can be moved from the 10% of designs with the highest energy use intensity to lower than 97% of other simulated designs. However, this design change significantly increases the building embodied carbon, with the new design having a building embodied carbon which is higher than 90% of other buildings simulated. Alternatively, by reducing the spatial daylight autonomy by 32.8%, the design can have an energy use intensity which is lower than 75% of other simulated designs, with a 4.4% reduction in energy use intensity, and a building embodied carbon which is lower than 60% of other simulated designs, enabling a 1.3% reduction in building embodied carbon.

Analytical Quality Risk Assessment and Design of Experiments to Green HPTLC Method for Simultaneous Estimation of Sildenafil Citrate and Dapoxetine Hydrochloride.

A green and robust high-performance thin-layer chromatographic method has been developed for the simultaneous estimation of sildenafil citrate and dapoxetine hydrochloride. A fractional factorial design was applied for analytical quality risk assessment of potential analytical risk factors. The identified critical analytical risk factors were optimized using the design of experiment-based response surface analysis by full factorial design. The analytical design space was navigated for the optimization of the method and the control strategy was framed for low-risk life-cycle management of the chromatographic method. The chromatographic analysis of sildenafil and dapoxetine was carried out on a TLC plate coated with silica gel G60 F254 using n-butanol:ethyl acetate:ethanol (8.0 + 2.0 + 0.5, v/v) as mobile phase. The chromatographic peaks of sildenafil and dapoxetine were found to be at Rf 0.29 and 0.69, respectively. The method was found to be accurate, precise, robust, specific and sensitive. The fixed-dose combinations of sildenafil and dapoxetine were assayed and results were found in compliance with their labeled claim. The present method was developed using safe and eco-friendly organic solvents for the safety of analysts and the protection of the environment. The greenness profiles of developed and reported methods were evaluated using the NEMI scale and AGREE software.

Implementation of White Analytical Chemistry-Assisted Analytical Quality by Design Approach to Green Liquid Chromatographic Method for Concomitant Analysis of Anti-Hypertensive Drugs in Human Plasma.

According to current concepts of white analytical chemistry (WAC), the use of organic solvents those are teratogenic and carcinogenic must be avoided for the protection of the environment and of the analysts. This led to the development and validation of the WAC-assisted green liquid chromatographic technique (reverse-phase high-pressure liquid chromatography (RP-HPLC)) for the simultaneous analysis of anti-hypertensive drugs (azilsartan medoxomil, chlorthalidone and cilnidipine) in human plasma and their fixed-dose combinations. The analytical quality by design approach was used in conjunction with the design of experiments and chemometrics concepts to develop the method. To develop the green RP-HPLC method, critical method variables (CMVs) and critical analytical attributes were identified using the multivariate analytical tools principal component analysis and partial least square regression. Using the Box-Behnken design, the design of experiments was used for CMV optimization and response surface analysis. It was possible to explore the analytical design space for the life cycle management of the RP-HPLC method. The developed method was found to be validated following International Council for Harmonization Q2 (R1) and M10 requirements. Using the red, green and blue paradigm, the existing and proposed chromatographic methods were evaluated for their validation efficacy, greenness profile and cost-effectiveness.

Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction

Hybrid modeling workflows combining machine learning with mechanistic process descriptions are becoming essential tools for bioprocess digitalization. In this study, a hybrid deep modeling method with state–space reduction was developed and showcased with a P. pastoris GS115 Mut+ strain expressing a single-chain antibody fragment (scFv). Deep feedforward neural networks (FFNN) with varying depths were connected in series with bioreactor macroscopic material balance equations. The hybrid model structure was trained with a deep learning technique based on the adaptive moment estimation method (ADAM), semidirect sensitivity equations and stochastic regularization. A state–space reduction method was investigated based on a principal component analysis (PCA) of the cumulative reacted amount. Data of nine fed-batch P. pastoris 50 L cultivations served to validate the method. Hybrid deep models were developed describing process dynamics as a function of critical process parameters (CPPs). The state–space reduction method succeeded to decrease the hybrid model complexity by 60% and to improve the predictive power by 18.5% in relation to the nonreduced version. An exploratory design space analysis showed that the optimization of the feed of methanol and of inorganic elements has the potential to increase the scFv endpoint titer by 30% and 80%, respectively, in relation to the reference condition.

Red, Green and Blue Model-based Assessment and Principles of White Analytical Chemistry to Robust Stability-Indicating Chromatographic Estimation of Thiocolchicoside and Diclofenac Sodium.

White analytical chemistry (WAC) is a recent approach for evaluating analytical procedures based on their effectiveness in validating results, capacity to be environmentally friendly and economic effectiveness. The detection of diclofenac sodium (DCF) and thiocolchicoside (THC) simultaneously has been established using a WAC-driven stability indicating chromatographic method (SICM). For the concurrent stability study of THC and DCF, the suggested chromatographic technique was developed employing a safe and environmentally acceptable organic solvents. To identify critical analytical method parameters (AMPs) and analytical quality attributes (AQAs), the design of experiments (DoE)-based screening design was applied. For the DoE-based response surface modelling (RSM) of critical AMPs and AQAs, the Box-Behnken design (BBD) was employed. A robust SICM was developed by navigating the analytical design space for simultaneous estimation of THC and DCF. The IR, NMR, and mass spectral data were used to characterize the degradation products. The red, green, and blue (RGB) models were used to evaluate the suggested method's validation effectiveness, greenness power, and economic efficiency with published chromatographic techniques. The effectiveness of the chromatographic method's validation concerning the ICH Q2 (R1) guideline was evaluated using the red model. Analytical greenness (AGREE) evaluation tool and eco-scale assessment (ESA) approach were used to evaluate the green model's methodology. The blue model-based assessment was carried out for comparison of handling of instruments, cost, and time during sample analysis. The red, blue, and green scores of the techniques were averaged to arrive at the white score of the suggested and reported methods. For the concurrent stability study of THC and DCF, the suggested technique was shown to be validated, environmentally friendly, and cost-effective. The suggested approach could be a cost-effective and environmentally friendly analytical technique for determining the stability and monitoring the quality of fixed-dose combinations of THC and DCF. Development of stability-indicating HPTLC method for concomitant analysis of THC and DCF using concepts of DoE and white analytical chemistry.

Reaction kinetics determination and uncertainty analysis for the synthesis of the cancer drug lomustine

Fast and reliable model development frameworks are required to support current trends in modernization of pharmaceutical processing, promoting the use of digital platforms to assist process design and operation. In this work, we use a parameter estimation framework built into the PharmaPy library to determine rate parameters and uncertainty regions of different mechanistic and semi-empirical kinetic expressions for the synthesis of the drug lomustine. The parameter estimation procedure was complemented by identifiability analysis, resulting in simplified reaction mechanisms. Comparison of parameters and their uncertainty in process design was demonstrated through design space analysis, showing important differences in model prediction and the extent of their corresponding design spaces. The results of this work can serve to analyze lomustine manufacturing processes that include separation and isolation steps, where parametric uncertainty is expected to propagate along the manufacturing line and impact process feasible operation, and attainment of critical quality attributes of the product.

Design space analysis for supercritical CO2 radial inflow turbine stators

Radial inflow turbines(RITs) play a vital role in power generation due to their small size, compact construction and large power density, especially when applying to supercritical CO2(sCO2) power cycles. Correct preliminary design of the RITs is important for enhancing the efficiency of cycles. Most preliminary design studies for RITs simply impose empirically developed angle constraints for the rotor inlet conditions instead of giving much attention to the stators. In addition, the previous design procedure can only calculate one geometry at a time, which does not allow the selection of the most suitable geometry that fits the cycle parameters and constraints. Hence, this paper presents a workflow to correctly size a stator for achieving a desired rotor inflow conditions. Then a stator design-space analysis with utilising an existing 500 kW sCO2 rotor is conducted. Based on a number of given stator radius ratio(r3/r4), blade number(Zs) and blade trailing edge thickness(t3), the obtained design map contains a total number of Nr3/r4×NZs×Nt3 preliminary design cases. New insights are discussed, including that the workflow is functional; the blade angles need to adjust between no-loss and loss cases; the rotor–stator interaction loss will increase the stator inlet/outlet operational parameter when guaranteeing the target rotor inlet conditions; and including of the stator losses in turbine design is significant.

Reversed‐phase high‐performance liquid chromatography analytical method development and validation for cefepime and sulbactam injection formulation assay: A quality by design approach

AbstractA trustworthy high‐performance liquid chromatography approach for the simultaneous measurement of cefepime and sulbactam was created using quality by design. Finding reliable chromatographic settings for quality peaks and suitable component separation within a manageable run time was the key objective. Critical quality attributes for risk measurement were evaluated. To create an analytical design space and create a control strategy, the quantitative link between critical material attributes and critical quality attributes was built. Acetonitrile volume, trimethylamine volume, and flow rate were the three independent parameters considered in the mathematical models. Acetonitrile:high‐performance liquid chromatography water:triethylamine and pH 6.0, adjusted with orthophosphoric acid (50.0:50:0.15, v/v/v) as the mobile phase at 1.1 ml/min, were the ideal and anticipated conditions. We obtained appropriate baseline separation of both medications in about 10 min using these ideal conditions. The main determinant of the perturbation plot responses was found to be the quantity of acetonitrile. At all three levels, the percent recoveries for both medications ranged from 99% to 99.68%. Relative standard deviations were less than 2% for both drugs' intermediate accuracy and repeatability. A straightforward, precise, and repeatable high‐performance liquid chromatography method for regular quality control testing was created as a consequence.

Multivariate Analysis and Response Surface Modeling to Green Analytical Chemistry-Based RP-HPLC-PDA Method for Chromatographic Analysis of Vildagliptin and Remogliflozin Etabonate.

The fixed-dose combination (FDC) of vildagliptin (VDG) and remogliflozin etabonate (RGE) is used as antidiabetic medicine. Numerous reverse phase high-pressure liquid chromatographic (RP-HPLC) methods have been reported for the estimation of VDG and RGE using toxic organic solvents such as acetonitrile and methanol. These organic solvents are also hazardous to the environment. Hence, the robust and green analytical chemistry-based RP-HPLC-PDA method has been developed for chromatographic analysis of VDG and RGE for the safety of analysts and protection of the environment. The multivariate analysis has been carried out for the identification of critical method risk parameters (CMRPs) and critical method performance attributes (CMPAs) using principal component analysis (PCA). The identified CMRPs and CMPAs were linked with each other for optimization of the RP-HPLC-PDA method using DoE-based response surface modeling. The analytical design space (ADS) has been explored for robust chromatographic analysis of VDG and RGE. The chromatographic analysis of VDG and RGE has been carried out using Shim-Pack C18 column (250 mm L, 4.6 mm ID, 5.0 µm PS) and isopropyl alcohol-0.1% (v/v) formic acid (FA) in water (45 + 55, v/v, pH -3.5). The developed method has been validated in accordance with ICH Q2 (R1) guidelines. The method has been applied for the assay of VDG and RGE in their FDCs. The results of the assay were found in compliance with the labeled claims. The developed RP-HPLC-PDA method did not include any toxic or carcinogenic solvents. Hence, it is safe for analysts and the environment. The greenness profiles of the published and proposed RP-HPLC methods were evaluated by the national environmental method index (NEMI) scale, and the analytical greenness scores were calculated using the AGREE software. The developed method can be used as an eco-friendly tool in the pharmaceutical industry for routine analysis and quality control of FDCs of VDG and RGE. Development of a green and robust RP-HPLC method for the estimation of VDG and RGE using safe organic solvents. The analytical quality by design (AQbD) approach has been implemented in the development of a method to minimize solvent wastage. The method was applied for the assay of FDCs of VDG and RGE.

Network Pharmacological Analysis on the Herbal Combinations for Mitigating Inflammation in Respiratory Tracts and Experimental Evaluation.

The regulation of inflammatory mediators, such as TNF-α, IL-6, IL-1β, and leukotriene B4, could play a crucial role in suppressing inflammatory diseases such as COVID-19. In this study, we investigated the potential mechanisms of drug combinations comprising Ephedrae Herba, Schisandra Fructus, Platycodonis Radix, and Ginseng Radix; validated the anti-inflammatory effects of these drugs; and determined the optimal dose of the drug combinations. By constructing a herb-compound-target network, associations were identified between the herbs and tissues (such as bronchial epithelial cells and lung) and pathways (such as the TNF, NF-κB, and calcium signaling pathways). The drug combinations exerted anti-inflammatory effects in the RAW264.7 cell line treated with lipopolysaccharide by inhibiting the production of nitric oxide and inflammatory mediators, including TNF-α, IL-6, IL-1β, and leukotriene B4. Notably, the drug combinations inhibited PMA-induced MUC5AC mRNA expression in NCI-H292 cells. A design space analysis was carried out to determine the optimal herbal medicine combinations using the design of experiments and synergy score calculation. Consequently, a combination study of the herbal preparations confirmed their mitigating effect on inflammation in COVID-19.

Quality by design-based development and validation of an HPLC method for simultaneous estimation of pregabalin and piperine in dual drug-loaded liposomes.

The current research work describes the development of a rapid HPLC method for the concurrent detection of pregabalin and piperine in dual drug-loaded nanoformulations. The primary goal was to recognize the chromatographic conditions wherein propitious segregation of the integrants with quality peaks can be attained. An attempt to expound the target analytical profile was made to accomplish this goal, and critical method attributes (CMAs), viz. percentage acetonitrile content, injection volume and pH, which affect critical quality attributes (CQAs), were identified using systemic risk analysis. Box-Behnken design was employed to develop a relationship between CMAs and CQAs, which engenders an analytical design space. Efficient chromatographic separation for pregabalin and piperine was attained using an analytical C18 column and mobile phase comprising acetonitrile-water (pH6.9; 70:30%, v/v) in an isocratic elution mode with a 1ml/min flow rate. The elution was descried at an isosbestic wavelength of 221 nm using a photodiode array detector. The International Conference on Harmonization guidelines were adopted for the developed HPLC method. The validated HPLC method can be further utilized for the simultaneous quantification and detection of pregabalin and piperine in other lipid-based nanopharmaceuticals such as polymeric nanoparticles, nanocrystals, solid-lipid nanoparticles, metallic nanoparticles, etc., in in vitro and in vivo studies.

Quality by design assisted high‐performance liquid chromatography parameters for simultaneous estimation of simvastatin and fenofibrate

AbstractIn a present study quality by design was used to develop a reliable high‐performance liquid chromatography method for simultaneous estimation of simvastatin and fenofibrate. A robust chromatographic setting for quality peaks and appropriate component separation within a reasonable run duration was generated. Furthermore, to determine critical quality attributes (CQA), a quantitative relationship between critical material attributes and CQA was established using Box‐Behnken design to produce analytical design space and develop a control approach. The mathematical models used three independent characteristics, acetonitrile volume, buffer molarity, and flow rate. The optimum and expected conditions were acetonitrile and potassium dihydrogen orthophosphate buffer (pH 2.9 adjusted, with orthophosphoric acid) (80.65:19.35 v/v) as an optimized mobile phase at a flow rate of 0.99 ml/min. We achieved adequate baseline separation of both drugs in just 10 min with these optimum parameters. The amount of acetonitrile was revealed to be the most important factor determining the perturbation plot responses. The %recoveries for both medicines were 99.15%–101.86% at all three levels. Both drugs showed relative standard deviations for repeatability, and intermediate precision were less than 2%. As a result, a simple, accurate, and repeatable high‐performance liquid chromatography approach for routine quality control testing was developed.

Chemometric-Based AQbD and Green Chemistry Approaches to Chromatographic Analysis of Remogliflozin Etabonate and Vildagliptin.

According to the green chemistry approach, during method development, the usage of toxic and carcinogenic organic solvents should be avoided or minimized for the safety of the environment and analysts. The chromatographic methods such as reverse-phase high-pressure liquid chromatography (RP-HPLC) and high-performance thin-layer chromatography (HPTLC) include the usage of class 2 organic solvents as per the International Council for Harmonization (ICH) Q3C (R6) guideline. The chromatographic analysis by HPTLC requires less organic solvent compared to the RP-HPLC method. Hence, HPTLC-based chromatographic analysis of vildagliptin (VIL) and remogliflozin etabonate (RMG) has been carried out using green chemistry and analytical quality by design (AQbD) approaches. The principal component analysis (PCA)-based chemometric analysis was applied for the identification of critical method variables (CMV) for the development of the method. The design of experiments (DoE)-based Box-Behnken design (BBD) was applied for response surface modeling (RSM) and optimization of CMV. The analytical design space (ADS) and analytical control point were navigated for the development of the HPTLC method as per the quality target analytical profile. The chromatographic analysis of VIL and RMG was carried out using silica gel G60 F254 as the stationary phase and acetone-ethyl acetate-water-triethylamine (7.0 + 2.5 + 0.3 + 0.2, v/v) as the mobile phase. The HPTLC method was validated as per the ICH Q2 (R1) guideline. The HPTLC method was applied for the assay of fixed-dose combinations (FDCs) of VIL and RMG, and the results were found to comply with their labeled claim. The developed method included the usage of organic solvents that belong to the class 3 category as per the ICH Q3C (R6) guideline. Hence, the developed method can be used as an eco-friendly alternative to published chromatographic methods for quality control and routine analysis of FDCs of VIL and RMG in the pharmaceutical industry. Chromatographic analysis of VIL and RMG using green chemistry and AQbD approaches. Application of the method for assay of drugs in their combined pharmaceutical dosage forms.

Application of Taguchi OA and Box-Behnken Design for the Implementation of DoE-based AQbD Approach to HPTLC Method for Simultaneous Estimation of Azilsartan and Cilnidipine.

Hypertension is the most prominent disease found in people due to stressful routines and the working environment. The fixed-dose combination (FDC) of azilsartan medoxomil (AZL) and cilnidipine (CLN) is used for the treatment of hypertension. According to the green chemistry approach, organic solvents should be minimized in the development of the analytical method for the safety of the environment. The high-performance thin-layer chromatographic (HPTLC) method required less amount of organic solvent for the analysis of the drug. Hence, it was thought of interest to develop an accurate and robust HPTLC method for the estimation of AZL and CLN in their FDC. The development of the method was carried out by the implementation of the analytical quality by design approach using the Taguchi orthogonal array and BBD for regulatory compliance as per the upcoming ICH Q14 guideline. The analytical design space and control strategy was framed for the lifecycle management of the method. The chromatographic separation was performed using silica gel GF254 and toluene ethylacetate-methanol (6.5 + 1.5 + 2.0, v/v). The method was applied for the assay of FDC and results were found in compliance with the labeled claim. The developed method was also applied for the estimation of spiked human plasma and the recovered amount of drugs was found in the range of 80-85%.

Application of Chemometry and Design of Experiments to Green HPTLC Method for Synchronous Estimation of Multiple FDCs of Cilnidipine.

Numerous fixed-dose combinations (FDCs) of cilnidipine (CIL) with chlorthalidone (CLT) and azilsartan medoxomil (AZL) are used for the treatment of hypertension. Numerous reverse-phase high-pressure liquid chromatography (RP-HPLC) and high-performance thin-layer chromatography (HPTLC) methods have been reported in the literature for the estimation of FDCs of CIL. But no HPTLC method has been reported yet for synchronous estimation of multiple FDCs of CIL to save time, organic solvent, and cost of analysis. In the recent scenario of green chemistry, the minimum usage of organic solvent in the development of the chromatographic method is highly desirable for the safety of the environment and analysts. Hence, a robust and green HPTLC method has been developed for the synchronous estimation of multiple FDCs of CIL using the analytical quality by design (AQbD) approach. The chemometric tool was applied for the identification of the critical method variables (CMVs) and critical analytical attributes (CAAs) for the HPTLC method development. The design of experiments (DoE) was applied for the response surface analysis of identified CMVs and CAAs using the Box-Behnken design. The analytical design space and control strategy was framed for the lifecycle management of the HPTLC method. The chromatographic separation was performed using silica gel G60 F254 as the stationary phase and toluene-ethyl acetate-methanol (6.5 + 2 + 1.5, v/v) as the mobile phase. The method was validated as per the International Council for Harmonization Q2 (R1) guideline. The developed method was applied for the synchronous estimation of multiple FDCs of CIL, and results were found in compliance with labeled claims. The developed HPTLC method can be used as a green, economical, and rapid analytical tool for routine analysis and quality control of multiple FDCs of CIL in the pharmaceutical industry. Development of a HPTLC method for synchronous estimation of multiple FDCs of CIL using the AQbD approach based on principles of chemometry and DoE. Application of the developed method for synchronous assay of multiple FDCs of CIL to save time, cost, and solvent for analysis.

Spherical gear coupling design space analysis for high misalignment applications

Spherical gear couplings are machine elements that enable power transmission between highly misaligned shafts. The highly crowned tooth surfaces and the presence of undercut sections, have been a matter of disagreement between existing geometry generation methods available in the scientific literature. The main reason for this, are the geometry variations which arise in the generated parts, and consequently, the effect of such variations on the contact point location and clearance distribution. In this paper the influence of the main design parameters of spherical gear couplings (namely, the crowning ratio, the pitch diameter, the pressure angle, etc.), on the geometrical properties of the gear tooth surfaces are investigated. An algorithm to calculate the maximum misalignment angle is proposed, which is one of the most crucial design parameters. It shows that the values obtained with models existing in the literature are not applicable to highly crowned spherical gear couplings. Finally, design criteria are described to help the designer choose proper spherical gear coupling tooth geometry parameters to fit in a certain space and achieve a given maximum misalignment angle without further geometrical issues (undercut or pointed teeth).

An optimum security enabled System‐on‐Chip selection for Internet of Things applications using genetic algorithm modeling

SummaryThe System‐on‐Chip (SoC) is the core component in embedded systems that push toward the evolution of the Internet of Things. The quick growth of embedded SoC devices has a substantial influence to overcome security issues in embedded system design. Since microcontroller‐based systems are security and safety‐critical, this article focuses on security aspects of state‐of‐the‐art microcontrollers through performing design space analysis of several crypto‐core algorithms. These crypto functions are analyzed and compared to identify and implement the appropriate algorithm for on‐chip security. The genetic algorithm (GA) optimization model is utilized for the optimal selection of secured SoC from the commercial devices that are stored in the database. In this work, the fitness function is proposed with various levels such as performance‐centric, security enabled, low operating power, and application‐specific SoC selection. We also validate the GA results by implementing the security benchmarks on resultant devices by analyzing the execution time and performance. The accuracy of the GA‐based optimum SoC selection is estimated using confusion matrix method that produces the accuracy of .

Chemometrics and Monte-Carlo Simulation Assisted RP-LC Method for Estimation of Cinacalcet Hydro- chloride in Pharmaceutical Products

Cinacalcet hydrochloride (CNT) is a novel calcimimetic agent widely used in the treatment of hyperparathy- roidism. For the first time, the authors utilized the novel concept of analytical procedure development employing several unique scientific tools for quantification CNT from its pharmaceutical dosage form. The objective behind the present work was to establish a scientifically sound and systematic work frame that overcomes the drawbacks of the earlier reported method for estimating CNT level in samples and ensuring superior method performance throughout the analytical life-cycle. In this process, at first, the risky method variables were earmarked and were subjected to a response surface methodology, followed by Monte-Carlo simulation (MCS) based robust- ness-cum-optimization studies. The inclusion of the MCS approach assessed the method performance with no additional laboratory experimentation and established the innovative hyphenation's aptness with chemometrics tools. The control strategies were established based on analytical design space and method performance evaluation results by a simulative approach. The study revealed that methanol %, flow rate, and pH are the three critical method variables influencing analytical attributes: retention time, the number of plates, and tailing. The analytical conditions include a C18 column (150mm × 4.6mm, 5μm) with an isocratic mobile phase (80:20, % v/v) of methanol and 0.01M KH2PO4 buffer (pH maintained at 3.5 using orthophosphoric acid) flowing at 1.1ml/min. Diode array detection was performed at 282 nm. Method validation was befitting to federal needs as linearity (0.5-160 μg/ml), accuracy (>99%), and precision below 1% of relative standard deviation are indicative of method suitability for the purpose. In a nutshell, the present method describes a typical analytical workflow with the significant advantage of obtaining more excellent scientific information with less systematized experimentation. It was found suitable for routine quality control of CNT in drug substance and drug product.