Design Space Approach Research Articles

Unveiling the optimal path: High-pressure homogenization and D-phase emulsification methods for borage oil nanoemulsion design

Borage oil contains high levels of essential omega-6 fatty acids, which are important for skin structure and function. For this reason, this oil can be used for the treatment of cutaneous diseases including atopic dermatitis. This disease is associated with an abnormality in essential fatty acids (EFAs) metabolism, particularly in the production of gamma-linolenic acid, leading to impaired incorporation of EFAs into the phospholipid membrane. EFAs bioavailability can be enhanced by using a borage oil nano-based drug delivery system. In this study a borage oil nanoemulsion was prepared using high-pressure homogenization (HPH) and D-phase emulsification (DPE), respectively, high and low energy methods. A design space approach was performed to optimize the formulations. The optimized HPH nanoemulsion (HPH-NE) presented a particle size and zeta potential (ZP) of 425.3 ± 5.6 nm, and − 19.4 ± 3.7 mV, respectively. For the DPE nanoemulsion (DPE-NE) the particle size was 334.4 ± 5.2 nm, and the zeta potential was − 34.6 ± 1.0 mV. Furthermore, DPE-NE presented higher toxicity compared to HPH-NE, possibly related to the presence of the polyol. These nanoemulsions may improve the borage oil bioavailability for oral administration. Thus, they can be used as an adjuvant therapy in the treatment of atopic dermatitis.

Analytical method development supported by DoE-DS approach for enantioseparation of (S,S)- and (R,R)-moxifloxacin

In this paper, method for enantiomeric purity testing of fourth-generation fluoroquinolone, moxifloxacin hydrochloride, was developed and validated. Exceptional enantioselectivity for this assay was achieved using cyclodextrin type Chiral Stationary Phase (CSP), phenylcarbamate-β-cyclodextrin CSP, and mobile phase consisted of acetonitrile and triethylammonium acetate (TEAA) buffer. Analytical Quality by Design (AQbD) methodology, comprising Design of Experiments (DoE) - Design Space (DS) approach, was used for method development. In order to select appropriate Critical Method Parameters (CMPs), risk assessment was done using combined three step strategy that involved Ishikawa diagram - CNX (Control, Noise and eXperimental) - FMEA (Failure Mode and Effect Analysis). Three CMPs were further selected and investigated in this study: acetonitrile content in the mobile phase (30–50%, v/v), triethylamine content in the TEAA buffer (0.1–1.5%, v/v) and aqueous phase pH (3.5–4.5). Monte Carlo simulations were performed and 3D-DS was computed. One point situated in the center of 3D-DS was selected as working point for method validation, with the following values of CMPs: acetonitrile content in the mobile phase set to 37% (v/v), triethylamine content in TEAA 0.8% and pH value of the aqueous phase set at 4.0. Also, 2D-DS was created (with fixed one factor – pH value of aqueous phase at 4.0) which also gave us confirmation that the selection of working conditions was suitable. The proposed enantioselective method was further on tested for its quantitative robustness, as well as for its suitability for the intended purpose through validation studies.

Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores.

Transition-metal chromophores with earth-abundant transition metals are an important design target for their applications in lighting and nontoxic bioimaging, but their design is challenged by the scarcity of complexes that simultaneously have well-defined ground states and optimal target absorption energies in the visible region. Machine learning (ML) accelerated discovery could overcome such challenges by enabling the screening of a larger space but is limited by the fidelity of the data used in ML model training, which is typically from a single approximate density functional. To address this limitation, we search for consensus in predictions among 23 density functional approximations across multiple rungs of "Jacob's ladder". To accelerate the discovery of complexes with absorption energies in the visible region while minimizing the effect of low-lying excited states, we use two-dimensional (2D)efficient global optimization to sample candidate low-spin chromophores from multimillion complex spaces. Despite the scarcity (i.e., ∼0.01%) of potential chromophores in this large chemical space, we identify candidates with high likelihood (i.e., >10%) of computational validation as the ML models improve during active learning, representing a 1000-fold acceleration in discovery. Absorption spectra of promising chromophores from time-dependent density functional theory verify that 2/3 of candidates have the desired excited-state properties. The observation that constituent ligands from our leads have demonstrated interesting optical properties in the literature exemplifies the effectiveness of our construction of a realistic design space and active learning approach.

Design Space Approach for the Optimization of Green Fluidized Bed Granulation Process in the Granulation of a Poorly Water-Soluble Fenofibrate Using Design of Experiment.

In the pharmaceutical industry, the systematic optimization of process variables using a quality-by-design (QbD) approach is highly precise, economic and ensures product quality. The current research presents the implementation of a design-of-experiment (DoE) driven QbD approach for the optimization of key process variables of the green fluidized bed granulation (GFBG) process. A 32 full-factorial design was performed to explore the effect of water amount (X1; 1–6% w/w) and spray rate (X2; 2–8 g/min) as key process variables on critical quality attributes (CQAs) of granules and tablets. Regression analysis have demonstrated that changing the levels of X1 and X2 significantly affect (p ≤ 0.05) the CQAs of granules and tablets. Particularly, X1 was found to have the pronounced effect on the CQAs. The GFBG process was optimized, and a design space (DS) was built using numerical optimization. It was found that X1 and X2 at high (5.69% w/w) and low (2 g/min) levels, respectively, demonstrated the optimum operating conditions. By optimizing X1 and X2, GFBG could enhance the disintegration and dissolution of tablets containing a poorly water-soluble drug. The prediction error values of dependent responses were less than 5% that confirm validity, robustness and accuracy of the generated DS in optimization of GFBG.

Application of the analytical quality by design principles to the development of a qualitative surface‐enhanced Raman scattering method: A proof of concept

AbstractAnalytical quality by design (AQbD) is a systematic approach that allows developing analytical methods in a more science‐based way, due to the higher quality of information collected during the development process. However, its application remains limited to the development of separation methods. (i.e., liquid chromatography and capillary electrophoresis). Its application to spectroscopic techniques remains underexplored, despite the potential benefits. The aim of this work was to demonstrate the application of the AQbD principles to surface‐enhanced Raman scattering (SERS) method development, detailing each step characterizing this approach. First, crystal violet (CV) was chosen as a model compound and the analytical target profile was defined. Risk assessment was performed to individuate the critical method parameters. The intensity of the CV band at 1175 cm−1 was selected as critical method attribute to be modeled and maximized. A screening study was conducted to study 11 aggregation agents (AAs) at different concentration levels (range 0.010–1 M) and in two solvent media (aqueous and methanolic). The two AAs exhibiting the strongest signal, one for each medium, were retained. Once these parameters were fixed, an I‐optimal design was applied to optimize the entire analysis process. Here, the volumes of nanoparticle suspension and AA solution added to the SERS samples were simultaneously varied. Two method operable design regions, one for each medium, were computed using a Bayesian design space approach. The latter enabled evaluating the failure risk associated to each experimental condition explored and choosing those that best fit the analytical purpose in the experimental domain.

Recommended Best Practices for Lyophilization Validation\u20142021 Part I: Process Design and Modeling

This work describes lyophilization process validation and consists of two parts. Part I focuses on the process design and is described in the current paper, while part II is devoted to process qualification and continued process verification. The intent of these articles is to provide readers with recent updates on lyophilization validation in the light of community-based combined opinion on the process and reflect the industrial prospective. In this paper, the design space approach for process design is described in details, and examples from practice are provided. The approach shows the relationship between the process inputs; it is based on first principles and gives a thorough scientific understanding of process and product. The lyophilization process modeling and scale-up are also presented showing the impact of facility, equipment, and vial heat transfer coefficient. The case studies demonstrating the effect of batch sizes, fill volume, and dose strength to show the importance of modeling as well as the effect of controlled nucleation on product resistance are discussed.Graphical abstract

Design of experiments and design space approaches in the pharmaceutical bioprocess optimization

The optimization of pharmaceutical bioprocesses suffers from several challenges like complexity, upscaling costs, regulatory approval, leading to the risk of delivering substandard drugs to patients. Bioprocess is very complex and requires the evaluation of multiple components that need to be monitored and controlled in order to attain the desired state when the process ends. Statistical design of experiments (DoE) is a powerful tool for optimizing bioprocesses because it plays a critical role in the quality by design strategy as it is useful in exploring the experimental domain and providing statistics of interest that enable scientists to understand the impact of critical process parameters on the critical quality attributes. This review summarizes selected publications in which DoE methodology was used to optimize bioprocess. The main objective of the critical review was to clearly demonstrate potential benefits of using the DoE and design space methodologies in bioprocess optimization.

Using Design Space and Response Surface Methodology for developing a liquid chromatography method for simultaneous determination of five statins in pharmaceutical form

AbstractThis study describes the development of a method allowing the simultaneous separation and quantification of five statins by High performance liquid chromatography/Diode Array Detector (HPLC/DAD). Optimization was accomplished using chemometric tools such as the Design Space (DS) and Response Surface Methodology (RSM). Central Composite Design (CCD) and DS were applied for the optimization of the chromatographic procedure as well as the robustness of the chromatographic method by taking the ratio of the percentage of acetonitrile (%ACN) Buffer solution, the pH and the mobile phase flow rate as critical parameters. Satisfactory results were obtained after the optimization phase with a percentage of mobile phase equal to 46.19%, a pH of 4.16 and the flow rate is 1.4 mL min−1 by setting the resolution limits above 6, and the target retention time of 20 min. Using the DS and CCD approach, we have developed a robust and reliable procedure for the simultaneous and accurate separation and quantification of the five statins.

Complying with the Guideline for Quality and Equivalence for Topical Semisolid Products: The Case of Clotrimazole Cream.

Semisolids constitute a significant proportion of topical pharmaceutical dosage forms available on the market, with creams being considered profitable systems for releasing active substances into the skin. This work aimed at the development of a generic Clotrimazole topical cream, based on the assumptions that assist the development of such formulations. First, the critical parameters to obtain a final formulation as similar as possible to the reference product were defined. Then, the percentages of cetyl palmitate and octyldodecanol were identified as critical variables and chosen for optimization in further studies. A “quality by design” approach was then used to identify the effect of process variability on the structural and functional similarity (Q3) of the generic product qualitatively (Q1) and quantitatively (Q2). A two-factor central composite orthogonal design was applied and eleven different formulations were developed and subjected to physicochemical characterization and product performance studies. The results were used to estimate the influence of the two variables in the variation of the responses, and to determine the optimum point of the tested factors, using a design space approach. Finally, an optimized formulation was obtained and analysed in parallel with the reference. The obtained results agreed with the prediction of the chemometric analysis, validating the reliability of the developed multivariate models. The in vitro release and permeation results were similar for the reference and the generic formulations, supporting the importance of interplaying microstructure properties with product performance and stability. Lastly, based on quality targets and response constraints, optimal working conditions were successfully achieved.

The glucocorticoid derivative with the phthalimide group cationic nanocrystal for ophthalmic application: a design space development approach

The glucocorticoid derivative of budesonide with a phthalimide group is a drug candidate to treat inflammatory eye diseases; nevertheless, it presents low water solubility. Drug nanocrystals have been proposed to overcome this hurdle. The development of an innovative ophthalmic anti-inflammatory nanosuspension was performed using a design space approach. We obtained the particle size reduction of this glucocorticoid derivative on a nanometer scale (approximately 165.0 nm), applying wet bead milling on a super reduced scale. The design of experiment supported the optimization of the formula evaluating the parameters that influence reducing the particle size and also allowed determining the design space. Considering the two statistical models developed and the size range obtained, we proposed that the optimized formulation for the glucocorticoid derivative nanosuspension may be 1.0 wt% glucocorticoid derivative and 0.092 wt% cetylpyridinium chloride. This formulation was characterized by the morphological, physical–chemical, and mucoadhesive in vitro test and showed potential for ophthalmic use with reduced frequency of product application, improved efficiency, and safety, which may promote better patient compliance.

Development of freeze-drying cycle via design space approach: a case study on vaccines

Freeze-drying is a dehydration process that provides improved stability of vaccine formulations for shipment and storage. During the primary drying steps of the process, product temperature has to be maintained below a critical value to avoid visual defects of the product, leading to an increase of the sublimation time and thus of the operational costs. In this work, we used the design space approach together with experimental analysis for the development of the primary drying step of a vaccine model formulation. First, the formulation was characterized by determining the glass transition and the collapse temperatures. Successively, the dynamic design space of primary drying was calculated via mathematical modelling, and a proven acceptable range (PAR) was defined around the selected operating values. Finally, the cycle and the PAR were validated by performing a freeze-drying cycle at pilot scale and by evaluating the values of the product critical quality attributes (e.g. moisture content, visual aspect, reconstitution time).

The development of Fructus corni quality standard considering the effects of processing

The quality standards for Fructus Corni have been established based on the effects of the manufacturing processes. Three critical process parameters (CPPs) of extraction, filtration, and concentration to prepare Fructus Corni concentrate were identified by Plackett–Burman design with a single batch of Fructus Corni , which were heating medium temperature, extraction time, and water addition. Morroniside yield, loganin yield, and dry matter yield were process critical quality attributes (CQAs). CPPs arranged with a Box–Behnken design were applied to treat different batches of Fructus Corni. After constructing a model that included CPPs, material properties, and process CQAs, loganin content was found to be the critical material attribute (CMA). The design space was calculated with a probability method. According to the limits of process CQAs, the minimum content of loganin in Fructus Corni was calculated with an error propagation method, which was 6.92 mg·g −1 . When the content of loganin in Fructus Corni reaches up to 6.92 mg·g −1 , the material is considered high-quality and is most suitable for the process. High-quality material can be used for production of Fructus Corni concentrate. This method can also be used to set material quality standards for other Chinese medicines. • A method to identify critical material attributes of herbal materials was presented. • A method to set herbal material quality standards was presented. • Process parameters were optimized with a design space approach.

Application of Design Space, Uncertainty, and Risk Profile Strategies to the Development and Validation of UPLC Method for the Characterization of Four Authorized Phosphodiesterase Type 5 Inhibitors to Combat Counterfeit Drugs.

Counterfeit medicines are an increasing scourge that are difficult to identify and they have become industrialized and widespread through highly organized illegal channels. This research aims to develop a robust method to determine four phosphodiesterase type-5 inhibitors in counterfeit drugs based on ultra-performance liquid chromatography. Experimental design methodology (DOE) and design space (DS) recommended by ICH Q8 were used side-by-side in the development phase to define the optimal parameters as well as the robustness of the chromatographic method. Moreover, both the uncertainty and risk profile derived from the β-content and γ-confidence tolerance interval were investigated during the validation phase to examine the performance of this method. Successful chromatographic results, in a high resolution between the four active ingredients and an optimal analysis time of less than 1.6 min, were achieved at the end of the optimization phase. In addition, validation results show a low risk of future measurements outside acceptance limits set at 5%. Our procedure was successfully applied in the routine phase to identify 23 illicit formulations of an erectile dysfunction drug. An efficient method for the characterization of 4 authorized phosphodiesterase in less than 1.6 min was established. A DS approach was applied to test the performance of this analytical method during analytical development. A risk profile was then carried out to approve the validity of the analytical method through the uncertainty profile approach.

Design space approach in the development of esculetin nanocrystals by a small-scale wet-bead milling process

Esculetin, a natural coumarin derived from herbs, has shown different potential pharmacological activities. However, the poor aqueous solubility of esculetin may limit its therapeutic efficacy. Nanocrystal is a promising dosage form to overcome this drawback by enhancing drug saturation solubility. Hence, a laboratory-scale wet-bead milling approach was employed to develop an esculetin nanocrystal formulation. Povacoat™ was selected as a stabilizer after screening different surfactants and polymers. Design of experiments was applied to identify and understand the relationship between process parameters and formulation compositions at the stage of formulation optimization. Furthermore, the optimized formulation was solidified using two different approaches (spray-drying and freeze-drying) and characterized by dynamic light scattering, laser diffraction, transmission electron microscopy, scanning electron microscopy, thermal analysis, and X-ray powder diffraction. An esculetin-Povacoat™ nanocrystal formulation that maintained a 200 nm particle size for 180 days was successfully obtained with specific critical process parameters and formulation composition within the design space.

A performance-based design framework for enhancing decision-making at the conceptual phase of a motorcycle rear suspension development

The functional design of a motorcycle rear suspension has become a complex process which involves different engineering disciplines such as computer aided design, structural analysis or multibody simulations. As a consequence of this multidiciplinarity, its development process is surrounded by multiple inter-related aspects and uncertainties which can compromise the feasibility of the solutions and hence making it difficult to foresees a priori the most appropriated design directions. This paper proposes an integrated methodology that supports early stage design decision-making for motorcycle rear suspensions by providing a rapid generative mechanism of feasible solutions with performance feedback for multiple requirements. The proposed framework integrates an object-oriented representation of the rear suspension with an adaptative design space approach for enhancing the capability to generate a variety of feasible solutions. A generative system coupled with the NSGA-II algorithm is proposed as responsible for exploring and managing the optimal functional design. The workflow has been structured in such a way all the design actions are conducted automatically. A case study of a Premoto3 rear suspension design is included in order to illustrated the effectiveness of the presented framework.

A novel framework for a rational, fully-automatised calibration routine for DEM models of cohesive powders

A new framework for calibration of DEM models of cohesive materials is presented. DEM simulations are a widespread numerical tool for modelling granular assemblies and related processes, but require careful calibration to give realistic predictive results. To this aim routine small-scale laboratory tests are used to investigate powders rheology while limiting resource investment, in conjunction with a rational approach to reduce computational costs as well. A specific order in numerical tests and calibrated variables is defined, enabling the implementation of an automatic iterative routine to calibrate material parameters from a given dataset. This method is successfully applied to calibrate four common increasingly cohesive powders of pharmaceutical relevance. Our framework saves an important amount of computational expense when compared to traditional parameters design space approaches, and proved to be able to calibrate very cohesive powder exhibiting plastic bulk volume loss of up to 25% (after uniaxial consolidation up to 10kPa).

Considerations on Protein Stability During Freezing and Its Impact on the Freeze-Drying Cycle: A Design Space Approach.

Freezing is widely used during the manufacturing process of protein-based therapeutics, but it may result in undesired loss of biological activity. Many variables come into play during freezing that could adversely affect protein stability, creating a complex landscape of interrelated effects. The current approach to the selection of freezing conditions is however nonsystematic, resulting in poor process control. Here we show how mathematical models, and a design space approach, can guide the selection of the optimal freezing protocol, focusing on protein stability. Two opposite scenarios are identified, suggesting that the ice-water interface is the dominant cause of denaturation for proteins with high bulk stability, while the duration of the freezing process itself is the key parameter to be controlled for proteins that are susceptible to cold denaturation. Experimental data for lactate dehydrogenase and myoglobin as model proteins support the model results, with a slow freezing rate being optimal for lactate dehydrogenase and the opposite being true for myoglobin. A possible application of the calculated design space to the freezing and freeze-drying of biopharmaceuticals is finally described, and some considerations on process efficiency are discussed as well.

Iterative reliable design space approach for efficient reliability-based design optimization

Reliability-based design optimization has gained much attention in many engineering design problems with the consideration of uncertainties. Nevertheless, the application is limited by the huge computational cost for the repeated reliability analysis in the optimization process. To address this issue, an iterative reliable design space approach is proposed with less number of reliability analysis required. Specifically, a sequential optimization strategy is proposed to identify the iterative reliable design space and perform the equivalent deterministic optimization in a serial loop. Thus, the identification of the reliable design space, which is time-consuming, is eliminated from the equivalent probabilistic constraints. Furthermore, an improved shifting vector strategy is put forward for the identification. In this strategy, an approximate shifting vector is first constructed utilizing the partial derivatives at the current design point, and it is then modified based on an increment of the shifting vector and a correction provided by the true reliability analysis. Besides, several mathematical examples and engineering problems are tested to validate the performance of the proposed method. In conclusion, the proposed method is able to deal with different kinds of nonlinear problems with relatively high accuracy and efficiency.

Olive oil nanoemulsion preparation using high-pressure homogenization and d-phase emulsification – A design space approach

Olive oil has been extensively applied in the pharmaceutical and cosmetic industries due to its biological properties. These are attributed to monounsaturated fatty acids like oleic acid and other minor components, such as phenolics and triterpenic acids. Oil-in-water nanoemulsion may enhance the solubility of poorly water-soluble drugs, which comprise about 40% of the currently marketed ones. However, the development of vegetable oil nanoemulsions is challenging due to their complex composition. In this study, olive oil nanoemulsions were prepared using high-pressure homogenization (HPH) and d-phase emulsification (DPE), as high- and low-energy processes, respectively. DPE has the potential to overcome the drawbacks of conventional Phase Inversion Methods. Aiming to achieve a deeper understanding of HPH and DPE processes, a design of experiment approach was successfully applied. This approach allowed identifying and understanding the relationship between input factors and their associated output response, at the stage of the nanoemulsion development. Moreover, in a specific range of critical process parameters and compositions, within the design space, nanoemulsions with similar mean particle sizes of 275 nm were achieved with equal composition, regardless of the use of the HPH or DPE process.

Sizing of biomass based distributed hybrid power generation systems in India

A methodology for optimum sizing of battery integrated biomass gasifier based distributed power generation systems is discussed. Typically, biomass gasifier systems are sized considering peak demand resulting into lower operational efficiency due to part load operation during low demand period. The proposed methodology using design space approach enables designer with multiple combinations of gasifier engine and battery systems for given load profile from which an appropriate combination may be identified considering specific objective or constraints if any. Two gasifier operational strategies are discussed and compared using cost of energy. The methodology is further extended for sizing of hybrid systems incorporating gasifier, solar PV and battery system. The proposed methodology is illustrated using a realistic load profile generated through a structured household survey of an un-electrified hamlet. For given load profile, battery integrated gasifier engine system in intermittent operation mode has the lowest cost of electricity followed by gasifier engine system alone, hybrid system and solar PV battery system. Sensitivity analysis is done to incorporate uncertainty related to variation in key input parameters. The proposed sizing methodology may be helpful in wider replication of gasification systems by providing cost effective sizing of such systems.