Developing Cream Formulations: Renewed Interest in an Old Problem

Journal of Pharmaceutical Sciences 108 (2019) 3240-3251

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Journal of Pharmaceutical Sciences journal homepage: www.jpharmsci.org

Pharmaceutics, Drug Delivery and Pharmaceutical Technology

Developing Cream Formulations: Renewed Interest in an Old Problem ~ es 1, 2, Francisco Veiga 1, 2, Carla Vitorino 1, 3, 4, * Ana Simo lo das Ci^ Faculty of Pharmacy, University of Coimbra, Po encias da Saúde, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal lo das Ci^ LAQV. REQUIMTE, Group of Pharmaceutical Technology, Faculty of Pharmacy, University of Coimbra, Po encias da Saúde, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal 3 lo I, 1st floor, 3004-504 Coimbra, Center for Neurosciences and Cell Biology (CNC), University of Coimbra, Rua Larga, Faculty of Medicine, Po Portugal 4 Chemistry Centre, Department of Chemistry, University of Coimbra, Coimbra, Portugal 1 2

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 April 2019 Accepted 4 June 2019 Available online 16 June 2019

This work aimed at establishing a framework to screen and understand the product variability deeming from factors that affect the quality features of cream formulations. As per Quality by Design e based approach, cream quality target profile and critical quality attributes were identified, and a risk assessment analysis was conducted to qualitatively detect the most critical variables for cream design and development. A Plackett-Burman design was used to screen out unimportant factors, avoiding collecting large amounts of data. Accordingly, 2 designs of experiments (DoE-1 and DoE-2) were performed, and the effects of independent variables on the cream formulations responses were estimated. At different factor combinations, significant variability was observed in droplet size, consistency, hardness, compressibility, and adhesiveness with values ranging from 2.6 ± 0.9 to 10 ± 6 mm, 7.93 ± 0.05 to 13.53 ± 0.14 mm, 27.6 ± 0.3 to 58.4 ± 1.1 g, 38 ± 6 to 447 ± 37 g.s, and 25.7 ± 2.1 to 286 ± 33 g.s, respectively. The statistical analysis allowed determining the most influent factors. This study revealed the potential of Quality by Design methodology in understanding product variability, recognizing the most critical independent variables for the final product quality. This systematic approach in the pharmaceutical field will yield more robust products and processes, provisioning time and cost effective developments. © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Keywords: cream formulation quality by design quality target cream profile critical quality attributes Plackett-Burman design critical process parameters critical cream formulation attributes updated risk assessment

Introduction Dosage forms for topical application are intended to produce the desired therapeutic action at specific targets in the skin with the least adverse effects.1 In current dermatological therapy, semisolid formulations remain as preferred vehicles, enabling in situ drug release over extended periods of time. Among the different topical dosage forms available in the market, cream formulations keep receiving growing attention as profitable systems to deliver drugs and cosmetic agents into the skin. These are described as biphasic systems, consisting of 2 immiscible liquids where 1 of which is dispersed uniformly throughout the other to form oil-in-water (o/w) or water-in-oil (w/o) emulsions, being interesting formulations to deliver both hydrophilic and lipophilic drugs. However, in

* Correspondence to: Carla Vitorino (Telephone: þ351-239-488-431). E-mail address: [email protected] (C. Vitorino).

the pharmaceutical field, emulsion design is not a trivial, straightforward procedure but rather a complex subject to investigate, develop, and optimize.2 Thermodynamically unstable, such formulations are greatly susceptible to physical instability phenomena during manufacturing and shelf-life conditions, such as droplet coalescence, flocculation, and creaming.3,4 A rational cream formulation design requires particular attention not only to the selection of the vehicle components and respective concentrations but also to the cream production process. All those variables may impact drug release from the final product and its permeation rate and extent, formulation structure, quality features, and, subsequently, product quality, efficacy, and safety. In turn, cream formulations are highly versatile structures that could be tailored to fit different strengths, skin feel, rheological properties, and spreadability.5 Considering the dermatological arena, topical corticoid therapy is widely prescribed in dermatological disorders. Hydrocortisone (HC) is a synthetic glucocorticoid commercially available in

https://doi.org/10.1016/j.xphs.2019.06.006 0022-3549/© 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

~es et al. / Journal of Pharmaceutical Sciences 108 (2019) 3240-3251 A. Simo

different dosage forms such as creams and ointments, and it is extensively used owing to its particular pharmacological effects on inflammatory, rheumatoid, allergic, and autoimmune conditions.6 Drawbacks concerning the glucocorticoids inclusion in cream formulations rely on their low solubility and instability at neutral pH, which accelerates the chemical and the physical decomposition, with microbial development, ultimately influencing cream biopharmaceutical profiles.7,8 With regard to pharmaceutical technology research of HC cream formulations, it is fundamental to be aware of active ingredient and formulation limitations to optimize its development and manufacturing and, therefore, to hone glucocorticoid pharmaceutical effect. The application of Quality by Design (QbD) concepts to drug product development will provide an opportunity for pharmaceutical companies to improve formulation and manufacturing efficiencies and productivity, with substantial reduction in time and cost production, product variability, defects and batch rejection, so as to reach more flexible regulatory approvals to decrease postapproval changes and to produce high-quality pharmaceuticals under real-time release.1 Pharmaceutical QbD is a systematic and risk-based approach which introduced a new quality concept,9 encouraging a detailed understanding of how raw materials and process parameters influence the final product quality profile. The improvement of HC cream formulation development and manufacturing may be achieved centered on such planning. When applied in the early formulation design stages, QbD methodology reveals to be a groundbreaking solution to old pharmaceutical development limitations.10,11 Such approach suggests the identification of critical quality features and converts them into the characteristics that the final product should present and the inspection of how process parameters and formulation variables may be changed to reproducibly produce a drug product with the desired quality profile.12 A comprehensive QbD study comprises certain detailed elements: the definition of quality target product profile (QTPP) and critical quality attributes (CQAs), the accomplishment of risk assessment to identify critical process parameters (CPPs) and critical material attributes (CMAs), the definition of a design space based on design of experiments (DoEs), the establishment of a control strategy,9 and a continual improvement and innovation throughout the product life cycle. The impact of different factors on particular cream quality aspects has been reported in the literature, but there are remarkable hurdles concerning the QbD industrial implementation. Hence, the aim of the present work is to provide a forthwith and a practical screening planning suitable to be applied in a transversal way to the pharmaceutical product design and manufacturing, ensuring the successful development of high-quality cream formulations by industries. First, the QTPP and CQAs of HC cream were determined. Second, following risk assessment analysis, 2 Plackett-Burman designs (PBDs) were established aiming at achieving enhanced process and formulation knowledge and understanding, with critical process and formulation parameters identification. Finally, the best experimental conditions extracted from DoE analysis will be cross-validated. Materials and Methods Materials rios BasiMicronized HC was kindly provided by Laborato ^utica S.A. (Mort dIndústria Farmace agua, Portugal). Methyl parahydroxybenzoate and propyl parahydroxybenzoate were purchased from Alfa Aesar (Kandel, Germany). Kolliwax® GMS II (glycerol monostearate), Kolliwax® CA (cetyl alcohol), Kollicream® IPM (isopropyl myristate), and Dexpanthenol Ph. Eur. were kindly

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provided by BASF SE (Ludwigshafen, Germany). Stearic acid was n S.A. (Madrid, Spain). Triethaprovided by Acorfarma distribuicio nolamine was purchased from Panreac AppliChem (Darmstadt, Germany). Liquid paraffin was provided by LabChem Inc. (Zelienople, PA). Glycerol was purchased from VWR Chemicals (Leuven, Belgium). Water was purified (Millipore®) and filtered through a 0.22 mm nylon filter before use. All other solvents were from analytical or HPLC grade. Methods Preparation of HC Cream Formulations HC cream formulations were prepared following a conventional o/w cream preparation method. Briefly, excipients from the continuous and the dispersed phases were first dissolved accordingly. The dispersed phase was prepared by heating glycerol monostearate, isopropyl myristate, cetyl alcohol, stearic acid, propyl parahydroxybenzoate, triethanolamine, and liquid paraffin at 70 C. Similarly, the continuous phase was prepared by blending dexpanthenol, gycerol, methyl parahydroxybenzoate, and purified water, at the same temperature. HC was dissolved in the dispersed phase. Both phases were mixed and homogenized using an Ultra-Turrax X 10/25 (Ystral GmbH, Dottingen, Germany) at 11,000 rpm, for a specified time at 70 C. Specifically, the blending and homogenization equipment type were set up from a preliminary study, wherein the use of an Ultra-Turrax, in comparison to a mechanical blade impeller, led to a more homogeneous and reproducible product.13 Cream formulations were cooled down at room temperature. Batches of 500 g were considered. Quality by Design Definition of QTTP. The QTPP was established envisioning the cream quality features intended to reach, considering the drug product efficacy and safety aspects. Initial Risk Assessment. Based on prior knowledge, an initial risk assessment was performed resorting to an Ishikawa diagram. A risk estimation matrix (REM) was further constructed to identify and prioritize potential high-risk material attributes and process parameters that could influence cream CQAs. Definition of CQAs. Potential cream CQAs were identified from the QTPP and risk assessment data analysis. Design of Experiments. In order to assess the effect of process and formulation variables and identify which of those variables exerts more impact on cream CQAs, an initial screening was carried out considering the PBD. PBD is a fractional factorial design, which simultaneously evaluates a relatively large number of factors in a small number of experiments, thus enabling to forecast which factors are responsible for the final product quality. Specifically, 2 DoEs with 2 levels (2n), 5 variables, and 12 runs were generated. DoE-1 and DoE-2 were designed to screen cream CPPs and CMAs, respectively. The upper (þ1) and lower (1) levels for each factor were determined based on preliminary study results. The effects of independent variables on 10 dependent variables (pH, drug assay, droplet size, consistency, hardness, compressibility, adhesiveness, cohesiveness, elasticity, and stability index) were investigated, using the following polynomial model:

Y ¼ b0 þ b1 X1 þ b2 X2 þ …… þ bn Xn where Y is the response, b0 the constant, and b1 to bn are the coefficients of the response values. Each coefficient represents the effect

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of an assessed factor on a particular system response. The greater the absolute value of the coefficient, the greater is its impact on the studied response. The signal indicates the increasing or decreasing trend of the response when moving from the 1 to þ1 level. Based on the information derived from the fitted models, 2 different overall desirability (D) functions were retrieved using JMP 13.1.0 Software (Cary, NC). The D function is a transformation of the response variable ranging from D ¼ 0, a completely undesirable function, to D ¼ 1, representing the most desirable response. Such function is defined as the geometric mean of the individual desirability functions of the most critical responses rendering an overall model for cream formulation.14,15 Considering all the requirements for each response (match target), the D function enables to predict the optimum conditions for the independent variables. pH Topical products should be manufactured with an appropriate pH range because it may influence drug solubility, stability, and the potential of formulations to cause skin irritation. HC creams pH was determined at room temperature using a digital pH C3010 Multiparameter Analyzer (Consort bvba, Turnhout, Belgium). The pH meter was calibrated using standard buffer solutions (4.01, 7.00, 10.01). About 1.0 g of the manufactured cream was weighed and dispersed in distilled water, and the respective pH was measured. The determination was performed in triplicate, 24 h after batch manufacturing. Assay In semisolid drug products, physical separation phenomena may occur during the manufacturing process and shelf life conditions. Hence, to ensure cream formulation integrity, it is essential to ascertain drug content of the final product.16 An appropriate amount of accurately weighed cream was removed from the top, middle, and bottom of the container and transferred to a flask. The contents were homogenized with methanol and placed in a sonication bath at a temperature of 60 C for 15 min, filtered, suitably diluted in mobile phase, and analyzed through HPLC for determining HC concentration. A Shimadzu LC-2010CHT apparatus equipped with a quaternary pump, an autosampler unit, and a L2450 UVvisible dual wavelength detector was used. A RP18 (4.6 mm  125 mm) Lichrospher 100 analytical column (Merck KGaA, Gernsheim, Germany), with a precolumn, was employed for the analysis. The mobile phase consisted of a 75:25 (v/v) mixture of acetonitrile and water pumped, and a constant flow rate of 1.0 mL/ min was used for 25 min at 30 C. An injection volume of 10 mL was considered for all standards and samples. The detection was performed at 242 nm.17 Droplet Size Emulsions are colloidal dispersions wherein droplet size is one of the main factors that affect their optical appearance, texture, and physical stability and consequently their quality profile. Formulation droplet size analysis was carried out using an Eclipse 50i optical microscope (Nikon Instruments Europe BV, Amsterdam, The Netherlands), 30 days after batch manufacturing. A minimal amount of each formulation was dispersed on a slide, and the cover slip was softly placed to not break system structure. Three microscopy images were acquired for each sample, and droplet length was measured (n ¼ 10 per image) using imaging software (NIS Elements, version 3.10). Rheological Aspects Consistency. Consistency describes the degree of sample resistance when submitted to a deformation force. HC creams consistency was

performed with a PNR 12-Penetrometer (Anton Paar ProveTec GmbH, Germany). Six containers of each formulation were completely filled, without forming air bubbles, and stored at 25 ± 0.5 C for 24 h. The tested sample was placed on the penetrometer base, and the penetrating needle was released during 5.0 s. This needle was, then, removed, and the depth of penetration measured. This is expressed in tenths of millimeters to which the needle sink into the formulation samples, under the influence of gravity for a fixed period of time. The harder and more consistent is the tested sample, the lower is the needle penetration. Texture Profile Analysis. Cream texture analysis was carried out using a Texture Analyser TA.XT Plus (Stable Micro Systems Ltd., Surry, UK). Textural features (hardness, compressibility, adhesiveness, cohesiveness, and elasticity) of HC cream were determined. A texture profile analysis mode was performed using an analytical probe (P/10, 10 mm Delrin) which was twice depressed into the samples at a defined rate (5 mm/s) with a deepness of 15 mm and 8 s among consecutive compressions. Six replicates were accomplished for each formulation at a constant temperature of 25 C. Texture Exponent 6.1.16.0 software was used to data collection and calculation.18 Stability Studies Predictive assessment of physical stability of the HC creams was carried out after 30 days of manufacture through LUMiSizer (LUM GmbH, Berlin, Germany) equipment. This technique is an analytical photocentrifugation system for measuring the transmitted intensity of near-infrared light as a function of time and position along the entire length of the sample. The data are displayed as a function of the radial position, as the distance from the center of rotation (transmission profiles). Transmission profiles shape and progression comprise information of separation process kinetics (sedimentation or creaming). The separation behavior of the individual samples can be compared and analyzed in detail by tracing the variation in transmission.19,20 The stability of the different formulations was quantitatively described through the instability index parameter. All samples were analyzed in duplicate after 42 h of centrifugation conducted at an acceleration of 4000 rpm and 40 C. Instability indices were calculated using the SEPView® software. Statistical Analysis The statistical analysis was performed using GraphPad Prism 5 Software (San Diego, CA) by applying ANOVA with Turkey-Kramer multiple comparison posttest. Differences among mean values were considered statistically significant when p < 0.05. Results and Discussion Quality by Design Approach Definition of the QTPP In accordance with the QbD paradigm, pharmaceutical development is initiated with the establishment of the product QTPP, accomplishing cream quality, efficiency, and safety features.17,21 Based on the formulation quality expectations, scientific knowledge, prior research observations, and regulatory aspects, HC cream QTPP was defined in Table 1. Initial Risk Assessment Resorting to risk analysis, the starting point was to gather variables that could influence product CQAs and hence generate quality failure. To prioritize process and formulation parameters that demonstrate to be a hazard for cream quality profile, an Ishikawa diagram

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Table 1 Quality Target Profile and CQAs Identification for HC Cream Formulation QTPP

Target

CQAs

Justification

Dosage form

Cream

e

Route of administration Dosage strength Dosage design Appearance Color Odor Identification Y1: pH

Topical 1.0% w/w Oil in water emulsion with HC solubilization White smooth cream No addition of artificial colors No objectionable odor USP <621>/Eur. Ph. 2.2.29 5.5-7.0

e e e e e e e Yes

Y2: Assay

90.0%-110.0% of the labeled amount of HC and a RSD NMT 6.0% USP <854>/Eur. Ph. 2.2.24 2.5-4.5 mm

Yes

Emulsion-based semisolid product assists in topical delivery improvement Local administration avoiding systemic side-effects To ensure formulation efficacy e Influence on patient compliance Influence on patient compliance and acceptability Influence on patient compliance and acceptability Critical for safety and efficacy Impact on physicochemical stability. Compatible with skin pH to prevent irritation on application To set up the dose that will ensure drug availability to promote therapeutic effect Impact on formulation uniformity and stability Impact on drug product efficacy and stability

Crystallization Y3: Droplet size Rheological aspects Y4: Consistency Y5: Hardness Y6: Compressibility Y7: Adhesiveness Y8: Cohesiveness Y9: Elasticity In vitro release profile

Yes Yes

Preservatives content Impurities

10.5-13.5 mm 20.0-30.0 g 30.0-50.0 g.s 30.0-50.0 g.s 0.8-1.0 0.8-1.0 Compliant with in vitro release testing topical guideline (REF) USP <51>/Eur. Ph. 5.1.3 USP <1086>/Eur. Ph. 5.20

Yes Yes Yes Yes Yes Yes Yes Yes Yes

Microbial content Residual solvents Y10: Instability Index Container closure system

USP <61>/Eur. Ph. 2.6.12 USP <467>/Eur. Ph. 5.4 NMT 0.1 Appropriate for the dosage form

Yes Yes Yes e

Package integrity

No failure

e

Impact on cream spreadability To increase HC residence time on the skin and consequently its optimal duration Impact on in situ cream preservation To ensure drug release To assess formulation delivery performance for enhanced therapeutic efficacy To ensure cream safety and stability Should be maintained below set limits to ensure safety and efficacy of formulation To ensure formulation safety To ensure formulation safety To maintain HC cream performance during the storage period To ensure patient compliance, portability and manufacturing simplicity To assure stability, clinical effectiveness and safety

The investigated CQAs are highlighted (bold). Eur. Ph., European Pharmacopeia; NMT, not more than; RSD, relative standard deviation; USP, United States Pharmacopeia.

(Fig. 1) and a REM (Fig. 2) were carried out to ascertain which of these parameters need to be further studied and controlled. An Ishikawa diagram represents a cause-effect correlation among all variables which potentially affect formulation CQAs. Accordingly, the risk factors are subdivided into different classes, which enable to systematically and proactively discern and mitigate those responsible for product nonconformities and, on the other hand, to establish a priori some of the working conditions. Thereafter, the main factors mentioned in Figure 1 were ranked in a REM.11,22 The projected REM displays a qualitative risk estimation, exhibiting the potential process parameters and material attributes risks. From the risk assessment data analysis, specific parameters were selected for subsequent screening studies. The outcome of this procedure is to determine which material attributes and process parameters are critical and, as such, needs to be experimentally investigated and controlled, within appropriate ranges, to ensure product QTPP. Definition of CQAs On the basis of prior knowledge and QTPP, HC cream CQAs that present the greatest probability to generate product failure were systematized in Table 1. For this purpose, pH (Y1), drug assay (Y2), droplet size (Y3), consistency (Y4), hardness (Y5), compressibility (Y6), adhesiveness (Y7), cohesiveness (Y8), elasticity (Y9), and instability index (Y10) were identified as the most critical cream quality attributes and for this reason were subsequently investigated. Design of Experiments Factors potentially affecting product quality attributes were cataloged into 2 categories: process- and formulation-related. From

the REM analysis, 5 process factors (X1-X5) and 5 formulation factors (X10 -X50 ) (Table 2) were found to be highly influent variables. To identify critical process parameters and material attributes, 2 screening plannings were performed, DoE-1 followed by DoE-2 (Table 3), respectively. Low (1) and high (þ1) level values of each studied factor were defined based on preliminary experiments (Table 2). A total of 24 formulations were produced. The effects of those variables on HC cream responses (Y1-Y10) were investigated (Table 4), and a sum-up is described below. Experimental plannings are useful instruments because they allow to minimize the number of experiments required to identify which factors undermine cream CQAs. This assumes critical importance in the industrial context, wherein the application of QbD methodology is particularly relevant for costly and timeconsuming development of complex formulations. To evaluate the influence of each variable, formulations were carefully characterized for the main quality attributes, and the coefficient values and corresponding levels of confidence were acquired for all the considered responses. The magnitude and direction of each coefficient explain the nature of each factor effect on a specific response. In Tables 5 and 6 are gathered the relative strength of each factor. An overview of the fitted models indicates that in DoE-1, homogenization rate (X5) > blending time (X2) > phase addition order (X1) demonstrated a considerable effect on formulations compressibility (Y6) > adhesiveness (Y7) > hardness (Y5) > droplet size (Y3). Based on these premises, process variables such as homogenization rate, homogenization time, and blending temperature were carefully fixed to the second stage of this study aiming at reducing production time and costs. Specifically, the combinatorial analysis

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Figure 1. Ishikawa diagram showing critical parameters of a hydrocortisone cream development. Log P, octanol-water partition coefficient. 367  239 mm (150  150 DPI).

pointed out the F11 manufacturing process conditions to proceed to the formulation variables screening, because it corresponded to the DoE-1 formulation which reached a reduced droplet size in the shortest time and at the lowest energy level, meeting the suitable CQAs for topical administration.

In DoE-2, coefficients magnitude displayed a significant effect of glycerol monostearate (X10 ) > stearic acid:triethanolamine (X40 ) > cetyl alcohol (X30 ) > isopropyl myristate (X20 ) > glycerol (X50 ) amount on formulations compressibility (Y6) > adhesiveness (Y7) > hardness (Y5) > consistency (Y4) > droplet size (Y3).

Figure 2. REM presenting initial risk assessment levels of individual hydrocortisone cream formulation and process parameters. Low, low risk parameter; Medium, medium risk parameter; High, high-risk parameter. 346  172 mm (150  150 DPI).

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Table 2 Experimental Plannings Using Plackett-Burman Design Coefficients

Independent Variables

Low Level (1)

High Level (þ1)

X1: X2: X3: X4: X5:

Phase addition order Blending time Blending temperature Homogenization time Homogenization rate

DP->CP 2.5 min amb 10 min 11,000 rpm

CP->DP 5.0 min 70 C 20 min 22,000 rpm

X10 : X20 : X30 : X40 : X50 :

Glycerol monostearate amount Isopropyl myristate amount Cetyl alcohol amount Stearic acid:triethanolamine amount Glycerol amount

10.0% 4.0% 1.6% 1.6%/0.07% 4.0%

20.0% 8.0% 3.2% 3.2%/0.14% 8.0%

DoE-1

b1 b2 b3 b4 b5 DoE-2

b10 b20 b30 b40 b50

DP, dispersed phase; CP, continuous phase.

The globule size, consistency, hardness, compressibility, and adhesiveness were the major impact responses (CQAs) because significant changes were observed at different combinations of the experimental conditions, mainly on formulation-related variables. pH, cohesiveness, elasticity, and stability index were considered the minor impact responses, once did not present significant changes at different levels of process parameters and formulation variables combination. In general, it is possible to infer that formulation parameters have greater impact on cream responses than process parameters. A factor-by-factor detailed analysis is provided in the following sections. Size Matters When manufacturing cream formulations, obtaining a small and homogeneous droplet size is highly desirable because it will result in an increased total surface area, consequently improving drug release from the vehicle and favoring its skin absorption.23 Y3 depends essentially on the preparation method, the emulsifying agent type and concentration, and the volume fraction of the dispersed phase. An efficient emulsifying agent will not only stabilize the final formulation by reducing the interfacial tension but also facilitate the emulsification process. Optical microscopy was the analytical method used for the droplet size range assessment. DoE-1 Inspecting the effect of process parameters, spherical oil droplets with a narrow size distribution, ranging from 2.6 ± 0.9 to 10 ± 6 mm

were obtained. According to the different factor combinations, significant differences in Y3 response were found (p < 0.05). In DoE-1, the process parameters that mostly influenced mean droplet size (Table 5) were phase addition order (X1) and homogenization rate (X5), although in distinct trends. Homogenization time (X4), blending time (X2), and temperature (X3) appear to have no significant impact on Y3 (
Table 3 Process and Formulation Experimental Matrices ID

F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12

DoE-1

ID

X1

X2

X3

X4

X5

CP->DP CP->DP DP->CP CP->DP CP->DP CP->DP DP->CP DP->CP DP->CP CP->DP DP->CP DP->CP

2.5 5.0 5.0 2.5 5.0 5.0 5.0 2.5 2.5 2.5 5.0 2.5

70 amb 70 70 amb 70 70 70 amb amb amb amb

10 20 10 20 20 10 20 20 20 10 10 10

11,000 11,000 22,000 11,000 22,000 22,000 11,000 22,000 22,000 22,000 11,000 11,000

DP, dispersed phase; CP, continuous phase.

F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24

DoE-2 X10

X20

X3 0

X40

X50

20.0 20.0 10.0 20.0 20.0 20.0 10.0 10.0 10.0 20.0 10.0 10.0

4.0 8.0 8.0 4.0 8.0 8.0 8.0 4.0 4.0 4.0 8.0 4.0

3.2 1.6 3.2 3.2 1.6 3.2 3.2 3.2 1.6 1.6 1.6 1.6

1.6/0.07 3.2/0.14 1.6/0.07 3.2/0.14 3.2/0.14 1.6/0.07 3.2/0.14 3.2/0.14 3.2/0.14 1.6/0.07 1.6/0.07 1.6/0.07

4.0 4.0 8.0 4.0 8.0 8.0 4.0 8.0 8.0 8.0 4.0 4.0

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Table 4 Effect of Process and Formulation Variables on Cream CQAs ID

Responses/QTPP Compliance Assessment Y1

DoE-1 F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 F12 DoE-2 F13 F14 F15 F16 F17 F18 F19 F20 F21 F22 F23 F24

6.594 ± 0.006 6.580 ± 0.005 6.61 ± 0.07 C 6.477 ± 0.016 6.515 ± 0.005 6.626 ± 0.003 6.65 ± 0.05 C 6.60 ± 0.07 C 6.64 ± 0.02 C 6.703 ± 0.010 6.683 ± 0.006 6.677 ± 0.016 6.62 ± 0.02 C 6.917 ± 0.009 6.74 ± 0.02 C 6.76 ± 0.01 C 6.84 ± 0.04 C 6.713 ± 0.005 6.873 ± 0.017 6.830 ± 0.016 6.893 ± 0.005 6.647 ± 0.012 6.770 ± 0.014 6.75 ± 0.03 C

C C C C C

C C C

C

C C C C C C

Y2 (%/RSD)

Y3 (mm)

104/3 C 101/15 F 72/10 F 99/6 C 98/4 C 108/36 F 99/5 C 105/35 F 110/26 F 56/23 F 100/6 C 99/5 C

7.8 ± 3.0 4.5 ± 1.6 2.9 ± 0.8 10 ± 6 F 9.2 ± 3.6 3.6 ± 1.8 4.1 ± 1.2 2.6 ± 0.9 2.9 ± 1.1 2.7 ± 0.6 2.9 ± 1.0 6.3 ± 3.5

F F C

101/2 C 100/7 F 96/7 F 102/9 F 98/3 C 98/7 F 96/3 C 103/14 F 98/2 C 95/2 C 102/2 C 98/3 C

5.3 4.0 5.7 5.5 4.2 5.4 4.8 4.3 4.7 6.6 4.6 6.2

± ± ± ± ± ± ± ± ± ± ± ±

1.5 1.2 1.3 1.6 0.9 1.3 1.4 1.1 1.2 2.0 1.6 1.9

Y4 (mm)

Y5 (g)

F C C C C C C F

11.52 ± 0.07 C 12.47 ± 0.11 C 9.85 ± 0.13 F 10.45 ± 0.17 F 9.77 ± 0.14 F 9.83 ± 0.14 F 13.38 ± 0.15 F 10.28 ± 0.20 F 10.50 ± 0.16 F 10.45 ± 0.22 F 10.98 ± 0.19 C 11.33 ± 0.11 C

34.5 29.9 56.0 46.6 58.4 52.8 28.1 37.1 37.9 41.8 38.9 35.0

F C F F C F F C F F F F

8.80 ± 0.10 F 7.93 ± 0.05 F 9.93 ± 0.05 F 8.15 ± 0.08 F 7.95 ± 0.11 F 8.00 ± 0.08 F 9.40 ± 0.12 F 8.88 ± 0.09 F 11.22 ± 0.23 C 8.72 ± 0.12 F 12.17 ± 0.21 C 13.53 ± 0.14 F

191 ± 9 F 228 ± 4 F 83.2 ± 2.1 F 236 ± 4 F 261 ± 7 F 235 ± 7 F 105 ± 10 F 83 ± 3 F 61.9 ± 1.0 F 116 ± 4 F 32.0 ± 0.6 F 27.6 ± 0.3 C

± ± ± ± ± ± ± ± ± ± ± ±

1.3 1.4 2.0 1.5 1.1 1.4 0.8 2.0 0.6 1.5 1.0 0.4

F F F F F F C F F F F F

Y6 (g.s)

Y7 (g.s)

Y8

62 ± 7 F 45.0 ± 4 C 102 ± 9 F 79 ± 7 F 102 ± 5 F 79 ± 7 F 42 ± 5 C 38 ± 6 C 61 ± 5 F 59 ± 4 F 57 ± 3 F 57.5 ± 0.9 F

56 ± 10 F 33 ± 3 F 77 ± 11 F 59 ± 5 F 87 ± 4 F 56 ± 3 F 32 ± 6 C 25.7 ± 2.1 F 50 ± 5 F 45 ± 4 C 44 ± 3 C 41 ± 3 C

0.939 ± 0.017 0.906 ± 0.019 0.884 ± 0.023 0.913 ± 0.021 0.919 ± 0.021 0.90 ± 0.05 C 0.902 ± 0.019 0.93 ± 0.10 C 0.90 ± 0.04 C 0.94 ± 0.02 C 0.919 ± 0.017 0.905 ± 0.022

C C C C C

290 ± 16 F 307 ± 22 F 117 ± 9 F 414 ± 22 F 447 ± 37 F 400 ± 40 F 106 ± 10 F 119 ± 12 F 93 ± 5 F 214 ± 16 F 41 ± 4 C 43 ± 3 C

211 ± 23 F 216 ± 13 F 80 ± 9 F 275 ± 20 F 286 ± 33 F 265 ± 32 F 67 ± 9 F 79 ± 8 F 65 ± 7 F 150 ± 17 F 27.4 ± 3 C 30.9 ± 1.4 C

0.957 ± 0.020 0.93 ± 0.03 C 0.95 ± 0.03 C 0.88 ± 0.03 C 0.92 ± 0.06 C 0.91 ± 0.03 C 0.95 ± 0.03 C 0.931 ± 0.015 0.939 ± 0.018 0.874 ± 0.017 0.935 ± 0.011 0.94 ± 0.03 C

C

C

C C

C C C C

Y9

Y10

0.99 ± 0.03 C 0.81 ± 0.05 C 0.94 ± 0.07 C 0.97 ± 0.04 C 0.989 ± 0.016 C 0.82 ± 0.04 C 0.81 ± 0.11 C 0.63 ± 0.04 F 0.92 ± 0.09 C 0.80 ± 0.05 C 0.83 ± 0.06 C 0.88 ± 0.05 C

0.059 ± 0.005 0.08 ± 0.02 C 0.07 ± 0.04 C 0.046 ± 0.002 0.028 ± 0.005 0.046 ± 0.003 0.120 ± 0.002 0.052 ± 0.003 0.042 ± 0.010 0.048 ± 0.007 0.069 ± 0.010 0.092 ± 0.002

0.92 ± 0.05 C 0.82 ± 0.05 C 0.83 ± 0.03 C 0.93 ± 0.08 C 0.92 ± 0.06 C 0.94 ± 0.07 C 0.60 ± 0.08 F 0.86 ± 0.10 C 0.83 ± 0.05 C 0.96 ± 0.07 C 0.74 ± 0.04 F 0.853 ± 0.022 C

0.049 ± 0.004 C 0.0435 ± 0.0005 C 0.14 ± 0.01 F 0.0440 ± 0.0010 C 0.039 ± 0.002 C 0.047 ± 0.002 C 0.074 ± 0.013 C 0.083 ± 0.003 C 0.0745 ± 0.0005 C 0.0405 ± 0.0005 C 0.165 ± 0.002 F 0.105 ± 0.0010 F

C

C C C F C C C C C

C, compliant; F, noncompliant; RSD, relative standard deviation.

droplets size.28 For example, an inverse tendency was denoted between F1 and F4, which were submitted to the same homogenization rate but at different homogenization times. In turn, F5, prepared at 22,000 rpm during 20 min, contrary to the expected, did not reach a lesser droplet diameter once homogenization time exceed the optimal value.

Interestingly, F12 droplet size is statistically different from that obtained in F11, the formulation with the most similar manufacturing process conditions. This disparity may be attributed to the different blending times. Besides not considered a critical process parameter, it suggests that a slower and timely phase addition will provide a better system equilibration. Note that the

Table 5 Coefficient Values of Cream Quality Responses Obtained From a Plackett-Burman Planning to Assess Process Variable Influence on HC Cream Design and Development and Results of Student t-Test Analysis Response Term

b0

b1

b2

b3

b4

b5

Y1: pH Significant level t value Y2: Assay (%) Significant level t value Y3: Droplet size (mm) Significant level t value Y4: Consistency (mm) Significant level t value Y5: Hardness (g) Significant level t value Y6: Compressibility (g.s) Significant level t value Y7: Adhesiveness (g.s) Significant level t value Y8: Cohesiveness Significant level t value Y9: Elasticity Significant level t value Y10: Instability index Significant level t value

6.6134 100.000 729.16834 95.9026 100.000 23.00434 4.95062 100.000 13.72403 10.9014 100.000 133.59329 41.4104 100.000 52.7645 65.2935 100.000 31.03032 50.4324 100.000 26.53822 0.9126 100.000 182.99471 0.8657 100.0000 63.355965 0.0829 100.000 6.59988

0.0310 99.815 3.41490 1.5180 28.168 0.36412 1.33434 99.913 3.69903 0.1542 93.675 1.88927 2.5684 99.830 3.2727 5.7350 99.179 2.72550 5.6213 99.571 2.95798 0.0066 80.868 1.32023 0.0291 96.2896 2.127676 0.0093 53.113 0.73996

0.0029 25.000 0.32158 0.3858 7.312 0.09254 0.4103 73.568 1.13753 0.1458 92.149 1.78714 2.6054 99.853 3.3198 5.9755 99.400 2.83982 4.2824 97.244 2.25343 0.0073 85.396 1.47103 0.0002 1.0772 0.013552 0.0266 95.187 2.12032

0.0203 96.682 2.23270 1.8885 34.619 0.45300 0.1985 41.370 0.55014 0.0153 14.794 0.18722 1.0948 83.231 1.3950 1.7275 58.540 0.82100 0.4550 18.848 0.23943 0.0007 11.061 0.13961 0.0054 30.4422 0.393010 0.0181 83.392 1.44341

0.0359 99.957 3.96006 6.0507 84.295 1.45140 0.5784 88.067 1.60339 0.2403 99.554 2.94453 1.7529 97.109 2.2335 4.1866 94.922 1.98965 2.6561 83.312 1.39770 0.0015 24.105 0.30814 0.0106 55.7405 0.772468 0.0195 86.136 1.54960

0.0039 32.665 0.42571 4.4046 70.084 1.05653 0.9625 98.782 2.66809 0.7875 100.000 9.65058 5.9239 100.000 7.5481 8.1144 99.974 3.85633 6.3635 99.865 3.34856 0.0015 22.858 0.29171 0.0157 74.6493 1.151927 0.0061 36.840 0.48777

~es et al. / Journal of Pharmaceutical Sciences 108 (2019) 3240-3251 A. Simo

3247

Table 6 Coefficient Values of Cream Quality Responses Obtained From a Plackett-Burman Planning to Assess Formulation Variable Influence on HC Cream Design and Development and Results of Student t-Test Analysis Response Term

b00

b10

b20

b30

b40

b50

Y1: pH Significant level t value Y2: Assay (%) Significant level t value Y3: Droplet size (mm) Significant level t value Y4: Consistency (mm) Significant level t value Y5: Hardness (g) Significant level t value Y6: Compressibility (g.s) Significant level t value Y7: Adhesiveness (g.s) Significant level t value Y8: Cohesiveness Significant level t value Y9: Elasticity Significant level t value Y10: Instability index Significant level t value

6.7792 100.000 1298.900 98.94577 100.000 81.8812 5.0935 100.000 44.8356 9.5569 100.000 166.6854 138.3073 100.000 66.2351 216.0410 100.000 40.3366 145.9979 100.000 42.2257 0.9270 100.000 219.7997 0.8491 100.000 103.2295 0.0749 100.000 19.1094

0.0292 100.000 5.5886 0.13725 8.968 0.1136 0.0720 46.897 0.6338 1.2986 100.000 22.6494 72.9082 100.000 34.9156 129.4680 100.000 24.1728 87.6679 100.000 25.3555 0.0146 99.908 3.4696 0.0650 100.000 7.8982 0.0313 100.000 7.9924

0.0297 100.000 5.6950 0.74663 45.867 0.6179 0.3159 99.072 2.7806 0.3264 100.000 5.6926 18.9481 100.000 9.0742 20.4250 99.970 3.8134 11.0282 99.782 3.1896 0.0072 90.672 1.7030 0.0442 100.000 5.3754 0.0091 96.751 2.3170

0.0236 99.991 4.5241 0.43117 27.627 0.3568 0.041778 28.436 0.3678 0.6958 100.000 12.1362 17.2544 100.000 8.2631 25.1260 99.999 4.6912 16.8746 99.999 4.8805 0.0035 58.388 0.8183 0.0028 26.673 0.3422 0.0028 52.086 0.7227

0.0742 100.000 14.2110 0.59923 37.641 0.4959 0.5180 99.992 4.5597 0.6347 100.000 11.0704 24.1355 100.000 11.5584 31.7930 100.000 5.9359 18.6654 100.000 5.3985 0.0021 38.517 0.5056 0.0239 99.502 2.90554 0.0153 99.898 3.9111

0.0019 28.791 0.3726 0.84687 51.118 0.7008 0.0489 33.033 0.4308 0.4403 100.000 7.6790 1.6439 56.604 0.7872 15.6230 99.517 2.9169 8.1306 97.831 2.3515 0.0047 72.964 1.1116 0.0399 99.999 4.8486 0.0050 78.161 1.2754

final droplet size is established by the balance of dispersed phase deformation, breakup, and coalescence.29,30 DoE-2 The formulation variables considered did not promote significant differences (p > 0.05) on Y3 response (droplet size values ranging from 4.0 ± 1.2 to 6.6 ± 2.0 mm). In this experimental planning, the formulation parameters that mostly influenced mean droplet size (Table 6) were the concentration of stearic acid:triethanolamine (X40 ) followed by isopropyl myristate amount (X20 ). Glycerol monostearate amount (X10 ), cetyl alcohol amount (X30 ), and glycerol amount (X50 ) seem to have no significant impact on droplet size ( 0.05). Indeed, the amount of emulsifying agent plays an important role in droplet formation because it reduces the interfacial tension between the different phases, enables an efficient emulsification of the lipid content in the aqueous phase, stabilizes the oil droplets, and prevents their coalescence. Theoretically, o/w or w/o emulsion formation depends on the emulsifying hydrophilic or lipophilic predominant domains. For o/w emulsion production, the required emulsifying hydrophilic-lipophilic balance (HLB) value should lie in the range of 8-16. In the manufactured formulations, the emulsifying agent is a neutral soap with a HLB value of 12.91. The prevalence of hydrophilic portions in their structure (HLB >7) enables

its migration, preferably, into the water phase to form an o/w emulsion.32,33 The smaller the droplet size is required, the more emulsifying agent is needed. Less X40 may result in greater droplet size and unstable emulsion because the molecules number may not be enough to stabilize every oily droplet, leading to phase separation.34 In the present study, it is possible to remark the suitability of the emulsifying agent to produce lesser oil droplet size and stable cream formulations with a HLB ranging from 12.76 to 12.75. Considering isopropyl myristate amount, the negative value of b20 reveals a decrease in droplet size with an increase in X20 variable. This ester is a nongreasy emollient used as a semisolid base in different dosage forms for topical purposes. Isopropyl myristate presents a particular characteristic because reducing the greasy feel caused by the oily excipients, spreading properties will be improved.35 In the pharmaceutical development stage, the solubility enhancement process of hydrophobic drugs plays an important role to achieve the bioavailability and therapeutic action of the drug at the target site. Therefore, in semisolid formulations, isopropyl myristate has been used as a solvent conferring significant improvements on drug solubilization.36 Moreover, as penetration enhancer, isopropyl myristate has been extensively used in cream formulations to improve drug bioavailability and penetration to the skin.31 As aforementioned, blending stage concerns a combination of different processes, including dispersed phase deformation, breakup, and coalescence. Indeed, droplet size is a function of the dispersed phase volume fraction because increasing oily components results in changes on the droplet size toward greater globules. At higher dispersed phase volume fractions, the growing of droplets collisions favors the coalescence processes in detriment of droplets breakage.27,37,38 This is in disagreement with the obtained results. Such contradictory trend could be explained by the lesser viscosity of the dispersed phase introduced by isopropyl myristate. Increasing the amount of isopropyl myristate, a reduction in oily

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melting temperature along with the viscosity of the dispersed phase is observed, which promotes an increase in the efficiency of the homogenization process and a droplet size reduction. The low viscosity of isopropyl myristate also contributes to the overall viscosity reduction of the system.39 As such, the deformation of the dispersed phase will increase as the viscosity of the dispersed phase decreases, keeping more efficiently the breakage process.29 What Rheology Can Tell Us For semisolid pharmaceutical dosage forms such as creams, it is imperative to understand the rheological aspects (consistency and mechanical properties). Their impact on formulation performance, physical stability, and patient acceptability may compromise drug delivery to and across the skin and, ultimately, product efficacy.16 In the light of current knowledge, changes in rheological properties may be achieved by modifications in the viscosity of the individual phases, in the dispersed phase volume fraction or in the emulsifying agent concentration.13,40 Several rheological aspects were herein evaluated through consistency and textural analysis. DoE-1 In this design, a general analysis indicates that process parameters (Table 5) that majorly govern consistency and mechanical properties are homogenization rate (X5), phase addition order (X1), and blending time (X2), while in distinctive tendencies. It was observed significant differences at different factor combinations (p < 0.05). The negative coefficient values obtained for X5 and X1 variables show that an increase in the factors level leads to a lessening in Y4 (consistency) results. In this particular response, the smaller the penetration value, the higher is the formulation consistency. An opposite trend was verified to homogenization time (X4) and blending time (X2) variables effect. According to data analysis, droplet size decreases when a homogenization rate of 22,000 rpm (high level, þ1) is applied because the mechanical energy disrupt larger droplets into smaller ones. Cream manufacturing requires a certain amount of energy to reduce the interfacial tension between the dispersed and continuous phases. Increasing the blending time, an enhancement in droplet breakup is verified, and smaller droplets are produced. Some authors have described a direct relationship between droplet size and cream rheology features.41-43 However, such correlation is not well understood yet. This is consistent with the positive value of b5 retrieved from Y5, Y6, and Y7, which reveals that increasing the homogenization rate (high level, þ1), an increase in hardness, compressibility, and adhesiveness were found. This behavior can be ascribed to homogenization speed elevation. Note, however, that when overblending is attained, the opposite trend is observed due to droplet coalescence phenomena, eventually resulting in phase separation and viscosity loss.44 Regarding to previous studies, the hardness values attained in this work are acceptable for skin cream application. The same trend was observed for compressibility (the force per unit time required to deform the product) and adhesiveness (the required force to remove the product from the surface with which is into contact), which are correlated to the spreadability of the cream on the skin surface and bioadhesion, respectively. A balance between such parameters may condition the container-formulation system selection and the easiness spread on the skin surface.18,45 Considering phase addition order, the systems which experienced a phase-inverse preparation method achieved a higher formulation consistency, as indicated by the negative values of b1.41

This reinforces the impact of preparation method on droplet size distribution, cream physical properties, and stability.24 DoE-2 Regarding formulation variables screening (Table 6), the amount of glycerol monostearate (X10 ) was the dominant factor, followed by cetyl alcohol (X30 ), stearic acid:triethanolamine (X40 ), glycerol (X50 ), and isopropyl myristate (X20 ). Indeed, the type, viscosity, and concentration of oily components had a remarkable impact on the cream. The results indicate that the consistency, hardness, compressibility, and adhesiveness values (Y4, Y5, Y6, and Y7, respectively) rise significantly owing to the increase in formulation components concentration (p < 0.05).1,41 Emulsion consistency and mechanical properties can be controlled by the addition of rheology modifiers, such as glycerol monostearate and cetyl alcohol. The direct thickening effect of those components on dispersed phase viscosity and formulation consistency improve creams physical stability because the mechanical barrier against oil droplets movement prevents the coalescence process.46 The results showed that the upper amount of glycerol monostearate and cetyl alcohol produces formulations with greater rheological profile. The contribution of triethanolamine and stearic acid to the increment of dispersed phase volume fraction and viscosity also impacts the rheological aspects of the whole system.47 Pertaining to glycerol amount, a significant rise in cream consistency, hardness, compressibility, and adhesiveness was acknowledged, irrespective of the lipid content. In topical formulations, glycerol is a component broadly used as humectant, emollient, and solvent.31 Its viscosity is the main contribution to the superior viscosity exhibited by the continuous phase. Rising the continuous phase viscosity, the viscosity of the whole system augments. Excipient melting point is also an important property because it can condition the texture, stability, and appearance of the cream formulation, by dictating distinct viscosities accordingly.33 Assay Similarly to other semisolid products, especially for biphasic systems, such as cream formulations, HC assay can substantially be impacted either by process or formulation variables. In practical terms, a noncompliant assay can result in nonhomogeneity, which leads to an inaccurate dosing of the final product and further rejection with associated significant financial losses. For this purpose, HPLC was the analytical method carried out to confirm if HC content is within the range defined in QTPP. Specifically, triplicate samples, at the top, middle, and bottom of each DoE formulation, were tested for Y2. DoE-1 Considering the effects of process parameters, the HC formulation content ranged from 55.80% to 110.34%. Despite the uncertainty associated to the coefficient estimation, it can be observed than noncompliant data are dictated essentially by the homogenization time (X4) and the homogenization rate (X5), see Table 4. To reach a consistent HC assay, the optimal homogenization time and speed should be set up during the production process because each of these parameters will, individually, negatively impact on the drug content distribution. It is generally noticed that combining a higher homogenization rate (22,000 rpm) for a

~es et al. / Journal of Pharmaceutical Sciences 108 (2019) 3240-3251 A. Simo

prolonged period of time (20 min) will render physical instability phenomena, resulting in uniformity loss. DoE-2 Inspecting now the effects of the formulation variables, HC content varied from 95.14% to 103.36%, although a relative standard deviation higher than 6% has been observed for some of the experiments. In this case, the lack of compliance cannot be ascribed to a specific isolated or combination variable. Analysing Stability The physicochemical principles underlying emulsion formulation and stabilization are particularly complex, involving many physical separation processes, such as flocculation, coalescence, sedimentation, or creaming. The evaluation of the separation phenomena plays an imperative role in process and product optimization. In the present study, the stability of formulated creams was assessed by analytical centrifugation through a LUMiSizer stability Analyser, which combines the centrifuge force with nearinfrared measurements. This instrument enables to assess emulsions separation processes giving a fast stability ranking and shelflife prediction of undiluted products at their original concentration, in min/h rather than mo/y preconized by real time experiments. From the evaluation of transmission profiles, the demixing behavior and stability of the samples can be traced.20,48,49 The instability index is a dimensionless number and ranges from 0 (more stable) to 1 (more unstable). This means that for the same total clarification, samples with high clarification rates tend to be more unstable. The instability index of formulated HC creams were found within the range of 0.0280-0.1195 in DoE-1 and 0.0405-0.1650 in DoE-2. This parameter is representative of the overall demixing of each sample. Statistical analysis suggests that no process and formulation factors showed a significant impact on creams stability (p > 0.05). In DoE-1, F5 exhibits higher consistency and the lesser instability index. F7 presents the lower consistency and the greatest instability index. Likewise, in DoE-2, F14 has the highest consistency value and the smaller instability index. F24 displays the least consistency value and is one of the formulations with higher instability index. Stability is not considered critical for the manufactured cream formulations, mainly ascribed to their high viscosity. Note that, cream physical stability is determined by the ability to mitigate physical instability processes, and it may be accomplished by reducing the movement speed of the dispersed phase droplets, increasing the viscosity of the continuous phase, and decreasing interfacial tension between both phases, by an emulsifier addition. It has been described a direct relationship between cream viscosity and the viscosity of its dispersed phase. A high apparent viscosity is imperative to retard the movement of the oil droplets, holding an emulsion physically stable. Minor Impacted Responses

3249

particular influence on drug skin penetration and degradation processes. Its effect on drug skin transport, ionization, solubility, and log P has been extensively reported.51 The semisolid formulations pH widely affects preservatives effectiveness. In the present work, propyl parahydroxybenzoate and methyl parahydroxybenzoate (pH 4-8) presented highly stability and effectiveness over the pH range of the produced formulations.31,52 Statistical analysis confirms that process parameters and formulation factors have no impact on cream pH (p > 0.05). Cohesiveness and Elasticity Cohesiveness and elasticity are mechanical parameters related to structural reformation following cream application, and the rate at which the deformed sample returns to its original condition, after the removal of the deforming force, respectively.18 In DoE-1, cohesiveness and elasticity presented similar results varying, respectively, between 0.884 ± 0.023 and 0.936 ± 0.025 and 0.633 ± 0.042 to 0.991 ± 0.032. In DoE-2, the cohesiveness values ranged from 0.874 ± 0.017 to 0.957 ± 0.020, and formulations elasticity from 0.596 ± 0.079 to 0.962 ± 0.070. The high value of cohesiveness provides full structural recovery following cream application. The results are high enough for topical application. It is described that lower quantitative values of elasticity indicate a larger cream elasticity.53 The quantitative values acquired from texture profile analysis warrant the suitability of cream cohesiveness and elasticity According to the different process and formulation variable combinations, no significant differences in Y8 and Y9 responses were observed (p > 0.05). Toward Optimal Conditions On the basis of prior knowledge, an initial risk assessment was performed to identify and prioritize potential high-risk variables that may influence identified cream CQAs. The outcome of this procedure was to determine which process and formulation parameters were critical and needed to be experimentally investigated (DoEs) to ensure the final cream quality profile. Risk assessment analysis must be accomplished in early phases, but it is important to be updated at different development stages as further information becomes available and greater knowledge is obtained.1 As per results shown in Tables 5 and 6, an updated REM was constructed (Fig. 3) enlightening the different levels of the main factors affecting cream CQAs after the accomplishment of delineated experiments. Having studied the effect of independent variables on the responses, a fine-tuning of the previous pattern trends can be scrutinized through a D function definition for each performed DoE. This function provides a mathematical argument to select the optimal CPPs and CMAs combinations. Such function is especially useful to accomplish the best compromise among several responses. The goal of the optimization of pharmaceutical formulations is generally to determine the levels of the most important variables from which a robust product with high quality features may be yielded. The optimization procedure was carried out concerning the most critical responses in the quality product profile.

pH The pH of cream formulations ranged from 6.48 to 6.70 in DoE-1 and from 6.62 to 6.92 in DoE-2, not significantly affecting the evaluated responses (p > 0.05). Formulations intended for topical application should ideally present a pH close to this range because this quality parameter can influence drug and cream stability. Also, in topical formulation design and development, a suitable pH must be ensured to prevent skin irritation upon application.46,50 Topical formulation pH has

DoE-1 Considering process parameters analysis, the optimal experimental conditions was carried out concerning the most critical responses. Predicted values of Y1, Y2, Y3, Y4, Y5, Y6, and Y7 were 97.22%, 4.58 mm, 11.62 mm, 29.9 g, 45.4 g.s, and 34.86 g.s, respectively, at X1, X2, X3, X4, and X5 levels of o/w addition order, 2.5 min, 25  C, 13 min, and 11,000 rpm, respectively. These calculated values

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~es et al. / Journal of Pharmaceutical Sciences 108 (2019) 3240-3251 A. Simo

Figure 3. REM presenting updated risk assessment levels of individual hydrocortisone cream formulation and process parameters. Low, low risk parameter; Medium, medium risk parameter; High, high-risk parameter. 294  171 mm (150  150 DPI).

were in close accordance with the experimental results obtained and with the trends previous described. DoE-2 With respect to formulation variables, the predicted values of Y4, Y5, Y5, Y6, and Y7 12.23 mm, 25.33 g, 42.74 g.s, and 35 g.s, respectively, at X10, X20 , X30 , X40 , and X50 were 11%, 4%, 1.6%, low level, and 5.6%, respectively. These results corroborated the reliability of the screening procedure in identifying the most critical factors and in, preliminary, forecasting the optimal process and formulation conditions. Using the factor coordinates of D-DoE-1 and D-DoE-2 will be possible to obtain a cream formulation with its CQAs meeting their QTPP requirements. Conclusion This study successfully implemented QbD principles to cream design and development. Such approach assisted in the reduction of practical issues in pharmaceutical technology research by forecasting the most critical formulation and process parameters on product quality and performance. Risk assessment tools and DoEs revealed to be profitable aspects, by minimizing the experiment number required for a detailed and careful analysis of product variability sources, ensuring a robust development of a high-quality dosage form. From the combinatorial factor analysis, globule size and rheological properties were the most influenced CQAs. Generally, phase addition order, homogenization time, homogenization rate, glycerol monostearate, isopropyl myristate, and stearic acid/triethanolamine amount were found to be the most influential process and formulation parameters for droplet size, consistency, hardness, compressibility, and adhesiveness.

The promising outcomes corroborates the applicability and relevance of QbD industrial implementation in the early stages of pharmaceutical development because it improves the fundamental understanding of cream formulation and manufacturing process, minimizing product variability and assuring its final quality. Acknowledgments ~o para a Cie ^ncia e a TecnoThe authors acknowledge Fundaça logia (FCT), Portuguese Agency for Scientific Research, for financial support through the Research Project no 016648 (Ref. POCI-010145-FEDER-016648), the project PEst-UID/NEU/04539/2013, and COMPETE (Ref. POCI-01-0145-FEDER-007440). This work was also supported by the grant FCT PTDC/CTM-BIO/1518/2014 from FCT and European Community Fund (FEDER) through the COMPETE2020 program. ~ es acknowledges the PhD research grant PD/BDE/ Ana Simo 135074/2017, assigned by FCT, from the Research Drugs & Devel~o e opment Doctoral Program and DendropharmaeInvestigaça ~o Farmace ^utica, Sociedade Unipessoal Lda. Serviços de Intervença The Coimbra Chemistry Center (CQC) is supported by FCT through Project UID/QUI/00313/2019. The authors also thank LAQV/REQUIMTE supported by National rio da Educaça ~o e Cie ^ncia, MEC) through project Funds (FCT/Ministe UID/QUI/50006/2013, co-financed by European Union (FEDER under the Partnership Agreement PT2020).  rios Basi - Indústria The authors also acknowledge Laborato ^utica S.A., for the kind donation of micronized hydrocorFarmace tisone, BASF SE for the samples availability of Kolliwax® GMS II, Kolliwax® CA, Kollicream® IPM, and Dexpanthenol Ph. Eur. and UCQFarma for making available the PNR 12- Penetrometer (Anton Paar ProveTec GmbH, Germany) and the LUMiSizer (LUM GmbH, Berlin, Germany) stability analyzer.

~es et al. / Journal of Pharmaceutical Sciences 108 (2019) 3240-3251 A. Simo

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