http://informahealthcare.com/mncISSN: 0265-2048 (print), 1464-5246 (electronic)

J Microencapsul, Early Online: 1–13! 2015 Informa UK Ltd. DOI: 10.3109/02652048.2015.1046513

RESEARCH ARTICLE

Biocompatible lidocaine and prilocaine loaded-nanoemulsion systemfor enhanced percutaneous absorption: QbD-based optimisation,dermatokinetics and in vivo evaluation

Poonam Negi1, Bhupinder Singh1,2, Gajanand Sharma1,3, Sarwar Beg1, and Om Prakash Katare1

1University Institute of Pharmaceutical Sciences, UGC Centre of Advanced Studies, Panjab University, Chandigarh, India, 2UGC-Centre of Excellence

in Nano Applications (Biomedical Sciences), Panjab University, Chandigarh, India, and 3Formulation Research, IPCA Laboratories Limited,

Mumbai, India

Abstract

Barrier properties of the skin and physicochemical properties of the drugs are the main hiccupsin delivering local anaesthetic molecules topically. The present work endeavours for systematicoptimisation and evaluation of nanoemulsions (NEs) of local anaesthetic drugs, lidocaine andprilocaine, employing the systematic approach of Quality by Design. A 33 Box–Behnken designwas employed for systematic optimisation of the factors obtained from screening studiesemploying Plackett–Burman design and risk assessment studies. The superior permeation rates,and higher concentrations of the drugs in skin layers from the optimised NE carriers, wereachieved in permeation and dermatokinetic studies, when compared to marketed cream.Furthermore, rapid onset of action was demonstrated by the NE system in rabbit eye cornealreflex model and biocompatibility was confirmed from the absence of any marked skinchange(s) in the normal skin histology. The developed NE systems demonstrated it as apromising carrier for topical delivery of lidocaine and prilocaine.

Keywords

Dermatokinetic modelling, formulation bydesign, local anaesthetic, phospholipid,skin bioavailability, submicron emulsion,transdermal

History

Received 5 August 2014Revised 21 March 2015Accepted 2 April 2015Published online 11 June 2015

Introduction

Topically applied local anaesthetics have diverse applicabilityin alleviating pain associated with various minor surface-skinsurgical conditions and invasive procedures like venipuncture andintravenous catheterisation. The major advantages over infiltrationanaesthesia include its non-invasiveness, easier application, com-paratively lesser side effects, and therefore, higher acceptabilityamong patients. Among various other topical anaesthetic prepar-ations, the eutectic mixture of local anaesthetics, i.e. EMLA�cream is the most frequently employed formulation (Russell andDoyle, 1997). However, the delayed onset of local anaestheticaction is the major drawback associated with such existingformulations (Tadicherla and Berman, 2006). The hydrophobicnature of the stratum corneum layer is the major barrier for thepercutaneous absorption of local anaesthetic drugs. Furthermore,the sensory nerve endings, responsible for pain sensation, arepresent primarily in the dermis (Sobanko et al., 2012).

Several physical methods to improve the penetration of localanaesthetic drugs and, therefore, to reduce the onset of local

anaesthetic action are available, like iontophoresis, sonophoresis,magnetophoresis, electroporation and microporation (Shipton,2012). However, these methods are very costly, and requirespecial devices and qualified staff for their application, and thusare not employed frequently (DeCou et al., 1999; Shipton, 2012).Use of chemical penetration enhancers, potentially used tofacilitate the percutaneous absorption of local anaesthetic drugsare often reported to cause dermal irritation and at times, seriousside effects (Yang et al., 2009). An alternative delivery strategy toaugment the penetration and, thus, the skin bioavailability oftopical anaesthetic drugs is incorporating drugs into colloidalcarrier delivery systems. Of the several available carrier systems,submicron emulsions are of particular interest in the presentcontext. Submicron emulsions, with their droplet size usually inthe range of 20–200 nm, are non-equilibrium systems, unlike thethermodynamically spontaneous microemulsions. These colloidalsystems, often termed as nanoemulsions (NEs) (Piemi et al., 1999;Solans et al., 2002, 2005), offer several meritorious visagesincluding low skin irritation, powerful permeation ability and highdrug-loading capacity, when compared to the other carriers suchas microemulsions, liposomes or solid lipid nanoparticles(Sonneville-Aubrun et al., 2004; Solans et al., 2005; Tadros,2006).

In the recent past, there has been tremendous interest growingtowards systematic development of drug formulations employingQuality-by-Design (QbD) approach so as to obtain the ‘‘bestpossible’’ product composition along with the requisite under-standing of the product and process behaviour (Singh et al.,2011). Such systematic QbD-based methods invariably exploit theutility of design of experiments and risk assessment approaches

Address for correspondence: Dr Om Prakash Katare, M. Pharm, Ph.D.,Professor of Pharmaceutical Sciences, Division of Pharmaceutics,University Institute of Pharmaceutical Sciences, UGC-Centre ofAdvanced Study, Panjab University, Chandigarh 160 014, India. E-mail:drkatare@yahoo.comDr Bhupinder Singh Bhoop, M. Pharm, Ph.D., D. St, Professor andDean Faculty of Pharmaceutical Sciences, University Institute ofPharmaceutical Sciences, Coordinator, UGC Centre of AdvancedStudies (Pharm Sciences), Coordinator, UGC Center for Excellencein Nano Applications, Panjab University, Chandigarh 160 014, India.E-mail: bsbhoop@yahoo.com

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lately termed as formulation by design (FbD). Not only to developthe ‘‘optimised’’ drug delivery systems in a systematic manner,but use of FbD but also tends to diminish the expenditure ofresources, i.e. experimentation, time and money (Singh et al.,2005; Lionberger et al., 2008; Negi et al., 2014).

The present research work, therefore, was undertaken todevelop the systematically ‘‘optimised’’ NEs of lidocaine andprilocaine employing the principles of QbD. The permeability andskin absorption potential of the developed NE systems wasevaluated employing the Wistar rat skin. The dermatokineticmodelling was employed to study the drug accumulation in theskin layers (i.e. epidermis and dermis). The histopathologicalevaluation was carried out to confirm the biocompatibility of thedeveloped system. Finally, anaesthetic efficacy was evaluatedusing the corneal reflex model in the rabbit eye.

Materials

Lidocaine (Lido) and prilocaine (Prilo) were obtained ex gratisfrom M/s IPCA Labs Ltd. Ratlam, India, and Phospholipon 90G�

from M/s Phospholipid GmbH, Nattermannallee, Germany.Poloxamer 407 from M/s BASF India Limited, Turbhe, India,and Carbopol 934� from M/s Lubrizol, Mumbai, India wereprovided as the gift samples. Tween 80 and propylene glycol (PG)were purchased from M/s Loba Chemie, Mumbai, India, whilesoybean oil from M/s Bengal Chemicals Ltd., Kolkata, India.Ultrapure water (Milli-Q� Integral system; M/s Merck Millipore,Billerica, MA) was used throughout the study. The commercialcream (CC), i.e. EMLA� containing Lido (2.5% w/w) and Prilo(2.5% w/w), was procured from a local drug house. All otherchemicals employed in various studies were of analytical grade,and were used as such.

Methods

Risk assessment studies

Risk assessment studies were carried out as a prelude to theformulation development for identifying the plausibility of risk(s)or failure(s), which at times, lead to the potential product failure.A risk assessment plan was envisaged by constructing an Ishikawafish-bone diagram using Minitab 17 software (M/s Minitab Inc.,Philadelphia, PA) for demarcating the causes and sub-causes,which ostensibly tend to affect the quality attributes of the NEs.Furthermore, the failure mode and effect analysis (FMEA) was

carried out for quantitative estimation of risk(s) and to detect theplausibility of failure modes affecting the drug product quality(Table 1). The scores were assigned to the factors encounteredduring formulation of NEs by high-pressure homogenisation(HPH) based on the severity, detectability and occurrence ofrisk(s), to calculate the risk priority number (RPN) as perEquation (1) (Fahmy et al., 2012). The factors with high RPNwere finally selected for factor optimisation studies.

RPN ¼ S � O� D; ð1Þ

where RPN is risk priority number; S is severity; O is occurrenceand D is detectability.

Factor screening studies

Screening studies are based on the principles of ‘‘factor sparsity’’,where only a few of the factors among the numerous ones areidentified to explain major proportion of the experimentalvariation in the drug product (Singh et al., 2005). The ‘‘factors’’responsible for the major variability were declared as the active orinfluential variables, while others were termed as inactive, lessinfluential or simply, the ‘‘noise variables’’. Following the riskassessment studies, the high risk factors were subjected to factorscreening studies for quantitatively estimating the risk associatedwith the formulation and process variables of the drug product.An 11-factor 12-run supersaturated Plackett–Burman design(PBD) was employed for screening the formulation and processvariables of Lido- and Prilo-loaded NEs. Table 2 illustrates thedesign matrix as per PBD along with the description of high andlow levels of various formulation and process variables employedfor NEs. Various NEs were prepared by HPH and evaluated forparticle size and polydispersity index (PDI) as the selected keyquality attributes. Analysis of the design-generated data wascarried out by fitting it to the first-order linear model obviating theinteraction effect(s), while analysing the coefficients for each ofthe factors. The Pareto charts were used for quantitativelyanalysing the effect of individual formulation and processvariables.

Preparation of NEs employing high pressurehomogenisation

Lido and Prilo bases were directly combined in a definite massratio (1:1) in glass vials, and mixed manually using a spatula at

Table 1. Summary of FMEA analysis enlisting the RPN scores for the studied formulation and process variables.

FMEA Rank Scores

S. No. Failure modes Unit Severity (S) Occurrence (O) Detection (D) RPN

1 Oil conc. % 8 6 6 2882 Type of oil – 7 5 3 1053 Emulsifier conc. % 7 5 4 1404 Type of emulsifier – 8 5 5 2005 Cosolvent conc. % 7 5 4 1406 Type of cosolvent – 5 3 4 607 Stabiliser conc. % 7 5 5 1758 Type of stabiliser 5 4 4 809 Phospholipid conc. % 7 4 4 112

10 Type of phospholipid – 6 6 5 18011 Order of mixing – 5 5 4 10012 Primary emulsion speed rpm 6 5 4 12013 Primary emulsion time min 4 5 5 10014 Homogenisation pressure bar 8 7 5 28015 Homogenisation cycles N 7 6 4 16816 Temperature �C 3 3 2 18

Bold text represents high risk factors with RPN scores4100.

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ambient temperature until a visually homogenous liquid oil(eutectic mixture) was obtained. The eutectic mixture, soobtained, was allowed to equilibrate at room temperature(21–25 �C) for 24 h prior to use (Brodin et al., 1984). NEswere prepared by mixing eutectic mixture of Lido (2.5% w/w)and Prilo (2.5% w/w) in soybean oil (3% w/w). Aqueous phasewas prepared by dispersing phospholipid (Phospholipon 90G;1% w/w), Tween 80 (3–7% w/w), poloxamer 407 (1% w/w)and PG (10% w/w) into water (q.s.) under magnetic stirring.The aqueous phase was mixed with the oily phase using highshear mixer (Heidolph Silent Crusher M, M/s InkarpInstruments Private Limited, Mumbai, India) at 10 000 rpmfor 30 min to obtain the coarse primary emulsions. Thesecoarse emulsions were then passed through the HPH (M/s GEANiro Soavi, Parma, Italy) at various cycles and homogenisationpressures (Table 3) at ambient temperature (Sharma et al.,2014).

Systematic FbD optimisation of NEs as per theexperimental design

A three-factor, three-level Box–Behnken design (BBD) wasselected to optimise varied response variables. The selectedcritical formulation attributes were the emulsifier concentration(X1), homogenisation pressure (X2) and homogenisation cycle(X3) employed at three different levels of each factor, viz. low(�1), intermediate (0) and high (+1) equidistant from each other,including quintuplicate studies at the centre point (0, 0, 0)formulations. All other formulation and process variables werefixed throughout the study. Table 3 summarises an account of the13 experimental runs studied, along with the coded values andactual values for the studied factors (Gannu et al., 2010; Singhet al., 2011). Various NE formulations prepared as per the designwere investigated for particle size and PDI as the responsevariables.

Characterisation of NEs

Micromeritics and zeta-potential measurement

The mean particle size, PDI and zeta potential of the developednanocarriers were determined by dynamic light scattering employ-ing Delsa Nano particle size analyser (M/s Beckman Coulter Inc.,Brea, CA) installed at Institute of Microbial Technology,

Table 2. Design matrix portraying the layout of various experimental runs as per PBD for factor screening.

RunEmulsifier

conc.Homogenisation

pressurePoloxamer

conc.

Soyalecithinconc.

Primaryemulsion

stirring speed

Primaryemulsion

Stirring timePG

conc.Oil

conc.Homogenisation

cycleType of

oilType of

emulsifier

1 1 1 �1 1 1 1 �1 �1 �1 1 �12 1 1 1 �1 �1 �1 1 �1 1 1 �13 �1 �1 1 �1 1 1 �1 1 1 1 �14 �1 1 1 1 �1 �1 �1 1 �1 1 15 1 1 �1 �1 �1 1 �1 1 1 �1 16 1 �1 �1 �1 1 �1 1 1 �1 1 17 �1 �1 �1 �1 �1 �1 �1 �1 �1 �1 �18 1 �1 1 1 �1 1 1 1 �1 �1 �19 �1 �1 �1 1 �1 1 1 �1 1 1 1

10 �1 1 1 �1 1 1 1 �1 �1 �1 111 �1 1 �1 1 1 �1 1 1 1 �1 �112 1 �1 1 1 1 �1 �1 �1 1 �1 1

Levels

Factors Low (�1) High (+1)

Emulsifier conc. (% w/w) 3 7Homogenisation pressure (bar) 300 900Poloxamer conc. (% w/w) 0.5 1Phospholipid conc. (% w/w) 0.5 1Primary emulsion stirring speed (rpm) 5000 10 000Primary emulsion stirring time (min) 15 20PG conc. (% w/w) 7 10Oil conc. (% w/w) 3 5Homogenisation cycles 3 9Type of oil Olive oil Soybean oilType of emulsifier Tween 20 Tween 80

Table 3. Design matrix showing experimental runs of BBD and theirresponses.

Runs X1 (g) X2 (bar) X3 (cycles)Particle

size (nm) PDI

1 1 0 1 134 0.3142 �1 0 1 201 0.3223 �1 1 0 196 0.3434 �1 �1 0 219 0.3425 0 0 0 147 0.3126 0 �1 1 150 0.3287 �1 0 �1 210 0.3688 1 0 �1 159 0.3359 0 1 1 96 0.326

10 0 1 �1 125 0.35511 1 �1 0 151 0.34812 0 �1 �1 174 0.38913 1 1 0 110 0.321

Levels used, actual (coded)

Independent variables Low (�1) Medium (0) High (+1)

X1 (g) 3 5 7X2 (bar) 300 600 900X3 (cycles) 3 6 9

DOI: 10.3109/02652048.2015.1046513 QbD-based development and optimization of lidocaine and prilocaine nanoemulsion 3

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Chandigarh, India. The mean value of three repeated measure-ments for each sample was reported as the final measurement.

Morphology

Morphology of the NEs was determined with the aid of atransmission electron microscope (TEM) installed at CentralInstrumentation Laboratory, Panjab University, Chandigarh,India. The nano-dispersion was negatively stained with 1%aqueous solution of phosphotungstic acid and dried on amicroscopic carbon-coated grid, viewed and photographedunder the electron microscope at suitable magnification(s).

QbD-based optimisation data analysis and validation

The QbD optimisation data analysis was carried out afterevaluating the prepared NEs for response variables, like particlesize and PDI. Subsequently, mathematical modelling was carriedout employing multiple linear regression analysis by selectingsecond-order quadratic polynomial model to explore the plausi-bility of significant interaction(s) among the studied responses(Bhatia et al., 2013). Only the polynomial coefficients corres-ponding to each model term, which were found to be highlysignificant, (p50.005) were considered during framing thecorresponding polynomial equation(s). Furthermore, the gener-ated model was evaluated by analysing the model parameterslike coefficient of correlation (r2), lack of fit and predicted errorsum of squares. The response surface analysis was carried outthrough 3D-response surface plots and 2D-contour plots,generated using Design Expert� ver. 9.0.1 (M/s Stat-Ease Inc.,Minneapolis, MN). The optimum formulation was located bynumerical optimisation technique using desirability function by‘‘trading-off’’ of the response variables, i.e. both minimisation ofparticle size and PDI.

Validation of the QbD methodology was accomplished byselecting seven NE formulations from the numerical optimisationtechnique on the basis of desirability function. The check-pointvalidation formulations were evaluated, and the observed andpredicted values for the responses, i.e. particle size and PDI, werecritically compared. Percent bias (percent error) was calculatedwith respect to the observed responses and the residual plots wereconstructed.

Incorporation of NE in secondary topical vehicle

In order to make the optimised NEs rheologically acceptablefor topical applications; these were further incorporated inCarbopol� 934 hydrogel (1% w/w). The aqueous gel baseof Carbopol� 934 was prepared and the optimised NE wasslowly mixed with continuous stirring to obtain a NE-basedhydrogel.

HPLC analysis

A liquid chromatographic (LC) pump with autosampler(Shimadzu LC-2010 CHT) connected to a UV–vis detectorwas used for the quantitative determination of Prilo and Lidosimultaneously. This system was connected to a computer withinbuilt ‘‘Class LC solution’’ software (M/s Shimadzu Corp.,Tokyo, Japan). A Purospher� C18 (5 mm, 250 mm� 4.6 mm)column (M/s Merck KGaA, Darmstadt, Germany) was used with a77:23 methanol–NaH2PO4 (0.02 M; pH 5) buffer as mobile phaseand a flow rate of 1 mL/min. Volumes of 20mL were injected inthe column and the Prilo and Lido were analysed at a wavelengthof 210 nm. The column temperature was maintained at 30 �C. Themethod was previously validated in terms of precision (52%),accuracy (498%), linearity (r240.999) with the limits of

detection 0.9616 mg/mL for Prilo and 0.7414 mg/mL for Lido,and the limit of quantification as 2.914 mg/mL for Prilo and2.246mg/mL for Lido, respectively.

Preparation of rat abdominal skin

The animal study was carried out in accordance with the approvalof the Animal Ethical Committee, by the Panjab UniversityAnimal Ethics Committee, duly approved for the purpose ofcontrol and supervision of experiments on animals by theGovernment of India (Ref. letter no. CAH/09/70; IAEC/156).Wistar rats weighing 150–200 g were sacrificed employingcervical dislocation and the full thickness skin was removedfrom the abdominal region. The hair of rats was removed withsurgical blade no. 22 with utmost caution and freed from anyadhering fat material. The excised skin was washed with normalsaline, and used for ex vivo skin permeability studies.

Ex vivo permeation study

The excised rat skin was mounted between donor and receptorcompartments of the Franz diffusion cells (cross-sectional area of3.142 cm2) with stratum corneum facing the donor compartment.The test formulations (1 g), each containing 25 mg/g Lido and25 mg/g Prilo, were placed in the donor compartment and 30 mLof phosphate buffered saline (pH 7.4) containing 30% (v/v) ofethanol was placed in the receptor compartment. Ethanol wasused to maintain the sink conditions. The assembly wasmaintained at 32 ± 1 �C with the help of a thermo-regulatedouter water jacket, while the diffusion medium was stirredcontinuously using a magnetic stirrer. At the predetermined timepoints, aliquots of 1 mL were periodically drawn and replenishedwith an equal volume of the fresh diffusion medium (Raza et al.,2013a). Drug concentration in the receiver compartment wasdetermined using HPLC and the cumulative amount of Lido andPrilo (Qn) permeated was calculated according to Equation (2)

Qn ¼ Cn � V0 þXn�1

i¼1

Ci � Vi; ð2Þ

where Cn represents the drug concentration of the receivermedium at each sampling time, Ci the drug concentration of theith sample, and V0 and Vi represent the volumes of the receiversolution and the sample, respectively.

The flux values were calculated from slope of the linear graphbetween the amounts of drug released per unit surface area versustime (Raza et al., 2011a, 2011b). The study was conducted intriplicate for 5 h.

Skin absorption study

Skin mounted on the diffusion cell was carefully taken off at theend of permeation studies. The adhered formulation on the skinwas carefully removed and analysed for the drug content. Thecleaned skin tissue was washed thrice with ultrapure water anddried on lint-free cotton swab. The skin tissue was chopped intosmall pieces and macerated in ethanol (5 mL) for 24 h forcomplete drug extraction to take place (Negi et al., 2014). Afterfiltering the solution through a membrane (0.45 lm), the filtratewas analysed using a validated HPLC technique.

Dermatokinetic modelling

The excised skins of Wistar rats were used for the studies. Theskin tissue was prepared as discussed in ‘‘Preparation of ratabdominal skin’’ section. Franz cell diffusion assembly was usedfor the studies as discussed under permeation studies with a doseof application equivalent to 25 mg of Lido and 25 mg of Prilo. In

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this case, at the respective sampling times, the whole skin wasremoved from the Franz cell. The skin was washed thrice toremove any adhering formulation and subsequently soaked in hotwater (60 �C) to detach the epidermis from dermis. Both of thesections were chopped into small pieces separately and maceratedin ethanol (5 mL) for 24 h for complete drug extraction to takeplace. After filtering the solution through a membrane (0.45 lm),the filtrate was analysed using the HPLC technique. The obtaineddata were fitted into one-compartment model (Raza et al., 2013a,2013b), as per Equation (3)

Cskin ¼Kp � CSkin

max

Kp � Ke

e�Kpt � e�Ket� �

; ð3Þ

where Cskin is the concentration of drug either in epidermis or indermis at time t, Kp is the dermal permeation constant, CSkin

max is themaximum concentration achieved either in epidermis or indermis, Ke is the skin elimination constant.

Win-Nonlin Ver 5.0 software (M/s Certara Inc., Princeton, NJ)was employed to compute the various dermatokinetic parameters,viz. Kp, CSkin

max , Ke, TSkinmax (time required to achieve CSkin

max and areaunder the curve (AUC0–3 h) using Wagner–Nelson method. Dataanalysis was accomplished using nonlinear function minimisationemploying Gauss–Newton algorithms built in the software.Statistical validity of the results was discerned on the basis ofminimisation of various model fitness parameters, like AkaikeInformation Criterion, Schwartz Criterion, Sum of Squares due toResiduals and maximisation of Pearsonian correlation coefficientand model selected entered.

Surface corneal reflex in rabbits

The in vivo anaesthetic activity of formulations was assayed inrabbits according to the conjunctival reflex test, alreadydemonstrated to be specifically suitable for evaluating the effectof local anaesthetic drugs (Maestrelli et al., 2009). Male NewZealand white rabbits weighing between 4 and 5.5 kg body weightwere procured from Chaudhary Charan Singh HaryanaAgriculture University, Hisar, India. One rabbit was housed percage. The cages were placed in the experimental room 24 h beforethe test for acclimatisation. The animals were kept at 23 ± 1 �Cwith a 12-h light–dark cycle, fed with a standard laboratory dietand tap water ad libitum. All the efforts were made to minimiseanimal suffering and to limit the number of animals used. Animalswere divided into three groups, each group constituting of threerabbits each). Group 1 received the marketed cream, i.e. CC,Group 2 NE and Group 3 NE gel. A fixed amount of each samplewas instilled in the conjunctival sac of the right eye of the rabbit,whereas a corresponding blank formulation (without drug) wassimultaneously instilled in the left eye as the control. Localanaesthesia was determined by observing the corneal reflex ontouch with a bristle (i.e. human straight hair). Followingapplication of the formulation, the observations were measuredevery minute initially, till the complete elimination of the cornealreflex, i.e. onset of anaesthesia. Afterwards, reappearance ofduration of anaesthesia was observed every 5 min till the cornealreflex reappeared. Comparative efficacy of the formulations wasstatistically evaluated employing one-way ANOVA (Bhatia et al.,2007; Daniel and Cross, 2013).

Histopathological studies

Male Laca mice (4–6 weeks old; 15–20 g) were divided into threegroups, with each group consisting of three animals. Hairs on thedorsal side of the animals were removed with the help of a 0.1 mmanimal hair clipper. The skin was wiped with a saline-wettedcotton swab 3–4 times. After drying, Group 1 received topical

saline treatment, while Group 2 and Group 3 received topicalapplication of NE and NE gel, respectively. After exposure for24 h, the formulation remaining on skin was carefully removedand cleaned with saline-soaked cotton. Thereafter, animals weresacrificed by cervical dislocation; skin samples were harvestedand fixed in 10% formalin solution. Skin samples obtained wereappropriately processed and stained with haematoxylin and eosin.The processed skins were observed microscopically for thehistopathological changes (Negi et al., 2014).

Statistical analysis

Statistical analysis was performed using a one-way ANOVA totest the difference between flux and skin absorption of testformulations to that of CC formulation in ex vivo skin permeationstudy. One-way ANOVA was also followed in the in vivo efficacystudies to compare the onset and duration of action of differenttest formulations (Daniel, 2008). Statistical difference wasconsidered as significant, when p50.001 (Daniel and Cross,2013).

Results and discussion

Risk assessment studies

For the formulation of NEs, emulsifier selected were Tween 80and Tween 20 as they revealed the maximum solubility for thedrugs. The combination of different surfactants can have thepositive influence on the reduction of particle size of the NEs.The other surfactants used were Poloxamer 407 and phospholipid.The cosolvents selected were PG and PEG 400 as these werecompletely miscible with the eutectic mixture of the drugs, amongall other cosolvents used.

Table 1 enlists the details of formulation and process variablesemployed during FMEA and the RPN scores calculated, whichquantitatively describe their effect and plausible consequences onthe response variables of NEs (Guebitz et al., 2012; Vora et al.,2013). The assignation of scores to the factors during FMEA is anin-house exercise which employs extensive brain storming toprioritise the factors and the scores are assigned based on the priorknowledge, experience of the formulator and existing literaturereports. A cut-off value of RPN (i.e. 100 or above) was consideredto discriminate the ‘‘high risk’’ factors against the ‘‘low risk’’factors. High RPN scores (i.e. above 100) were observed for thefactors, viz. oil concentration, type of oil, emulsifier concentra-tion, type of emulsifier, cosolvent concentration, stabiliser(Poloxamer 407) concentration, phospholipid concentration, pri-mary emulsion speed, primary emulsion time, homogenisationpressure and homogenisation cycles.

Factor screening studies

The high-risk factors with RPN score 4100 short-listed fromFMEA were subjected to factor screening studies using PBD, tofinally embark upon the formulation and process variables. Thefirst-order polynomial equations, along with their correspondingpolynomial coefficients, generated for each of the responsevariables during the factor screening studies, indicated theabsence of any interaction(s) among the factors. Furthermore,the influence of each factor on the response variables was alsoevaluated with the help of half-normal plots and Pareto charts.Figure 1 illustrates the Pareto charts for the response variables,particle size and PDI. Very significant effect of three factors, A(i.e. concentration of emulsifier), B (i.e. homogenisation pressure)and J (i.e. homogenisation cycle), was observed on both theresponses, i.e. particle size and PDI, as is apparent from theirhigher magnitude than the t-value limit and Bonferroni limit of

DOI: 10.3109/02652048.2015.1046513 QbD-based development and optimization of lidocaine and prilocaine nanoemulsion 5

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the Pareto charts (Figure 1). The factors A, B and J exhibited thepositive influence on the particle size and PDI. All other factorsconsidered during screening studies were fixed at a constant valueowing to their insignificant influence on the responses. In anutshell, only the factors, i.e. concentration of emulsifier (A),homogenisation pressure (B) and homogenisation cycles (J) werefinally selected for further optimisation studies.

Response surface mapping and QbD-optimisation dataanalysis

The QbD-enabled optimisation data analysis was carried out byanalysing the response variables employing second-order quad-ratic polynomial models. Application of ANOVA suggested thatthe chosen quadratic model was highly significant (p50.05)along with the model terms (p50.0001). Table 3 enlists theindependent variables and the responses as per the BBD. Thespecial polynomial mathematical model encompassing 10 coef-ficients (�0–�33) was postulated with �0 as the intercept (Table 4).All the coefficients represent quadratic and interaction terms, asdepicted in Equation (4).

Y ¼ �0 þ �1X1 þ �2X2 þ �3X3 þ �12X1X2 þ �13X1X3

þ �23X2X3 þ �11X21 þ �22X2

2 þ �33X23 :

ð4Þ

The model generated for response variables was found to behighly statistically significant (p50.0001). The r2 values for thesemodels ranged between 0.9738 and 0.9783, indicating excellent fit

of the generated polynomials to the response data (p50.05 in allthe cases). All the models were also found to have insignificantvalues of ‘‘lack of fit’’ ratifying the suitability of proposedmodel was appropriate. Close proximity in the magnitude ofadjusted (Adj) and predicted (Pred) r2 to the actual model r2 alsocorroborated excellent fit to the data.

Figure 2(A)–(C) depicts the 2D-contour plots and 3D-responsesurface plots for particle size. A nonlinear dip in the valuesof particle size followed by a rising trend was observed withincrease in the emulsifier concentration and homogenisationpressure, as is evident from the twisted shape response surfaceplot (Figure 2A). Similarly, with increase in homogenisationpressure and homogenisation cycle, a sharp decrease in theparticle size was observed (Figure 2B). This can be attributedto the generation of high shear forces along with presenceof emulsifier, which ultimately reduces the surface inter-facial tension leading to diminution in the particle size.Furthermore, Figure 2(C) depicts that at all the levels ofemulsifier concentration, a decreasing trend in the particle sizewas observed. The results obtained were in agreement witha published report, wherein the NEs with diameters range of 50–100 nm for skincare products were obtained at the high hom-ogenisation pressure of 1200 bar (Sonneville-Aubrun et al.,2004).

Figure 2(D)–(F) depicts the 2D-contour plots and 3D-responsesurface plots for PDI. Both emulsifier concentration and hom-ogenisation pressure showed negative influence on PDI at all thelevels. At high level of emulsifier, reduction in PDI was observedat all the levels of homogenisation cycles and vice versa.Analogous trend was also observed for influence of homogenisa-tion pressure versus homogenisation cycle, and emulsifierconcentration versus homogenisation cycle on PDI. Minimumvalues for PDI was observed at high levels of all the three factors.Overall, the homogenisation pressure and homogenisation cycleshowed the most influential effect on the particle size and PDI,followed by the emulsifier concentration.

The search for optimum NE formulation was carried outemploying numerical optimisation and desirability function tomeet the desired goals for the response variables. Table 5 presentsthe constrained set for numerical optimisation. The optimumformulation was selected based on the criteria, i.e. minimum valueof particle size and PDI by applying constraints on Y1

(96� Y� 105) and Y2 (0.312�Y� 0.35) for attaining the desir-ability function value close to unity. A total of seven check-pointformulations were chosen from the RSM, evaluated and theobserved data compared with the predicted responses. The percentbias for response variables ranged between �0.017 and 1.718,

Figure 1. Pareto charts depicting the effect of individual formulation and process variables during screening: (A) particle size and (b) PDI.

Table 4. Model summary statistics of the measured responses.

Polynomial coefficients for response variables

Coefficient code Particle size (nm) PI

�0 147 0.31�1 �35.25 �7.125E�003�2 �22.13 �7.750E�003�3 �10.88 �0.020�11 �7.00 �7.000E�003�22 �4.00 6.250E�003�33 �1.25 8.000E�003�12 29.63 5.875E�003�13 �10.12 0.021�23 �0.63 0.071R2 0.9783 0.9738

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Figure 2. Two-dimensional contour plots(front) and corresponding response surfaceplots depicting the effect of various inputvariables particle size, (A) emulsifier con-centration (X1) ?and homogenisation pressure(X2), (B) emulsifier concentration (X1) andhomogenisation cycle (X3),(C) homogenisation pressure (X2) and hom-ogenisation cycle (X3) and effect of variousinput variables on PI, (D) emulsifier con-centration (X1) and homogenisation pressure(X2), (E) emulsifier concentration (X1) andhomogenisation cycle (X3), (F) homogenisa-tion pressure (X2) and homogenisation cycle(X3).

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with overall bias as �0.342 ± 0.671%, indicating very high degreeof prognostic ability of the QbD experiments. Linear correlationplots drawn between the actual and the predicted responsevariables (Figure 3A and B) demonstrated high values of r2

(particle size, 0.991; PDI, 0.972) indicating excellent goodness offit. The residual plots were found to be quite regulated, as theyshowed uniform, relatively narrow and random scatter around thezero-axis. Overall, the results clearly demonstrated unambiguousaccuracy and validity of the proposed Scheff’s model in thesuccessful postulation of the polynomial model and predictionof response variables.

Morphology, micromeritics and zeta-potential

The TEM photomicrograph and particle size distribution ofthe optimised system are shown in Figure 4. Results revealedthe non-segregated and spherical nature of NE with sizearound 100 nm (i.e. d 0.5¼ 100 nm) low value of PDI, (i.e.0.329), assuring narrow distribution of the polydispersedphase. The zeta potential for the optimised NE formulation(i.e. �0.205 mV) was close to zero as the emulsifiers used werenon-ionic in nature (Raza et al., 2013a, 2013b). The stabilityof emulsions and NE(s) containing nonionic surfactants isalready reported to be independent of values of their zetapotential (Tadros, 2006).

Permeation studies

The permeation abilities of the various formulations wereevaluated using the ex vivo permeation experiments. The perme-ation parameters of Lido and Prilo from the optimised NE, NE gelformulation and marketed cream, i.e. CC, are presented in Table 6and permeation profiles are shown in Figure 5. A steady increasein permeation of these drugs in the receptor chambers wasobserved with time. Considering the indication for the localanaesthetic formulation a fast onset time is required, and a highrelease rate is, therefore, very vital. The permeation rates andpermeability coefficient values of Lido and Prilo from theoptimised NE formulations were significantly higher than themarketed cream (p50.001). The flux of Lido and Prilo fromNE and NE gel were 1.55–4.50-folds higher than that of CC(p50.001).

The permeation enhancing ability of NEs for topical deliverycould be explained by virtue of its nano-carrier properties. First,the small droplet diameters of NEs maintain close contact to thestratum corneum, thus increasing the amount of encapsulateddrugs into the viable skin (Jenning et al., 2000). Second, due tothe oily droplets in the nanometric size might embed into thestratum corneum, drug molecules could directly be deliveredfrom oily droplets into the stratum corneum without transfer viahydrophilic phase of NEs.

Figure 3. Linear and residual plots betweenthe observed and predicted values: (A) par-ticle size and (B) PDI.

Table 5. Selected criteria for numeric optimisation, and the composition of final optimised formulation.

Variable Goal Lower limit Upper limit Importance

Emulsifier conc. (A) In range �1 1 ***Homogenisation Pressure (B) In range �1 1 ***Homogenisation cycle In range �1 1 ***Particle size In range 96 105 ****Polydispersity index (PI) In range 0.312 0.35 ****

A B C Particle size (nm) PI Desirability

0.00 1.00 1.00 102 0.330 1.000

The asterisks indicate weightage of critical material attributes.

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Further, the presence of permeation enhancers likePhospholipon 90G� and PG in NEs also facilitate the percutan-eous absorption of drugs (Shakeel et al., 2007). It has beenreported that at lower concentration, the phospholipid moleculesget incorporated in the skin layers, fluidise and loosen the lipidicmatrix of the skin, thus promote the drug permeation (Yokomizoand Sagitani, 1996). PG can help in improving the partitioncoefficient (skin/vehicle) of drug, thereby, increasing the skinpermeation (Trommer and Neubert, 2006).

Addition of Carbopol� 934 into NE decreased the permeabilityof Lido and Prilo. This is ascribed to the much higher viscosity ofhydrogel than that of NEs, accounting for retardation of mobilityand consequently, the permeation of drugs (Peltola et al., 2003).After the permeation study for 5 h, the skin absorption of Lido andPrilo (Table 6) of different formulations was calculated. The trendfor the skin absorption was observed to be quiet similar to that ofQns. The skin absorption was 0.759 mg cm�2 for Lido and0.827 mg cm�2 for Prilo in case of NE, and 0.495 mg cm�2 forLido and 0.457 mg cm�2 for Prilo in case of CC. Significantenhancement (p50.001) could be attributed to the reservoir effectof NEs because of the formation of nano-depots of the drugmolecules within the skin layers and favourable integration ofNE lipids components to those of the skin lipids (Raza et al.,2011a).

Dermatokinetic modelling

The major drawback of local anaesthetic products is the lag timeof 45–60-min required for application of the topical product foreffects to be noted (Sintov and Brandys-Sitton, 2006). Therefore,disposition of drugs in the different skin layers was monitoredover a short-time interval, and data were processed usingdermatokinetic modelling (assuming one-compartment open

Figure 4. Particle size distribution of theoptimised NE dispersion and inset shows theTEM photomicrograph of the optimised NEsat 15 000�.

(A)

(B)

Figure 5. Graphs depicting cumulative amount permeated versus time ofNE formulations and the reference formulation, i.e. CC: (A) prilocaineand (B) lidocaine (mean ± SD; n¼ 3).

Table 6. Permeation parameters (mean ± SD) of prilocaine and lidocaine through rat skin from various topical formulations (n¼ 3).

Prilocaine Lidocaine

FormulationsFlux

(mg cm�2 h�1)Permeability

Coefficient� 10�3Skin absorption

(mg/cm2)Flux

(mg cm�2 h�1)Permeability

Coefficient� 10�3Skin absorption

(mg/cm2)

CC* 10.82 0.457 0.498 11.56 0.4699 0.495NE 48.06y 2.032y 0.827y 36.32y 1.476y 0.759yNE gel 18.94y 0.801y 0.526y 17.98y 0.7309y 0.523y

*Commercial cream.yp50.001 versus CC.

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model) to gain the maximum insight. Figure 6(A) and (B) showsthe distribution of drugs in epidermis and dermis of the Wistar ratskin, respectively. Delivery of Lido and Prilo in the skin layers byNE gel was found to be significantly greater (p50.05) than thatfrom the marketed cream. Table 7 gives the numeric values ofAUC0�3 h, CSkin

max , skin penetration rate constant (Kp), TSkinmax and

skin elimination rate constant (Ke). AUC of both the drugs, Lidoand Prilo, was also found to be significantly greater (p50.001each) in the dermis than in the epidermis. The results, therefore,vouch that the NE gel delivered local anaesthetic drugs to thedermis layer quite efficiently providing the drugs supplyadequately to the pain sensitive nerve endings.

In vivo studies

The NE and NE gel formulations revealed significantly strongeranaesthetic effect (p50.001) with respect to the correspondingconventional formulation at the same drugs concentration(p50.001). The quicker onset of action of NE (2.50 ± 0.50 min)and NE gel (6.03 ± 0.51 min) was obtained vis-a-vis conventionalformulation (11.25 ± 0.90 min) (Figure 7A). Moreover, NE for-mulations revealed the prolonged duration of action as comparedto conventional marketed formulation (Figure 7B). The order oftotal duration of local anaesthetic action was NE gel4NE4CC.

The duration of action of NE gel (i.e. 68.66 ± 2.51 min) was littlehigher than that of NE dispersion (i.e. 65.41 ± 1.66 min), thoughthis difference was not found to be statistically significant. Boththe nano-carrier formulations revealed more prolonged durationof action when compared to the conventional formulation(51 ± 2 min). The results of in vivo studies are, therefore, inconsonance with those of the skin permeation and dermatokineticstudies. The favourable effect of the NE carriers could be ascribedto their high affinity for epidermal and mucosal surfaces, thus,undergo a preferential uptake and enable a better skin penetrationthrough ocular epithelium. By virtue of the carrier effect, the drugmolecules become quickly accessible to the site of action, further,due to the high surface area provided by nano-carriers andformation of local reservoirs within skin layers, these result ina more intimate contact between skin tissues and drug mol-ecules and therefore, enhance their capability to prolong theanaesthetic effect.

Skin histopathology

Figure 8 depicts the photomicrographs of mouse skin surfacetreated with normal saline (Control), NE, NE gel and marketedcream. Different scores ranging between 0 and 1, were assigned tothese formulation-treated skin photographs, according to the

Figure 6. Dermatokinetic profile(mean ± SD) showing the drug concentrationof prilocaine and lidocaine in (A) epidermisand (B) dermis of Wistar rats at various timepoints (n¼ 3).

Table 7. Various dermatokinetic parameters (mean ± SD) of prilocaine- and lidocaine-loaded topical formulations in epidermis and dermis of Wistarrats (n¼ 3).

NE gel Commercial cream

Epidermis Dermis Epidermis Dermis

Dermatokineticparameters Prilocaine Lidocaine Prilocaine Lidocaine Prilocaine Lidocaine Prilocaine Lidocaine

AUC0–3 h (mg cm�2 h) 110.89 ± 23.67 121.62 ± 17.51 195.54 ± 33.17 194.99 ± 36.04 60.45 ± 11.29 115.77 ± 27.61 136.79 ± 35.92 95.00 ± 16.39Cmax (mg cm�2) 79.63 ± 10.22 82.74 ± 12.95 125.86 ± 22.24 121.30 ± 22.92 44.71 ± 5.05 64.67 ± 15.45 89.09 ± 13.73 48.00 ± 11.19Tmax (h) 0.51 ± 0.15 0.47 ± 0.14 0.57 ± 0.17 0.59 ± 0.19 0.49 ± 0.11 0.66 ± 0.25 0.57 ± 0.34 0.73 ± 0.23Ka (h�1) 2.69 ± 0.14 3.47 ± 0.15 2.00 ± 0.88 1.91 ± 1.11 2.08 ± 0.15 1.54 ± 0.24 1.77 ± 0.31 1.38 ± 0.21Ke (h�1) 1.13 ± 0.15 1.19 ± 0.25 1.55 ± 0.98 1.50 ± 1.25 1.94 ± 0.13 1.49 ± 0.12 1.76 ± 0.30 1.32 ± 0.19

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appearance and frequency of the signs of the skin problems likeepidermal liquefaction, sub-epidermal oedema, collagen fibreswelling, inflammatory cell infiltration and skin appendageelongation (Table 8). The control-treated group revealed normalskin histology with intact multilayers of epidermis, dermis andsubcutaneous fatty layer, whereas little changes were observedin the skin section, treated with the marketed cream. The skinsections treated with tested formulations showed no markedchanges in the normal histology vouching biocompatible nature ofthe formulations. Thus, the topical drug delivery of the developedNE systems can be considered as safe.

Conclusions

The present studies successfully ratify the use of systematic QbDparadigms for formulation of optimised NEs of Lido and Prilousing HPH. Implementation of risk assessment techniques like,FMEA helped in identifying the possible failure modes in theproduct, followed by factor screening studies revealed selection offactors critically influencing the product quality. The ex vivostudies revealed high permeation rates of the developed NEsthan the conventional formulation. Dermatokinetic modellingrevealed the presence of sufficient concentration of drugs in thedermis layer of the skin. The in vivo efficacy studies in rabbitsconstrued significant improvement in the onset and durationof local anaesthetic action vis-a-vis the marketed cream. Ina nutshell, the present studies corroborated that the developednano-sized emulsion systems provide effective topical delivery ofdrugs Lido and Prilo, by increasing their availability at the site ofaction.

Figure 8. Photomicrographs of skin histology sections treated with (A) control, (B) NE treated, (C) NE gel treated and (D) marketed.

(A)

(B)

Figure 7. (A) Onset of anaesthesia and (B) duration of anaesthesia onrabbit eye (mean ± SD); n¼ 3.

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Acknowledgements

The authors are thankful to M/s IPCA Labs Ltd. Ratlam, India forgenerously providing the gift samples of lidocaine and prilocaine, whileto M/s BASF, Germany and M/s Phospholipid GmbH, Nattermannallee,Germany, for the ex gratis supply of poloxamer 407 and phospholipids,respectively.

Declaration of interest

Financial grants obtained from University Grants Commission (UGC),New Delhi are gratefully acknowledged. The authors report no declar-ations of interest.

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Table 8. Histopathological skin compatibility score.

Parameter (score)

Test samplesEpidermal

liquefactionSub-epidermal

oedemaCollagen

fibre swellingInflammatory

cell infiltrationSkin appendage

elongation Total score

Control 0 0.3 0 0.3 0 0.6Marketed 0.3 0.3 0.5 0.5 0.3 1.9NE 0.3 0.3 0.5 0.3 0 1.4NE gel 0.3 0.3 0.3 0.3 0.3 1.5

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