Factorial Design Based Multivariate Modeling and Optimization of

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Factorial Design Based Multivariate Modeling and Optimization of Tunable Bioresponsive Arginine Grafted Poly (CystaminebisacrylamideDiaminohexane) Polymeric Matrix based Nanocarriers Rongbing Yang, Kihoon Nam, Sung Wan Kim, James Turkson, Ye Zou, Yi Y. Zuo, Rahul V. Haware, and Mahavir B Chougule Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.6b00861 • Publication Date (Web): 09 Nov 2016 Downloaded from http://pubs.acs.org on November 12, 2016

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Molecular Pharmaceutics

Factorial Design Based Multivariate Modeling and Optimization of Tunable Bioresponsive Arginine Grafted Poly (Cystaminebisacrylamide-Diaminohexane) Polymeric Matrix based Nanocarriers Rongbing Yang1,2, Kihoon Nam3,4, Sung Wan Kim3, James Turkson5, Ye Zou6, Yi Y. Zuo6, Rahul V. Haware7, Mahavir B Chougule1,2,5,8,9* 1

Translational Drug and Gene Delivery Research (TransDGDR) Laboratory, Department of Pharmaceutical Sciences, Department of Pharmaceutics and Drug Delivery, Research of Institute of Pharmaceutical Sciences, School of Pharmacy, University of Mississippi, University, MS, USA 2 Translational Drug Delivery Research (TransDDR) Laboratory, Department of Pharmaceutical Sciences, The Daniel K. Inouye College of Pharmacy, University of Hawai’i at Hilo, Hilo, HI, USA 3 Center for Controlled Chemical Delivery (CCCD), Department of Pharmaceutics and Pharmaceutical Chemistry, University of Utah, Salt Lake City, UT, USA 4 School of Dentistry, University of Utah, Salt Lake City, UT, USA 5 Natural Products and Experimental Therapeutics Program, University of Hawaii Cancer Center, Honolulu, HI, USA. 6 Department of Mechanical Engineering, University of Hawaii at Manoa, Honolulu, HI, USA 7 College of Pharmacy & Health Sciences, Campbell University, Buies Creek, NC, USA 8 Pii Center for Pharmaceutical Technology, Research Institute of Pharmaceutical Sciences, University of Mississippi, University, MS, USA. 9 National Center for Natural Products Research, Research Institute of Pharmaceutical Sciences, University of Mississippi, University, MS, USA.

*

Corresponding author:

Dr. Mahavir B. Chougule, Department of Pharmaceutics and Drug Delivery, School of Pharmacy, Faser Hall, The University of Mississippi, University, Mississippi 38677, USA; Phone: 662 915 2670, Fax: (662) 915-1177; email: [email protected] and [email protected]

1 ACS Paragon Plus Environment


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Abstract Desired characteristics of nanocarriers are crucial to explore its therapeutic potential. This investigation aimed to develop tunable bioresponsive newly synthesized unique arginine grafted poly (cystaminebisacrylamide-diaminohexane) [ABP] polymeric matrix based nanocarriers of using L9 Taguchi factorial design, desirability function, and multivariate method. The selected formulation and process parameters were ABP concentration, acetone concentration, the volume ratio of acetone to ABP solution, and drug concentration. The measured nanocarrier characteristics were particle size, polydispersity index, zeta potential, and percentage drug loading. Experimental validation of nanocarrier characteristics computed from initially developed predictive model showed nonsignificant differences (p > 0.05). The multivariate modeling based optimized cationic nanocarrier formulation of < 100 nm loaded with hydrophilic acetaminophen was readapted for a hydrophobic etoposide loading without significant changes (p > 0.05) except for improved loading percentage. This is the first study focusing on ABP polymeric matrix based nanocarrier development. Nanocarrier particle size was stable in PBS 7.4 for 48 h. The increase of zeta potential at lower pH 6.4, compared to the physiological pH, showed possible endosomal escape capability. The glutathione triggered release at the physiological conditions indicated the competence of cytosolic targeting delivery of the loaded drug from bioresponsive nanocarriers. In conclusion, this unique systematic approach provides rational evaluation and prediction of a tunable bioresponsive ABP based matrix nanocarriers which was built on selected limited number of smart experimentation.


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Key Words: Nanocarrier, Bioresponsive, Multivariate model, Multiple linear regression, Optimization, Taguchi factorial design, Anticancer drugs



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1. Introduction Cancer is a second leading cause of the worldwide mortality 1. About 1.66 million new cases are expected to be diagnosed in USA in 2015 and probable mortality due to cancer will be about 0.59 millions 2. A total of 1.36 million cancer deaths are predicted in EU in 2015 3. Current cancer treatment requires a specific regimen for the different types of cancer. These cancer modalities comprise surgery, and/or radiotherapy, and/or chemotherapy. The efficacy of non-selective radiotherapy, and/or chemotherapy has been limited due to the adverse effects. Drug loaded nanocarriers with specific characteristics, such as size in the range of macromolecules (e.g. albumin), could increases accumulation of therapeutic agents at the tumor site and thereby exhibits an improved efficacy against cancer 4. This is associated with their enhanced permeation and retention (EPR) effect (particle size < 300 nm) due to leaky tumor vasculature and boosted pharmacokinetic (PK) parameters 5. Thus, the nanoparticle application in the cancer treatment could enhance efficacy and reduce side effects of therapeutic agents 6. The successful application of nanocarrier drug delivery in the cancer treatment depends on the various characteristics of formulated nanocarriers. A preferred nanocarrier particle size for anti-cancer therapy is between 30-100 nm. The nanocarriers of particle size of > 100 nm are rapidly cleared by the spleen compared to nanocarrier of 30-100 nm

7, 8

. Contrary, nanocarriers of particle size of < 30 nm swiftly

undergo hepatic and renal clearance

7, 8

. The particle size distribution known as

polydispersity index (PDI) is another important parameter used to describe nanocarrier particle size uniformity 9. A homogeneous size distribution of nanocarriers shows lower PDI values. Such preparations have better reproducibility. PDI affects the nanocarrier


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surface modifications, such as PEGylation or ligand's conjugations along with their impact on nanocarrier clearance from the body. The nanocarrier circulation lifetime and tumor uptake is dictated by their surface charges

5, 10

. The nanocarrier interactions with

the physiological conditions are a complex process. The positive charge of nanocarrier could enhance the interaction with negatively charged tumor blood vessels and tumor cells. It leads to increase of diffusion depth within the tumor tissue 10. Neutral or slightly negatively charged nanocarriers could minimize nonspecific binding to the endothelium. This results in the prolonged circulatory lifetime 5. Clearly, an optimal control of particle size, charge, percentage drug loading, release profile, stability, and biocompatibility is a critical factor in the development of nanocarrier formulations. Consequently, the effects of formulation and process parameters on the characteristics of nanocarriers should be systematically evaluated to formulate nanocarriers with tunable properties. Design of experiment (DoE) can be used for this purpose, as it enables to vary various parameters simultaneously. Thus, DoE helps to capture maximum information with fewer numbers of experiments. Fractional factorial designs like Taguchi factorial design can be used as a ‘guiding experimental design’ to investigate the interactions between factors and responses

11

. This method has ability to evaluate the effect of

parameters on the responses with minimum number of experiments. Moreover, this fractionated factorial design provides flexibility with the number of levels of defined factors

12

. Although the Taguchi factorial design method is not commonly used in the

pharmaceutical industry, it has been widely used in various manufacturing industries, such as machinery manufacturing, to improve the quality control of the processing with minimum or no modification of the manufacturing process

13

. It also includes the loss



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function, which describes how variance of factors can cost a loss on the target value of responses. This method uses signal to noise ratio as a loss function. Our group has successfully applied Taguchi method for the development of gemcitabine or onconase loaded albumin nanocarriers

14-16

. Taguchi factorial design method can only select the

optimized batch from one of the experiments or determine the best combination of factors levels for one response only. However, a multivariate model can be used to integrate multiple design variables for a systematic understanding of their impact on the desired optimal response. We hypothesized that the development of tunable bioresponsive cationic drug loaded arginine grafted poly (cystaminebisacrylamide-diaminohexane) polymer (ABP) based matrix nanocarriers of < 100 nm using Taguchi factorial design and multivariate model would be an efficient method to prepare the nanocarriers with targeted profile. This hypothesis was tested by formulating tunable model hydrophilic acetaminophen (APAP) and hydrophobic etoposide (ETO) loaded ABP polymer-based matrix nanocarrier systems using Taguchi factorial design. We have synthesized biocompatible and biodegradable ABP using arginine, a natural amino acid and bioreducible disulfide linkage. To the authors’ knowledge, this is the first study that focuses on the development of ABP based matrix nanocarrier system. Our previous studies were dedicated to develop ABP polymer-based nanocomplex of 150-200 nm size for the delivery of genes and drugs 17-19

. The matrix based delivery system would provide prolonged stability under

physiological conditions compared with nanocomplex or micelles

20, 21

. Moreover, it

could also provide a controlled release profile of loaded therapeutic agent with minimum burst release effect. Herein, we report a unique modeling approach that will be applicable


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for the development of bioengineered or natural polymeric matrix based nanocarriers for the delivery of therapeutic agetns . 2. Materials and Methods 2.1 Materials Tert-Butyl-N-(6-aminohexyl)

carbamate

(N-Boc-1,6-diaminohexane,

N-Boc-DAH),

trifluoroacetic acid (TFA), triisopropylsilane, triisobutylsilane, dithiothreitol (DTT), N,Ndiisopropylethylamine (DIPEA), and piperidine were purchased from Sigma-Aldrich (St. Louis, MO). N,N’-cystaminebisacrylamide (CBA) was purchased from PolySciences, Inc. (Warrington,

PA).

2-(1H-benzotriazole-1-yl)-1,

1,

3,

3-tetramethyluronium

hexafluorophosphate (HBTU) was purchased from Novabiochem (San Diego, CA). Fmoc-L-Arg(pbf)-OH was purchased from Anaspec, Inc. (San Jose, CA). A hydrophilic model drug Acetaminophen (APAP; Pubmed CID: 1983) was a gift from Dr. Rajesh N. Davé (Distinguished Professor of Chemical, Biological and Pharmaceutical Engineering, Site Director, NSF-ERC on Structured Organic Particulate Systems, New Jersey Institute of Technology, Newark, NJ, USA). Etoposide (ETO; > 97% by HPLC; Pubmed CID: 36462) was purchased from Fisher Scientific (Pittsburgh, PA, USA). Vivaspin 500 ultracentrifuge filters (Lot: 14VS50026) with a cutoff molecular weight of 10,000 Da (Viva Products Inc., Littleton, MA, USA), spin columns (to fit 50 mL centrifuge tube), and column medium Sephadex G25 medium (Lot: 10038032) were obtained from VWR international (Bridgeport, NJ, USA). All other analytical grade chemical reagents and chemicals were purchased from commercial sources.



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2.2 Synthesis and characterization of Poly (cystaminebisacrylamide-diaminohexane) polymer Poly (cystaminebisacrylamide-diaminohexane) polymer (ABP) of molecular weight of 4.5 kDa was synthesized and characterized as previously described (Figure 1I) 17. Briefly, the backbone polymer (poly (CBA-DAH)) was synthesized by Michael reaction. N-BocDAH was dissolved in methonal/water solution (9:1, v/v) and one equivalent of CBA was added to solution. Reaction maintained for 5 days at 60 °C in the dark under nitrogen atmosphere. After precipitation with diethyl ether, t-Boc groups of product was removed using TFA solution (TFA: triisobutylsilane: H2O = 95: 2.5: 2.5, v/v). Then, poly (CBADAH) was dialyzed (molecular weight cut off = 1k Da) and lyophilized 22. To synthesize the ABP, Fmoc and pbf protected L-arginine was grafted to poly (CBA-DAH) using HBTU and DIPEA in DMF at room temperature for 2 days. Fmoc groups were removed using piperidine (30% in DMF) then, pdf group were removed using TFA solution. Synthesis scheme of ABP was presented in Figure 1I. The ABP was characterized by size-exclusion chromatography and 1H [NMR (400 MHz, D2O) ] as described previously 17

.


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Figure 1. (I) Synthesis scheme of poly (cystaminebisacrylamide-diaminohexane) polymer (ABP), molecular weight about 4,500 Da, (a) MeOH:H2O = 9:1, v/v, 60 °C, 5 days, and trifluoroacetic acid:triisobutylsilane:H2O = 95: 2.5: 2.5, v/v, 0 °C, 30 min, (b) Fmoc protected and -OH functionalized arginine, 2-(1H-benzotriazole-1-yl)- 1, 1, 3, 3tetramethyluronium

hexaﬂuorophosphate,

N,N-diisopropylethylamine

in

dimethylformamide, room temperature, 2 days, and 15% piperidine/ dimethylformamide, room temperature, 30 min, and trifluoroacetic acid:triisopropylsilane:H2O = 95: 2.5: 2.5, v/v, room temperature, 30 min; and (II) preparation of drug loaded arginine-grafted biodegradable ABP based matrix nanocarriers: addition of acetone into the aqueous solution of polymer and drug mixture, the aggregation of polymer in presence of acetone has led to formation of nanocarriers where drug molecules were entrapped; the final nanocarriers were obtained after the evaporation of acetone and removal of un-entrapped drug.



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2.3 Formulation of nanocarriers and Taguchi orthogonal array factorial design Nanocarriers were prepared using the desolvation technique as described in our previous publications with a slight modification

15, 23

(Figure 1II). The varying concentrations of

aqueous ABP solution and APAP solution were mixed in a glass vial. Aqueous diluted acetone solution or pure acetone was added via syringe pump (New Era Pump System, Inc., Farmingdale, NY, USA) into the aqueous polymer drug mixture with a controlled speed of 0.5 mL/min under the constant stirring at 400 rpm with various time depending on the volume of batches. The polymer was insoluble in acetone and hence, an addition of aqueous solution of acetone triggered aggregation of polymer forming APAP loaded ABP polymeric matrix based nanocarriers (APAP-NC). In the next step, acetone was allowed to evaporate from nanosuspension at room temperature for 30 minutes. Finally, un-entrapped drug was removed by spin column filtration with Sephadex G25 medium. The selected design variables for the nanocarriers preparations were ABP concentration (0.1, 0.2, and 0.3 mM), acetone concentration (60%, 80%, and 100% v/v), volume ratio of diluted acetone to ABP polymer-drug solution (0.250, 0.375, and 0.500), and APAP concentration (0.210, 0.276, and 0.342 mM)

15

. The polymer to drug molar ratio was in

the range of 0.29 to 1.43 for this design. Only main effect and two-factor interactions were considered in the Taguchi orthogonal factorial design. Thus, these independent factors were selected to minimize their higher order interactions. These formulation parameters specifically drug and polymer concentration helps to understand the individual effect of formulation parameters on the nanocarrier characteristics. These design variables were denoted as A, B, C, and D respectively. The levels of all variables were selected based on the preliminary studies

14, 15, 23

and were coded into 0, 1, and 2


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from low, intermediate, and high level. The four design variables were varied at three levels (34 factorial design) using L9 Taguchi orthogonal array design to formulate nanocarriers. A total of nine batches of nanocarriers were prepared in triplicate. All the formulations were characterized for particle size, PDI, zeta potential, and percentage drug loading. These responses were denoted as R1, R2, R3, and R4 in corresponding order. 2.4 Characterization of nanocarriers 2.4.1 Particle size and PDI The formulated APAP-NC formulations were dispersed in an equal volume of water at 25 °C. The particle size and polydispersity index (PDI) of nanocarriers were measured by a dynamic light scattering system (DLS system, PSS-NICOMP, Santa Barbara, CA, USA) with 90° scattering angle. 2.4.2 Zeta potential The formulations were initially dispersed in water with volume ratio of 1:20 at 25 °C. The zeta potential of dispersed nanocarriers was measured by nanoparticle electrophoretic mobility in triplicate using a NICOMP ZLS 380 analyzer (PSS-NICOMP, Santa Barbara, CA, USA) as described previously 14, 24. 2.4.3 Entrapment efficiency and percentage loading Entrapment efficiency and percentage loading were determined using Vivaspin-2 ultracentrifuge filters with a 10,000 Da cut-off molecular weight. The 0.5 mL of APAPNC formulation was placed on the top of the Vivaspin filter membrane. It was subsequently centrifuged at 17,000 g for 10 min in Thermo Scientific Sorvall Legend 17R Refrigerated Micro-centrifuge (Amarillo, TX, USA). The concentration of unentrapped APAP in an aqueous filtrate collected at the bottom of Vivaspin-2



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ultracentrifuge tubes was measured by Dionex UltiMate 3000 HPLC (Sunnyvale, CA, USA). HPLC analysis was carried with the modification of the reported method

25

.

Methanolic aqueous solution (30%; v/v) was used as a mobile phase. A reverse phase XB-C18 column (Kinetex, 00G-4605-EP; 5 µm, 100 Å, 250×4.6 mm, Phenomenex, Torrance, CA, USA) was used at about 28°C. The absorbance was measured at λmax of 280 nm to detect the APAP content and λmax of 285 nm to detect the ETO content. The retention time was around 3.8 minutes for APAP and 5.8 minutes for ETO

25

. The

percentage loading (Equation 1) were calculated. % =

− × 100 1

Where, PL is percentage drug loading (%), CI is the concentration of initial drug (µg/mL), CU is the concentration of unloaded drug (µg/mL), CTE is the concentration of total excipients (µg/mL). A hydrophobic drug ‘ETO’ loaded nanocarriers (ETO-NC) were also developed using the similar formulation and process parameters, except to dissolve ETO in ABP aqueous solution instead of APAP. The size, PDI, zeta potential, and percentage loading was measured and compared with APAP-NC. 2.5 Taguchi data analysis and selection of optimal formulation The results of Taguchi orthogonal array factorial design based nine batches performed in triplicate were analyzed using Minitab® 17 (Minitab Inc., State college, PA, USA) and Microsoft Excel®. The modeling scheme for development of ABP based nanocarriers was outlined in Figure 2. The effects of four design variables (ABP concentration, volume ratio of acetone to ABP, acetone concentration and APAP concentration) on four responses (particle size, PDI, zeta potential, and percentage loading) were analyzed based 12 ACS Paragon Plus Environment

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on ANOVA and the signal to noise ratio (S/N). The strength of design variables at each level was quantified by calculating signal to noise ratios under three main criteria such as smaller is better (Equation 2), larger is better (Equation 3), and on-target or nominal is best (Equation 4). 1 log = −10 × 2

!

= 10 × "

#$%&'( ) * +)

= −10 × 3

4

Where Y is response, ( is mean of response, n is the number of observation, and σ is the variance.

Figure 2. Modeling scheme for formulating acetaminophen (APAP) loaded argininegrafted biodegradable poly (cystaminebisacrylamide-diaminohexane) polymer (ABP) nanocarrier (APAP-NC). (Act is acetone; VAct:VABP is the volume ratio of diluted acetone added in and ABP drug mixture solution; PDI is polydispersity index.)



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Taguchi orthogonal design was used for categorical variables regardless of the continuous property of design variables. Four design variables and their three levels were dummy coded into 12 variables in order to apply the multivariate model (ABP concentration 0.1, ABP concentration 0.2, ABP concentration 0.3, acetone concentration 60%, acetone concentration 80%, acetone concentration 100%, volume ratio of acetone to ABP-drug solution 0.250, volume ratio of acetone to ABP-drug solution 0.375, volume ratio of acetone to ABP-drug solution 0.500, APAP concentration 0.210, APAP concentration 0.276, and APAP concentration 0.342). The value was either 0 or 1 for each coded variable. Multivariate regression model was built on the data collected by L9 Taguchi orthogonal design. The obtained discrete multivariate regression equations (Equation 6-9) were used to predict the means and standard deviations of 34 full factorial results as described under 3.2. The optimum desirable properties of target formulation were 50.00 nm particle size, 0.190 PDI, 24.50 mV zeta potential, and 1.750% percentage loading capacity. A desirability function (Equation 5) was used to calculate the desirability of each predicted formulation of a full factorial design in order to select the desired formulation batch. Desirability function was defined as the sum of the square of difference between predicted values to optimum desirable values of each four responses. 71 − 71 72 − 72 73 − 73 -./01230045 = 6 8 +6 8 +6 8 71 72 73 74 − 74 +6 8 5 74


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Where, E is estimated values, T is targeted values, R1 is the particle size (nm), R2 is the polydispersity index, R3 is the zeta potential (mV), and R4 is the percentage drug loading (%). A formulation with lowest desirability value was selected as an “optimal batch” having 50.00 nm particle size, 0.190 PDI, 24.50 mV zeta potential, and 1.750% percentage loading capacity. This optimal batch was formulated in triplicate and characterized on their four responses. The model predicted and experimental responses were validated using t-test (two-sample assuming unequal variances). 2.6 Morphology of nanocarriers The topography of nanocarriers was examined by 120 kV Hitachi HT7700 Transmission Electron Microscope (TEM) and atomic force microscope (AFM, Innova, Bruker, Santa Barbara, CA). For TEM analysis, placebo nanocarriers suspended in distilled water were applied on top of a carbon-coated-Formvar-coated grid (200 mesh; 3.05 mm diameter). The images were scanned with 100 kV accelerating voltage and 8000x direct magnification. For AFM imaging, 10 µL of the placebo nanocarrier suspension was spotted on freshly cleaved mica. Sample was washed three times with 200 µL Milli-Q water. The sample was dried under nitrogen stream. Topographical images were obtained in air with the contact mode. TEM image with ImageJ® was further analyzed to obtain the number averaged size of nanocarriers by counting about 80 nanoparticles in a 1790x1790 pixel image. 2.7 Preliminary stability studies and glutathione triggered drug release A preliminary stability of nanocarriers was studied in phosphorylate buffer solution (PBS) pH 7.4 for 2 days by monitoring particle size using PSS-NICOMP DLS system. The zeta



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potentials of nanocarriers was measured at pH 7.4 and pH 6.4 by NICOMP ZLS 380 analyzer. The formulation was dispersed in PBS 7.4 or 6.4 with volume ratio of 1:20 at 25 °C before analysis of size or zeta potential. The drug release profile of nanocarriers was evaluated using PBS 7.4 with and without 10 mM of glutathione (GSH) as release medium. Concentration of GSH in the cell was reported in the range of 7~35 mM while concentration of GSH in plasma were drop to about 2 µM regardless of the elevated GSH concentration reported in some cancer tissue compared with normal tissue

26-28.

Considering extracellular GSH concentration and interior levels, 0 and 10 mM of GSH were used to study the effect of the differential concentration of GSH on release of drug from developed nanocarriers. The 100 µL of nanocarrier suspension was placed into a 2

mL glass vial capped with a dialysis membrane (100,000 Da cut-off molecular weight) with a diameter of 6.5 mm. Glass vials were immersed into a 10 mL of release medium with constant stirring at 400 rpm. A 100 µL release medium was sampled at specific time point (0, 4, 8, 24, 48, and 72h). The ETO content from collected samples were measured using HPLC method as described in the previous section. 3. Results and Discussion 3.1 Taguchi analysis 3.1.1 Formulation of ABP nanocarriers using Taguchi orthogonal array design A

synthetic

biocompatible

and

biodegradable

poly

(cystaminebisacrylamide-

diaminohexane) polymer (ABP) is used for the first time in this study to develop the cationic matrix based nanocarriers. Taguchi factorial design is a tool to improve the quality of the manufacturing process 11, 13. This design was used to identify the effects of four design variables (ABP concentration, volume ration of acetone to ABP-drug solution,


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acetone concentration and APAP concentration) and their levels on the formulation characteristics or responses of nanocarriers. The desolvation method was used to formulate newly developed ABP polymeric matrix based APAP-NC. The data obtained from L9 Taguchi orthogonal array design with triplicate are reported in Table 1. The developed nanocarriers showed particle size, PDI, zeta potential, and percentage drug loading in the range of 32.90 to 74.40 nm, 0.190 to 1.020, 9.90 to 24.50 mV, and 0.320 % to 1.750 % respectively. Table 1. Characteristics of formulated nanocarriers based on L9 Taguchi orthogonal array design with four design variables and five responses. [ A - ABP concentration (mM); B - Volume ratio of acetone and ABP; C - Acetone concentration (%); D - APAP concentration (mM); R1 - size (nm); R2 - polydispersity; R3 - zeta potential (mV); R4 percentage drug loading (%). All values in the parenthesis indicate standard deviation.]

A 0 0 0 1 1 1 2 2 2 *

Design Variables B C 0 0 1 1 2 2 0 1 1 2 2 0 0 2 1 0 2 1

D 0 1 2 2 1 0 0 2 1

R1 74.40 (5.90) 63.50 (11.20) 52.60 (8.60) 48.50 (1.70) 49.60 (4.80) 64.60 (8.20) 39.60 (3.30) 74.20 (11.90) 32.90 (11.70)

Responses R2 R3* 0.442(0.091) 9.90 (2.10) 1.023 (0.292) 21.20 (0.60) 0.192 (0.074) 24.50 (2.70) 0.353 (0.043) 23.20 (2.50) 0.221 (0.063) 20.20 (6.60) 0.552 (0.103) 18.50 (2.70) 0.253 (0.034) 21.70 (4.00) 0.641 (0.071) 19.20 (0.40) 0.403 (0.072) 24.00 (1.90)

R4 0.890 (0.36) 1.750 (0.79) 1.310 (0.82) 1.240 (0.28) 0.650 (0.10) 0.600 (0.32) 0.650 (0.22) 0.770 (0.20) 0.320 (0.10)

Zeta potential was measured in water.

3.1.2 Main effect plot The main effect plots for four responses obtained from Taguchi orthogonal array design was reported in Figure 3. This plot indicates the impact of main effects of four design variables on each response. Total of five significant effects (p < 0.05) were found (Figure



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3I-III). The decrease of nanocarrier size was found with the use of higher acetone concentration (80%) (Figure 3I). The use of higher concentrated acetone may result in tighter packing of polymer molecules during nanocarrier formation. A similar relationship between non-solvent concentration and particle size of nanocarriers in our previous studies

15, 23

. The effect of the non-solvent on the particle size of protein based

nanocarriers developed using desolvation method was studied

29-31

. An increase of

particle size from about 30 nm to about 45 nm was observed with use of mixture of the acetone and methanol (50:50 v/v). As compared to acetone, this mixed solvent system might not provide a tight nanoparticle packing. These effects were observed in the formulation of curcumin loaded albumin nanocarriers 29. Introducing higher volume of acetone led to higher PDI (Figure 3II). The higher amount of acetone added at a fixed flow rate is likely to prolong the duration of acetone interaction with the polymer molecules resulting in a higher PDI values. This is in agreement with our previous observations 29, 30. Sadeghi et al 29 reported an PDI increase with less than 1 volume ratio of albumin solution to desolvation solvent, such as ethanol or acetone or their mixture. Gülseren et al. reported a wider distribution of whey protein based nanocarrier size with increasing the concentration of ethanol from 20% to 100% 30. Additionally, the use of 100% acetone has decreased nanocarriers' PDI (Figure 3II). A rapid aggregation of polymer associated with the use of higher acetone concentration which may result in production of nanocarriers with lower PDI

29

. The use of 100%

acetone as a desolvanting agent in the albumin nanocarrier formulation produced a smaller PDI as compared to 30% acetone, when the volume ratio of alubumin to nonsolvent was less than 1 29. A decrease in the PDI with increased acetone concentrationwas


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observed when acetone concentration was used in the range of 70% to 90%

31

. It was

found that higher PDI was obtained with higher concentration of drug molecules in the solution (Figure 3II). The higher concentration of drug molecules in the solution would increase the interaction between polymer and drug molecules. This interaction might cause the alteration of the desolvation process and may be responsible for observed increase in the PDI. An increment in acetone concentration resulted in the increased zeta potential of nanocarriers (Figure 3III). The compact nanocarriers obtained with higher acetone concentration might possess lower water content in the nanocarrier matrix. Primary amine groups were the major hydrophilic function groups on the ABP polymer chain. Thus, a decreased amount of amine groups inside the nanocarrier matrix would be expected to increase the amount of amine groups on the surface. This should lead to increase nanocarrier zeta potential. These results are opposite to that of reported by Sadeghi et al. 29. In this report, the hydrophobic non-solvent was not evaporated from the albumin nanocarrier suspension. Due to the present of non-solvent in suspension, an increase in the hydrophobicity of the nanocarriers might lead to the decrease of zeta potential. Non-significant effects (p > 0.05) were observed or percentage drug loading in the range of the selected levels of all the design factors (Figure 3 IV).



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Figure 3. Main effects plots for L9 Taguchi orthogonal design indicating impact of selected four design variables on the mean values and standard deviations of four response variables. The design variables were ABP concentration ([ABP], mM); volume ratio of acetone to ABP solution (Vact/VABP); acetone concentration ([Act], %); and APAP concentration ([APAP], mM). The four response variables were (I) particle size (nm), (II) polydispersity (PDI), (III) zeta potential (mV), and (IV) percentage loading (%). * The significance of impact of design variables on the response variables corresponds to p < 0.05.

3.1.3 ANOVA analysis of predicted and experimental characteristics of ABP nanocarriers The extent of the statistical impact of individual design variables on the nanocarrier properties was determined using ANOVA analysis with two degrees of freedom.


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ANOVA has compared the effect of each factors on each responses. Table 2 presented the significance of each factor to each response. F-statistic and p-value (95% confidence level) showed a significant impact of the majority of selected factors on the responses with few exceptions. APAP concentration had no significant effect on the particle size of nanocarriers (F = 11.37, p = 0.079). A volume ratio of acetone to ABP solution had no significant effect on the percentage loading (F = 19.12, p = 0.050). The interaction between polymers and solvent molecules govern the formulation process of ABP based nanocarriers formation in the desolvation method. The initial encounter between nonsolvent and polymer is the major factor in determining the nanocarrier particle size. These findings are in agreement with our previously reported albumin nanocarriers using ethanol as non-solvent and with other researchers 15, 23 29, 30. Table 2. F- and p-value of four design variable on four responses based on ANOVA of Taguchi orthogonal array design to formulate APAP-NC. [ A - ABP concentration (mM); B - Volume ratio of acetone and ABP; C - Acetone concentration (%); D - APAP concentration (mM); R1 - size (nm); R2 - polydispersity; R3 - zeta potential (mV); R4 percentage drug loading (%). Critical F value at the confidence level of 95% is 19.46 and any F > critical F is significant; p is p-value from F-test, A indicates statistical significant. Y - Yes and N - No.] Design variables A B C D

R1 F 66.12 48.55 219.39 11.37

p 0.015 0.020 0.005 0.079

A Y Y Y N

F 74.27 212.07 369.57 172.10

R2 P 0.013 0.005 0.003 0.006

A Y Y Y Y

F 28.04 45.13 161.93 49.48

R3 p 0.034 0.022 0.006 0.020

A Y Y Y Y

F 111.74 19.12 26.08 52.97

R4 p 0.009 0.050 0.037 0.019

A Y N Y Y



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3.1.4 Signal to noise ratio analysis of ABP nanocarriers Taguchi factorial design incorporates the loss functions, which were based on the signal to noise ratio (S/N ratio) 32. This function states that any variation away from nominal or target profile leads to deviation from the final product characteristics. As the variation from target profile increases, the quality of the final product decreases exponentially. An appropriate ratio can be selected based on the nature of the responses. There are three most commonly used S/N ratios based on divergence from the nominal or target limit 33. These three situations include larger the better (e.g. percentage drug loading should be as large as possible), smaller the better (e.g. PDI should be at minimum level), and on-target or nominal is best (e.g. particle size of nanocarrier equal to the target specified value of 50.00 nm). The S/N ratio based three noise situations were recorded in Table 3. Table 3. Signal to noise ratio (S/N) to identify effects of the design variables levels on the responses under three situations: larger the better (Zeta potential, percentage loading), smaller the better (PDI), and on-target or nominal is the best (particle size) based on Taguchi orthogonal array design of APAP-NC formulation. [A - ABP concentration (mM); B - Volume ratio of acetone and ABP; C - Acetone concentration (%); D - APAP concentration (mM); R1 - size (nm); R2 - polydispersity; R3 - zeta potential (mV); R4 percentage drug loading (%).] Design variables A

B

C

Levels

R1

R2

R3

R4

0 1 2 0 1 2 0 1

52.91 67.09 46.36 72.40 51.31 42.65 55.95 52.92

32.37 45.59 52.14 50.31 40.97 38.82 55.95 45.29

64.25 45.85 70.51 47.49 75.11 58.01 47.6 73.18

18.87 34.10 31.26 30.16 34.28 19.79 25.07 29.92


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2 0 1 2

D

57.49 51.31 54.52 60.53

37.21 40.08 44.02 46.00

43.57 45.12 62.87 72.62

29.24 33.65 21.89 28.69

The larger or smaller effect of each factor level was identified by comparing S/N ratios of each response and these factors were ranked based on their S/N ratios (STable 1, supplementary data)

11

. The size was primarily affected by the volume ratio of acetone

and polymer solution. The PDI and drug loading percentage values were dependent on the concentration of polymer compared to other design factors. The concentration of acetone was the strongest factor affecting the zeta potential values of nanocarriers 34. The S/N ratio analyses only identify the factors level having the highest impact on minimizing the response variation to produce the best quality product. The ANOVA analysis has identified which formulation and process parameters have non-significant effect (p > 0.05) on each response (Table 2). Therefore, A1B0C2 is the optimized batch for particle size of nanocarriers; A2B0C0D2 is the optimized batch for PDI; A2B1C1D2 is the optimized batch for zeta potential; and A1C1D0 is the optimized batch for percentage drug loading. Subsequently, separate multivariate models were developed to quantify the impact of all selected design variables on individual response. 3.2 Optimization and validation for targeted profile of nanocarriers by multivariate model Nano-scale delivery system performance is dependent on physicochemical properties such as particle size, PDI, surface charge, percentage loading, and interactions with biological system

5, 8, 10, 24

. Furthermore, a formulation with “well controlled desired”

characteristics might enable the development of effective drug delivery systems for the



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targeted delivery of therapeutic agents to the site of action. Therefore, a systematic understanding of formulation and process parameters effects on the nanocarriers' characteristics is a beneficial approach to developing the formulation with varying characteristics. Multivariate regression models (Equation 6-9) was developed using L9 Taguchi orthogonal array design experimental data (include all triplicates). 71 = 55.55 + 7.96 × ?@ − 1.31 × ?A − 6.65 × ? − 1.38 × C@ + 6.91 × CA − 5.53 × C + 15.54 × @ − 7.26 × A − 8.28 × − 3.24 × -@ + 0.38 × -A + 2.86 × -

(6)

72 = 0.453 + 0.095 × ?@ − 0.073 × ?A − 0.022 × ? − 0.099 × C@ + 0.171 × CA − 0.072 × C + 0.087 × @ + 0.137 × A − 0.223 × − 0.093 × -@ + 0.153 × -A − 0.060 × -

(7)

73 = 20.274 − 1.755 × ?@ + 0.379 × ?A + 1.377 × ? − 2.002 × C@ − 0.055 × CA + 2.057 × C − 4.423 × @ + 2.552 × A + 1.870 × − 2.227 × -@ + 0.220 × -A + 2.007 × -

(8)

74 = 0.908 + 0.395 × ?@ − 0.053 × ?A − 0.342 × ? + 0.012 × C@ + 0.099 × CA − 0.110 × C − 0.104 × @ + 0.130 × A − 0.026 × − 0.274 × -@ + 0.061 × -A + 0.213 × -

(9)

These equations were used to predict nanocarrier characteristics of 34 full factorial design. Total 81 APAP-NC formulations with different levels of design variables with their properties such as particle size, PDI, zeta potential, and percentage loading were predicted (STable 2, supplementary data). The optimized formulation was chosen based on desirability function using predicted mean values with following four criteria: targeted


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size of 50.00 nm, minimized PDI to 0.190, maximized zeta potential to 24.50 mV, and maximized percentage loading to 1.750%. It was found that the 0.300 mM of ABP polymer concentration, 100% v/v of acetone concentration, 0.375 volume ratio of acetone to ABP solution, and 0.342 mM of APAP concentration could result nanocarriers with 50.40 ± 4.80 nm of particle size, 0.315 ± 0.068 of PDI, 25.50 ± 3.10 mV of zeta potential, and 0.887 ± 0.032 % of percentage loading (Table 4) with 0.88 of the polymer to drug molar ratio. Table 4. Optimization of APAP-NC formulation based on developed multivariate regression (MLR) model. [ A - ABP concentration (mM); B - Volume ratio of acetone and ABP; C Acetone concentration (%); D - APAP concentration (mM); R1 - size (nm); R2 - polydispersity; R3 - zeta potential (mV); R4 - percentage drug loading (%). All values in the parenthesis indicate standard deviation.] A

B

C

D

0.300

0.375

100

0.342

Status Experimental values Theoretical Values from MLR model p-Value from t-test

R1 54.20 (4.00)

R2 0.252 (0.105)

R3* 22. 90 (1.30)

R4 0.803 (0.065)

50.40 (4.80)

0.315 (0.068)

25.50 (3.10)

0.887 (0.032)

0.35

0.43

0.26

0.12

* Zeta potential was measured in water.

Validation batch was formulated in the triplicate. Analysis of t-test on predicted data from multivariate model and experimental data showed non-significant (p > 0.05) differences in the nanocarrier formulation properties such as particle size (p = 0.352), PDI (p = 0.432), zeta potential (p = 0.256), and percentage loading (p = 0.115) (Table 4).



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Figure 4. Characterization of ABP based nanocarriers: (I) The particle size distribution of optimized APAP-NC using DLS. (II) Size and morphology evaluation using transmission electron microscopy (TEM); scale bar equivalent to 500 nm, (III) Size evaluation using atomic force microscopy (AFM); scale bar equivalent to -29.4 nm to 39.3 nm for height profile and 5x5 µm for the lateral size.


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3.4 Morphology of nanocarriers The shape of placebo nanocarriers was examined by TEM (Figure 4II). The formulated nanocarriers were spherical in shape with a size of 70 ± 3 nm. The nanocarrier size obtained via TEM was found slightly larger than our result with Nicomp Particle Sizer (Figure 4I&II). This might be because the particles of the smaller size were under estimated during the counting and calculating. The similar trend was observed in previous study when they compared the size of gold nanoparticle obtained from TEM and the one from DLS technique 35. The surface topography of placebo nanocarriers was further examined by AFM (Figure 4III). The size of about 50 nm was obtained by analyzing height profile. It was in the agreement with our DLS particle size analysis (Figure 4I). However, the lateral size of some particles on AFM image was about 200 nm, which indicated the presence of aggregates. This might be due to the drying process used in sample preparation for AFM analysis. Both TEM and AFM results have confirmed the spherical shape of developed nanocarriers 36. 3.5 Hydrophobic drug loaded nanocarriers Most of the chemotherapeutic drugs used in the clinic are hydrophobic and their solubility is one limiting factor in their product development

37

. The US Food and Drug

Agency (FDA) approved albumin-bound paclitaxel nanoparticle formulation was able to overcome the limitation associated with poor solubility of paclitaxel and adverse effects resulting due to the use of Chromophore

38

. Therefore, nanocarriers could overcome the

limitation and improve the efficacy of the hydrophobic chemotherapeutic drugs. The



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developed cationic ABP nanocarrier formulation was assessed for its capability to load the hydrophobic drug, ETO. The optimized design variables used to develop ETO-NC formulations were 0.3 mM of ABP, 0.375 of volume ratio of ABP to acetone, and 100% v/v of acetone dilution fraction. ETO-NC formulations showed size of 48.90 ± 3.50 nm, PDI of 0.289 ± 0.035, zeta potential of 22.20 ± 4.60 mV, and percentage loading of 5.600 ± 0.300 %. APAP-NC formulations and ETO-NC formulations showed no significant differences (p > 0.05) in their particle size, PDI, and zeta potential. However, ETO-NC formulations showed significant (p < 0.01) 7-fold higher percentage loading as compared to the APAP-NC formulations. This suggests an improved hydrophobic drug loading efficiency of ABP based nanocarrier, which was generally observed with liposomes by other groups

39, 40

. The higher loading efficiency might be caused by entrapment of the

hydrophobic drug molecules with hydrophobic backbone of ABP polymer. Our previous studies showed that the ABP polymeric based nano-complexes of 150-200 nm size were successfully used for the delivery of therapeutic agents for the treatment of various cancers

17

. ABP nano-complexes with pDNA or siRNA were also effectively delivered

into mouse model of ovarian cancer xenografts 17 and ovarian cancer cells respectively 19. Paclitaxel-PEGylated ABP nanoconjugate forming polycomplex micelles with the size of 200 nm to co-deliver the drug and pDNA to breast cancer and lung cancer cells 17-19. Our results suggest that the ABP nanocarriers could be used for the delivery of hydrophilic as well as hydrophobic molecules. 3.6 Nanocarrier preliminary stability study and glutathione triggered drug release The preliminary stability of ETO-NC was assessed by measuring the particle size of nanocarriers in PBS 7.4 for 2 days (Figure 5). The size of the nanocarriers was observed


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in the range of 50-60 nm till 47 hours. It indicated that nanocarriers were able to maintain their particle size under the physiological salt strength and the pH environment. Only nanocarriers with the size of < 200 nm could enhance their accumulation via EPR effect 7, 8

. The nanocarrier of > 100 nm size cannot penetrate into deep tissue of tumor whereas

the ones of < 20 nm size unable to maintain the prolonged circulation life-time

41

. The

prolonged circulation life-time could improve the tumor accumulation of nanocarriers 42. Therefore, ABP nanocarriers of 50-60 nm size could minimize clearance and, penetrate into the tumor tissue via EPR effect while maintaining a relatively longer circulatory lifetime to further improve the tumor accumulation of the nanocarriers. The newly developed ABP based matrix nanocarriers would provide dual benefits of prolonged circulatory lifetime and enhanced tumor uptake by EPR effect 7, 8. 80

Size (nm)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


60 40 20 0 0

10

20

30

40

50

Time (h)

Figure 5. Stability of optimized ETO-NC in phosphorylate buffer solution (PBS) 7.4 over 48 h. Formulated ETO-NC was mixed with PBS at 1:20 volume ratio and particle size of the nanocarriers were measure by DLS at time points of 0, 2, 8, 24 and 48 h. Results are represented as mean ± SD (n = 3).

We have designed ABP polymer to utilize the proton sponge effect to deliver the nanocarriers into cytosol

43-45

. Zeta potential of ETO-NC formulations were measured 29

ACS Paragon Plus Environment


under PBS pH 6.4 and 7.4. Zeta potential was found significantly increased (p < 0.01) to 34.20 ± 5.10 mV at pH 6.4 compared to 10.40 ± 2.60 mV at PBS pH 7.4 (Figure 6). The increase in zeta potential of nanocarrier at pH 6.4 compared to pH 7.4 may be due to the protonation of amine groups

46

. Similar trend of increase zeta potential was reported on

the chitosan and other polysaccharides while pH was dropped

47

. This zeta potential

increase suggested that the ABP nanocarriers would favor proton sponge effect at endosomal pH 6.4, which may results in the endosomal escape of nanocarriers, and subsequently release the drug in the cytoplasm of cells46, 48.

50

Voltage (mV)

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* p = 0.002

40 30 20 10 0 DPBS 7.4

DPBS 6.4

Figure 6. Zeta potential of optimized nanocarriers (ETO-NC) in phosphorylate buffer solution of pH 7.4 and 6.4. Formulated ETO-NC was mixed with PBS 7.4 or 6.4 at volume ratio of 1: 20. The zeta potential was measured by NICOMP ZLS 380 analyzer. Results are represented as mean ± SD (n = 3).

ETO-NC formulations (48.90 ± 3.50 nm of size, 0.289 ± 0.035 of PDI, 22.20 ± 4.60 mV of zeta potential, and 5.600 ± 0.300 % of percentage loading) were used to study the release profile. Glutathione (GSH) is the most abundant tripeptide molecule in human cells and it degrades disulfide bonds. Elevated level of GSH were observed in the human 30 ACS Paragon Plus Environment

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cancer cells compared to normal cells

49

. The GSH mediated degradation of disulfide

linkage within ABP polymer helps in achieving cytosol targeted release of therapeutic agents. 17, 19. Nanocarriers release under physiological PBS 7.4 and 10 mM of GSH were evaluated. The high concentration of GSH was found in cytosol of cancer cells and other type of cells. The GSH concentration can be as high as 10 mM depending on the cell type 50

. Therefore, we selected 10 mM GSH to verify the GSH trigger bioresponsive property

of developed ABP nanocarriers. It was found that 40% and 80% of ETO was released in 4 h and 48 h in presence of release medium containing 10 mM GSH respectively (Figure 7). The release of ETO was minimal without GSH, < 10% after 4 h and < 20% after 48 h. Similarly, the reducing environment-triggered release from pDNA loaded ABP nanocomplex of 150-200 nm was observed in our previous studies by using dithiothreitol as reducing reagent with incubation period of 30 min 17, 18.



0 mM Glutathione 10 mM Glutathione

80

Cumulative Release (%)

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60 40 20 0 0

20

40

60

80

Time, h

Figure 7. Triggered release of etoposide from nanocarriers by Glutathione in phosphorylate buffer solution (PBS) 7.4. The 100 µL of formulated ETO-NC was placed into a 2 mL glass vial capped with a dialysis membrane (100,000 Da cut-off molecular weight) with a diameter of 6.5 mm. Glass vials were immersed into a 10 mL of release medium with constant stirring at 400 rpm under ambient conditions. A 100 µL release medium was sampled at specific time point (0, 4, 8, 24, 48, and 72h). The ETO content form collected samples were measured using HPLC method. Results are represented as mean ± SD (n = 3). The release kinetic was analyzed by fitting it into different release models, including zero order, Korsmeyer-Peppas, Weibull, Higuchi, and Michaelis-Menten. Korsmeyer-Peppas (n = 1.03), Weibull, and Michaelis-Menten had shown a value of R2 above 0.9. R2 of zero order and Higuchi were 0.8652 and 0.4937 respectively. However, when the first 8h data was used to fit with zero order release kinetics, the R2 value was increased to near 1. This indicated two steps release of drug, where initial release was zero order. The fitness to Korsmeyer-Peppas and Weibull model indicated the formulated nanocarrier was a polymeric matrix system. Korsmeyer-peppas showed a Super Case II transport 51, which 32 ACS Paragon Plus Environment

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means the dominated release mechanism was polymer relaxation and particle swelling. Michaelis-Menten model 52 was for enzyme kinetics. It was verified that the release of ETO from nanocarriers as result of nanocarrier backbone degradation via GSH. Therefore, ETO was released from swollen nanocarriers with an enzymatic degrading mechanism. The developed ABP nanocarriers were able to load hydrophilic as well as hydrophobic drugs and showed bioresponsive property via GSH triggered release of loaded therapeutic agent. Considering the nanocarrier size of less than 100 nm, the zeta potential of 25 mV, and GSH triggered release, we expect that the developed nanocarrier will be able to efficiently internalised by cells and effectively delivery loaded drug within cells to exert a therapeutic effect. The nanoparticles of less than 100 nm and zeta potential of 10 mV were found increase the anticancer effect compared to that of drug solution in our and other reported studies. Additionally, GSH triggered release nanocarriers also showed an enhanced intracellular drug delivery. Our future studies with ETO-NC include the

evaluation of anticancer efficacy against cancer cells and development of tumor specific receptor targeting moiety-conjugated nanocarriers. These nanocarriers could be used for the delivery of therapeutic agents such as drugs, genes, and proteins for the treatment of cancer and other diseases. 4. Conclusions A smart experimentation setup based on Taguchi factorial design (L9 orthogonal array) with ANOVA and S/N ratio, were used to optimize a newly developed cationic matrix based APAP-NC batches. Multivariate models with desirability function were developed to formulate tunable nanocarriers by combining all four responses (particle size, PDI, zeta potential, and percentage drug loading), which was not feasible by ANOVA and S/N ratio analysis. These models predicted the optimum formulation composition to produce 33 ACS Paragon Plus Environment


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targeted nanocarriers properties such as particle size, PDI, zeta potential, and percentage loading. A validation of predicted values with experimental values showed insignificant differences (p > 0.05). The optimized spherical ABP based nanocarriers were able to load hydrophilic drug, APAP, or hydrophobic drug, ETO. Developed ABP polymer based nanocarriers were stable at physiological pH. The triggered release of loaded drug in the presence of a physiological concentration of GSH indicates developed nanocarriers potential for bioresponsive cytosolic delivery of therapeutic agents. The release kinetics showed that ETO release from the nanocarriers occurs due to swelling followed by enzymatic degradation. The physicochemical properties of developed tunable bioresponsive ABP based matrix nanocarriers using a unique modeling approach clearly show a promising delivery system for an efficient delivery of therapeutic agents.

Acknowledgements Dr. Mahavir Chougule's lab and Professor Sung Wan Kim’s Group acknowledges Hawai’i Community Foundation, Honolulu, HI 96813, USA, for research support on lung cancer (LEAHI FUND for Pulmonary Research Award; ID# 15ADVC-74296). Dr. Chougule acknowledges the support of the National Institute of General Medical Science of the National Institutes of Health under award number SC3GM109873. The Chougule group would like to acknowledge the 2013 George F. Straub Trust and Robert C. Perry Fund of the Hawai’i Community Foundation, Honolulu, HI 96813, USA, for research support on lung cancer. Dr. Chougule also acknowledges a seed grant from the Research Corporation of the University of Hawai’i at Hilo, Hilo, HI 96720, USA, and the Daniel K. Inouye College of Pharmacy, University of Hawaii at Hilo, Hilo, HI 96720, USA, for


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providing start-up financial support to his research group. The authors also acknowledge the Department of Pharmaceutics and Drug Delivery, School of Pharmacy, University of Mississippi, University, MS, USA for providing start-up financial support to Dr. Chougule’s lab. Authors would like to thank Dr. Rajesh N. Davé, (Distinguished Professor of Chemical, Biological and Pharmaceutical Engineering, Site Director, NSFERC on Structured Organic Particulate Systems, New Jersey Institute of Technology, Newark, NJ, USA) for providing APAP. Authors also want to acknowledge Ms. Susanne R. Youngren-Ortiz for her kind proofreading of this manuscript. Professor Sung Wan Kim’s Group would like to acknowledge Dr. Mahavir Chougule’s invitation to share in the innovative work compiled by excellent group of collaborators. The Kim group would also like to thank JoungPyo Nam for his work supporting Dr. Kihoon Nam, whom has since moved to the University of Utah’s School of Dentistry. Dr. Yi Y. Zuo would like to acknowledge the support of National Science Foundation (CBET-1254795).

Supporting Information. STable 1 include ranking of factors in respect of their effect on responses and STable 2 include the predicted full factorial results.

References 1. Cara, E. Cancer Now Second Leading Cause Of Death Worldwide: 14.9 Million Cases and 8.2 Million Deaths In 2013. http://www.medicaldaily.com/cancer-now-secondleading-cause-death-worldwide-149-million-cases-and-82-million-335846 (January 14, 2016), 2. Siegel, R. L.; Miller, K. D.; Jemal, A. Cancer statistics, 2015. CA-CANCER J CLIN 2015, 65, (1), 5-29. 3. Malvezzi, M.; Bertuccio, P.; Rosso, T.; Rota, M.; Levi, F.; La Vecchia, C.; Negri, E. European cancer mortality predictions for the year 2015: does lung cancer have the highest death rate in EU women? Annals of Oncology 2015, 26, (4), 779-786.



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4. Matsumura, Y.; Maeda, H. A new concept for macromolecular therapeutics in cancer chemotherapy: mechanism of tumoritropic accumulation of proteins and the antitumor agent smancs. Cancer research 1986, 46, (12 Part 1), 6387-6392. 5. Dawidczyk, C. M.; Kim, C.; Park, J. H.; Russell, L. M.; Lee, K. H.; Pomper, M. G.; Searson, P. C. State-of-the-art in design rules for drug delivery platforms: lessons learned from FDA-approved nanomedicines. J CONTROL RELEASE 2014, 187, 133-144. 6. Ott, P. A.; Chang, J.; Madden, K.; Kannan, R.; Muren, C.; Escano, C.; Cheng, X.; Shao, Y.; Mendoza, S.; Gandhi, A.; Liebes, L.; Pavlick, A. C. Oblimersen in combination with temozolomide and albumin-bound paclitaxel in patients with advanced melanoma: a phase I trial. Cancer Chemother Pharmacol 2013, 71, (1), 183-91. 7. Ilium, L.; Davis, S.; Wilson, C.; Thomas, N.; Frier, M.; Hardy, J. Blood clearance and organ deposition of intravenously administered colloidal particles. The effects of particle size, nature and shape. International Journal of Pharmaceutics 1982, 12, (2), 135-146. 8. Tabata, Y.; Ikada, Y., Phagocytosis of polymer microspheres by macrophages. In New Polymer Materials, Springer Berlin Heidelberg: 1990; Vol. 94, pp 107-141. 9. Crommelin, D. J. A.; de Vlieger, J. S. B., Non-biological complex drugs: the science and the regulatory landscape. Springer International Publishing: 2015. 10. Bertrand, N.; Wu, J.; Xu, X.; Kamaly, N.; Farokhzad, O. C. Cancer nanotechnology: the impact of passive and active targeting in the era of modern cancer biology. Advanced Drug Delivery Reviews 2014, 66, 2-25. 11. Roy, R. K., A primer on the Taguchi method. Society of Manufacturing Engineers: 2010. 12. Ilzarbe, L.; Álvarez, M. J.; Viles, E.; Tanco, M. Practical applications of design of experiments in the field of engineering: a bibliographical review. Quality and Reliability Engineering International 2008, 24, (4), 417-428. 13. Jeyapaul, R.; Shahabudeen, P.; Krishnaiah, K. Quality management research by considering multi-response problems in the Taguchi method–a review. International Journal of Advanced Manufacturing Technology 2005, 26, (11-12), 1331-1337. 14. Youngren, S. R.; Tekade, R. K.; Gustilo, B.; Hoffmann, P. R.; Chougule, M. B. STAT6 siRNA matrix-loaded gelatin nanocarriers: formulation, characterization, and ex vivo proof of concept using adenocarcinoma cells. BIOMED RES INT 2013, 2013. 15. Tekade, R. K.; Youngren-Ortiz, S. R.; Yang, H.; Haware, R.; Chougule, M. B. Designing Hybrid Onconase Nanocarriers for Mesothelioma Therapy: A Taguchi Orthogonal Array and Multivariate Component Driven Analysis. Molecular Pharmaceutics 2014, 11, (10), 3671-3683. 16. Kalariya, M.; Padhi, B. K.; Chougule, M.; Misra, A. Clobetasol propionate solid lipid nanoparticles cream for effective treatment of eczema: formulation and clinical implications. Indian journal of experimental biology 2005, 43, (3), 233-40. 17. Kim, T.; Ou, M.; Lee, M.; Kim, S. W. Arginine-grafted bioreducible poly (disulfide amine) for gene delivery systems. Biomaterials 2009, 30, (4), 658-664. 18. Nam, K.; Nam, H. Y.; Kim, P. H.; Kim, S. W. Paclitaxel-conjugated PEG and arginine-grafted bioreducible poly (disulfide amine) micelles for co-delivery of drug and gene. Biomaterials 2012.


Page 37 of 40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


19. Kim, S. H.; Jeong, J. H.; Kim, T.; Kim, S. W.; Bull, D. A. VEGF siRNA delivery system using arginine-grafted bioreducible poly (disulfide amine). Molecular Pharmaceutics 2008, 6, (3), 718-726. 20. Das, S.; Chaudhury, A. Recent advances in lipid nanoparticle formulations with solid matrix for oral drug delivery. AAPS PharmSciTech 2011, 12, (1), 62-76. 21. Borovikova, L.; Titova, A.; Matveeva, N.; Pisarev, O. Stabilizing selenium nanoparticles with chymotrypsin: The effect of pH and nanoparticle-enzyme concentration ratios on the stability of nanocomplexes. Russian Journal of Physical Chemistry A 2013, 87, (6), 998-1001. 22. Ou, M.; Wang, X.-L.; Xu, R.; Chang, C.-W.; Bull, D. A.; Kim, S. W. Novel biodegradable poly (disulfide amine) s for gene delivery with high efficiency and low cytotoxicity. Bioconjugate Chemistry 2008, 19, (3), 626-633. 23. Tekade, R. K.; Chougule, M. B. Formulation development and evaluation of hybrid nanocarrier for cancer therapy: Taguchi orthogonal array based design. BIOMED RES INT 2013, 2013, 712678. 24. Patel, A. R.; Spencer, S. D.; Chougule, M. B.; Safe, S.; Singh, M. Pharmacokinetic evaluation and in vitro-in vivo correlation (IVIVC) of novel methylenesubstituted 3,3' diindolylmethane (DIM). EUR J PHARM SCI 2012, 46, (1-2), 8-16. 25. Ebube, N. K.; Jones, A. B. Sustained release of acetaminophen from a heterogeneous mixture of two hydrophilic non-ionic cellulose ether polymers. International Journal of Pharmaceutics 2004, 272, (1), 19-27. 26. Montero, D.; Tachibana, C.; Winther, J. R.; Appenzeller-Herzog, C. Intracellular glutathione pools are heterogeneously concentrated. Redox biology 2013, 1, (1), 508-513. 27. Jones, D. P.; Carlson, J. L.; Samiec, P. S.; Sternberg, P.; Mody, V. C.; Reed, R. L.; Brown, L. A. S. Glutathione measurement in human plasma: evaluation of sample collection, storage and derivatization conditions for analysis of dansyl derivatives by HPLC. Clinica chimica acta 1998, 275, (2), 175-184. 28. Cheng, R.; Feng, F.; Meng, F.; Deng, C.; Feijen, J.; Zhong, Z. Glutathioneresponsive nano-vehicles as a promising platform for targeted intracellular drug and gene delivery. J CONTROL RELEASE 2011, 152, (1), 2-12. 29. Sadeghi, R.; Moosavi-Movahedi, A.; Emam-jomeh, Z.; Kalbasi, A.; Razavi, S.; Karimi, M.; Kokini, J. The effect of different desolvating agents on BSA nanoparticle properties and encapsulation of curcumin. Journal of Nanoparticle Research 2014, 16, (9), 1-14. 30. Gülseren, Đ.; Fang, Y.; Corredig, M. Whey protein nanoparticles prepared with desolvation with ethanol: Characterization, thermal stability and interfacial behavior. Food Hydrocolloids 2012, 29, (2), 258-264. 31. Von Storp, B.; Engel, A.; Boeker, A.; Ploeger, M.; Langer, K. Albumin nanoparticles with predictable size by desolvation procedure. Journal of Microencapsulation 2012, 29, (2), 138-146. 32. Taguchi, G., Taguchi methods: Signal-to-noise ratio for quality evaluation. Amer Supplier Inst: 1991; Vol. 3. 33. Cavazzuti, M., Optimization Methods: From Theory to Design Scientific and Technological Aspects in Mechanics. Springer Berlin Heidelberg: 2012.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 40

34. Budhian, A.; Siegel, S. J.; Winey, K. I. Haloperidol-loaded PLGA nanoparticles: systematic study of particle size and drug content. International journal of pharmaceutics 2007, 336, (2), 367-375. 35. Albertini, B.; Greco, S.; Cassetti, E.; Schoubben, A.; Blasi, P.; Ricci, M., Abstract Book - Poster. In Gold Nanoparticle Size Evaluation Using Different Methods, CRS Italy Local Chapter: Pavia, Italy, 2013; p 47. 36. Suh, W.; Han, S.; Yu, L.; Kim, S. W. An angiogenic, endothelial-cell-targeted polymeric gene carrier. Molecular Therapy 2002, 6, (5), 664-672. 37. Chidambaram, M.; Manavalan, R.; Kathiresan, K. Nanotherapeutics to overcome conventional cancer chemotherapy limitations. Journal of Pharmacy & Pharmaceutical Sciences 2011, 14, (1), 67-77. 38. Petrelli, F.; Borgonovo, K.; Barni, S. Targeted delivery for breast cancer therapy: the history of nanoparticle-albumin-bound paclitaxel. Expert Opinion on Pharmacotherapy 2010, 11, (8), 1413-1432. 39. Moysan, E.; Bastiat, G.; Benoit, J. P. Gemcitabine versus modified gemcitabine: a review of several promising chemical modifications. Molecular Pharmaceutics 2012, 10, (2), 430-444. 40. Immordino, M. L.; Brusa, P.; Rocco, F.; Arpicco, S.; Ceruti, M.; Cattel, L. Preparation, characterization, cytotoxicity and pharmacokinetics of liposomes containing lipophilic gemcitabine prodrugs. J CONTROL RELEASE 2004, 100, (3), 331-346. 41. Perrault, S. D.; Walkey, C.; Jennings, T.; Fischer, H. C.; Chan, W. C. Mediating tumor targeting efficiency of nanoparticles through design. Nano Letters 2009, 9, (5), 1909-1915. 42. Jain, R. K.; Stylianopoulos, T. Delivering nanomedicine to solid tumors. Nature Reviews Clinical Oncology 2010, 7, (11), 653-664. 43. Firdessa, R.; Oelschlaeger, T. A.; Moll, H. Identification of multiple cellular uptake pathways of polystyrene nanoparticles and factors affecting the uptake: Relevance for drug delivery systems. European journal of cell biology 2014, 93, (8), 323-337. 44. Huang, J. G.; Leshuk, T.; Gu, F. X. Emerging nanomaterials for targeting subcellular organelles. Nano Today 2011, 6, (5), 478-492. 45. Nel, A. E.; Mädler, L.; Velegol, D.; Xia, T.; Hoek, E. M.; Somasundaran, P.; Klaessig, F.; Castranova, V.; Thompson, M. Understanding biophysicochemical interactions at the nano–bio interface. Nature Materials 2009, 8, (7), 543-557. 46. Benjaminsen, R. V.; Mattebjerg, M. A.; Henriksen, J. R.; Moghimi, S. M.; Andresen, T. L. The possible “proton sponge” effect of polyethylenimine (PEI) does not include change in lysosomal pH. Molecular Therapy 2013, 21, (1), 149-157. 47. Carneiro-da-Cunha, M. G.; Cerqueira, M. A.; Souza, B. W.; Teixeira, J. A.; Vicente, A. A. Influence of concentration, ionic strength and pH on zeta potential and mean hydrodynamic diameter of edible polysaccharide solutions envisaged for multinanolayered films production. Carbohydrate Polymers 2011, 85, (3), 522-528. 48. Iversen, T.-G.; Skotland, T.; Sandvig, K. Endocytosis and intracellular transport of nanoparticles: present knowledge and need for future studies. Nano Today 2011, 6, (2), 176-185. 49. Balendiran, G. K.; Dabur, R.; Fraser, D. The role of glutathione in cancer. Cell Biochemistry and Function 2004, 22, (6), 343-352.


Page 39 of 40

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50. Navarro, J.; Obrador, E.; Carretero, J.; Petschen, I.; Avino, J.; Perez, P.; Estrela, J. M. Changes in glutathione status and the antioxidant system in blood and in cancer cells associate with tumour growth in vivo. Free Radical Biology and Medicine 1999, 26, (3), 410-418. 51. Thomas, N. L.; Windle, A. A theory of case II diffusion. Polymer 1982, 23, (4), 529-542. 52. Chen, W. W.; Niepel, M.; Sorger, P. K. Classic and contemporary approaches to modeling biochemical reactions. Genes & Development 2010, 24, (17), 1861-1875.



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Factorial Design Based Multivariate Modeling and Optimization of

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