Development of a Physiologically Relevant Population

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Development of a physiologically relevant population pharmacokinetic in vitro-in vivo correlation approach for designing extended-release oral dosage formulation Tae Hwan Kim, Soyoung Shin, Jürgen B. Bulitta, Yu Seok Youn, Sun Dong Yoo, and Beom Soo Shin Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.6b00677 • Publication Date (Web): 03 Nov 2016 Downloaded from http://pubs.acs.org on November 9, 2016

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Molecular Pharmaceutics

1

Development of a physiologically relevant

2

population pharmacokinetic in vitro-in vivo

3

correlation approach for designing extended-release

4

oral dosage formulation Tae Hwan Kima, Soyoung Shinb, Jürgen B. Bulittac, Yu Seok Youn a, Sun Dong Yoo*a,

5

Beom Soo Shin*d

6 7 a

8 9

b

Department of Pharmacy, College of Pharmacy, Wonkwang University, Iksan, Jeonbuk, Korea c

10 11

School of Pharmacy, Sungkyunkwan University, Suwon, Gyeonggi-do, Korea

d

College of Pharmacy, University of Florida, FL, USA

College of Pharmacy, Catholic University of Daegu, Gyeongsan, Gyeongbuk, Korea

12 13 14 15 16

1 ACS Paragon Plus Environment


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*Corresponding Authors:

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Beom Soo Shin, Ph.D.

19

College of Pharmacy, Catholic University of Daegu

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13-13 Hayang-ro, Hayang-eup, Gyeongsan-si, Gyeongbuk 38430, Korea

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Tel: +82-53-850-3617

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Fax: +82-53-850-3602

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E-mail: [email protected]

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Sun Dong Yoo, Ph.D.

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School of Pharmacy, Sungkyunkwan University

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2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do 16419, Korea

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Tel: +82-31-290-7757

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Fax: +82-31-292-8800

30

E-mail: [email protected]

31 32 33

‡Sun Dong Yoo and Beom Soo Shin contributed equally to this work.


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GRAPHICAL ABSTRACT

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ABSTRACT

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Establishing a level A in vitro-in vivo correlation (IVIVC) for a drug with complex absorption

39

kinetics is challenging. The objective of the present study was to develop an IVIVC approach

40

based on population pharmacokinetic (POP-PK) modeling that incorporated physiologically

41

relevant absorption kinetics. To prepare three extended release (ER) tablets of loxoprofen, three

42

types of hydroxypropyl methylcellulose (HPMC 100, 4000, and 15000 cps) were used as drug

43

release modifiers, while lactose and magnesium stearate were used as the diluent and lubricant,

44

respectively. An in vitro dissolution test in various pH conditions showed that loxoprofen

45

dissolution was faster at higher pH. The in vivo pharmacokinetics of loxoprofen was assessed

46

following oral administration of the different loxoprofen formulations to beagle dogs (n=22 in

47

total). Secondary peaks or shoulders were observed in many of the individual plasma

48

concentration vs. time profiles after ER tablet administration, which may result from secondary

49

absorption in the intestine due to a dissolution rate increase under intestinal pH compared to that

50

observed at stomach pH. In addition, in vivo oral bioavailability was found to decrease with

51

prolonged drug dissolution, indicating site-specific absorption. Based on the in vitro dissolution

52

and in vivo absorption data, a POP-PK IVIVC model was developed using S-ADPAT software.

53

pH-dependent biphasic dissolution kinetics, described using modified Michaelis-Menten kinetics

54

with varying Vmax, and site-specific absorption, modeled using a changeable absorbed fraction

55

parameter, were applied to the POP-PK IVIVC model. To experimentally determine the biphasic

56

dissolution profiles of the ER tablets, another in vitro dissolution test was conducted by

57

switching dissolution medium pH based on an in vivo estimate of gastric emptying time. The


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model estimated, using linear regression, that in vivo initial maximum dissolution rate (Vmax(0)in

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vivo)

60

dissolution profiles obtained from POP-PK modeling could be converted to in vitro dissolution

61

profiles and vice versa. Monte Carlo simulations were performed for model validation, and

62

prediction errors for Cmax and AUC were all within the acceptable range (90 to 110%) according

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to the FDA guidelines. The developed model was successfully applied for the prediction of in

64

vivo pharmacokinetics of a loxoprofen double-layered tablet using the in vitro dissolution profile.

65

In conclusion, a level A IVIVC approach was developed and validated using population

66

modeling that accounted for pH-dependent dissolution and site-specific absorption. Excellent

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correlations were observed between in vitro and in vivo dissolution profiles. This new approach

68

holds great promise for the establishment of IVIVCs for drug and formulation development

69

where absorption kinetics strongly depend on complex physiologically absorption processes.

was highly correlated (r2> 0.998) with in vitro (Vmax(0)in

vitro),

indicating that in vivo

70 71

Keywords: in vitro-in vivo correlation (IVIVC); population pharmacokinetic modeling;

72

extended release formulation; loxoprofen.

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1. INTRODUCTION

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Oral solid formulations, such as tablets and capsules, are the most preferred and available type

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of drug formulation in the current market. Once these solid formulations are administered via the

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oral route, they undergo disintegration, dissolution, and absorption into the systemic circulation.

78

The rate and extent of drug absorption are reflected in the drug concentration present in the

79

blood, which is directly related to drug effect. Thus, in order to enhance therapeutic effects while

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minimizing unwanted side effects, it is crucial to maintain optimal drug concentration levels

81

within the body by modifying the rate and extent of drug absorption. Since drug release profiles

82

of extended release (ER) formulations can alter the pharmacokinetics/pharmacodynamics of a

83

drug, release profile design is a starting point for the ER formulation developmental process.

84

Once a target ER dissolution profile has been decided based on the supposed optimal

85

pharmacokinetics, the pharmacokinetics of the ER formulation needs to be evaluated or

86

compared with the conventional immediate release (IR) formulation via human and animal

87

pharmacokinetic studies

88

repeating in vivo experiments in order to prove the pharmacokinetic similarity between the

89

reference and test formulations. However, both clinical and non-clinical studies are costly, time-

90

consuming, and present various ethical issues. Therefore, surrogate methods for evaluating

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bioequivalence between newly formulated ER and reference formulations are constantly

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attempted.

1-2

. During ER formulation development, the greatest difficulty is

93

Since a difference in dissolution rate would lead to a difference in drug systemic blood

94

concentration, a mathematical correlation between the in vitro dissolution profile and in vivo

95

systemic exposure could possibly predict the in vivo profile based on the in vitro profile. The in


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vitro-in vivo correlation (IVIVC) is known to be the best option for the development of a new ER

97

formulation, as it reduces development time as well as cost

98

publications regarding IVIVC (PubMed search term “in vitro in vivo correlation”) has

99

consistently grown, with significant increases over the past 10 years, reflecting emerging

100

3-7

. Since 1997, the number of

research interest in IVIVC.

101

Although IVIVC is a great tool for development of ER formulations, there are several

102

limitations of the conventional IVIVC approach. Conventionally, the in vitro dissolution profile

103

can be characterized by experimental methods, i.e., dissolution test across various pH, media,

104

and apparatus. The in vivo dissolution or absorption profiles can be characterized based on the

105

drug concentration vs. time data by mathematical methods such as the Wagner-Nelson

106

Loo-Riegelman 9, or numerical deconvolution

107

describe complex systemic disposition kinetics, such as non-linear kinetics or enterohepatic

108

recirculation, and assume that all dissolved drugs are completely absorbed into the systemic

109

circulation. Thus, the conventional IVIVC approaches can only be applied for highly permeable

110

drugs without permeability limitations, such as Biopharmaceutics Classification System (BCS)

111

class I or II drugs 5, 11-12.

10

8

and

methods. However, these methods cannot fully

112

Even for highly permeable drugs, the prediction of in vivo behavior based on in vitro

113

dissolution, i.e., IVIVC may become challenging in certain cases. These cases include when drug

114

dissolution is significantly affected by environmental pH, when the drug has an absorption

115

window, and/or when permeability in the gastrointestinal tract varies widely by location

116

Gastrointestinal fluid pH varies widely in the gastrointestinal tract. Thus, the solubility of weakly

117

basic or acidic drugs in the gastric and intestinal fluids is often different, resulting in differences

5, 13

.



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in stomach and small intestinal dissolution rates, and in turn affecting plasma drug concentration

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profiles and bioavailability. Aside from solubility, gastrointestinal segment anatomy and

120

physiological condition are also important determinants of drug absorption. Therefore, drug

121

absorption may depend on the interplay between drug properties and gastrointestinal tract

122

physiology. Without taking into account these variable factors, in vitro dissolution characteristics

123

alone cannot accurately predict in vivo bioavailability 14-15. Nevertheless, there have been limited

124

attempts to apply dynamically changing dissolution and permeability variables to the

125

conventional IVIVC approach, in order to model changing environmental conditions as the drug

126

migrates through the gastrointestinal tract. Therefore, the demand for improving IVIVC

127

predictability through the incorporation of physiologically meaningful data has increased

128

Recently, mechanistic/physiologically relevant absorption models are increasingly used to

129

establish IVIVC. These mechanistic absorption models allow incorporating physiological factors

130

such as pH-dependent dissolution

131

potential to overcome limitations of conventional approaches.

17-18

or site-dependent absorption

19-22

14, 16

.

and show promising

132

The aim of the present study was to establish a novel IVIVC model for drugs with complex

133

dissolution and absorption characteristics, which exhibit poor predictability in the conventional

134

IVIVC model. The population approach was adopted to IVIVC modeling, which allows greater

135

flexibility in assessing in vivo pharmacokinetic variability and complex absorption processes.

136

This in turn provides additional information on in vivo drug performance. We applied the

137

population pharmacokinetic IVIVC (POP-PK-IVIVC) approach using loxoprofen as a model

138

drug. Loxoprofen is a non-steroidal anti-inflammatory drug (NSAID) and its in vitro dissolution

139

and in vivo absorption have been indicated to be pH-dependent. POP-PK-IVIVC would provide a


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novel approach for the establishment of IVIVC, and assist rational strategy for predicting drug

141

release profiles and developing ER formulations.

142 143

2. MATERIALS AND METHODS

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2.1. Materials

145

Loxoprofen was provided by Boryung Pharmaceutical Co., Ltd. (Seoul, Korea). Ketoprofen

146

(internal standard), acetic acid, and formic acid were purchased from Sigma-Aldrich Co. (St.

147

Louis, MO, USA). High performance liquid chromatography (HPLC) grade acetonitrile and

148

water were purchased from J.T. Baker Co. (Philipsburg, NJ, USA). Ethanol (HPLC grade),

149

hydrochloric acid, and potassium dihydrogen phosphate were purchased from Merck Co.

150

(Darmstadt, Germany).

151

Sodium carboxymethyl cellulose and microcrystalline cellulose were purchased from Whawon

152

Pharm. Co. (Seoul, Korea). Hydroxypropylmethyl cellulose (HPMC) 2208-100, -4,000, and -

153

15,000 cps were obtained from Shin-Etsu Chemical Co., Ltd. (Tokyo, Japan). Magnesium

154

stearate was purchased from Faci Asia Pacific Pte Ltd. (Jurong Island, Singapore).

155

Polyvinylpyrrolidone K30 was purchased from BASF Co., Ltd. (Rhineland-Palatinate,

156

Germany). Sodium hydroxide and sodium chloride were purchased from Samchun Chemical

157

Co., Ltd. (Seoul, Korea)

158

2.2. Formulation

159

An immediate release (IR) tablet containing 60 mg of loxoprofen and three different types of

160

extended release (ER) tablets containing 180 mg of loxoprofen each were prepared. Tablet ER-A

161

was designed to present a fast release profile, whereas Tablets ER-B and ER-C were designed to



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present medium and slow release profiles, respectively. For the preparation of IR tablets,

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microcrystalline cellulose was used as the diluent, sodium carboxymethyl cellulose as the

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disintegrant, and polyvinylpyrrolidone K30 as the binder. To prepare ER tablets, three types of

165

HPMC (HPMC 2208-100 cps, HPMC 2208-4000 cps and HPMC 2208-15000 cps) were used as

166

drug

167

polyvinylpyrrolidone K90 as the binder. Magnesium stearate was used as the lubricant for both

168

IR and ER tablets. Compositions of these formulations are listed in Table 1. Tablets containing

169

loxoprofen were manually prepared by the wet granulation method. Initially, loxoprofen was

170

mixed with diluent and disintegrant. The dried mixture was kneaded with respective binder

171

dissolved in ethanol, and the dampened mixture was passed through a 1.4 mm sized mesh. The

172

wet granules were then dried at 60˚C for approximately 1 h. After drying, the granules were

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passed through a 1.4 mm sized mesh again. Magnesium stearate (1%) was added to the dried

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granules and mixed. The resulting lubricated granules were weighed and compressed at 10 kN

175

force by a hydraulic tablet press (Carver, Inc., Wabash, IN, USA) with a round-shaped punch

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(diameter: 11.7 mm). The mean surface areas of the produced tablets were 74.5·π mm2 for IR

177

and 85.6·π mm2 for ER tablets.

release

modifiers,

microcrystalline

cellulose

was

used

as

the

diluent,

and

178

To examine application of the physiologically predictive IVIVC, double-layer (DL) tablets

179

containing loxoprofen 180 mg and comprising both IR and ER layers (drug content ratio between

180

IR and ER layers = 1:2) were also manufactured.

181 182

Table 1. Composition (w/w %) of loxoprofen formulations.


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Substances

IR

ER-A

ER-B

ER-C

Loxoprofen

31.0 (60 mg)

37.5 (180 mg)

37.5 (180 mg)

37.5 (180 mg)

Microcrystalline cellulose

50.0

53.1

20.25

20.25

Na carboxymethyl cellulose

9.0

-

-

-

Polyvinylpyrrolidone K30

9.0

-

-

-

Polyvinylpyrrolidone K90

-

3.75

3.75

3.75

HPMC - 100 cps

-

4.65

32.5

-

HPMC - 4000 cps

-

-

5.0

5.0

HPMC - 15000 cps

-

-

-

32.5

Mg stearate

1.0

1.0

1.0

1.0

Total

100.0

100.0

100.0

100.0

183 184

2.3. Analytical method

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2.3.1. Quantitative analysis of loxoprofen in dissolution medium

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Loxoprofen concentrations in the dissolution medium were determined by HPLC using a

187

Waters Alliance 2695 separation module coupled with Waters 2487 dual absorbance detector

188

(Waters, Milford, MA, USA). Loxoprofen in samples were separated on a Zorbax SB300-C18

189

column (250 × 4.6 mm, i.d., 5 µm, Agilent, Santa Clara, CA, USA) with a Security Guard

190

Cartridge Kit (Phenomenex, Torrance, CA, USA). An isocratic solvent system consisting of

191

methanol with 0.25% (v/v) aqueous triethylamine and acetic acid (60:40 v/v %) was used as the

192

mobile phase at a flow rate of 1 mL/min. The column oven temperature was set at 30°C and the

193

total run time was 5.5 min. The sample injection volume was 10 µL and loxoprofen was detected

194

at 220 nm in injected samples. The loxoprofen working standard solutions were prepared by



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serial dilution of the stock solution in the mobile phase at the concentrations of 1, 2.5, 5, 10, 25,

196

50, 100, 250, and 500 µg/mL.

197

2.3.2. Quantitative analysis of loxoprofen in Beagle dog plasma

198

Loxoprofen concentrations in dog plasma were determined by liquid chromatography-tandem

199

mass spectrometry (LC-MS/MS). Briefly, a portion (50 µL) of the internal standard (IS) solution

200

(ketoprofen 100 ng/mL in methanol) was spiked into 50 µL of the plasma sample and vortexed

201

for 30 sec. Methanol (200 µL) was then added as a precipitation agent and vortexed for 1 min.

202

The mixture was then centrifuged for 10 min at 4,000 × g, and 100 µL of the supernatant was

203

transferred to a polypropylene HPLC vial and mixed with 100 µL of distilled water. The mixture

204

was vortexed for 30 sec and a portion (10 µL) was injected into the LC-MS/MS.

205

Drug analysis was conducted using an Agilent 6430 triple-quadrupole mass spectrometer

206

coupled with an Agilent 1200 HPLC (Agilent Technologies, Santa Clara, CA, USA). Loxoprofen

207

was separated on a Kinetex C18 column (50 × 2.1 mm, i.d., 2.6 µm, Phenomenex, Torrance, CA,

208

USA) with a KrundKatcher ultra column inline filter (Phenomenex, Torrance, CA, USA). An

209

isocratic solvent system consisting of acetonitrile and 0.05% (v/v) aqueous formic acid (30:70

210

v/v %) was used as the mobile phase. The flow rate of the mobile phase was maintained at 0.35

211

mL/min. The column oven temperature was 30°C and the total run time was 4.5 min. The mass

212

spectrometer was operated using electron spray ionization (ESI) in positive ion mode. The mass

213

transition of the precursor/product ions were monitored at 245.1→83.0 for loxoprofen and

214

253.1→209.0 for ketoprofen. Mass spectrometric data was processed using MassHunter

215

Quantitative Analysis software (Agilent Technologies, Santa Clara, CA, USA). The lower limit

216

of quantification was 0.5 ng/mL and the assay was validated using the matrix-matched quality


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217

control (QC) samples (including QC samples at the lower limit of quantification). The intra- and

218

inter-day accuracy and precision ranged from 96.1% to 110.7% and 1.7% to 9.7%, respectively.

219

2.4. In vitro dissolution testing

220

2.4.1. In vitro dissolution in various pH

221

In vitro dissolution testing was performed on ER tablets containing loxoprofen to evaluate the

222

effect of pH on dissolution rate. The paddle method was employed using USP Apparatus II,

223

Distek Dissolution System 2500 coupled with the Evolution Dissolution Sampler 4300 (North

224

Brunswick, NJ, USA). The dissolution media were: 1) 0.1 N HCl (pH 1.2), 2) acetate buffer (pH

225

4.0), 3) phosphate buffer (pH 6.8), and 4) distilled water (900 mL). Medium temperature was

226

maintained at 37 ± 0.5°C, and the paddle stirring speed was fixed at 50 rpm. The samples were

227

collected by an auto-sampler at 0.25, 0.5, 1, 1.5, 2, 3, 5, 6, 8, 10, 12, 15, and 24 h time points. At

228

each time point, the sampled medium volume was replaced by fresh medium. All collected

229

samples were filtered through a 45-µm polyethylene syringe filter (Distek, North Brunswick, NJ,

230

USA). Obtained samples were immediately analyzed using a validated HPLC method.

231

2.4.2. In vitro dissolution with buffer transition

232

In vitro dissolution testing was performed to mimic the time-dependent dissolution rates

233

during tablet passage through the gastrointestinal tract by applying the buffer transition method.

234

Dissolution was initiated using a medium of 0.01 N HCl at a pH 2.0 (750 mL). The dissolution

235

medium pH was then increased from 2.0 to 6.8 via the addition of 250 mL of 0.2 M Na3PO4 at

236

the 1.79 h time point, which was the predicted gastric emptying time based on the in vivo

237

dissolution profile estimated from modeling. The initial pH of the medium (pH 2.0) was based

238

on the reported gastric pH in Beagle dogs

23-24

. The paddle stirring speed was fixed at 100 rpm.



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The samples were collected by an auto-sampler at 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5,

240

3, 3.5, 4 6, 8, 10, 12, 16 and 24 h time points. At each time point, the sampled medium volume

241

was replaced by fresh medium. The collected samples were filtered through a 45-µm

242

polyethylene syringe filter (Distek, North Brunswick, NJ, USA). Obtained samples were

243

immediately analyzed by a validated HPLC method.

244

2.5. In vivo pharmacokinetic study

245

2.5.1. Animal study

246

Beagle dogs (22 male dogs, 14 - 18 months) were purchased from Orient Bio (Seongnam,

247

Korea). All animals received care in compliance with the Guidelines of the Animal Care

248

Committee at Korea Animal Medical Science Institute. Dogs were randomly divided into five

249

groups: IR (n = 6), ER-A, ER-B, ER-C, and DL tablet (n = 4 each), and the study was conducted

250

in parallel. The animals were fasted overnight prior to drug administration. IR tablets containing

251

60 mg of loxoprofen, three different ER tablets containing 180 mg of loxoprofen, a DL tablet

252

containing 180 mg of loxoprofen were administered. All tablets were dosed with 30 mL of water

253

and administered orally. The IR tablet was administered twice (τ = 6 h) to evaluate intra-

254

individual variability. Blood samples (3 mL) were collected via the cephalic vein into a

255

heparinized (5 IU/mL) tube at 0, 0.25, 0.5, 1, 1.5, 2, 3, 4, 6, 6.25, 7, 7.5, 8, 9, 10, 12, 14, 16, and

256

24 h time points following IR tablet administration, and at 0, 0.25, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12,

257

and 24 h time points following ER or DL tablet administration. Food was re-supplied at 9 h after

258

the first loxoprofen dose for ER groups and 3 h after the second dose for IR group. Plasma

259

samples were harvested by centrifugation of collected blood at 4,000 × g at 4ºC for 10 min,

260

immediately frozen, and stored at -20˚C until analysis.


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261

2.5.2. Non-compartmental analysis

262

The pharmacokinetic parameters of loxoprofen were determined by non-compartmental

263

analysis using WinNonlin (version 2.0, Pharsight, NC, USA). These parameters included the

264

apparent clearance (CL/F), terminal half-life (t1/2), apparent volume of distribution (Vd/F), and

265

the area under the plasma concentration–time curve from time zero to the last observation time

266

point (AUC0-24h) and to infinity (AUCinfinity). The maximum plasma concentration (Cmax) and the

267

time to reach Cmax (Tmax) were obtained directly from observational data. Relative bioavailability

268

(BA) of the different ER tablets, and DL tablet was estimated using the ratio of the dose-

269

normalized AUCinf of a specific ER or DL tablet formulation compared to that of the IR tablet.

270

Data was presented as the geometric mean ± standard deviation (SD). Statistical analysis was

271

conducted using SPSS software (version 17.0, IBM Co., NY, USA), and the significance level

272

was set at p < 0.05.

273

2.6. Establishment of an IVIVC model

274

2.6.1. Overall process

275

The overall process of establishing an IVIVC model for loxoprofen ER formulations is

276

summarized in Figure 1.

277



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278 279 280

Figure 1. Overall process of IVIVC model establishment. Step 1: In vitro dissolution tests were

281

performed in various pH to determine the dissolution characteristics of loxoprofen. Step 2: In

282

vivo dissolution profiles were estimated from in vivo plasma concentration vs. time data via

283

population pharmacokinetic modeling. Step 3: Based on the estimated pH transition time

284

obtained from in vivo modeling (Step 2), in vitro dissolution profiles were obtained via biphasic

285

dissolution tests. Step 4: in vivo (Step 2) and in vitro (Step 3) dissolution rate parameters

286

(Vmax(0)) were correlated, and the final IVIVC model was used to predict in vivo drug

287

concentration profiles from in vitro dissolution data.


Page 17 of 58

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288

Step 1: In vitro dissolution profiles of ER tablet were obtained from in vitro dissolution tests

289

under various pH conditions. Strongly pH-dependent dissolution profiles were observed,

290

indicating that loxoprofen dissolution rate in the stomach and in the intestine may be

291

significantly different.

292

Step 2: Following oral administration of different ER formulations, loxoprofen in vivo plasma

293

concentration vs. time profiles were generated and fitted to the POP-PK model in order to

294

estimate in vivo dissolution parameters. Since dissolution has been indicated to be pH dependent,

295

the dissolution of loxoprofen was described using a modified Michaelis-Menten kinetic model

296

with varying Vmax over time. Site-specific absorption, which the in vivo study had indicated to be

297

present, was incorporated in the POP-PK model by allowing the dissolution rates and the

298

absorbed fraction to be changeable over time.

299

Step 3: Based on the in vivo modeling results, in vitro biphasic dissolution profiles of three ER

300

tablets with buffer transition were obtained and modeled. The pH switching time point was based

301

on in vivo estimations of pH transit, i.e., gastric emptying time. The modified Michaelis-Menten

302

kinetic model used in the in vivo dissolution model was also used as a structure for the in vitro

303

biphasic dissolution profiles.

304 305

Step 4: In vitro and in vivo dissolution parameters obtained from population pharmacokinetic modeling were correlated and the predictive IVIVC was established.

306

Loxoprofen pharmacokinetic profiles obtained from a total of 22 dogs were utilized in

307

development of the model. The PK profiles obtained from dogs administered IR tablets

308

(loxoprofen 60 mg per tablet, n=6) and 3 types of ER tablets (loxoprofen 180 mg per tablet, n=4,

309

each) were used to establish the IVIVC. Additional PK profiles obtained from dogs administered



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Page 18 of 58

310

double layer (DL) tablets (IR 60 mg and ER-C 120 mg per tablet, n=4) were used for the

311

application of the population pharmacokinetic IVIVC model.

312

2.6.2. pH-dependent in vitro dissolution kinetics (Step 1)

313

The in vitro dissolution of three different ER tablets was characterized in various media of

314

differing pH. ER tablets presented strongly pH-dependent dissolution profiles, i.e., the

315

dissolution rates of loxoprofen were faster at high pH compared to low pH. Thus, it was

316

indicated that the dissolution rates of loxoprofen in the stomach and intestine may be

317

significantly different.

318 319

2.6.3. Estimation of the in vivo dissolution profile by population pharmacokinetic modeling (Step 2)

320 321

Figure 2. A structural model for the pharmacokinetics of loxoprofen in dogs, incorporating site-

322

dependent dissolution and absorption processes.


Page 19 of 58

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323 324

The structural model for the pharmacokinetics of loxoprofen is depicted in Figure 2. Based on

325

the pH-dependent dissolution profiles obtained in vitro (Step 1), in vivo dissolution kinetics was

326

described using a modified Michaelis-Menten equation. Since the dissolution rates of loxoprofen

327

were dependent on pH, the in vivo maximum dissolution rate (Vmax) was permitted to be

328

changeable to account for drug passage through the gastrointestinal tract. Although the Weibull

329

model is one of the most successful functions in ﬁtting the experimental dissolution curves,

330

Michaelis-Menten allowed more flexibility to incorporate the pH-dependent dissolution

331

characteristics in our model. The differential equation for the amount of undissolved drug was

332

written as follows:

333

dX Solid dt

= −

V max (t) ⋅ X Solid AM 50 + X solid

(Eq.1.1)

334

where Xsolid represents the amount of drug in the tablet compartment, Vmax(t) represents the

335

maximum rate of drug release at time t, and AM50 is the amount of drug at which the dissolution

336

rate is half of the maximal rate of Vmax(t). Vmax(t) was described using the following Hill-type

337

equation, which permitted parameter value change over time in order to reflect the pH gradient

338

from stomach to intestine:

339

V max (t) = V max (0)

 Time 10 1 + E max ⋅  T change50 10 + Time 10

  

(Eq.1.2)

340

where Vmax(0) is the initial maximum rate of drug release and Time represents the accumulated

341

time after drug administration. The maximum change of Vmax over time was characterized by

342

Emax. A positive Emax leads to the simulation of Vmax over time, and a negative Emax value

343

represents the inhibition of Vmax over time. Tchange50 is the time associated with a half-maximal



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Page 20 of 58

344

change of Vmax(t) during gastrointestinal pH increase, i.e., gastric emptying. The Hill coefficient

345

was fixed at 10 to support estimation. The Vmax function over time, Vmax(t), allows the model to

346

account for pH gradient-dependent complex dissolution processes. Since this dissolution model

347

was based on Michaelis-Menten kinetics, Michaelis-Menten parameters were normalized by the

348

administered dose in order to correct the dose influence on the dissolution rate. For IR tablets,

349

Emax was set to 0 because the dissolution rate of IR tablets at pH 1.2 and 6.8 was comparable.

350

The absorption of the dissolved drug was then described by the first-order rate constant ka. To

351

evaluate the intra-individual variability between the 1st and 2nd doses of the IR tablet, two

352

absorption rate constants (ka1 and ka2) were applied. The differential equation for the drug amount

353

in the gut compartment in vivo was described as follows:

354

dX gut V max (t) = F abs ⋅ ⋅ Xsolid − k a ⋅ Xgut dt AM 50 + Xsolid

(Eq.2.1)

355

Based on the assumption that permeability varies widely by intra-gastrointestinal tract location

356

(i.e., upper intestine permeability is high while lower intestine and colon permeability is low),

357

the absorbed fraction of the dissolved drug (Fabs) was allowed to change over time. The

358

differential equation for Fabs is as follows: Timeγ

359

Fabs = 1 −

360

where Time is the accumulated time after drug administration, TWindow50 is the time associated

361

with a half-maximal change of Fabs, and γ is the Hill coefficient. Fabs, therefore, decreases over

362

time, representing the reduced permeability of loxoprofen as it passes through the intestine. Fabs

363

was fixed to 1 for the IR formulation because dissolution reached 80% completion within 0.5 h

(Eq.2.2)

TWindow50γ + Timeγ


Page 21 of 58

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364

and because absorption was very rapid, with the time required to reach peak concentration (Tmax)

365

being 0.4 h.

366

The systemic disposition of loxoprofen was tested using a linear model with a central and two

367

or three peripheral compartments. It was decided that the final model use three systemic

368

disposition compartments based on the objective function value. Loxoprofen in the central

369

compartment (amount, X1) was assumed to be distributed to the shallow and deep peripheral

370

compartments (amounts, X2 and X3, respectively) and eliminated from the central compartment.

371

The differential equations for the amounts of loxoprofen in the central and peripheral

372

compartments were written as follows:

373

dX 1 = k a ⋅ Xgut − CLd shallow ⋅ C 1 + CLd shallow ⋅ C 2 − CLd deep ⋅ C 1 + CLd deep ⋅ C 3 − CL ⋅ C 1 (Eq.3) dt

374

dX 2 = CLd shallow ⋅ C 1 − CLd shallow ⋅ C 2 dt

(Eq.4)

375

dX 3 = CLd deep ⋅ C 1 − CLd deep ⋅ C 3 dt

(Eq.5)

376

C1, C2, and C3 represent loxoprofen concentrations in their respective compartments, and

377

CLdshallow and CLddeep represent distribution clearances to the shallow and deep peripheral

378

compartments.

379

The plasma concentration-time data obtained after oral administration of IR and ER tablets

380

were simultaneously fitted to the POP-PK model, allowing the estimation of the in vivo

381

dissolution profiles of different ER tablets. The POP-PK model fitting was conducted using the

382

Monte Carlo Parametric Expectation Maximization (MC-PEM) algorithm in parallelized S-

383

ADAPT (version 1.57). An importance sampling MC-PEM method (pmethod=4 in S-ADAPT)

384

was used for population pharmacokinetic parameter estimation. Relative standard errors 21 ACS Paragon Plus Environment


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Page 22 of 58

385

describing the uncertainty of each model parameter were calculated from a formula implemented

386

in S-ADAPT (poperr type=8). Between-subject variability (BSV) was estimated using an

387

exponential parameter variability model. Models were assessed with a full, block diagonal, or

388

major diagonal variance-covariance matrix. The goodness-of-fit for population modeling was

389

assessed using the objective function (-1 log-likelihood), plausibility of parameter estimates,

390

visual inspection of the observed and fitted concentrations, and standard diagnostic plots. The

391

predictive performance of the population model was evaluated by calculating visual predictive

392

checks. Simulations were performed using Berkeley Madonna (version 8.3.18).

393

2.6.4. In vitro biphasic dissolution kinetics (Step 3)

394

In vitro dissolution profiles for IVIVC were obtained by switching the medium pH at time

395

point based on the in vivo estimate of gastric emptying time, i.e., Tchange50 (Step 2). In vitro

396

biphasic dissolution was then modeled using modified Michaelis-Menten kinetics with varying

397

Vmax in Step 2 (Eq. 1.1 and 1.2) as a structural model. The in vitro dissolution profiles of

398

different ER tablets were simultaneously fitted to the kinetic model using the Monte Carlo

399

Parametric Expectation Maximization (MC-PEM) algorithm in parallelized S-ADAPT (version

400

1.57), facilitating the estimation of the in vitro dissolution parameters. The same Emax and AM50

401

were used for each of the different ER tablets. The mean value of Tchange50 was fixed at 1.79 h,

402

which was obtained from the estimation of the in vivo dissolution profile, while between subject

403

variability (BSV) for Tchange50 was estimated.

404

2.6.5. Correlation of in vitro and in vivo dissolution (Step 4)

405

Estimated values of the initial maximum rate of drug release (Vmax(0)) obtained from the in

406

vivo pharmacokinetics model [Vmax(0)in vivo (Step 2)] and the in vitro biphasic dissolution test


Page 23 of 58

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407

[Vmax(0)in vitro (Step 3)] for the three ER tablets were correlated via regression analysis using

408

SigmaPlot (version 12.0, Systat Software, Inc., CA, USA). The equation for correlation was then

409

applied to the previously developed population pharmacokinetic model to convert in vitro

410

dissolution profiles to in vivo ones.

411

2.7. Validation of the IVIVC model

412

The developed predictive IVIVC was validated internally using the data of ER-A, ER-B, and

413

ER-C tablets containing 180 mg of loxoprofen. The absolute percentage of prediction error

414

(%PE) was calculated as: Predicted − Observed

415

%PE =

416

According to the FDA guideline for IVIVC 6, %PE values should not exceed 15% for each

417

respective formulation, and the average %PE value of all studied formulations should be less

418

than 10%.

Observed

× 100

(Eq.6)

419

The predicted mean Cmax and AUC0-24h were calculated from individual plasma concentration-

420

time profiles obtained after 300 Monte Carlo simulations using Berkeley Madonna (version

421

8.3.18). The predictive performance was evaluated by comparing the predicted and observed

422

values.

423

For the application of the established predictive IVIVC, the plasma concentration-time profiles

424

of double layer (DL) tablets, consisting of 60 mg and 120 mg of the IR and ER-C formulations

425

respectively, were predicted. The loxoprofen present in the IR and ER-C tablet formulations was

426

introduced separately into the gut compartment with corresponding dissolution kinetics in the

427

model, and the plasma loxoprofen concentrations were predicted. Cmax and AUC0-24h were then



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Page 24 of 58

428

calculated from the predicted plasma concentrations and compared to the observed data.

429

Predictive performance was also evaluated by Monte Carlo simulations.

430

3. RESULTS

431

3.1. In vitro dissolution of loxoprofen from ER tablets

432

The in vitro dissolution profiles of loxoprofen from ER-A, ER-B, and ER-C tablets in different

433

media are shown in Figure 3. As the pH of the medium was increased from increased from 0.1 N

434

HCl to distilled water, the dissolution rate of each ER formulation significantly increased.

435

Among all the tested media, loxoprofen release was the fastest in distilled water. ER-A tablet

436

dissolution in distilled water was completed within 4 h, while dissolution of ER-B and ER-C

437

tablets was completed in 12 and 24 h, respectively. However, in 0.1 N HCl, drug release from all

438

three ER tablets was not completed by 24 h. For the IR tablet, over 80% of the drug was released

439

within 30 min regardless of the medium pH (data not shown).


Page 25 of 58

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440 441

Figure 3. In vitro release profiles of loxoprofen for (A) ER-A, (B) ER-B, and (C) ER-C tablets

442

in various pH conditions. Closed circles, triangles, squares, and diamonds represent 0.1 N HCl

443

(pH 1.2), acetate buffer (pH 4.0), phosphate buffer (pH 6.8), and distilled water (pH 7.0),

444

respectively. Data were presented as mean ± SD (n=3, each). 25 ACS Paragon Plus Environment


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Page 26 of 58

445

3.2. In vivo pharmacokinetics of loxoprofen

446

Following ER tablet administration, secondary peaks or shoulders were observed in many of

447

the individual plasma concentration-time profiles between 1.5 to 8 h postdose (Supporting

448

Information, SI Figure S1). However, since the extent as well as the time of the secondary peaks

449

were variable depending on the subject, the secondary peaks are less pronounced in the mean

450

plasma concentration vs. time profiles (Figure 4). In contrast, there were no double peaks in

451

plasma concentration-time profiles following IR tablet administration.

452 453

Figure 4. Average plasma concentration vs. time profiles of loxoprofen following two oral

454

administrations of the IR tablet (loxoprofen 60 mg, n=6, open circles), or a single oral

455

administration of either an ER-A (closed circles), ER-B (closed triangles), or ER-C tablet (closed

456

squares) (loxoprofen 180 mg, n=4, each) in Beagle dogs. Data were presented as mean ± SD. 26 ACS Paragon Plus Environment

Page 27 of 58

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457

Figure 4 shows the mean plasma concentration-time profiles of loxoprofen obtained after oral

458

administration of IR tablets (loxoprofen 60 mg, twice, τ = 6 h) and three ER tablet types

459

(loxoprofen 180 mg per tablet, once) to Beagle dogs. The non-compartmental pharmacokinetic

460

parameters of loxoprofen are summarized in Table 2. Following the oral administration of IR

461

tablets, loxoprofen was rapidly absorbed, with peak concentration (Cmax) being observed within

462

30 min. Compared to the IR formulation, ER formulations presented longer Tmax and lower Cmax

463

values. This increase in Tmax and decrease in Cmax were most prominent for ER-C tablets,

464

followed by ER-B and ER-A, which was consistent with the in vitro dissolution rate data. After

465

reaching Cmax, plasma concentrations of loxoprofen declined with elimination half-lives (t1/2)

466

ranging from 4.1 ± 1.0 to 5.6 ± 1.2 h. The mean apparent volume of distribution (Vz/F) ranged

467

from 9.8 ± 4.6 to 17.7 ± 7.5 L. There were no significant differences in t1/2 and Vz/F among the

468

different formulations.

469

The relative bioavailability and apparent systemic clearance (CL/F) were comparable between

470

the IR and ER-A (fast release) formulations, whereas the relative bioavailability reduced in both

471

ER-B and ER-C as the dissolution rate was decreased.

472

The non-compartmental pharmacokinetic parameters of loxoprofen following DL formulation

473

containing loxoprofen 180 mg (IR: ER-C = 1:2) administration are also presented in Table 2.

474

While the Cmax of DL tablet is comparable to IR tablet, the AUC values were lower than that of

475

IR tablet 60 mg with the relative bioavailability of 90.3%.

476 477

Table 2. Non-compartmental pharmacokinetic parameters of loxoprofen after IR, ER, and DL

478

tablet administration in Beagle dogs. Data represent the geometric mean ± SD.



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479

Page 28 of 58

Parameters

IR (n =6)

ER-A (n = 4)

ER-B (n = 4)

ER-C (n = 4)

DL (n = 4)

Dose (mg)

60 mg×2 (BID)

180

180

180

180

t1/2 (h)

4.5 ± 1.1

5.5 ± 1.3

5.5 ± 3.0

5.6 ± 1.2

5.6 ± 1.0

Tmax (h)

0.4 ± 0.1a

0.9 ± 0.4

1.7 ± 0.9

2.6 ± 1.3

0.9 ± 1.3

Cmax (µg/mL)

17.7 ± 4.2

29.8 ± 6.5

17.2 ± 3.3

12.1 ± 4.4

18.8 ± 4.4

AUC0-24h (µgh/mL)

65.3 ± 16.3

96.9 ± 20.5

89.3 ± 7.6

78.1 ± 20.3

87.9 ± 20.0

AUCinfinity (µgh/mL)

66.6 ± 16.0

99.1 ± 20.9

92.8 ± 7.9

81.9 ± 20.1

90.1 ± 20.0

Vz/F (L)

11.6 ± 4.6

14.4 ± 5.4

15.5 ± 7.9

17.7 ± 7.5

16.1 ± 7.5

CL/F (mL/min)

30.0 ± 6.7

30.3 ± 6.6

32.3 ± 2.8

36.6 ± 9.8

33.3 ± 9.0

Relative BA (%)

-

99.2 ± 21.0

92.9 ± 7.9

82.0 ± 20.2

90.3 ± 20.0

a

The second dose was assumed to be administered at 0 h.

480 481

3.3. Establishment of IVIVC model

482

3.3.1. Estimation of the in vivo dissolution profile by population pharmacokinetic modeling

483

To describe the plasma concentration profiles of loxoprofen and estimate in vivo dissolution

484

from plasma concentration profiles, the data obtained for IR and ER tablets were fitted

485

simultaneously on the POP-PK model. To evaluate the predictive performance of the POP-PK

486

model, Monte Carlo simulations were carried out. The full plasma concentration-time profiles

487

and the plots of the observed vs. predicted values (SI Figure S2) indicated that the POP-PK

488

model showed great predictability for the ER-A, ER-B, and ER-C formulations. The normalized

489

prediction distribution errors (NDPEs) of the model are shown in SI Figure S3. Overall, NDPE

490

values presented a normal distribution with a mean of zero and with 95% of markers within the

491

acceptable range (-2 to 2), indicating a good predictive performance by the final POP-PK model.

492

The obtained final population pharmacokinetic parameter estimates for loxoprofen are presented

493

in Table 3.


Page 29 of 58

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494


Table 3. Population pharmacokinetic parameter estimates of loxoprofen.

Parameter

Symbol

Unit

Volume of distribution of the central compartment

V1

L

Population mean (Between subject variability) 0.87 (0.457)

Volume of distribution of the shallow peripheral compartment

V2

L

21.5 (0.286)

Volume of distribution of the deep peripheral compartment

V3

L

3.49 (0.161)

Systemic clearance

CL

L/h

1.69 (0.15)

Distribution clearance to the shallow peripheral compartment

CLd

L/h

0.459 (0.439)

Distribution clearance to the deep peripheral compartment

CLd2

L/h

3.84 (0.183)

Rate constant for absorption from gut

ka

1/h

10.9 (1.38)

Rate constant for absorption from gut for the 2 dose

ka2

1/h

7.77 (0.61)

Time for half maximal bioavailability

TWindow50

h

8.5 (0.242)

Hill coefficient

γ

-

2.44 (0.281)

Time point at which Vmax in vivo changed by 50%

Tchange50 in vivo

h

1.79 (0.53)

Maximum fold change in Vmax in vivo over time

Emax in vivo

-

0.51 (0.289)

Amount of loxoprofen in the solid compartment at 0.5 Vmax in vivo

AM50 in vivo/dose

-

23.1 (0.046)

Initial Vmax in vivo for IR tablets

Vmax(0)IR in vivo/dose

1/h

62.2 (0.263)

Initial Vmax in vivo for ER-A tablets

V max(0)ER-A in vivo/dose

1/h

30.2 (0.435)

1/h

8.73 (0.276)

1/h

4.91 (0.387)

h

0.11 (0.455)

nd

Initial Vmax in vivo for ER-B tablets Initial Vmax in vivo for ER-C tablets

V max(0)ER-B in vivo/dose

Lag time for ER dissolution

V max(0)ER-C in vivo/dose TLag

SD of additive residual error

SDin

ng/mL

0.00216 (0)

Proportional residual error

SDsl

-

0.239 (0)

495 29 ACS Paragon Plus Environment


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Page 30 of 58

496

In this model, in vivo dissolution and systemic absorption were separately described. The

497

dissolution process was described using modified Michaelis-Menten kinetics consisting of four

498

dissolution rate parameters. Vmax(0)in vivo was estimated for IR, ER-A, ER-B, and ER-C tablets

499

separately, while the values of the AM50 in vivo, Emax

500

tablets. The present POP-PK model provided reasonable estimates of these dissolution

501

parameters and enabled estimation of in vivo dissolution profiles from the in vivo plasma

502

concentration vs. time data. The dose-normalized Vmax(0)in vivo was 30.2 h-1 for ER-A, 8.73 h-1 for

503

ER-B, and 4.91 h-1 for ER-C. The Vmax in vivo for each formulation was then predicted to increase

504

over time owing to the increase in pH from stomach to intestine (SI Figure S4).

in vivo,

and Tchange50 were shared for all ER

505

The model-predicted Fabs over time is shown with the estimated in vivo dissolution profiles of

506

each ER formulation in Figure 5. Since both in vivo dissolution rates and the absorbed fraction

507

can affect the extent of absorption, Fabs was multiplied by the in vivo dissolution rate to describe

508

the transfer of the drug from the tablet compartment to the gut compartment, whereas the

509

absorption rate (ka) was set as a constant. The predicted mean Fabs was greater than 0.9 until 3.4 h

510

post-drug administration, at which point a continuous decrease was present until Fabs reached 0.5

511

by 8.56 h. In vivo dissolution in the gastrointestinal tract for ER-A was completed within 2 h, a

512

time point when the predicted Fabs was higher than 0.97, which would facilitate the complete

513

absorption of the dissolved drug from ER-A. Thus, the bioavailability of ER-A was comparable

514

to that of the IR formulation. However, as the dissolution rate decreased, absorption of any

515

dissolved drug was affected by the decrease in Fabs. As such, the bioavailabilities of ER-B and

516

ER-C were lower.


Page 31 of 58

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517 518

Figure 5. Estimated in vivo dissolution profiles of ER-A (thin line), ER-B (dot and dashed line),

519

and ER-C (dashed line), as well as the decrease of drug absorption fraction (thick line) after

520

dissolution (Fabs) along the gastrointestinal tract, predicted by the population pharmacokinetic

521

model.

522 523

3.3.2. In vitro biphasic dissolution kinetics

524

Since the dissolution of loxoprofen ER formulations were significantly pH-dependent, in vitro

525

dissolution profiles needed to be determined by considering the pH changes in the

526

gastrointestinal tract. Thus, in vitro release profiles of loxoprofen from ER tablets for IVIVC

527

modeling were obtained by altering buffer pH to mimic the transition from stomach to intestine.

528

Since the gastric pH is relatively higher in dogs than in humans

529

using an acidic medium at pH 2.0. The buffer pH was then increased to 6.8 at 1.79 h, which was

23, 25

, dissolution was initiated



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Page 32 of 58

530

the estimated Tchange50 in vivo. The average gastric emptying time in the fasting dog has been

531

reported 71 – 100 min 23-24, 26. The dissolution profiles of ER-A, ER-B, and ER-C in the biphasic

532

medium are shown in Figure 6A. The dissolution rate decreased as HPMC viscosity increased

533

from ER-A to ER-C in ER tablets. By the 1.79 h time point, 59.8, 28.1 and 21.2% of loxoprofen

534

had been dissolved from ER-A, ER-B, and ER-C tablets respectively. After changing the buffer

535

pH to 6.8, the dissolution rates of all three formulations were accelerated and 100% dissolution

536

was achieved within 3.5 (ER-A), 10 (ER-B), and 16 h (ER-C) after dissolution test initiation.

537

3.3.3. In vitro dissolution model

538

The in vitro release profiles obtained by the buffer transition method (Figure 6) were then

539

fitted to a modified Michaelis-Menten kinetic model (Eq. 1.1). Changes to the maximum drug

540

release rate (Vmax) parameter over time accounted for pH dependent dissolution (Eq. 1.2). The

541

developed in vitro dissolution model adequately described overall drug release profiles, as

542

indicated by plots of the observed and fitted values (SI Figure S5). The final estimated in vitro

543

dissolution parameters of loxoprofen are presented in Table 4. The mean Tchange50 of 1.79 h was

544

adopted from in vivo population pharmacokinetic modeling. The Michaelis-Menten constants

545

AM50_in vitro, reflecting the mechanism of drug release from the ER formulation, and Emax in vitro,

546

representing the extent of Vmax acceleration, were assumed to be same for all tested ER

547

formulations. Conversely, the estimated initial maximum dissolution rate (Vmax(0)in vitro) for ER-

548

A, ER-B, and ER-C was 6.18, 2.41, and 1.83 respectively.


Page 33 of 58

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549 550

Figure 6. Comparison between observed in vitro dissolution profiles and in vivo dissolution

551

profiles estimated from the in vivo POP-PK model (A) or converted from the final POP-PK-

552

IVIVC model (B). Correlation between observed and converted in vitro release data by using

553

linear regression for ER-A, ER-B, and ER-C tablets (C). The closed circles, triangles, and

554

squares represent the observed data for ER-A, ER-B, and ER-C, respectively, and the lines

555

represent the predicted profiles.



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

556

Page 34 of 58

Table 4. In vitro dissolution parameter estimates of loxoprofen.

Parameter

Symbol

Unit

Time point at which Vmax in vitro changed by 50%

Tchange50 in vitro

h

Population mean (Between subject variability) 1.79 (0.0312)

Maximum fold change in Vmax in vitro over time Amount of loxoprofen in the solid compartment at 0.5 Vmax in

Emax in vitro

-

0.761 (0.289)

AM50 in vitro/dose

-

11.9 (0.046)

Initial Vmax in vitro for ER-A tablets

Vmax(0)ER-A in vitro/dose

1/h

6.18 (0.0683)

Initial Vmax in vitro for ER-B tablets

Vmax(0)ER-B in vitro/dose

1/h

2.41 (0.0756)

Initial Vmax in vitro for ER-C tablets

Vmax(0)ER-C in vitro/dose

1/h

1.83 (0.0609)

SD of additive residual error

SDin

ng/mL

1.49 (0)

Proportional residual error

SDsl

-

0.00159 (0)

vitro

557


Page 35 of 58

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558

3.3.4. Correlation of in vitro and in vivo dissolution

559

Comparing the in vitro and in vivo dissolution profiles, it was found that the in vivo dissolution

560

rates estimated using the in vivo POP-PK model were significantly higher than experimentally

561

obtained in vitro dissolution rates (Figure 6A). Linear regression was found to be the best model

562

for correlating in vivo and in vitro Vmax(0) values (SI Figure S6). The in vitro Vmax(0) could be

563

converted to the in vivo Vmax(0) by the following equation:

564

Vmax(0) in vivo = 5.77 ⋅ Vmax(0) in vitro − 5.42

565

The correlation coefficient (r2) was 0.998, which suggested that the in vitro and in vivo overall

566

dissolution rates were well correlated. This equation facilitated conversion of the in vivo

567

dissolution profiles obtained from the POP-PK model to in vitro dissolution profiles and vice

568

versa. Finally, the converted in vitro dissolution profiles from in vivo PK data using Eq. 7 were

569

in great agreement with the observed in vitro dissolution profiles (Figures 6B and 6C), indicating

570

the establishment of a level A IVIVC. The established level A IVIVC, with the in vitro

571

dissolution kinetics of ER-A, ER-B, and ER-C formulations, was able to predict complete in vivo

572

plasma concentration vs. time data following oral administration of ER tablets (Figure 7).

(Eq.7)



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Page 36 of 58

573 574

Figure 7. Visual predictive check plots for (A) ER-A, (B) ER-B, and (C) ER-C for the validation

575

of the final POP-PK IVIVC model using in vitro dissolution profiles as input data. The symbols

576

represent the observed data following oral administration of ER tablets (n=4, each) and the lines


Page 37 of 58

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577

represent the predicted profiles from in vitro dissolution data using the final POP-PK IVIVC

578

model.

579

3.3.5. Validation and comparative evaluation of the physiologically relevant POP-PK IVIVC

580

The established POP-PK IVIVC model was validated by Monte Carlo simulations. To evaluate

581

the effects of incorporating physiologically relevant factors into the present IVIVC modeling

582

approach, the predictabilities of the following three POP-PK IVIVC models were compared: a

583

model without any physiologically relevant factors (Model 1), a model with pH-dependent

584

dissolution (Model 2), and a model with both pH-dependent dissolution and site-dependent

585

absorption (Model 3). The observed and predicted Cmax and AUC0-24h values, and their respective

586

absolute percentages of prediction error (%PE), are listed in Table 5.

587

The %PE values for Cmax for the IVIVC models did not meet FDA guideline criteria, with the

588

exception of the model incorporating both physiologically relevant dissolution and absorption

589

(Model 3). As shown in Table 5, the incorporation of pH-dependent dissolution in Model 2

590

greatly improved Cmax prediction compared to Model 1, indicating that pH-dependent dissolution

591

kinetics was an important factor in the prediction of Cmax. The inclusion of site-dependent

592

absorption also improved overall predictability of Cmax and AUC. The final model (Model 3),

593

which included both pH-dependent dissolution and site-dependent absorption, showed the best

594

predictability among all the tested models. Overall, the inclusion of site-dependent dissolution

595

and absorption provided better curve fitting in PK modeling and improved the general

596

predictability of the IVIVC model, satisfying the FDA guidelines.

597



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Page 38 of 58

598

Table 5. Absolute percentages of the prediction error for Cmax and AUC0-24h of loxoprofen from three different IVIVC modeling

599

approaches.

Cmax Model

Model 1 (POP-PK IVIVC model)

Formulation

AUC0-24h

Observed* (µg/mL)

Predicted (µg/mL)

Prediction error (%)

Observed* (µgh/mL)

Predicted (µgh/mL)

Prediction error (%)

ER-A

29.82 (21.7)

22.92

23.1

96.95 (21.2)

84.39

12.9

ER-B

17.17 (19.1)

15.07

12.2

89.35 (8.6)

83.80

6.2

ER-C

12.06 (36.7)

9.32

22.7

78.07 (26.0)

82.72

6.0

Mean Model 2 (POP-PK IVIVC model incorporating pH dependent dissolution) Model 3 (POP-PK IVIVC model incorporating pHdependent dissolution and site-dependent absorption)

600

*

19.4

8.4

ER-A

29.82 (21.7)

25.16

15.6

96.95 (21.2)

84.17

13.2

ER-B

17.17 (19.1)

16.29

5.1

89.35 (8.6)

86.38

3.3

ER-C

12.06 (36.7)

13.85

14.8

78.07 (26.0)

84.07

7.7

Mean

11.8

8.1

ER-A

29.82 (21.7)

27.95

6.3

96.95 (21.2)

88.86

8.3

ER-B

17.17 (19.1)

17.32

0.9

89.35 (8.6)

83.56

6.5

ER-C

12.06 (36.7)

12.66

4.9

78.07 (26.0)

75.14

3.8

Mean

4.0

6.2

Data are presented as the mean (CV%) for the observed values.

601


Page 39 of 58

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602

3.4. Application of the predictive IVIVC model to DL tablets

603

As an application of the predictive IVIVC model, the final POP-PK IVIVC model was used to

604

predict the plasma concentration time profiles of loxoprofen after oral administration to dogs of

605

DL tablets consisting of 60 mg IR and 120 mg ER-C tablets. The observed and predicted Cmax

606

and AUC0-24h values obtained after administration of DL tablets and their respective absolute

607

percentages of prediction error (%PE) are listed in Table 6. The %PE was 8.0% for Cmax and

608

6.9% for AUC0-24h. Visual predictive checks for all the plasma concentration-time profiles also

609

showed adequate IVIVC model predictability for DL tablets (Figure 8).

610 611

Figure 8. Visual predictive check plots for the double-layered formulation using in vitro

612

dissolution profiles as input data. The symbols represent the observed data following oral

613

administration of DL tablets (n=4) and the lines represent the predicted profiles from in vitro

614

dissolution data using the final POP-PK IVIVC model.

615 39 ACS Paragon Plus Environment


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Page 40 of 58

616

Table 6. Observed and predicted Cmax and AUC values with their respective absolute

617

percentages of prediction error (%PE).

618

*

Parameter

Observed*

Predicted

PE (%)

Cmax (µg/mL)

18.79 (28.8)

17.29

8.0%

AUC0-24h (µgh/mL)

87.93 (8.6)

81.87

6.9%

Data are presented as the mean (CV%) for the observed values.

619 620

4. DISCUSSION

621

Oral absorption behavior is often very complex owing to various factors such as pH and site-

622

specific physiological characteristics in the gastrointestinal tract. Establishing a level A IVIVC

623

has been challenged by these factors. In the present study, a novel physiologically relevant POP-

624

PK IVIVC model for loxoprofen was developed and validated; the model exhibits pH-dependent

625

dissolution kinetics and regional absorption windows.

626

In vitro dissolution for loxoprofen ER tablet was determined by two types of methods, i.e.,

627

fixed dissolution media method and switched dissolution media method. Loxoprofen is known to

628

be BCS class I drug 27-29 and our preliminary data showed that loxoprofen was readily dissolved

629

in both simulated gastric (pH 1.2, solubility = 11.82 mg/mL) and intestinal fluid (pH 6.8,

630

solubility = 473.16 mg/mL). However, fixed pH dissolution data suggested that the dissolution

631

of loxoprofen formulations was strongly dependent on pH and the dissolution rate from ER

632

formulations would significantly increase at intestinal pH compared to that observed at stomach

633

pH (Figure 3). To establish optimal IVIVC, in vitro dissolution test reflecting in vivo dissolution

634

properties is desired 30. Thus, the additional in vitro dissolution test in which the buffer pH was 40 ACS Paragon Plus Environment

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635

switched from 2.0 to 6.8 during the test to mimic the transition from stomach to intestine was

636

conducted. The pH-dependent in vitro dissolution kinetics was also incorporated with POP-PK

637

IVIVC model and the buffer changing time was informed by model estimated gastric emptying

638

time. The final correlation was made between experimentally obtained in vitro dissolution profile

639

and model estimated in vivo dissolution profile using linear scaling factor.

640

In addition, in vivo pharmacokinetic data suggested that loxoprofen absorption was site-

641

dependent. The secondary peaks or shoulders in the plasma concentration-time profiles observed

642

after ER tablet administrations, which were not observed after IR formulations indicates the

643

presence of an effective absorption site in the intestine. Typically, the multiple-peak

644

phenomenon is known to be resulted from the presence of either enterohepatic recirculation or

645

two different sites of absorption

646

administration in the present study, they are less likely to indicate enterohepatic recirculation,

647

which occurs after systemic absorption regardless of formulation. As the dissolution rate of

648

loxoprofen ER tablets increases under intestinal pH compared to that at the stomach pH,

649

secondary absorption may happen in the intestine as the drug passes through the gastrointestinal

650

tract resulting in the secondary peaks and shoulders. The reduced relative bioavailability as the

651

dissolution rate was decreased (Table 2) also indicates the presence of the effective absorption

652

site and/or incomplete in vivo release. It is possible that the slowly released loxoprofen from ER

653

tablets bypass the main absorption window, resulting in less overall absorption, which is a

654

frequent problem during the development of ER formulations.

31

. Since double peaks were not observed after IR formulation

655

The present model described in vivo dissolution and systemic absorption separately, and

656

allowed inclusion of various physiological factors into the overall absorption process.

657

Conventional IVIVC approaches such as the Wagner-Nelson

8

and Loo-Riegelman 9, or 41

ACS Paragon Plus Environment


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10

Page 42 of 58

658

numerical deconvolution

659

dissolution, which is not the case for loxoprofen. Although loxoprofen is known to BCS class I

660

drug

661

windows.

27-29

methods assume that the drug absorption is complete after in vivo

, loxoprofen exhibits pH-dependent dissolution kinetics and regional absorption

662

Although conventional IVIVC approaches can be also applied for BCS class II drug, they may

663

have limitation on predicting sudden changes of dissolution and absorption by the physiological

664

factors. For example, they cannot predict the changes in dissolution when solubility of the BCS

665

class II drug is increased with the increased bile release stimulated by the food intake. However,

666

the food effect on the solubility or dissolution of low-solubility BCS class II drug could be

667

predicted by applying the present pH-dependent biphasic dissolution kinetics. Moreover, the

668

present approach has the flexibility to incorporate various factors affecting the absorption

669

processes and may be extended to IVIVC to BCS class IV drugs which have permeability

670

limitations in addition to poor solubility.

671

Recently, mechanistic/physiologically relevant absorption based IVIVC model has been

672

increasingly utilized as an alternative to conventional IVIVC approaches and demonstrated its

673

potential in various studies. These models attempt to incorporate different physiological factors

674

affecting drug absorption including drug release, GI transition, permeation, metabolism, and

675

elimination and provide more realistic predictions of in vivo drug performance. For example,

676

mechanistic/physiologically relevant absorption model was successfully applied to establish

677

IVIVC for weakly basic drugs exhibiting pH-dependent dissolution and supersaturation in the GI

678

tract

679

Advanced Compartmental Absorption and Transit (ACAT) model in GastroPlus®

680

SimcypTM 22.

17-18

. The different absorption depending on the GI segment can also be described by using 19-21

or


Page 43 of 58

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681

The present POP-PK IVIVC model incorporated the complex physiological factors in

682

loxoprofen absorption, i.e., pH-dependent dissolution and site-specific absorption separately. The

683

pH-dependent biphasic dissolution kinetics was described using modified Michaelis-Menten

684

kinetics with increasing Vmax, over time due to the pH change from stomach to intestine (SI

685

Figure S4). The site-specific absorption was modeled using a changeable absorbed fraction

686

parameter (Fabs) which was allowed to gradually decrease over time along the gastrointestinal

687

migration (Figure 5). Since both in vivo dissolution rates and the absorbed fraction can affect the

688

absorption, the product of Fabs and the % of in vivo dissolution at specific time represents the

689

total systemic absorption at specific time. According to the model estimation, absorption of any

690

dissolved drug was affected by the decrease in Fabs as the dissolution rate decreased, leading to

691

the lower bioavailabilities of medium (ER-B) and slow (ER-C) release formulations. These

692

predictions were in good agreement with the observed data (Table 2).

693

Furthermore, the present model also applied population pharmacokinetic modeling approach

694

which can analyze inter- and intra-individual variability. Integrating such variability allows

695

IVIVC model to utilize information from all the individual data and in turn make more realistic

696

predictions which reflect subjects’ and occasional variability. In the population approach, for

697

example, the average Cmax was obtained from individually predicted Cmax values at different

698

Tmax, which may be underestimated by using non-population approaches based on the averaged

699

data.

700

Inclusion of these physiologically relevant factors into the POP-PK model greatly improved

701

overall predictability of Cmax and AUC compared to the model without any physiologically

702

relevant factors (Table 5), satisfying the FDA guideline. According to the FDA guidelines, the



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Page 44 of 58

703

predictability of IVIVC is considered acceptable when prediction errors (%PE) for Cmax and

704

AUC are below 15% for each formulation, and mean %PE values are below 10% for validation 6.

705

The POP-PK IVIVC approach was successfully applied to predict in vivo pharmacokinetics of

706

loxoprofen following oral administration of DL tablets. The DL formulation containing

707

loxoprofen 180 mg (IR: ER-C = 1:2) showed relative bioavailability of 90.3% compared to the

708

IR tablet, which may be because it contains 120 mg of ER-C part with the low relative

709

bioavailability. Since dissolution is slow for ER tablets, the therapeutic onset time of ER

710

formulations may be delayed compared to the IR formulation. To achieve the quick therapeutic

711

onset time of ER tablets, a DL tablet which combines IR and ER tablets could be designed.

712

Onset time and duration of therapeutic effect can be manipulated by altering the IR to ER tablet

713

content ratio. Thus, identification of the proper combination ratio is necessary to achieve optimal

714

therapeutic effects. These results suggested that the proposed POP-PK IVIVC modeling

715

approach in the present study can be applied not only to determine dissolution rate, but also to

716

determine the optimal combination ratio of multiple formulations for the optimization of

717

pharmacokinetic characteristics.

718

In summary, a level A IVIVC was established using POP-PK modeling that accounted for pH-

719

dependent dissolution and site-specific absorption by applying dissolution rate parameters

720

changing over time. Excellent correlations were observed between in vitro and in vivo

721

dissolution profiles. The proposed model was successfully applied to predict the in vivo

722

pharmacokinetic profile of a loxoprofen DL tablet by using in vitro dissolution data. This new

723

approach holds great promise for the establishment of IVIVCs for drugs with poor predictability

724

by conventional IVIVC methods due to complex absorption kinetics.


Page 45 of 58

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725

ACKNOWLEDGMENT

726

This work was supported by the National Research Foundation of Korea (NRF) Grant no.

727

2015R1D1A1A09059248 and 2014R1A1A2053333.

728 729 730

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731

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23. Sagawa, K.; Li, F.; Liese, R.; Sutton, S. C., Fed and fasted gastric pH and gastric

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24. Lui, C. Y.; Amidon, G. L.; Berardi, R. R.; Fleisher, D.; Youngberg, C.; Dressman, J. B.,

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804

27. Jung, S. J.; Choi, S. O.; Um, S. Y.; Kim, J. I.; Choo, H. Y. P.; Choi, S. Y.; Chung, S. Y.,

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relationship. Journal of Pharmaceutical and Biomedical Analysis 2006, 41 (2), 469-475.

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28. Singh, J.; Walia, M.; Harikumar, S. L., SOLUBILITY ENHANCEMENT BY SOLID DISPERSION METHOD: A REVIEW. 2013; Vol. 3. 29. Maurya, D.; Belgamwar, V.; Tekade, A., Microwave induced solubility enhancement of poorly water soluble atorvastatin calcium. J Pharm Pharmacol 2010, 62 (11), 1599-606. 30. Mudie, D. M.; Amidon, G. L.; Amidon, G. E., Physiological parameters for oral delivery and in vitro testing. Mol Pharm 2010, 7 (5), 1388-405.

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Graphical Abstract Graphical Abstract 209x61mm (300 x 300 DPI)


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Figure 1. Overall process of IVIVC model establishment. Step 1: In vitro dissolution tests were performed in various pH to determine the dissolution characteristics of loxoprofen. Step 2: In vivo dissolution profiles were estimated from in vivo plasma concentration vs. time data via population pharmacokinetic modeling. Step 3: Based on the estimated pH transition time obtained from in vivo modeling (Step 2), in vitro dissolution profiles were obtained via biphasic dissolution tests. Step 4: in vivo (Step 2) and in vitro (Step 3) dissolution rate parameters (Vmax(0)) were correlated, and the final IVIVC model was used to predict in vivo drug concentration profiles from in vitro dissolution data. Figure 1 104x148mm (300 x 300 DPI)



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Figure 2. A structural model for the pharmacokinetics of loxoprofen in dogs, incorporating site-dependent dissolution and absorption processes. Figure 2 150x93mm (300 x 300 DPI)


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Figure 3. In vitro release profiles of loxoprofen for (A) ER-A, (B) ER-B, and (C) ER-C tablets in various pH conditions. Closed circles, triangles, squares, and diamonds represent 0.1 N HCl (pH 1.2), acetate buffer (pH 4.0), phosphate buffer (pH 6.8), and distilled water (pH 7.0), respectively. Data were presented as mean ± SD (n=3, each). Figure 3 90x182mm (300 x 300 DPI)



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Figure 4. Average plasma concentration vs. time profiles of loxoprofen following two oral administrations of the IR tablet (loxoprofen 60 mg, n=6, open circles), or a single oral administration of either an ER-A (closed circles), ER-B (closed triangles), or ER-C tablet (closed squares) (loxoprofen 180 mg, n=4, each) in Beagle dogs. Data were presented as mean ± SD. Figure 4 150x111mm (300 x 300 DPI)


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Figure 5. Estimated in vivo dissolution profiles of ER-A, ER-B, and ER-C, as well as the decrease of drug absorption fraction after dissolution (Fabs) along the gastrointestinal tract, predicted by the population pharmacokinetic model. Figure 5 150x97mm (300 x 300 DPI)



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Figure 6. Comparison between observed in vitro dissolution profiles and in vivo dissolution profiles estimated from the in vivo POP-PK model (A) or converted from the final POP-PK-IVIVC model (B). Correlation between observed and converted in vitro release data by using linear regression for ER-A, ER-B, and ER-C tablets (C). The closed circles, triangles, and squares represent the observed data for ER-A, ER-B, and ER-C, respectively, and the lines represent the predicted profiles. Figure 6 82x160mm (300 x 300 DPI)


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Figure 7. Visual predictive check plots for (A) ER-A, (B) ER-B, and (C) ER-C for the validation of the final POP-PK IVIVC model using in vitro dissolution profiles as input data. The symbols represent the observed data following oral administration of ER tablets (n=4, each) and the lines represent the predicted profiles from in vitro dissolution data using the final POP-PK IVIVC model. Figure 7 90x180mm (300 x 300 DPI)



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Figure 8. Visual predictive check plots for the double-layered formulation using in vitro dissolution profiles as input data. The symbols represent the observed data following oral administration of DL tablets (n=4) and the lines represent the predicted profiles from in vitro dissolution data using the final POP-PK IVIVC model. Figure 8 140x101mm (300 x 300 DPI)


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Development of a Physiologically Relevant Population

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