European Journal of Pharmaceutical Sciences 37 (2009) 341–350

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European Journal of Pharmaceutical Sciences

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Biopharmaceutic and pharmacodynamic modeling of the in vitroantiproliferative effect of new controlled delivery systems of cisplatin

Daniel Morenoa, Sara Zalbaa, Helena Colomb, Inaki F. Trocóniza,Conchita Tros de Ilarduyaa, María J. Garridoa,∗

a Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Navarra, Irunlarrea, 1, 31008-Pamplona, Spainb Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, University of Barcelona, Spain

a r t i c l e i n f o

Article history:Received 10 October 2008Received in revised form 15 January 2009Accepted 7 March 2009Available online 24 March 2009

Keywords:Biopharmaceutic–pharmacodynamicmodelingCisplatin antiproliferative effect

a b s t r a c t

A biopharmaceutic–pharmacodynamic model is proposed to characterize the antiproliferative effect ofcontrolled release formulations of cisplatin in cancer cell culture. In vitro release profiles from PLGA[poly(d,l-lactide-co-glycolide)] systems were described using a model based on the characterization oftwo drug release processes: diffusion and matrix degradation. Cytotoxicity data available consisting of thenumber of survival cells after a continuous exposure to free or encapsulated cisplatin were simultaneouslymodeled under the Gompertz framework incorporating the drug release model.

The release model parameters showed that particle size was inversely related to the diffusion rate. Theantiproliferative effect was described as a function of drug concentrations and exposure times. Two mech-anisms were included: (i) an inhibition of cell proliferation, where cisplatin released from PLGA systems

PLGA cisplatin nanoparticlesPLGA-cisplatin microparticles

was mainly involved, followed by (ii) stimulation of cell death due to cisplatin activity and mediated bythe activation of a signal transduction process. Cell accumulation in G2/M phase of the cell cycle followedby the activation of caspase-3, supported both mechanisms.

The selected drug-effect model and its model parameters were independent from the formulation,which makes it a suitable tool to explore in silico, alternative in vitro and in vivo scenarios to optimizethese delivery systems.

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. Introduction

Cisplatin (cis-diamminedichloroplatinum, CIS) is one of theost potent anticancer agents known. However, its adminis-

ration is associated with serious side effects and resistancehenomenon, which represent limitations on its therapeutic appli-ations (González et al., 2001; Kartalou and Essigmann, 2001).o improve these characteristics, the new drug delivery systemsased on micro- and/or nanoparticles, appear to be a very promis-

ng strategy in the therapy of cancer because they can reduceoxicity, thereby improving the therapeutic index through moreelective and controlled delivery of the agent in the tumour tar-et (Harashima et al., 1999; Avgustakis et al., 2002; Koziara et al.,

006).

For cisplatin various types of formulations have been developedo decrease its side effects (Avgustakis et al., 2002; Huo et al., 2005;

oreno et al., 2008a), and in relation to its antitumoural effect, it

∗ Corresponding author. Tel.: +34 948425600x6529; fax: +34 948425649.E-mail address: mgarrido@unav.es (M.J. Garrido).

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928-0987/$ – see front matter © 2009 Elsevier B.V. All rights reserved.oi:10.1016/j.ejps.2009.03.005

© 2009 Elsevier B.V. All rights reserved.

as been reported that the induction of apoptosis was more effec-ive after the intermittent administration of sub-therapeutic doseshan after a single high dose (Kishimoto et al., 2005).

On the other hand, the encapsulation of paclitaxel in nanoparti-les led to overcome the resistance phenomenon observed for thisrug in the colon cancer treatment (Koziara et al., 2006). Thesevidences suggest the idea that the sustained release formulationsould be an adequate system for increasing therapeutic efficacynd possibly overcoming the resistance phenomenon (Verrijk etl., 1992; Iinuma et al., 2002; Kim. et al., 2008).

One of the properties of these formulations is their abil-ty to modify the body distribution of the entrapped compoundHarashima et al., 1999; Hamelers et al., 2006), depending, amongther factors, on the polymer characteristics and the rate of admin-stration. The consequence is that the pharmacological effect will belso affected (Harashima et al., 1999; Rice et al., 2006) because the

rug effect is mediated by the pharmacokinetic, pharmacodynamicrug properties and the biological system related characteristics.

n this way, the quantitative determination of the drug release raten vitro and the mechanism by which it occurs could be the firstpproach to understand the drug effect (Duvvuri et al., 2006).

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42 D. Moreno et al. / European Journal of

Several standard mathematical models based on the geometryf the system and the physicochemical properties of the drug, haveeen developed and applied to describe the in vitro drug releaserocess, providing a mechanistic interpretation of the release kinet-

cs (Costa and Sousa Lobo, 2001).Recently, new delivery systems for cisplatin based on PLGA

icro- and nanoparticles designed for intraperitoneal and intra-enous administration, respectively, have been characterized inn vitro studies (Moreno et al., 2008a). The authors found thathose formulations were able to (i) increase the efficacy in termsf activation of apoptotic proteins, (ii) modify the cell cycle pro-les, and (iii) alter the antiproliferative profiles. On the other hand,he time course of viable DHD/K12Prob adenocarcinoma colonells after free cisplatin treatments in in vitro study, has beenppropriately described using a semi-mechanistic pharmacoki-etic/pharmacodynamic (PK/PD) model reported by Moreno et al.2008b).

Therefore, the aim of the current study is to describe quanti-atively the release profiles of new controlled delivery systems ofisplatin and the time patterns corresponding to their antiprolifer-tive cell effect.

. Materials and methods

.1. Materials

PLGA polymer with a molecular weight (Mw) of 12,000 Dand a co-polymerization rate of 50:50 (lactic:glycolic) (Resomer02H) was purchased from Boehringer Ingelheim (Germany). Cis-latin (cis-platinum diammine dichloride), polyvinyl alcohol (PVA7–89% hydrolyzed, Mw 13,000–23,000), Trizma hydrochloridend cisplatin were obtained from Sigma–Aldrich (Madrid, Spain).

.2. Methods

.2.1. PLGA formulations of cisplatinPLGA micro- (MPs) and nanoparticles (NPs) loaded with cis-

latin were prepared by a water–oil–water (w/o/w) emulsionolvent evaporation method (Moreno et al., 2008a). Briefly, for MP,solution of cisplatin in Tris–HCl (1.67 mg/mL) was emulsified in

.5 mL of chloroform containing 100 mg of PLGA, using an Ultra-urrax system. This first emulsion (w/o) was added to 3 mL of PVA% saturated with cisplatin (1 mg/mL) and emulsified by the sameystem. The final emulsion (w/o/w) was mixed with 7 mL of PVA% saturated also with cisplatin. For NPs, two different protocolsesulting in two different types of nanoparticles were describedelow:

1. NP-A: an aqueous solution of cisplatin (2.5 mg/mL) was emul-sified in 2 mL of dichloromethane containing 100 mg of PLGA,using a microtip probe sonicator. This primary emulsion (w/o)was mixed with 6 mL of PVA 9% saturated with cisplatin(1 mg/mL), using again the probe sonicator system.

. NP-B: a solution of cisplatin in Tris–HCl (1.67 mg/mL) was emul-sified in 0.5 mL of chloroform containing 100 mg of PLGA, usinga microtip probe sonicator. This emulsion (w/o) was then mixedwith 2 mL of PVA 9% saturated with cisplatin (1 mg/mL), usingthe Ultra-Turrax system. The w/o/w emulsion was transferreddropwise to 8 mL of PVA 9% saturated also with cisplatin.

All final w/o/w emulsions were agitated for 3 h at room tem-erature until the organic solvent was evaporated. The differentarticles were collected by ultracentrifugation, washed with water,reeze-dried and stored at −20 ◦C until use. The size and zeta poten-

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2

3

aceutical Sciences 37 (2009) 341–350

ial (�) were determined by laser diffractometry using a Zetasizerano Series (Malvern Instruments, UK) after resuspension of each

ormulation in 1 mL of PBS.

.2.2. In vitro cisplatin release from PLGA systemsThe loading of cisplatin in all formulations was quantified by

n HPLC-technique. Five milligrams of the each formulation wasuspended in 1 mL of PBS. The suspensions were placed into micro-entrifuge tubes and maintained at 37◦ C with constant stirring. Atredetermined time intervals, between 0 and 35 days, an aliquotf the supernatants from each tube was collected, centrifuged18,000 rpm, 10 min) and used for the HPLC analysis. This assayas developed according to the protocol described by Augey et al.

1995) and modified by Moreno et al. (2008a). In brief, an aliquotf 90 �l of the supernatant was mixed with 10 �l of a solutionf sodium diethyldithiocarbamate (DDTC) and incubated at 37 ◦Cor 1 h. Afterwards, the mixture was cooled on ice for 10 min. Theisplatin–DDTC chelates were extracted with chloroform and a vol-me of 10 �l was injected into the chromatographic system. Thenalytical separation was performed at 30 ◦C by a Kromasil C-1825 × 0.46 cm i.d. of 5 �m particle size). The mobile phase consistedf a mixture of methanol/water (25:75) and was fixed at a flow ratef 1 mL/min. Detection was performed at 254 nm. The accuracy ofhe assay was >90%. The method was linear within the concentra-ion range studied (0.2–100 �g/mL) and the limit of quantificationas set at 0.2 �g/mL.

.2.3. In vitro cytotoxicityDHD/K12PROb adenocarcinoma colon cell line, obtained from

DIX rats, was grown as adherent monolayers in 25-cm2 cultureasks at 37 ◦C in a 5% CO2 humidified atmosphere and maintained

n a mixture of Dulbecco’s modified Eagle’s and Ham’s F-10 mediumupplemented with 10% fetal bovine serum and 0.01% gentamicin.

Cells were seeded into 96-well microtiter plates at a densityf 20 × 103 cells/well/200 �l and incubated in 5% CO2 humidifiedtmosphere at 37 ◦C for 24 h. To evaluate the dependence of drugctivity on concentration and exposure time, each plate was treatedith one of the following concentrations: 2.5, 10, 18, 50 or 100 �M

f free or encapsulated cisplatin and incubated for 3, 10, 24, 48, 72nd 144 h. After each treatment, the plates were washed and theurvival cells were quantified using the supravital stain neutral redssay (Löwik et al., 1993). Optical density was read at 540 nm usingmicrotite plate reader (Labsystems iEMS Reader MF). Wells withntreated cells were also included in each plate. Two linear stan-ard curves where the number of cells (from 5 × 103 to 100 × 103

ells/well and from 1 × 103 to 10 × 103 cells/well) were related tohe absorbance measurements, were previously generated.

.2.4. Cell cycle analysisDHDK12-Prob cells (25 × 104 cells/well) were seeded into 6-well

ulture plates. After 24 h, the plates were treated with 2.5, 10 and0 �M of free and encapsulated cisplatin following the protocolescribed above. Wells with untreated cells were also included inach plate. After each exposure time, the plates were washed withBS and the cells were detached by trypsine, collected in micro-ubes and washed by centrifugation. The pellets were incubatedor 30 min at 37 ◦C, with 100 �l of Tween 20 (0.2% PBS) and 20 �l ofibonuclease type IIA (45 U/mL). Afterwards, the cells were stainedith propidium iodide (25 �g/mL) for 10 min in darkness. The anal-

sis of each sample was performed on a Becton Dickinson FACScan

ow cytometer using the CellQuest Software (Moreno et al., 2008a).

.2.5. Caspase-3 activityCaspase-3 activity was determined using the Caspase-Glo®

/7 luminometric Assay Kit (Promega Corporation, Madison, USA)

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D. Moreno et al. / European Journal of P

ccording to the manufacturer’s protocol (Birdsey et al., 2008).density of 20 × 103 cells/well was seeded into 96-well cul-

ure plates (MicroWellTM white-walled plates for luminescence).fter 24 h, the plates were treated with the following concen-

rations: 2.5, 10 and 50 �M of free and encapsulated cisplatin,nd incubated for 10, 24, 48, 72 and 144 h. In each plate, con-rol (untreated) cells were grown in the same conditions ashe treated cells. At each time, the medium was removed andells were washed with PBS twice and mixed with the reagentaspase-Glo® 3/7 (100 �l/well) during 30 min. The RLU (relative

uminescence units) was quantified using a microplate Luminome-er Orion II (Berthold Systems, Germany). A standard curve wasarried out using the commercial protein, and results from thisxperiment were expressed as fg of caspase-3 activated/numberf cells.

. Data analysis

All the analyses were done using the naïve pool approach withhe software NONMEM version VI (Beal and Sheiner, 1992). Withhis type of approach only residual variability is estimated, and thisas modeled initially with a combined error model; if one of the

omponents (additive or proportional) of the residual error wasegligible, it was deleted from the model.

The analysis was done sequentially. First, the kinetic modelsere fitted to the cumulative release data of cisplatin for each for-ulation, followed by the pharmacodynamic model development,here the time course of cisplatin into the cell culture mediumreviously predicted, was included to describe the cytotoxic effect.

Selection between models was based on the precision of param-ter estimates, goodness-of-fit plots, and the minimum value ofbjective function [−2 log(likelihood): −2LL] provided by NON-EM. Because some of the models compared were not nested, −2LLas not used directly for comparative purposes, and the Akaike

nformation criteria (AIC) (Akaike, 1976), computed as −2LL + 2Np,here Np is the number of the parameters in the model, was used

nstead. The model with the lowest value of AIC, given that preci-ion of model parameters and data description were adequate, waselected.

.1. Drug release models

The in vitro fraction release profiles (Ft), calculated as the ratioetween the absolute cumulative amounts of drug released at time(Mt) and infinite time (M∞), from each formulation were used toest the following models:

he zero order kinetics model :Mt

M∞= k0 · t (1)

here k0 is the zero order release constant. This model assumeshat drug release is constant.

he Higuchi model (Higuchi, 1963) :Mt

M∞= k · t0.5 (2)

here k represents the release rate constant reflecting the designariables of the system. The model assumes that Fickian diffusions the rate limiting step and the predominant release mechanism.

orsmeyer Peppas model (Korsmeyer et al., 1983) :Mt

M∞= k · tn

(3)

here k represents a rate constant incorporating structural andeometric characteristics of the device, and n is the release expo-ent. For spherical devices, a value of n = 0.45 suggests a Fickian

9i

aceutical Sciences 37 (2009) 341–350 343

iffusion, n = 0.85 a mechanism of case-II transport and val-es between 0.43 and 0.85, a superposition of both phenomenaanomalous transport).

The Peppas–Sahlin model (Peppas and Sahlin, 1989):

Mt

M∞= k1 · tm + k2 · t2m (4)

here k1 and k2, represent the rate constants reflecting the con-ribution of two mechanisms of release, diffusion and erosion,espectively. The model assumes that both processes are additiveuring drug release. Regardless of the geometric device, the value offor non-Fickian transport is twice that for a pure Fickian diffusionechanism.These models represent the most common approach to analyze

he main mechanism of release from different types of devices.owever, all of them should be used to analyze the first 60% ofrelease curve (Peppas, 1985).

To analyze complete release kinetics, other models can beested:

aker Lonsdale model :32

[1 −

(1 − Mt

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− Mt

M∞= k · t (5)

= 3 · D · K · Cs

r20 · �

(6)

here k is the release constant which depends on the diffusionoefficient (D), drug specific volume (K), drug solubility (Cs), tortu-sity factor of the capillary system (�) and radius of the sphericalatrix (r0) (Baker and Lonsdale, 1974).

opfenberg model :Mt

M∞= 1 − (1 − k · t)n (7)

here k is the release constant and the value of n is 1, 2 and 3or a slab, cylinder and sphere, respectively (Hopfenberg, 1976).his model describes drug release from heterogeneous geometricurfaces displaying erosion which would be the limiting step.

Sigmoidal model was proposed by Duvvuri et al. (2006) forultiphasic entire release profiles. The model includes: (i) phase

, where drug is released by a diffusion process including a burstffect, (ii) phase II, which occurs during the water uptake into theatrix and, (iii) phase III, where drug release is controlled by the

inetics of polymer degradation.

Mt

M∞= A · (1 − e−k1·t) + B

(1 + e−k2·(t−T50))(8)

here A is the fraction of drug released during the phase I, k1 is theelease rate constant during this phase; B is the fraction of total drugeleased during the phase III, k2 is the release rate constant duringhis phase and T50 is the time taken to release 50% of entrappedrug.

.2. Cell cytotoxicity models

The Gompertz model has been used repeatedly to describe theemporal aspects of cell and tumour growth (Wen-tao et al., 2006;

oreno et al., 2008b). In the present study, the time profiles of theumber of viable DHD/K12-Prob cells (N) in absence of the drug

n the medium were described with Eq. (9), where dN/dt accountsor the rate of change of N, kprol represents the first order rate con-tant of cell proliferation, and NMAX is the maximum number ofells given the current design conditions, which corresponds to the

0% of convergence of the cells in each well. The term log (NMAX/N)

mplies zero rate of change when N approximates NMAX;

dN

dt= kprol × log

[NMAX

N

]× N (9)

3 Pharmaceutical Sciences 37 (2009) 341–350

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44 D. Moreno et al. / European Journal of

This model allows us to discriminate between design dependentN0, and NMAX), system dependent (kprol) and drug dependent (seeelow) model parameters.

In general, for short periods of drug exposure, cell death is notmmediate and its manifestation requires a certain period of time.uch a delay, considered as the time needed to observe the onset ofrug action, was also implemented in the model using the followingxpressions:

dN

dt= kprol × log

[NMAX

N

]× N − N × S (10)

dS

dt= kdel × f (C) × N − kdel × S (11)

here, dS/dt accounts for the rate of change in the drug induced-ignal (S) responsible for inducing the antiproliferative effect, anddel is the parameter governing the delay between the time at whichhe cells begin to be exposed to the drug and the observed onset ofction, f(C) represents an EMAX function of drug concentration (C)nd S.

This model was previously reported by Moreno et al. (2008b) toescribe the antiproliferative effect of cisplatin in culture DHD/K12-rob cells. However in the present study, the model required someodifications due to the effect observed for cisplatin encapsu-

ated in the PLGA systems, especially during the early times ofrug exposure. In this period of time, the antiproliferative effecteems to be modulated by the slow delivery of the drug fromhe formulations in comparison with free drug. The inclusion ofn inhibitory effect of the cell proliferation rate was able to cap-ure all the data obtained in this study but, especially those forow concentrations during the first 24 h. This inhibition is rep-esented by the following expression which is an extension ofq. (10):

dN

dt= kprol × INH × log

[NMAX

N

]× N − N × S (12)

INH = 1 − g(C), where g(C) represents an inhibitory EMAX modelIMAX) dependent on cisplatin concentrations in the medium.

This model indicates that the different rates of drug release intohe medium can play an important role in the mechanism for therug effect.

. Statistical analysis

Particle diameters, �-potential and the loading of cisplatin areepresented as mean ± standard deviation (SD). Data were analyzedsing the nonparametric Kruskal–Wallis test (for more than tworoups) followed by the U-Mann–Whitney test (for two groups).tatistical significance was set at P < 0.05.

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Table 1Characteristics of PLGA micro- and nanoparticles involved in the “in vitro

Nanoparticles

A

Size (�m) 0.18 ± 0.02a,b

�-potential (mV) −18.7 ± 0.5Loading (�g drug/mg polymer) 7.2 ± 1.5Drug concentration (�g drug/mL) 32.2 ± 6.6c

All results are expressed as the mean of three replicates.a Statistical difference: P < 0.05 between NPs A vs. B.b Statistical difference: P < 0.0001 for size.c Statistical difference: P < 0.05 for drug concentration MP vs. NPs.

ig. 1. Time course of the cisplatin released in the in vitro studies expressed ashe mean cumulative fraction (Ft = Mt/M∞). Symbols represent the mean observedata (n = 3) and vertical lines the SD. NP-A, NP-B and MP, represent nanoparticle A,anoparticle B and microparticle, respectively.

. Results

.1. Physico-chemical characterization of PLGA particles andisplatin release

Table 1 lists the different characteristics of the three PLGA for-ulations for cisplatin. The particle size was clearly influenced by

he stirring speed during the homogenization processes with theltra-Turrax and/or with the probe sonication. The PLGA polymeronferred a negative �-potential in all formulations, and no statis-ical differences were observed in the size and �-potential betweenoaded and non-loaded cisplatin formulations (data not shown).

The comparative “in vitro” mean cumulative fractional releaserofiles of cisplatin from NPs and MP are represented in Fig. 1. In thisgure, a triphasic release profile was observed for all formulations.he kinetics and duration of each phase were dependent on theize of the particle. In addition, similar release profiles were foundhen cell culture medium instead of PBS, was used.

.2. Analysis of the in vitro release kinetics

The models described by Eqs. (1)–(4) were applied to dataorresponding to 60% of the cisplatin release curves of each for-ulation, to characterize the main mechanism of drug release. The

alues of AIC obtained for the different models are summarized inable 2. The lowest value was obtained for Eq. (3) correspondingo the Korsmeyer–Peppas model. The model predictions were ableo describe the tendency of the experimental data for all formula-ions as represented in Fig. 2. When the Peppas–Sahlin model was

” studies.

Microparticle B

B

0.45 ± 0.12a,b 9.21 ± 3b

−20.56 ± 0.6 −22.1 ± 0.86.7 ± 0.9 9.2 ± 2.2

33.7 ± 4.8c 41.1 ± 9.8c

D. Moreno et al. / European Journal of Pharmaceutical Sciences 37 (2009) 341–350 345

Table 2Results of AIC from the different models fitted to the release data.

AIC

NP-A NP-B MP

Zero-order −37.37 −59.79 −78.41Higuchi −54.24 −80.65 −101.46Korsmeyer–Peppas −83.77 −95.88 −125.84Peppas–Sahlin −81.77 −93.88 −123.84Baker–Lonsdale −159.92 −145.64 −138.55Hoepfenberg −39.89 −60.32 −73.58S

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igmoidal −106.28 −124.40 −164.47

IC, Akaike information criteria; NP-A, nanoparticle A; NP-B, nanoparticle B; MP,icroparticle.

pplied, the estimate for the k2 parameter was negligible, suggest-ng that the erosion process in cisplatin release during this period ofime, was not relevant. Therefore with these approaches, the main

echanism implicated in cisplatin release seems to be the diffusionrocess.

However, to describe the entire release kinetics, where theechanism of matrix erosion may be implicated in the drug

ffect but over longer periods, models such as the Baker–Lonsdale,opfenberg and sigmoidal models, respectively, were applied toll experimental data. Although the AIC for Baker–Lonsdale was alightly lower than for the other two models, the data were notroperly adequately captured by this model, and it only could beonsidered adequate for the early times of the release correspond-ng to the NPs release profile. Note that to apply this model, theinearization of the data is required, and a change in the shapef the formulation over time can be probably implicated in theechanism of drug transport.The complexity of the release process requires models applica-

le to S-shaped release profiles like the empirical sigmoidal model,hich provided the best description of the time profiles of cisplatin

eleased for the three formulations, as is represented in Fig. 3. More-ver, no trend in the residual distribution vs. time was observednd the model parameters, listed in Table 3, could be estimated

ith good precision. The results from the sigmoidal model (Eq. (8))

how that, the fraction of drug released during the phase I was veryimilar for both NPs, 0.371 and 0.328 for NP-B and NP-A, respec-ively, and lower for MP, 0.26. However, the duration of this phase

ig. 2. Cumulative fraction of cisplatin released (Ft) vs. time profiles after fitting theorsmeyer–Peppas equation. Symbols represent the mean observed values (n = 3)ith their corresponding SD and solid lines are the model predictions. NP-A, NP-B

nd MP, represent nanoparticle A, nanoparticle B and microparticle, respectively.

actfw(i

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ig. 3. Cumulative fraction of cisplatin released (Ft) vs. time profiles after fitting theigmoidal model. Symbols represent the mean observed values (n = 3) with their cor-esponding SD and solid lines the model predictions. NP-A, NP-B and MP, representanoparticle A, nanoparticle B and microparticle, respectively.

1/k1) was shorter for particles with the smallest size, 7.3 h for NP-, in comparison with particles with higher size, 11.2 and 11.3 h forP and NP-B, respectively. This finding suggests that the particle

ize plays a significant role in this phase as well as in the phase II.he values of T50 characterizing this phase II, were 20.2, 18.7 and0.8 days, for MP, NP-B and NP-A respectively. On the other hand,he duration (1/k2) of the phase III was approximately the same forll formulations, 6.33, 5.85 and 6.85 days for MP, NP-B and NP-A,espectively, although the release fraction was higher for MP (0.81)ompared to NPs (0.68 for both).

.3. Modeling of cell cytotoxicity

Eqs. (10) and (11) have been previously applied to describe thentiproliferative effect of free cisplatin in DHD/K12PROb culturedells. In this study, this model was applied to data correspondingo all treatments with free and encapsulated cisplatin, and it wasound that the presence of a signal transduction process associatedith the mechanism of irreversible cell loss, was again significant

P < 0.001). This result supports the fact that this mechanism is

ntrinsic to cisplatin activity independently of the formulation.

Although the time-effect profiles for cisplatin, free and encap-ulated, were described by this model, the results showed that lowoncentrations during the early exposure times of cisplatin (freend encapsulated) were not completely well captured by the model

able 3arameter estimates corresponding to the sigmoidal release model.

arameter Formulations

NP-A NP-B MP

Estimate Estimate Estimate

0.328 (0.12) 0.371 (0.07) 0.265 (0.06)1 (day−1) 3.28 (0.36) 2.12 (0.32) 2.15 (0.16)

0.686 (0.07) 0.680 (0.05) 0.812 (0.04)2 (day−1) 0.146 (0.13) 0.171 (0.14) 0.158 (0.07)50 (days) 10.80 (0.15) 18.70 (0.04) 20.20 (0.05)

, fraction of total drug released during phase I; B, fraction of total drug releaseduring phase III; k1, rate constant of drug released during phase I; k2, rate constantf drug released during phase III; T50, time taken to release 50% of the entrappedrug. Estimates are listed with the relative standard error calculated as the standardrror divided by the parameter estimate in parentheses. NP-A, nanoparticle A; NP-B,anoparticle B; MP, microparticle.

346 D. Moreno et al. / European Journal of Pharmaceutical Sciences 37 (2009) 341–350

Fig. 4. Schematic representation of the final pharmacodynamic model applied todkng

pcio

Table 4Parameter estimates corresponding to the antiproliferativemodel selected.

Parameters Estimate (RSE)

N0 (cells × 103) 14.3 (0.02)kprol (day−1) 0.57 (0.02)NMAX (cell × 103) 137 (0.02)C50 (�g/mL) 9.85 (0.43)EMAX 0.196 (0.35)IMAX 1a

IC50 (�g/mL) 9.08 (0.19)kdel (day−1) 1.82 (0.12)

N0, initial number of cells seeded in each well; kprol , first-orderrate constant for cell proliferation; NMAX , maximum numberof cells obtained in the experimental conditions; C50, drugconcentration eliciting half of the maximum cisplatin effect(EMAX) on the signal transduction activation; IMAX , maximumeffect elicited by cisplatin on the cell proliferation process;IC50, drug concentration eliciting half the maximum inhi-bition on kprol; kdel , parameter controlling the delay of the

fid

Frr

escribe the antiproliferative effect of cisplatin, free and released from PLGA devices.prol represents the first-order rate constant for cell proliferation; S, apoptotic sig-al responsible for the irreversible loss of cells and kdel , first-order rate constantoverning the delay between drug exposure and onset.

redictions. Therefore, a more complex mechanism must be impli-ated in the effect. When an additional mechanism of action wasnvestigated by the incorporation of an inhibitory drug effect (INH)n kprol (Eq. (12)), this showed a significant improvement of the

eaDF(

ig. 5. Time course of the cell viability for five different concentrations: control (©), 2.5 (�epresent mean experimental data (n = 9) together with SD and lines the model predictionespectively.

apoptotic signal. Estimates are listed with the relative stan-dard error in parentheses, calculated as the standard errordivided by the parameter estimate.

a Parameter fixed.

t (P < 0.001). That inhibition was characterized by an IMAX modelependent on cisplatin concentration in the medium. The pres-

nce of a new delay compartment for this last mechanism waslso explored, but it did not reach statistical significance (P > 0.05).espite the complexity of the final model which is represented inig. 4, all the parameters could be estimated with a good precisionTable 4). Since the estimate of IMAX was close to 1, indicating that

), 10 (�), 18 (�), 50 (�) and 100 (*) �M, of free and encapsulated cisplatin. Symbolss. NP-A, NP-B and MP, represent nanoparticle A, nanoparticle B and microparticle,

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D. Moreno et al. / European Journal of P

ell proliferation process can be totally blocked by cisplatin, it wasubsequently fixed to 1. Fig. 5 shows that this model performs veryell at each concentration level for each type of formulation.

.4. Cell cycle analysis and caspase-3 activity

An experimental exploration was carried out to corroborate theechanisms involved in the selected model for cell antiprolifer-

tion. The inhibitory effect of cisplatin on the cell proliferationrocess could be explained by the modifications found in the cellycle analysis. Fig. 6 shows that all treatments with cisplatin innsynchronized cells were able to induce cell arrest in G2/M phaseith a maximum effect at 48 h of treatment, except for the high

oncentration (50 �M) of free drug. In this case, the regulation wasound in a previous phase G0/G1 disappearing the phase G2/M veryapidly. A specific cell cycle check point at the boundary of the2 and M phases have been suggested to be involved in apoptosis

nduction in a variety of cells treated with cisplatin. In the apoptosisathway, the caspase-3 is the main protein implicated in this effect.

he activation of this intracellular protein was measured after freend encapsulated cisplatin treatments, as is shown in Fig. 7. Theaximum levels of the caspase-3 activated was observed at 72 h of

reatments, suffering a delay in relation to the time for the max-mum arrest in the cell cycle. The activation of caspase-3 is the

rdor

ig. 6. Percentage of cells distributed in the cell cycle for control and cisplatin treatments.P, represent nanoparticle A, nanoparticle B and microparticle, respectively.

aceutical Sciences 37 (2009) 341–350 347

olecular mechanism implicated in the apoptosis and therefore,n the irreversible loss of cells during cisplatin treatments.

. Discussion

Three different PLGA systems entrapping cisplatin have beeneveloped to characterize the antiproliferative effect of thisrug, based on the previous results reported by Moreno et al.2008a) for the free drug. In the present study, a biopharmaceu-ic/pharmacodynamic model has been proposed to investigate theffect of the controlled release of cisplatin in its mechanism ofction and then in its cytotoxicity. The data obtained in the cur-ent study were analyzed using parametric models, however otherlternatives, for example based on fuzzy models can be considered,s it has been shown by Belic et al. (2003).

The release profiles obtained from the PLGA formulations wereodeled in a quantitative manner, in relation to some parameters

erived from the pharmaceutical dosage form (Costa and Sousaobo, 2001; Duvvuri et al., 2006).

The drug transport inside the pharmaceutical systems and itselease sometimes involves multiple steps due to the presence ofifferent physical or chemical phenomena, which makes it difficultr even impossible to obtain a mathematical model describing cor-ectly all processes (Duvvuri et al., 2006). Here, several models were

Bars represent the mean experimental values (n = 3) with their SD. NP-A, NP-B and

348 D. Moreno et al. / European Journal of Pharm

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ca3endeath (Mueller et al., 2006). Therefore, this mechanism seems to be

ig. 7. Time profiles of caspase-3 activated. Bars represent the mean experimentalata (n = 3) and vertical lines the SD. NP-A, NP-B and MP, represent nanoparticle A,anoparticle B and microparticle, respectively.

pplied to explore the rate-limiting step in the cisplatin release pro-les from MP and NPs previously characterized by Moreno et al.2008a). It is known that for a drug incorporated into the PLGA sys-ems the release processes are: diffusion, degradation/dissolutionf PLGA matrix, and combination of both processes. Although, sev-ral mathematical models have been used to elucidate the exactrug release mechanism, the choice of a model depends on theharacteristics of both drug and polymer (Costa and Sousa Lobo,001; Kim, 2000).

Cisplatin is a small, slightly soluble molecule with the abilityo diffuse through the spaces of the PLGA polymer and disperse inpherical matrices of this hydrophobic polymer. This hydrophobicharacteristic of PLGA allowed us to consider its erosion irrelevanturing the initial phases of release (Duvvuri et al., 2006). In addi-ion, the half-life of the polymer mass loss for PLGA (50:50) has beeneported around 14 days leading to a complete re-absorption of thearticle in approximately 50 days (Anderso and Shive, 1997). Thus,iffusion would be the predominant mechanism of drug release as

t was confirmed by the results obtained for the formulations usedn this work, after applying the Korsmeyer–Peppas model for the

0% of the release curves (see Fig. 2). The estimates of the exponentor Fickian diffusion n were 0.29, 0.31 and 0.32 for NP-A, NP-B and

P, respectively, closer (but not equal) to 0.43. This result can bexplained by the polydispersion found in the particle size distribu-

iabb

aceutical Sciences 37 (2009) 341–350

ion of each formulation (Ritger and Peppas, 1987). However theomplexity of the drug release processes from these formulationsade that, in our case those mechanism-based models could not

escribe the entire course of drug release. The empirical sigmoidalodel proposed by Duvvuri et al. (2006) for microspheres of ganci-

lovir, where any mechanistic process is considered, could describedequately the complete cisplatin release profiles over 35 days forPs and MP (Fig. 3).

The initial burst effect observed in all formulations could bettributed to the diffusion of cisplatin which is poorly encapsulatednd present close to the pores in the surface. In fact, the hetero-eneous nature of these types of polymeric matrices containingapillaries contributes to the diffusion of the drug when the sol-ent is taken up into the spherical matrix (Klose et al., 2006). Thisurst effect is related inversely to the particle size because the sur-ace area available is higher, and the distance to diffuse the drughorter from NPs (0.37 vs. 0.33 for NP-a and NP-B, respectively)han from MP (0.26), as is observed in Fig. 1. In addition, duringhis phase I, k1 (parameter governing the release rate of drug inhis phase), was higher for NP-A (3.28) than for NP-B (2.12) and

P (2.15), indicating a more rapid release of cisplatin from parti-les with lower size. Similar results were also reported by otheruthors (Díez and Tros de Ilarduya, 2006; Moreno et al., 2008a).he extent and duration of phase I, may depend on drug distri-ution in the matrix and the efficiency of polymer packing duringhe particle hardening stage. This phase is followed by a very slow

inimal release phase (phase II), where a modest solvent uptakeccurs and induces a rapid solvent uptake associated with a massoss of the polymer and the fragmentation or degradation of the

atrix. This mechanism, represented in Table 3 by the parame-er T50, is also dependent on the particle size because of the timeo release 50% of the entrapped drug, is shorter for NP-A than forP-B and MP (Fig. 1). In this phase both processes, diffusion andegradation, are presented because the onset of the phase III isssociated with the rapid loss of polymer mass. The values of k2parameter governing the release rate of drug in phase III) are veryimilar for the three formulations, 0.146, 0.171 and 0.158 for NP-A,P-B and MP, respectively (Table 3), suggesting that this parameterepends mainly on the type of polymer used to manufacture thearticles (PLGA-Resomer 502H), as it was observed by Duvvuri etl. (2006).

The antiproliferative effects of cisplatin could be reasonable wellescribed using the model proposed by Moreno et al. (2008b),here the cytotoxicity was concentration-dependent, as has beenreviously reported by other authors (Wu et al., 2004; Berndtssont al., 2007). In addition, this cytotoxicity was also dependent onhe release rate of cisplatin from the formulations (Moreno et al.,008a). However, such effect required a time to be manifested,hich was associated with the activation of caspase-3 (Moreno et

l., 2008b; Wu et al., 2004). In this study, an extra mechanism (inhi-ition of kprol) could be identify due to the slow release of cisplatinrom the controlled delivery systems. The parameter estimates forprol, kdel and C50 obtained in the current analysis were similar tohose previously reported (Moreno et al., 2008b).

All treatments with cisplatin encapsulated were able to induceell arrest in the G2/M phase of the cell cycle with a maximumccumulation of cells at 48 h, followed by the activation of caspase-(Cummings and Schnellmann, 2002; Moreno et al., 2008a). This

ffect on the cell cycle implies that these cells could not enter in aew cycle inducing apoptosis and consequently a programmed cell

mplicated in the cell growth inhibition in a first step, followed byn irreversible cell loss (William-Faltaos et al., 2007). When inhi-ition of kprol was incorporated to the model, AIC was decreasedy 40 points improving the fit especially in all formulations and

D. Moreno et al. / European Journal of Pharmaceutical Sciences 37 (2009) 341–350 349

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ig. 8. Time course of the cytotoxic effect of cisplatin released from a hypothetical co.5 �M (solid line), 10 �M (dotted line) and 50 �M (dashed line).

or low concentrations of free cisplatin, which were also able tonduce cells accumulation in G2/M phase. Nevertheless the highoncentration of free drug, 50 �M, caused an accumulation of cellsn G0/G1 phase instead of G2/M phase (Mueller et al., 2006). Theontribution of this dual mechanism, cytostatic and cytotoxic, in theell cycle depending on the free cisplatin concentration, has beenlso reported by Ormerod et al. (1994) and Moreno et al. (2008a).

Results from Fig. 7 show that all treatments led to a slow butffective activation of caspase-3 over time reaching a maximum at2 h of treatments. The only exception was observed for free cis-latin at the concentration of 50 �M, which was able to induce aapid and intensive activation/deactivation of caspase-3, a mecha-ism that is associated with renal cells death, as has been previouslyeported by Cummings and Schnellmann (2002). Therefore, theain factor responsible for the irreversible lose of cells, can be

onsidered the activation of caspase-3 supporting the results pre-iously reported by Moreno et al. (2008b).

These results could explain those reported for Kishimoto et al.2005) where the intermittent administration of sub-therapeutic

oses of cisplatin was able to induce apoptosis more effectivelyhan a single high dose. This finding confirms the results observedn this study for the controlled release formulations of cisplatin.

On the other hand, the time course of the antiproliferativeffect of cisplatin depends (i) on the time course of drug release

bppdb

d release formulation under different conditions for three different concentrations,

nto the culture medium [described and predicted by the bio-harmaceutic/release model and its model parameter estimates1, k2, and T50], and on (ii) the pharmacodynamic model whichescribes the action of cisplatin based on a model integrating cyto-oxic and cytostatic effects and characterized by the estimateshown in Table 4. Therefore varying the values of k1, k2, and T50,s it has been done in Fig. 8, the time course of the antiprolifer-tive effects of cisplatin is altered due to a change in the releaseattern of the drug, being its pharmacodynamic properties unaf-

ected. The results from these simulations showed that k1 had thereatest impact on the antiproliferative action of cisplatin followedy T50 (see Fig. 8). Similar results were found by Duvvuri et al.2006) for PLGA microparticles of ganciclovir, where a high drug-elease rate during phase I combined with a moderate long T50phase II) was optimal for reaching and maintaining therapeuticevels.

In conclusion, the findings observed in our work sug-est that the controlled release formulations of cisplatin seemo be a good strategy in the treatment of cancer. The

iopharmacokinetic–pharmacodynamic model developed madeossible to explore, (i) the antiproliferative effect of cisplatin inde-endently of the sustained release formulation used, and (ii) toetermine how the release rate of the drug from a formulation cane improved to obtain the desired effects.

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50 D. Moreno et al. / European Journal of

cknowledgments

We kindly acknowledge Dr. D. García-Olmo (research unit oflbacete General Hospital, Spain) for providing the cells. This workas supported by a research grants (PCT-090100-2007-27) from the

panish Government and the University of Navarra (FUN). Danieloreno and Sara Zalba were supported by a fellowship from theovernment of Navarra.

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