Zhengxi Zhu1. 1. Department of Chemical Engineering and Materials Science, University of Minnesota , Minneapolis, Minnesota 55455, United States.
Abstract
Flash nanoprecipitation (FNP) can generate hydrophobic drug nanoparticles in ∼ 100 nm with a much higher drug loading (e.g., > 40 wt %) than traditional nanocarriers (e.g., < 20 wt %). This paper studies the effects of drug molecules on nanoparticle stability made via FNP and demonstrates that chemically bonding a drug compound (e.g., paclitaxel) with a cleavable hydrophobic moiety of organosilicate (e.g., triethoxysilicate) is able to enhance the particle size stability. A nonionic amphiphilic diblock copolymer, poly(lactic-co-glycolic acid)-block-poly(ethylene glycol) (PLGA-b-PEG), is used as a model surfactant to provide steric stabilization. The experiments here show that the lower the drug solubility in the aqueous medium, the more stable the particles in terms of Ostwald ripening, which are consistent with the prediction by the LSW theory. The initial particle size distribution is sufficiently narrow and of insignificance to Ostwald ripening. To correlate the particle stability with hydrophobicity, this study introduces the n-octanol/water partition coefficient (LogP), a hydrophobicity indication, into the FNP technique. A comparison of various drugs and their analogues shows that LogP of a drug is a better hydrophobicity indication than the solubility parameter (δ) and correlates well with the particle stability. Empirically, with ACDLogP > ∼ 12, nanoparticles have good stability; with ∼ 2 < ACDLogP < ∼ 9, nanoparticles show fast Ostwald ripening and interparticle recrystallization; with ACDLogP < ∼ 2, the drug is very likely difficult to form nanoparticles. This rule creates a quick way to predict particle stability for a randomly selected drug structure and helps to enable a fast preclinical drug screen.
Flash nanoprecipitation (FNP) can generate hydrophobic drug nanoparticles in ∼ 100 nm with a much higher drug loading (e.g., > 40 wt %) than traditional nanocarriers (e.g., < 20 wt %). This paper studies the effects of drug molecules on nanoparticle stability made via FNP and demonstrates that chemically bonding a drug compound (e.g., paclitaxel) with a cleavable hydrophobic moiety of organosilicate (e.g., triethoxysilicate) is able to enhance the particle size stability. A nonionic amphiphilic diblock copolymer, poly(lactic-co-glycolic acid)-block-poly(ethylene glycol) (PLGA-b-PEG), is used as a model surfactant to provide steric stabilization. The experiments here show that the lower the drug solubility in the aqueous medium, the more stable the particles in terms of Ostwald ripening, which are consistent with the prediction by the LSW theory. The initial particle size distribution is sufficiently narrow and of insignificance to Ostwald ripening. To correlate the particle stability with hydrophobicity, this study introduces the n-octanol/water partition coefficient (LogP), a hydrophobicity indication, into the FNP technique. A comparison of various drugs and their analogues shows that LogP of a drug is a better hydrophobicity indication than the solubility parameter (δ) and correlates well with the particle stability. Empirically, with ACDLogP > ∼ 12, nanoparticles have good stability; with ∼ 2 < ACDLogP < ∼ 9, nanoparticles show fast Ostwald ripening and interparticle recrystallization; with ACDLogP < ∼ 2, the drug is very likely difficult to form nanoparticles. This rule creates a quick way to predict particle stability for a randomly selected drug structure and helps to enable a fast preclinical drug screen.
At least 30–40%
of new drug candidates have poor water solubility
and are difficult to be administrated.[1] However, the trend of drug discovery is toward more hydrophobicity
and thus better permeability to get through the gastrointestinal tract
wall and cell membranes.[1] An enhanced dissolution
rate is able to compensate for the poor solubility. A variety of nanoscaled
particles as carriers therefore have been engineered, since they have
much higher surface areas and thus dissolution rates.[2] Moreover, particles in the size range of about 50–400
nm are able to accumulate in tumors during in vivo blood circulation
due to the enhanced permeability and retention (EPR) effect.[3] This passive targeting can enhance efficacy and
reduce chemotherapy side effects. Compared with different nanoscaled
particles, i.e., micelles,[4−7] liposomes,[8] and nanoemulsions[9,10] with a typical drug loading capacity (CDL %) below 20%, nanosuspensions[11−14] (usually called nanoparticles) have a much higher
drug loading and are able to show sufficient potency to kill tumors.Among different techniques to produce nanoparticles, i.e., milling,
high pressure homogenization, and the supercritical fluid process,
flash nanoprecipitation (FNP) shows advantages of fast processing,
simple equipment, smaller size, and narrower size distribution.[15−24] The FNP also permits combining several hydrophobic drugs and the
incorporation of imaging agents.[25] In the
FNP technique[18] (see Figure 1), a highly hydrophobic drug is dissolved along with a block
copolymer (BCP) in a water miscible organic solvent. This solution
is injected into a small chamber at a high velocity along with water.
The high velocity generates turbulent mixing, causing the hydrophobic
drug and polymer to coprecipitate very rapidly, forming nanoscaled
particles. The block copolymer is amphiphilic: typically a hydrophilic
poly(ethylene glycol) (PEG) block covalently bonded to a hydrophobic
block. The hydrophobic block precipitates with the drug, arresting
particle growth, while the pendant PEG blocks stabilize the particles
against aggregation.[23]
Figure 1
Schematic of impingement
mixing to form block copolymer-protected
nanoparticles (2D view of cross section).[26]
Schematic of impingement
mixing to form block copolymer-protected
nanoparticles (2D view of cross section).[26]However, like many other techniques,
the challenge of particle
stability still exists. In our previous work, various polymers as
the stabilizers, i.e., water-soluble polyelectrolytes (polylysine,
polyethylene imine, and chitosan)[23] and
nonionic amphiphilic diblock copolymers [polystyrene-block-poly(ethylene glycol) (PS-b-PEG), polycaprolactone-block-poly(ethylene glycol) (PCL-b-PEG),
polylactide-block-poly(ethylene glycol) (PLA-b-PEG), and poly(lactic-co-glycolic acid)-block-poly(ethylene glycol) (PLGA-b-PEG)],[22,27] have been explored to investigate their effects on the particle
formation and stability. Up to now, little work[28] has been reported to investigate the effects of drug compounds
on the particle stability, which will be discussed in this study.
As demonstrated in our previous study,[27] biodegradable PLGA-b-PEG (Scheme 1) is a suitable steric stabilizer for the FNP to inhibit the
particle aggregation, since the PLGA block is noncrystallizable as
well as has relatively high glass transition temperature and a right
solubility parameter (δ), ensuring that no unexpected particle
destabilization introduced by this additive.[27] β-carotene, hydrocortisone, hydrocortisone ethoxysilicate,
betulin, paclitaxel, and paclitaxel 2′,7-bis(triethoxysilicate)
will be used as the drugs. (Scheme 1) These
compounds or their analogues are listed in the US National Cancer
Institute (NCI) Drug Dictionary.[29] The
aims of this study are to give a guideline to choose the suitable
drug with good particle stability for flash nanoprecipitation especially
at a high drug loading (e.g., > 40 wt %), to create an approach
to
predict the particle stability for a randomly selected drug structure,
and to give a possible approach to improve the particle stability.
For the purpose of predicting particle stability, the n-octanol/water partition coefficient (LogP), a hydrophobicity
indication, will be introduced into the FNP technique. The properties
of n-octanol has been thought to resemble to those
of lipid bilayer membranes, suggesting to some extent that a drug
partition in octanol/water simulates its ability to passively diffuse
across biological membranes. LogP as a standard measurement
of drug hydrophobicity has been widely used in the pharmaceutical
industry. An empirical rule correlating LogP with
the particle stability made via FNP will be given to help enable a
fast preclinical drug prescreen.
Scheme 1
Structures of the Block Copolymer
and Hydrophobic Drug Compounds
Experimental Section
Materials
β-carotene is a
type of antioxidant
found in yellow and orange fruits and vegetables and in dark green,
leafy vegetables. The body can make vitamin A from β-carotene.
It is being studied in the prevention of some types of cancer.[29]Hydrocortisone is a steroid hormone produced
by the adrenal cortex with primary glucocorticoid and minor mineralocorticoid
effects. As a glucocorticoid receptor agonist, hydrocortisone promotes
protein catabolism, gluconeogenesis, capillary wall stability, and
renal excretion of calcium and suppresses immune and inflammatory
responses. Its synthetic counterpart is used, either as an injection
or topically, in the treatment of inflammation, allergy, collagen
diseases, asthma, adrenocortical deficiency, shock, and some neoplastic
conditions.[29]Betulin is isolated
from the bark of betula alba, the common white
birch. Its derivative, betulin acid, is a pentacyclic lupane-type
triterpene with anti-inflammatory, anti-HIV, and anti-neoplastic activities.
Betulinic acid induces apoptosis through induction of changes in mitochondrial
membrane potential, production of reactive oxygen species, and opening
of mitochondrial permeability transition pores, resulting in the release
of mitochondrial apogenic factors, activation of caspases, and DNA
fragmentation. Although originally thought to exhibit specific cytotoxicity
against melanoma cells, this agent has been found to be also cytotoxic
against nonmelanoma tumor cell types including neuroectodermal and
brain tumor cells.[29]Paclitaxel is
a compound extracted from the pacific yew tree, Taxus brevifolia, with antineoplastic activity. It binds
to tubulin and inhibits the disassembly of microtubules, thereby resulting
in the inhibition of cell division. This agent also induces apoptosis
by binding to and blocking the function of the apoptosis inhibitor
protein B-cell Leukemia 2 (Bcl-2).[29]β-carotene (≥97%), betulin (≥98%), water (HPLC
grade), and tetrahydrofuran (THF, HPLC grade) were purchased from
Aldrich and used as received. Paclitaxel was purchased from Polymed
Therapeutics, Houston. Paclitaxel 2′,7-bis(triethoxysilicate)
and hydrocortisone ethoxysilicate were synthesized by Wohl[30] (see Scheme S1 in Supporting
Information). Paclitaxel 2′,7-bis(triethoxysilicate)
were chemically very stable in water in pH 7 but would hydrolyze in
an acidic condition.[30]PLGA(10k)-b-PEG(2k) was synthesized by the ring-opening
polymerization of (d,l)-lactide and glycolide with
mPEG(2k)-OH as the initiator and Tin(II) 2-ethylhexanoate as the catalyst
in bulk at 150 °C. The obtained product was diluted in THF, dialyzed
(Spectra/Pro 7 RC, molecular weight cut off (MWCO) of 1000) with CH3OH for two days to remove unreacted monomers, and then concentrated
under vacuum. M̅n of PLGA(10k)-b-PEG(2k) was determined by NMR, and M̅w/M̅n was determined
by GPC as 1.46.[27] The PLGA blocks comprised
50% of lactic acid and 50% of glycolic acid confirmed by NMR and were
amorphous.
Particle Preparation
The two-stream
mixer and the FNP
process are illustrated in Figure 1. The chamber
dimensions were the same as those used by Johnson et al.[16] and Liu et al.[31] (type
500A-Y2X with dimensions described in Figure 4 and Table 1 in ref (16) and in Figure 1 in ref (31)). In this study, the mixer
was modified to allow unequal flow momentums from two opposite jets[24] (see Figure S1a in Supporting
Information or Figure 3 in ref (24)). Each mixer inlet was connected to a 10 mL
of gastight glass syringe (SGE Inc.) via Teflon tubing with 1.6 mm
ID. Both syringes were loaded on an infusion syringe pump (Harvard
Apparatus model 975). For typical mixing, 25 mg of the drug compound
and 25 mg of the BCP were dissolved in 5 mL of THF and were loaded
in one syringe. Another syringe was loaded with 5 mL of H2O. Two streams were impinged at a high velocity inside the mixer
chamber. In most cases the flow rate was 72 mL/min which produces
a mean jet velocity of 6.1 m/s through the 0.500 mm diameter nozzle.
The outlet of the mixer was connected via 12.7 cm of 1.6 mm ID Teflon
tubing to a beaker containing 90 mL of H2O to further dilute
the nanoparticles. The Reynolds number (Re),[32] a ratio of inertial force to viscous force,
was used to quantify the mixing.where ρ is a fluid density, η
is a fluid viscosity, V is a velocity, and Q is a flow rate. For jets mixing, a is
a diameter of an inlet nozzle, and s is a cross sectional
area of an inlet nozzle.[16,33,34]Re higher than a transition value, which mainly
depends on a mixer design, indicates a sufficient mixing quality producing
an asymptotic mean particle size.[18,27] Johnson and
Prud’homme[17] reported that the transition
of this T-mixer corresponded to a jet velocity of ∼2.1 m/s
by mixing THF and water at 35 °C. With a room temperature correction
to ρ and η, the jet velocity of 6.1 m/s in this study
was still high enough for providing sufficient mixing. In most of
the previous studies by others, the two stream jets mixer required
an equal momentum from two opposite streams, and Re was usually reported with Re1 of a single
stream.[16,31] However, a four stream jets mixer allowed
unequal momentums, and Re was usually reported by
accumulating multiple streams.[20,23] In this study, the
two stream jets mixer allowed unequal momentums from two opposite
jets. The density (960 kg/m3) and viscosity (1.66 mPa·s)
of a 50:50 THF/water mixture[15] in the chamber
were used to calculate Re, which to a certain extent
was able to better compare with a situation of mixing two identical
streams. A mean Re of 1770 for a single stream and
the accumulation of 3540 for two therefore were calculated. The concentration
of the final product in 95 mL of H2O and 5 mL of THF was
0.05 wt %. The residence time was about 110 ms from entering the chamber
to falling into the beaker. The total injection time was about 5 s.All β-carotene experiments were done with a four-stream vortex
mixer. The procedures were described in our previous work.[23,27] Typically two of the mixer inlets were connected to two gastight
plastic syringes (60 mL, Kendall Monojet) via Teflon tubing with 1.6
mm ID. Each plastic syringe contained 45 mL of water and was driven
by an infusion syringe pump (Harvard Apparatus, model 945). The other
two inlets were connected to two gastight glass syringes (10 mL, SGE)
via Teflon tubing. One of the syringes contained 5 mL of a β-carotene
(50 mg) and BCP (50 mg) THF solution; another contained 5 mL of pure
THF. The two glass syringes were driven by a second infusion syringe
pump (Harvard Apparatus, PHD 2000 programmable). The pumps propel
the four streams at high velocity into the small mixing chamber, generating
high turbulence. Complete dimensions (see Figure S1b in Supporting Information or Figure 4 in ref (20)) and evaluation of mixing
performance using competitive reactions are given by Liu et al.[20] The flow rates were 120 mL/min for the plastic
syringes and 13.3 mL/min for the glass syringes. From these flow rates,
an Re of ∼3000 (higher than the transition
value of ∼450[27]) was calculated,
using the relation (eq 2) reported in refs (19 and 20):where ρ is the density of the ith component, Q is the flow rate of the ith component, a in
this study is the shorter width of the ith inlet
nozzle (1.1 × 10–3 m), s is the cross sectional area of the ith inlet nozzle (1.65 × 10–6 m2), and η is the viscosity
of the ith component. The two water streams dominate Re, and this study assumes ρ = 1.0 × 103 kg·m–3 and
η = 8.9 × 10–4 Pa·s at room temperature. The outlet of the mixer was connected
via a Teflon tubing to a beaker, where the nanosuspensions were collected
without further dilution. The concentration of the final product in
90 mL of H2O and 10 mL of THF was 0.1 wt %. The total injection
time was about 23 s.
Characterization
All samples were
analyzed in the as-mixed
liquid, water with 5–10% of THF, and also without and with
1 wt % of saline added to this THF/water solution. Saline was used
to test the electrostatic stability of the particles; 1 wt % was chosen
because it is similar to the ion concentration in body fluids. The
particle size and distribution were determined by dynamic light scattering
(DLS) using a ZetaPALS (Brookhaven Instruments, diode laser BI-DPSS
wavelength of 659 nm, round cuvette). The light intensity correlation
function was collected at 25 °C and a scattering angle of 90°.
The correlation function is a combination of the diffusion coefficient, D, of each particle which is
converted into particle diameter, d, with the Stokes–Einstein equation (eq 3),where kb is the
Boltzmann constant and T is the absolute temperature.
Correlation functions were downloaded from the ZetaPALS and fit using
the REPES model. REPES yields a series of discrete particle diameters
to represent the particle size distribution. It has been found more
accurate than the cumulant model used in most commercial instruments.
The software, GENDIST, was used to solve the REPES algorithm[35,36] and provided the size in an intensity distribution. The intensity
averaged particle size, d̅I, is
defined in eq 4,where n is the number of particles with a diameter of d. The mass averaged diameter, d̅m, is more practically useful than the
usual intensity average for estimating drug loading and availability.
It is defined in eq 5,where m is the mass of a particle with a diameter
of d. As discussed in
our previous work,[23] the systematic errors
including both reproducibility
of mixing and property measurements were within ±10% for d̅m.Cryogenic transmission electron
microscopy (cryo-TEM) specimens were prepared as described also in
ref (23) and were imaged
at about −170 °C and 120 kV acceleration voltage by a
Gatan US1000 cooled CCD camera. The scanning electron microscopy (SEM)
specimens were prepared as described also in ref (23) and then were sputter-coated
with a 30 Å layer of platinum and imaged with a JEOL 6500 SEM.High-performance liquid chromatography (HPLC) was used to measure
the concentration of the encapsulated paclitaxel in the nanoparticles
and the free paclitaxel in THF and water mixture. The paclitaxel nanoparticles
were removed from 0.5 mL of the suspension using a centrifugal filter
(YM-100, Microcon) with a membrane cutoff of 100 kDa (8 nm pore size)
under 12 000 × g. The filtrate was freeze-dried.
Then 0.5 mL of THF was used to redisolve paclitaxel. The filtered
nanoparticles were freeze-dried and extracted by 5 mL of methanol/THF
(4:1) with stirring overnight. The carrier solvent was acetonitrile/ammonium
acetate (10 mmol·L–1) in water in pH 4 (adjusted
with glacial acetic acid) (mobile phase ratio 55/45) eluted through
a C18 RP (Beckman) HPLC column at a flow rate of 1 mL/min. The column
pressure was 0.9 kpsi. The injection volume was 30 μL. The paclitaxel
was detected by UV–Vis detector (Beckman 168) at the wavelength
of 228 nm. The peak retention time was about 7 min, and the run time
was 10 min. The CDL % is defined as the
ratio of the mass of the drug trapped in the nanoparticles to the
total mass of the nanoparticles. CDL %
of paclitaxel was 55 wt % by HPLC. 90.2% of paclitaxel was precipitated
as the nanoparticles, and 9.8% was in free molecules in the filtrate.δ were calculated with the Hoye method.[37] The chemical structures were drawn by ACD/ChemSketch (Freeware
downloaded from www.acdlabs.com, product version 12.01),
and their LogP were calculated with the ACDLogP add-on.
Results and Discussion
Nanoparticle Stability
There are three sources of nanoparticle
instability, i.e., aggregation, Ostwald ripening, and recrystallization.
As discussed in our previous work, polyelectrolytes, such as chitosan,[23] or amphiphilic BCPs, such as PLGA-b-PEG,[27] were able to effectively hinder
the nanoparticle aggregation. In this study, PLGA-b-PEG was used as a model surfactant, whose hydrophobic block was
noncrystallizable as well as had relatively high glass transition
temperature and a right solubility parameter, ensuring no unexpected
particle destabilization is introduced by this additive.[27] It was also showed that the molecular weights
of the PLGA block over the range from 5k to 15k and the PEG block
over the range from 2k to 5k had insignificant effects on the particle
stability.[27] PLGA(10k)-b-PEG(2k) was used in this study, and Figure 2 showed PLGA(10k)-b-PEG(2k) nanoparticles made via
FNP either without or with β-carotene. The PLGA-b-PEG/β-carotene particles were relatively stable for at least
3 weeks with the size slowly increasing from 57 to 90 nm.[27]
Figure 2
SEM images (cryo-TEM insert) and particle size distribution
by
DLS of PLGA(10k)-b-PEG(2k) (50 mg) nanoparticles
(a, c) without, and (b, d) with β-carotene (50 mg) made with
10 mL of THF and 90 mL of H2O (all scale bars are 100 nm).
SEM images (cryo-TEM insert) and particle size distribution
by
DLS of PLGA(10k)-b-PEG(2k) (50 mg) nanoparticles
(a, c) without, and (b, d) with β-carotene (50 mg) made with
10 mL of THF and 90 mL of H2O (all scale bars are 100 nm).Ostwald ripening is the phenomenon
by which small particles are
essentially consumed by large particles during the growth process,
since the small particles have a higher solubility than the large
particles as described by the Kelvin equation.[38] The driving force is to lower the surface energy. It usually
facilitates the interparticle recrystallization. Ostwald ripening
was first described by Lifshitz, Slyozov, and Wagner (LSW).[39,40] For a diffusion-controlled process, the average radius of the particles, r̅, changes with time according towhere K is a rate constant,
σ is an interfacial energy, D is a diffusion
coefficient of the solute molecule, ν is a volume of a solute
molecule, t is time, Ceq is a solute solubility, C is a solute concentration,
and S is a supersaturation ratio, C/Ceq. All values are in terms of the
solution, such as the mixture of 10 vol % of THF and 90 vol % of H2O (noted as 1THF/9H2O) used in this study. The
particle size is thus proportional to t1/3. With a specific drug compound, only Ceq and C alter the coarsening rate, dr̅/dt. With a constant C, increasing
the ratio of the organic solvent over water increases Ceq and thus dr̅/dt. To inhibit the Ostwald ripening for a given hydrophobic drug, therefore,
a minimum usage of the organic solvent is desired. For most hydrophobic
drugs, the range of σ, D, and ν typically
are less than 10-fold. However, the difference of Ceq can vary much larger than 10-fold. Ceq dominates the Ostwald ripening, and a lower Ceq is desired for the stability.In experiments,
the solubility of paclitaxel was 25 μg·mL–1 in 1THF/19H2O.[23] The PLGA-b-PEG/paclitaxel nanoparticles grew from
about 100 nm to tens of micrometers within 90 min (see Figure 3a and b). β-carotene had a solubility of 3.1
ng·mL–1 in 1THF/9H2O. The β-carotene
particles without adding any stabilizer spent about four hours growing
from 89 nm to about 180 nm, and all of the particles sedimented on
the bottom with the colorless supernatant within one day.[23] With PLGA-b-PEG, the particle
size slowly increased from 57 to 90 nm in 3 weeks[27] and was much more stable than PLGA-b-PEG/paclitaxel
nanoparticles. Paclitaxel 2′,7-bis(triethoxysilicate) even
had a lower solubility, was out of the detection limit of HPLC, and
was not able to be obtained in this study (<1 ng·mL–1). The particles spent 8 days growing from 55 to 153 nm (see Figure 4c and d). With PLGA-b-PEG, the
particle size slowly increased from 86 to 102 nm in 6 days (see Figure 5b). These comparisons showed that by changing the
drug solute, the lower the drug solubility in the aqueous medium,
the more stable the particles made via FNP. This observation was consistent
with the prediction by the LSW theory above that Ceq dominated the Ostwald ripening, and a lower Ceq was desired for the stability. Also it was
consistent with the study by Liu et al. on Ostwald ripening of β-carotene
nanoparticles where the β-carotene nanoparticles were made via
FNP but changing the ratio of THF over water. They made the same conclusion
that with FNP the lower the solute solubility in the mixture, the
slower the growth rate of the particles.
Figure 3
SEM images of PLGA(10k)-b-PEG(2k) (25 mg)/paclitaxel
(25 mg) nanoparticles made with 5 mL of THF and 95 mL of H2O (a) sprayed within 1 min on a silicon wafer (the scale bar is 100
nm) and (b) sprayed within 90 min, showing grown paclitaxel needles
(the scale bar is 10 μm). Particle size and distribution (c)
in 30 min and (d) in 120 min.
Figure 4
SEM images
of paclitaxel 2′,7-bis(triethoxysilicate) (35
mg, molar equivalent to 25 mg of paclitaxel) nanoparticles made with
5 mL of THF and 95 mL of H2O (a) sprayed within 1 min on
a silicon wafer and (b) sprayed in 8 days (both scale bars are 100
nm). Particle size and distribution w/o saline (c) in 10 min and (d)
in 8 days. ζ = +24 mV before adding saline, and the nanoparticles
grew to visually detectable size instantly after adding 1 wt % saline
and had ζ = +2.8 mV.
Figure 5
PLGA(10k)-b-PEG(2k) (25 mg)
protected paclitaxel
2′,7-bis(triethoxysilicate) (35 mg, molar equivalent to 25
mg of paclitaxel) nanoparticles made with 5 mL of THF and 95 mL of
H2O and (a) sprayed within 1 min on a silicon wafer (the
scale bar is 100 nm); (b) particle stability against time for 6 days;
(c) particle size distribution by DLS in 20 min without saline. No
noticeable size increase after adding saline in the 6th day, indicating
the nanoparticles were sterically stabilized by PLGA(10k)-b-PEG(2k).
SEM images of PLGA(10k)-b-PEG(2k) (25 mg)/paclitaxel
(25 mg) nanoparticles made with 5 mL of THF and 95 mL of H2O (a) sprayed within 1 min on a silicon wafer (the scale bar is 100
nm) and (b) sprayed within 90 min, showing grown paclitaxel needles
(the scale bar is 10 μm). Particle size and distribution (c)
in 30 min and (d) in 120 min.As described by the Kelvin equation (eq 8), small particles have a higher solubility than large particles.where Ceq(r) is a solubility surrounding
a particle of a radius r, and Ceq(∞) is a bulk solubility. The capillary
length, l,
is a characteristic length below which curvature-induced solubility
is significant and defined as l ≡ 2σν/kbT. As predicted by
the LSW theory, a higher Ceq of small
particles is able to accelerate Ostwald ripening. Therefore, the initial
particle size distribution is expected to have an effect in some degree
on the particle stability and is discussed here.With BCPs,
the particles of a hydrophobic drug made via FNP were
believed to be surrounded by amphiphilic BCPs via a kinetic process
during drug precipitation,[18,21,27] and the interfacial energy of the particles was reported by Johnson
et al. as σ = 1.9 × 10–3 J·m–2.[18] Liu et al. used this
value and well predicted Ostwald ripening of PEGylated BCP protected
β-carotene nanoparticles in THF/water (6/120–30/120)
mixtures.[21] This value is thus taken herein.
With a molecular weight of 854 g·mol–1 and
an assumption of the drug density of 1.0 × 103 kg·m–3, ν of 1.42 × 10–27 m3·molecule–1 and l of
1.33 nm at room temperature can be estimated. Since l/r ≪ 1, eq 8 can be
linearized into eq 9.If the particle size distribution at 30 min
given by DLS in Figure 3c is considered as
the initial distribution of the PLGA-b-PEG/paclitaxel
nanoparticles, the solubility ratio of the lower radius limit (rmin) over the upper (rmax), Ceq(16 nm)/Ceq(314 nm), was calculated as 1.08. Without BCPs, paclitaxel
nanoparticles had σ = γwater – γdrug = 7.28 × 10–2 – 6.85 ×
10–2 = 4.3 × 10–3 J·m–2 (surface tension of drug γdrug =
6.85 × 10–2 J·m–2 calculated
with ACD/I-Lab). l of 3.02 nm and Ceq(16 nm)/Ceq(314 nm) of 1.18
were also calculated. Compared with solubility changes by using other
drugs, this small solubility difference (Ceq(rmin)/Ceq(rmax) ≈ 1) between large and
small paclitaxel particles was insignificant. Therefore, for PLGA-b-PEG/paclitaxel nanoparticles the effect of the particle
size distribution on Ostwald ripening was negligible.For β-carotene
itself, nanoparticles[27] had σ = γwater – γdrug = 3.65 × 10–2 J·m–2 (γdrug = 3.63 × 10–2 J·m–2 calculated with ACD/I-Lab) and molecular weight of
537 g·mol–1. l of 16.1 nm
and Ceq(13 nm)/Ceq(249 nm) of 3.23 at 10 min were estimated by eq 8. In the same way, for paclitaxel 2′,7-bis(triethoxysilicate)
nanoparticles (see Figure 4c) with σ
= γwater – γdrug = 2.05 ×
10–2 J·m–2 (γdrug = 5.23 × 10–2 J·m–2 calculated with ACD/I-Lab) and molecular weight of 1178 g·mol–1, l of 19.8 nm and Ceq(8 nm)/Ceq(125 nm) of 10.1
at 10 min were estimated. By comparing the initial Ceq(rmin)/Ceq(rmax), PLGA-b-PEG/paclitaxel nanoparticles (1.08) < β-carotene nanoparticles
(3.23) < paclitaxel 2′,7-bis(triethoxysilicate) nanoparticles
(10.1). As predicted by the LSW theory, the stability trend should
be PLGA-b-PEG/paclitaxel nanoparticles > β-carotene
nanoparticles > paclitaxel 2′,7-bis(triethoxysilicate) nanoparticles.
However, this stability trend was opposite to the observed trend.
Therefore, compared with the solubility changes by using different
drugs, the solubility difference between the small and the large particles
made via FNP was considered to have an insignificant effect on the
particle stability. The particle size distributions were narrow enough
in terms of Ostwald ripening to study particle stability.The
third instability source is recrystallization, which converts
amorphous particles into crystalline ones, since amorphous drugs have
a higher solubility than the crystalline counterparts. The driving
force is to lower the free energy of the solid state. It is a reorganization
process of the precipitated solute molecules. Solvent molecules dissolved
in the solute matrix provide free volume, facilitate the relaxation
of the solute, and increase the rate of recrystallization inside the
particles. Since intraparticle recrystallization barely changes the
nanoparticle volume and all instable systems in this study showed
a significant volume increase of individual particles, intraparticle
recrystallization would not be studied in this paper. However, interparticle
recrystallization is able to significantly increase the particle volume.
The process requires solute molecules migrate from one particle to
another via either Ostwald ripening or particle aggregation. By adding
surface steric stabilizer, such as PLGA-b-PEG, particle
aggregation can be effectively hindered. Ostwald ripening again as
the source of particle instability and shown above has to be considered
in this study.
Enhanced Stability with Chemical Modification
As discussed
above with the LSW theory, the solubility of Ceq plays an important role on nanoparticle stability. For a
given drug compound, the water solubility can be decreased by (1)
decreasing the ratio of organic solvent over water,[19,21] (2) choosing a relatively poor organic solvent, or (3) being chemically
modified, such as bonding to a hydrophobic moiety or form a salt.
However, the amount of organic solvent was limited by the solubility
of a drug in it and processing conditions during feeding and cannot
be infinitely decreased. Feeding more water to decrease the ratio
of organic solvent over water will dilute the product too much, and
the concentration is too low. The option of organic solvents is limited
by water miscibility, solvent toxicity, and easiness of solvent removal.
Moreover, some drugs are relatively too water-soluble. A possible
approach is to modify the chemical structure of the drug and make
it less soluble. In this study, therefore, paclitaxel was chemically
bonded with ethoxysilicate (see Scheme S1a in
Supporting Information), which was a hydrophobic moiety and
was expected to be easily cleaved under an acidic condition in tumors.
Much work on hydrolysis of various paclitaxel organosilicate vs pH
was studied by Wohl[30] and showed promising
results for a controlled release in a mimic condition of tumor cells.
While at neutral pH, it was chemically very stable. In this study,
as shown in Figure 4c and d, even without the steric stabilizer of PLGA-b-PEG, d̅m of the paclitaxel 2′,7-bis(triethoxysilicate)
nanoparticles only increased from 55 to 153 nm in 8 days, showing
significant improvement of the particle stability compared with PLGA-b-PEG/paclitaxel particles with grown micrometer needles
in 90 min (see Figure 3b). Figure 4a and b showed that the particles remain spherical
for at least 8 days. The improved stability in the morphology and
the size indicated that the Ostwald ripening and recrystallization
were significantly inhibited. The strategy of chemical bonding the
marginally hydrophobic drug with hydrophobic moieties succeeded.SEM images
of paclitaxel 2′,7-bis(triethoxysilicate) (35
mg, molar equivalent to 25 mg of paclitaxel) nanoparticles made with
5 mL of THF and 95 mL of H2O (a) sprayed within 1 min on
a silicon wafer and (b) sprayed in 8 days (both scale bars are 100
nm). Particle size and distribution w/o saline (c) in 10 min and (d)
in 8 days. ζ = +24 mV before adding saline, and the nanoparticles
grew to visually detectable size instantly after adding 1 wt % saline
and had ζ = +2.8 mV.It was found that the paclitaxel 2′,7-bis(triethoxysilicate)
nanoparticles without the stabilizer had surface charges (ζ
= +24 mV) to inhibit the aggregation. After adding 1 wt % saline,
however, ζ decreased to +2.8 mV. The nanoparticles grew rapidly
and became visually detectable. The steric stabilizer, PLGA-b-PEG, was thus used to inhibit the aggregation. As shown
in Figure 5b, the
particles had a good stability with size increasing from 86 to 102
nm after 6 days without saline. After adding 1 wt % saline in the
6th day, no visible aggregation was observed. The DLS showed that
the size barely changed.PLGA(10k)-b-PEG(2k) (25 mg)
protected paclitaxel
2′,7-bis(triethoxysilicate) (35 mg, molar equivalent to 25
mg of paclitaxel) nanoparticles made with 5 mL of THF and 95 mL of
H2O and (a) sprayed within 1 min on a silicon wafer (the
scale bar is 100 nm); (b) particle stability against time for 6 days;
(c) particle size distribution by DLS in 20 min without saline. No
noticeable size increase after adding saline in the 6th day, indicating
the nanoparticles were sterically stabilized by PLGA(10k)-b-PEG(2k).
Stability Prediction
As described with the LSW theory
as well as observed in above experiments, the solubility of a hydrophobic
compound has dominant effects on the stability of the formed nanoparticles
in terms of Ostwald ripening and interparticle recrystallization.
For a random given drug to generate nanoparticles via the FNP, it
would be good to measure first the solubility in the solvent/antisolvent
mixture. If changing the ratio of the solvent to antisolvent is necessary
to optimize the process, a phase diagram is desired as well. In practice,
however, measuring the solubility and stability could be very time-consuming,
a quantitative relation between solubility with stability is unclear,
and generated nanoparticles are not necessarily sufficiently stable.
Therefore, having a theoretical indication of the solubility, the
correlation of this indication with the particle stability and then
a prediction of the stability are very meaningful. This approach is
also very useful to give a guideline before doing any chemical modification
of a drug compound.In this study, two well-known physical parameters,
Hildebrand solubility parameter (δ)[41] and LogP,[42] were investigated
to tentatively build the correlation between the solubility and the
stability. δ provides a numerical estimate of the degree of
interaction between materials, particularly for nonpolar materials
such as many polymers. Materials with similar values of δ are
likely to be miscible. It can be a good indication of solubility.
As well, the lower δ is, the higher the hydrophobicity is. The
octanol–water partition coefficient is a ratio of concentrations
of un-ionized compound between immiscible octanol with water. The
logarithm of the partition coefficient is called LogP. It is one of simple molecular descriptors in Lipinski’s
“Rule of 5”.[1] It serves as
a quantitative indication of lipophilicity and has been widely employed
in the pharmaceutical industry.Hydrocortisone, hydrocortisone
ethoxysilicate, and betulin were
therefore added to the list for the correlation study. As reported,
hydrocortisone has a water solubility of 0.3 mg/mL.[43,44] After adding 10 vol % of good solvent, i.e.,THF, the solubility
would be much higher. As expected, 50 mg of hydrocortison in 10 mL
of THF and 90 mL of H2O did not generate a detectable scattered
intensity by DLS, indicating nanoparticles were not generated since
the solubility was too high. Its analogue, hydrocortisone ethoxysilicate,
was thus synthesized to increase the hydrophobicity and lower the
solubility. The nanoparticles (50 mg) of hydrocortisone ethoxysilicate
had d̅m of 252 nm after 10 min than
the formation in 10 mL of THF and 90 mL of H2O and showed
fast increasing size in the next 10 min during the DLS measurement.
Unfortunately, hydrocortisone ethoxysilicate hydrolyzed fast back
into more hydrophilic hydrocortisone, and the nanoparticle size decreased
as the time went during the next six days (see Figure S2 in Supporting Information). It therefore was not
a good candidate for studying the nanoparticle stability herein but
able to give another example of the fast size increase at least in
the first 20 min.For betulin, like paclitaxel in Figure 3, the nanoparticles were not stable. The suspension
changed from
water clear to cloudy with visible needles within 30 min, indicating
fast Ostwald ripening and recrystallization. The SEM image (see Figure
S3 in Supporting Information) showed grown
crystalline needles sprayed on a silicon wafer within 30 min after
mixing.Table 1 listed δ and LogP of the drugs or their analogues. δ did not show
a good correlation
with the nanoparticle stability. The reason could come from the limitation
of δ, which was not suitable for polar compounds especially
with hydrogen bonds (such as water).[41,46,47] On the contrary, LogP showed a good
correlation. Empirically, with ACDLogP > ∼12,
nanoparticles showed good stability; with ∼2 < ACDLogP < ∼9, nanoparticles showed fast Ostwald ripening
and recrystallization; with ACDLogP < ∼2,
the drug is too soluble and very likely difficult to generate nanoparticles.
In order to fill the gap of this rule, over 2000 anticancer drugs
in the NCI dictionary were also screened, and very few real drugs
have been found to have ACDLogP of greater than 9,
since most of the super hydrophobic potential drugs had been abandoned
by the pharmaceutical industry due to an extremely low dissolution
rate. But one would reasonably expect that a drug with ∼9 <
ACDLogP < ∼12 is marginal.
Table 1
ACDLogP and δ
of Various Organic Compounds against Nanoparticle Stability
organic compound
δa (MPa1/2)
ACDLogP
stable (Y/N)
hydrocortisone
23.2
1.43 ± 0.47
no particle
odanacatib
29.7
2.92 ± 0.85
N[28]
curcumin
22.8
2.92 ± 0.48
N
itraconazol
19.1
4.35 ± 1.22
N[28]
hydrocortisone ethoxysilicate
21.2
6.37 ± 0.72
N
paclitaxel
22.3
7.38 ± 0.83
N
betulin
18.7
9.01 ± 0.39
N
vitamin E succinate
18.5
11.88 ± 0.30
Y[45]
paclitaxel 2′-triethoxysilicate
21.4
13.09 ± 1.00
Y[30]
paclitaxel 2′-trii-propoxysilicate
21.0
14.13 ± 1.01
Y[30]
β-carotene
17.8
15.51 ± 0.43
Y
paclitaxel 2′,7-bis(triethoxysilicate)
20.8
18.36 ± 1.15
Y
tetramenthoxysilane
16.7
18.66 ± 0.66
Y[30]
Estimated with the Hoye method as
well as assumed to treat the Si atom as a C atom.
Estimated with the Hoye method as
well as assumed to treat the Si atom as a C atom.
Rule Limitations
It was found that
without adding any
surface stabilizer β-carotene particles made via FNP showed
good short-term (∼4 h) stability due to slightly negative surface
charge[48] as judged by zeta potential measurements.[23] Paclitaxel 2′,7-bis(triethoxysilicate)
particles in this study (see Figure 4) showed
no sediment for 8 days. Compared with the time of the measurements
and possible postprocessing, this stability was long enough. By using
β-carotene therein, the effects of the hydrophobic drug on particle
instability were able to be removed so as the effects of mixer designs,[24] mixing processes,[23,27] and surface
stabilizers[23,27] can be individually studied.
It was also found that even with sufficient mixing some polymeric
stabilizers (e.g., PLA-b-PEG and PCL-b-PEG) destabilized the particles due to their undesired physical
properties (e.g., relatively low glass transition, polymer crystallization,
and unsuitable solubility parameters).[27] However, PLGA-b-PEG, an amphiphilic diblock copolymer,
had no negative impact on β-carotene particle stability. Moreover,
with very similar experimental conditions of this study, the molecular
weight of PLGA block over the range from 5k to 15k showed an insignificant
effect on controlling the particle stability.[27] PLGA-b-PEG as a model polymeric surfactant therefore
was used in this study to investigate the effects of the hydrophobic
drugs. The empirical rule above was based on this surfactant, which
did not have undesired physical properties to rather destabilize the
particles like PCL-b-PEG or PLA-b-PEG.[27]It is known that the solubility
of a drug in the water/solvent mixture also depends on the type of
a solvent and a feed ratio with water. The drug and polymer have to
be molecularly dissolved in a solvent before jets mixing with water.
With a fixed amount of drug or polymer, the solvent had a minimum
amount. However, adding too much solvent required much more water
to obtain either a high drug recovery or a stable nanosuspension with
limited Ostwald ripening and recrystallization, which decreased the
final concentration of the drug suspension. It has been found that
in the FNP technique for β-carotene, paclitaxel and its prodrugs,
50 mg of a drug (or with extra 10 to 50 mg of a polymer) dissolving
in 10 mL of a solvent and mixed with 90 mL of water (0.5 mg/mL of
a drug in production) was the most suitable combination.[19,21−23,27,30] The above empirical rule was based on this combination at room temperature.
For some cases, water was doubled in purpose, but no further dilution
was taken, which would trouble the particle postprocessing by freeze
or spray drying. In Table 2, ACDLogP and boiling point of common water miscible organic solvents
were listed. THF was a relative hydrophobic solvent, and a good solvent
for many organic drugs as well as for many common polymers. For drugs
with ACDLogP > ∼2, acetone was tested with
paclitaxel and its multiple prodrugs.[30] Their stability still well followed this empirical rule. For drugs
with ACDLogP < ∼2, a less hydrophobic solvent
such as acetone, ethanol (with ACDLogP slightly lower
than zero), or their mixture with THF can be considered to generate
instable naoparticles, which could decrease this empirical value.
But a value of no less than zero is still expected.
Table 2
ACDLogP and Boiling
Point of Water, Octanol, and Various Water Miscible Organic Solvents
water miscible solvent/antisolvent
boiling pointa (°C)
ACDLogP
methanol
65
–0.72 ± 0.18
ethanol
78
–0.19 ± 0.18
n-propanol
97
0.34 ± 0.18
ethylene
glycol
197
–1.69 ± 0.21
1,2-propylene
glycol
187
–1.34 ± 0.22
glycerin
182
–2.32 ± 0.49
acetonitrile
81
–0.45 ± 0.19
acetone
56
–0.16 ± 0.19
dimethyl sulfoxide (DMSO)
189
–1.35 ± 0.28
N,N-dimethylformamide (DMF)
153
–1.01 ± 0.28
tetrahydrofuran (THF)
66
0.33 ± 0.22
hexafluoroisopropanol (HFIP)
59
1.91 ± 0.79
water
100
–1.38 ± 0.21
n-octanol (water immiscible)
196
3.00 ± 0.18
From Sigma Aldrich
Inc.
From Sigma Aldrich
Inc.It should be noted
that LogP of a substance is
most relevant for neutral substances and is useful as a general reference
point to help compare overall hydrophobicity trends of compounds.
LogP does not account for modifications in the hydrophobicity
of ionizable compounds at varying pH. The appropriate descriptor for
these compounds is the distribution coefficient, D (also typically used in its logarithmic form, logD).[49] Since the software to calculate logD is not free for the public, LogP would
be better to demonstrate this work to the interested readers. The
algorithm model used in this study is ACDLogP developed
by the ACD company, since this model has been used by some of the
world’s largest pharmaceutical companies (e.g., GlaxoSmithKline
and Pfizer) and the ACD company also developed LogD model. There are various similar algorithm models available (e.g.,
ALogP, ALogPs, ABLogP, AClogP, COSMOFraq, cLogP, MlogP, MiLogP, ProLogP, XLogP, and LogKOW). Each algorithm model has its own
strengths and exceptions,[50,51] but the comparable
LogD model is not developed for all LogP models. Depending on the water miscible organic solvent used in
the FNP (e.g., THF, acetone, ethanol, or their mixtures), different
algorithm models of LogP possibly need to be tested
for the exceptions.
Conclusion
In this study, the effects
of the hydrophobic drug molecules on
particle stability were investigated. The work demonstrated that chemically
bonding a drug compound (e.g., paclitaxel) with a cleavable hydrophobic
moiety of organosilicate (e.g., triethoxysilicate) was able to significantly
improve the particle stability, expectedly due to a decreased drug
solubility and thus lowered interparticle molecular migration. This
modification opened an approach to enhance the particle stability
generated by FNP. Even without any surfactant but with slight surface
charges, paclitaxel 2′,7-bis(triethoxysilicate) nanoparticles
showed moderate stability (no sediment for 8 days). To better stabilize
the particles, PLGA-b-PEG was used as a model surface
stabilizer, whose hydrophobic block was noncrystallizable as well
as had relatively high glass transition temperature and a right solubility
parameter, ensuring no unexpected particle destabilization introduced
by this additive.[27]By changing the
solute with various drugs mostly from the NCI drug
dictionary and their analogues, the study showed that the lower the
solubility in the aqueous medium the greater the particle stability
in terms of Ostwald ripening, which was consistent with the prediction
by the LSW theory. The particle size distribution made via FNP was
sufficient narrow. Compared with a solubility change by using a different
drug solute, the particle solubility between small and large particles
showed a negligible effect on Ostwald ripening.The experiments
showed that the initial particle size distribution
made via FNP was bimodal or even trimodal rather than lognormal. Since
the DLS apparatus typically cannot differentiate size peaks within
3-fold, in some case the distribution appeared unimodal. Very little
has been known about the FNP kinetics which evolves in micro to miliseconds
and a nanoscale. This study considers the non-lognormal and non-unimodal
size distribution as evidence for “cluster–cluster aggregation”[22,27] rather than “nucleation and growth”.[18]To correlate the drug hydrophobicity with particle
stability, δ
and LogP were used as hydrophobicity indications
for the drug compounds. LogP showed a good correlation
with the nanoparticle stability. Empirically, with ACDLogP > ∼12, nanoparticles showed good stability; with ∼2
< ACDLogP < ∼9, nanoparticles showed
fast Ostwald ripening and interparticle recrystallization; with ACDLogP < ∼2, the drug was too soluble and very likely
difficult to generate nanoparticles. With ∼9 < ACDLogP < ∼12, the drug was expected to be marginal.
This work introduced LogP into the flash nanoprecipitation,
created a quick way to predict particle stability for a randomly selected
drug structure enabling a fast preclinical drug screen, and provided
a possible approach to enhance the particle stability. The limitations
of the rule were also discussed.
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