Article pubs.acs.org/IECR
Dissolution, Nucleation, Crystal Growth, Crystal Aggregation, and Particle Breakage of Amlodipine Salts: Modeling Crystallization Kinetics and Thermodynamic Equilibrium, Scale-up, and Optimization Andrej Pohar† and Blaž Likozar*,†,‡ †
Laboratory of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry Slovenia, Hajdrihova 19, 1000 Ljubljana, Slovenia ‡ Faculty of Chemistry and Chemical Technology, University of Ljubljana, Aškerčeva 5, 1000 Ljubljana, Slovenia S Supporting Information *
ABSTRACT: Both in the pharmaceutical industry and in pharmacology, crystallization and dissolution processes play an important role in the production and physiological action of active pharmaceutical ingredients. For the first, recrystallization or other phase transformations present an indispensable step in downstream separation and purification processing, while for the second, solubility is of vital importance for drug delivery systems such as tablets. In the present study, the anhydrous form of amlodipine was investigated from its basic structural and conformational characteristics using molecular modeling, to the laboratory-scale formation of its solid phase from solution, and finally, to industrial-size operation by applying models, based on the hydrodynamic characteristics in the crystallizer due to mixing (computational fluid dynamics (CFD)), transport phenomena (specifically heat transfer), and population balance modeling. Simulations revealed that an efficient process intensification and control may be realized through the seeding and widening of the metastable zone (nucleus absence albeit supersaturation), providing a uniform and monodisperse size distribution.
1. INTRODUCTION Amlodipine ((RS)-3-ethyl 5-methyl 2-[(2-aminoethoxy)methyl]-4-(2-chlorophenyl)-6-methyl-1,4-dihydropyridine-3,5dicarboxylate) salts such as besylate, mesylate, or maleate belong to the group of dihydropyridine calcium channel blockers.1 Amlodipine maleate (AM) is the calcium channel antagonist of the dihydropyridine class and is used for the treatment of hypertension and coronary artery disease.1,2 The radiation sensitivity of this active ingredient in a wide dose range is low, thus exhibiting the potential for radiosterilization.3 Crystallization, precipitation, dissolution, and related phenomena play an important role both in the production process of amlodipine in the pharmaceutical industry as well as in its end-user application in drug delivery systems. Crystallization and dissolution are mainly governed by several parallel processes, which finally lead to chemical and physical equilibrium. The mentioned processes include crystal nucleation, growth, aggregation, and breakage.4 These processes are thus governed by mass transfer and kinetics (e.g., diffusion of solute to liquid/solid interface and subsequent incorporation into the crystal lattice) but ultimately approach equilibrium both in terms of the liquid phase concentration and crystal size distribution. Although amlodipine is produced and consumed in large quantities worldwide, the mechanisms of its crystallization and dissolution, pertinent to both its downstream processing and drug release, were not extensively investigated, at least not in a quantitative manner. Most of the research of amlodipine precipitation is closely related to liquid chromatography, that is © 2014 American Chemical Society
the development of analytical procedures for its determination in a mixture of components.5−10 On the other hand, the physical and chemical characteristics and solid phase composition of the hydrated and anhydrous crystal forms of amlodipine salts (besylate and saccharinate) have been examined in several studies, for example, by Rollinger and Burger,1 Banerjee et al.,2 and Koradia et al.11 Additionally, the resolution, chelation, and binding of amlodipine besylate by tartrate, cyclodextrin, and cytochromes and the corresponding influence on the crystal structure were presented by Gotrane et al.,12 Bradea et al.,13 and Shah et al.14 While this binding promotes structural stability, γ radiation3 and elevated temperature15 cause its degradation. Considering quite a few studies elucidating the crystal structure and properties, very little is known about the mechanisms of the crystallization and dissolution of amlodipine salts, and some aspects of the processes are presented by Koradia et al.,16 Boetker et al.,17 and Qu et al.18 Computational fluid dynamics (CFD) has been recognized as an indispensable tool for modeling fluid dynamics in industrial crystallization systems. Furthermore, when coupled with crystallization kinetics, progress has been made in the understanding of the operational characteristics and has opened new ways for the optimization of existing industrial crystallization processes. Erriguible et al.19 recognized CFD Received: Revised: Accepted: Published: 10762
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All spectra were collected within 0.3 s collection time and with the resolution of 8 (the spectrum is produced with 1 data point for each 4 wavelengths over the specified spectral range). The homogeneous solutions of AM salt were prepared and well mixed by the stirrer prior to crystallization. 128 scans were collected with FTIR for each suspension spectrum and averaged. The spectra were then pretreated with Happ−Genzel apodization, and user-defined baseline models were established to predict the composition using the spectra of the suspensions of AM with ethanol. 2.2.2. Dissolution on the Laboratory Scale. Ethanol solubility of the anhydrous solid form of AM was measured at different temperatures (∼10, 20, 30, 40, 50, 60, 70, and 75 °C). Different amounts of solid AM were gradually added to 100 mL of pure ethanol in the 100 mL reactor, equipped with a magnetic stirrer. Spectra were collected using the FTIR spectroscopy probe at certain time intervals. AM solutions were thus analyzed online with the FTIR spectrometer. The concentrations of solutions were calculated with the validated calibration model, based on the absorbance at the wavenumber (FTIR) of 1212 cm−1. 2.2.3. Crystallization on the Laboratory Scale. The crystallization of the anhydrous solid form of AM from ethanol was monitored at different cooling and mixing rates (∼10, 15, 20, 25, 30, and 35 °C/h and 0, 150, 225, and 300 rpm, respectively). Eleven grams of solid AM was added to 100 mL (all component volumes were measured at 20 °C) of pure ethanol in the 100 mL reactor, equipped with a magnetic stirrer, at 75 °C. Temperature overshooting was used in order to ensure the complete dissolution of the solute prior to cooling, to make sure there were no nuclei present in the solution. Samples were taken out with 3 mL Pasteur pipettes at certain time intervals. The suspension samples were then filtered and analyzed with scanning electron microscopy and dynamic light scattering. The concentrations of solutions were calculated with a validated calibration model, based on the absorbance at the wavenumber (FTIR) of 1212 cm−1. 2.2.4. Crystallization on the Industrial Scale. Industrial crystallization of the anhydrous solid form of AM from ethanol was performed at different filling times (8−20 min), cooling times after filling to 25 °C and from 25 to 0 °C, and mixing rates during filling and crystallization (70 and 100 rpm). Approximately 100 kg of solid AM was added to 1000 L of pure ethanol in the 3580 L reactor, equipped with the Intermig impeller and an impeller with curved blades, at 55−70 °C. The suspension samples were analyzed with dynamic light scattering. The distributions of particles were calculated with a validated calibration model. 2.2.5. Scanning Electron Microscopy (SEM). Solid samples were analyzed prior to dissolution and after crystallization experiments using a scanning electron microscope (Zeiss Supra 35VP, Carl Zeiss, Jena, Germany), equipped with Zeiss SmartSEM (version V05.03.05) software, scanning the area between 10 × 10 μm and 4 × 4 mm. For SEM experiments, samples were dispersed on carbon tape on a carrier. 2.2.6. Dynamic Light Scattering (DLS). The formed crystals of AM, suitable for size determination, were obtained by the methods described above. Crystal distribution scattering analysis was performed at 12 °C and at standard pressure (1 bar). Data were collected using monochromate laser radiation (λ = 780 nm) on a Microtrac S3500 Analyzer System (Montgomeryville, PA, USA) using Flex software.
modeling as a suitable tool to better identify the important parameters of the process, for the case of a crystallization process induced by supercritical CO2. Wei20 has shown how CFD simulations coupled with crystallization kinetics can offer a guide to efficient scale-up strategies, without which an industrial crystal size distribution could not be predicted. The population balance method and computational fluid dynamics were combined in a work by Lian et al.21 Crystal nucleation and growth kinetics have been described by the discrete population balance equation which allowed for the prediction of the crystal size distribution, which was comparable to the experimental data. Kougoulos et al.22 have shown how CFD gives a qualitative engineering insight into the effects of the impeller configuration on the crystallization rates and particle size distribution. The necessity to model the interaction of multiple process phenomena, which all have to be considered to fully describe the crystallization process, was recognized by Kulikov et al.23 They showed how coupled simulation enables a rigorous description of the crystallization process. The current study demonstrates the description of dissolution, nucleation, growth, aggregation, and breakage of amlodipine salt crystals, utilizing appropriate models24−28 to analyze diffusive, kinetic, and equilibrium phenomena, relevant to the described simultaneous crystallization processes. The models may be used for both drug delivery systems (dissolution) as well as for the demonstrated scale-up and optimization of the industrial operation. It was displayed how a wholesome treatment of an industrial cooling crystallization process can accurately describe the operation and can be used for the prediction of the crystal size distribution with possible process optimization.
2. MATERIALS AND METHODS 2.1. Materials. The cardiovascular bioactive substance, anhydrous amlodipine maleate, was obtained from Krka, d. d., Novo mesto (Novo mesto, Slovenia) (EP/USP grade, assay: >99 wt %) and was used as received as the model compound in the present work. The anhydrate AM was produced by the dissolution of AM suspension and subsequent cooling crystallization of AM from the ethanol solution, respectively. The solvent used was ethanol (CH3CH2OH) (having ≤0.02 wt % in water weight), purchased from Sigma−Aldrich (St. Louis, MO, USA) and used without further purification. Liquid nitrogen was acquired from Messer (Ruše, Slovenia). Carbon conductive adhesive tape G3939 was received from Christine Gröpl (Tulln, Austria). Blue ribbon filter paper circles were obtained from Whatman (Maidstone, UK). 2.2. Methods. 2.2.1. Fourier Transform Infrared (FTIR) Spectroscopy Instrumentation. Active ingredient solutions were prepared in a 100 mL reactor by mixing different amounts of the ingredient with 100 mL of ethanol using a magnetic stirrer. The temperature of the solution or suspension was monitored with a thermocouple during the entire dissolution or crystallization, and no significant change of the temperature from the set point was observed during the processes. During dissolution, different amounts of AM crystals were continuously added to the homogeneous solution. During crystallization, the AM−ethanol suspension was sampled and filtered at certain time intervals. The liquid solution or suspension was analyzed with the ASI Applied Systems ReactIR FTIR spectroscopy probe, interfaced with the Optics and Electronics Module (Millersville, MD, USA). The FTIR system employed the laser source within 650−4000 cm−1 operating at 2 × 104 intensity. 10763
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2.2.7. Molecular Modeling (MM). Molecular modeling computations were carried out at the level of the theory of ab initio, using the Møller−Plesset perturbation theory MP2 correlation, implemented in ChemBio3D program suite. For geometry optimization, 6-31G* basis set was used, and the properties of the optimized geometry were also computed using the same basis set. In the starting model, two AM units were positioned in the four corners of N−H−O interaction sites. To determine the structure of AM, the Polak−Ribière formula was used as the search model. ChemBioDraw, version 12.0 (registered for 2013, CambridgeSoft, Cambridge, MA, USA), was used for drawing the chemical structure of amlodipine. 2.2.8. Crystallization Modeling. The hydrodynamics, thermodynamics, kinetics, and heat and mass transfer during crystallization from the supersaturated solution of amlodipine maleate from the solution phase AM form to the solid phase AM form was studied by simulating solid AM formation from the dissolving medium using computational fluid dynamics (Fluent; Ansys, Canonsburg, PA, USA) and a code developed in Matlab (MathWorks, Natick, MA, USA).
d(Vjacketρglycol (Tjacket)c p,glycol(Tjacket)Tjacket) dt = UA(T − Tjacket) + Q glycolρglycol (Tjacket)c p,glycol(Tjacket) (Tjacket inlet − Tjacket)
Tjacket = Tjacket inlet
Nu = aRebPr1/3(μ bulk /μwall )c Nu =
= UA(Tjacket − T )
+ Qρethanol (Tinlet)c p,ethanol(Tinlet)Tinlet T = Tinlet T=T
Vsolution = 0 dVsolution =Q dt
dt
=
The overall heat transfer coefficient (U) was calculated according to eq 6.
t = tstart
−1 ⎛1 dx w 1⎞ U=⎜ + + ⎟ kw h2 ⎠ ⎝ h1
tstart < t ≤ tend
Tthermocouple = T
1 (T − Tthermocouple) τ
(5)
a = 0.36; b = 2/3; c = 0.18
(1)
(6)
dxw is the tank wall thickness, kw is its thermal conductivity, and h2 is the heat transfer coefficient at the outer tank wall side. The material properties of ethanol, 50 wt % ethylene glycol, and stainless steel (vessel wall) were described using temperature-dependent correlations (valid at 250−350 K). 3.2. Computational Fluid Dynamics (CFD) Modeling. CFD is considered a powerful simulation tool for the investigation of the operation of industrial crystallizers.28 The three-dimensional geometry of the crystallizer with the Intermig and blade impeller was modeled, meshed, and imported into Fluent. The Reynolds-averaged k−ε turbulence model with standard wall functions was used to model the turbulent flow inside the tank. Mixing was modeled with the rotating frame of reference technique, which has shown a good agreement with experimental data.30 The SIMPLE (SemiImplicit Method for Pressure Linked Equations) pressure− velocity coupling scheme was used, with the spatial discretization of all quantities of second order. For the resolution of boundary layers, the mesh was created with the inflation layer control at the crystallizer wall, assuring that the distance of the first node from the wall was positioned inside the log-law wall layer. The no-slip boundary condition was used at crystallizer walls and the free-slip boundary condition for the surface of fluid. Industrial agitators were revolving at 70 and
ρethanol and cp,ethanol are the density and heat capacity of ethanol, while U is the overall heat transfer coefficient, and A is the area of the tank, filled with AM solution (the area, available for heat transfer). Q is the feed volumetric flow rate. Vsolution is the solution volume; Tjacket is the temperature in the jacket, and T is the temperature inside the tank. Tinlet is the inlet temperature of the solution, which was between 55 and 70 °C, depending on the batch. tstart designates the time (t) at which the filling of the tank began, and tend is the end of filling. The thermocouple response (Tthermocouple), measuring the temperature inside the tank, was described with the following first-order equation, where twetting is the time, at which the solution reached the thermocouple, and τ is the thermocouple time constant. dTthermocouple
d impellerNρ c pμ bulk h1d vessel ; Re = ; Pr = k μ bulk k
(4)
Nu, Re, and Pr are the dimensionless Nusselt, Reynolds, and Prandtl numbers. μbulk and μwall represent the solution viscosity in bulk and at the wall. ρ, cp, and k stand for the density, heat capacity, and thermal conductivity of the solution. h1 is the heat transfer coefficient at the inner vessel side; dvessel is the inside diameter of the tank; dimpeller is the diameter of the agitator; N is the rotational speed. For the impeller with curved blades, the constants (a, b, and c) in use are as follows.29
3.1. Heat Transfer Modeling. The time-dependent temperature profile inside the industrial crystallizer was calculated for use with the population balance model. The energy balance for the crystallizer vessel is as follows.
dt
t=0
ρglycol and cp,glycol are the density and heat capacity of the cooling liquid (50 wt % ethylene glycol), while Qglycol is its volumetric flow rate. At time t = 0, Tjacket was approximated with Tjacket inlet, which is the temperature of the liquid at the jacket inlet. The differing of the properties of the coolant over the jacket was neglected, while the variation of properties with time was taken into account. The following correlation was used for obtaining the heat transfer coefficient inside continuous stirred-tank.29
3. MODEL
d(Vsolutionρethanol (T )c p,ethanol(T )T )
(3)
(2)
t = twetting
The energy balance for the jacket was approximated by an ideal continuous stirred-tank model. 10764
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100 rpm. Likewise, the laboratory experiments with the magnetic stirrer were modeled, revolving at 150, 225, and 300 rpm inside the 100 mL jacketed laboratory-scale crystallizer. Turbulent mixing characteristics (i.e., velocity magnitude and the rate of the dissipation of turbulent kinetic energy) were exported from the program for use with the population balance model, specifically, for agglomeration and breakage modeling. In order to obtain an insight into the temperature distribution inside the industrial crystallizer, additional heat transfer simulations were formulated. The temperature of the cooling fluid, obtained from the results of heat transfer modeling, was prescribed as the boundary condition of the crystallizer. The stainless steel wall of the tank was also considered in the simulations (with the thickness of 12 cm and temperature-dependent thermal conductivity). The convergence criterion required that the scaled residuals decreased to 10−4 for all equations except the energy balance equation, for which the criterion was 10−6. 3.3. Population Balance Modeling. The prediction of crystal number and size was performed using the population balance model (PBE) (eq 7), where Ni represents the number of particles per solution volume (1/m3), t is time (s), and Di is particle diameter (m). rgrowth,i, rnucleation, rB,aggregation,i, rD,aggregation,i, rB,breakage,i, and rD,breakage,i represent the rate of growth (m/s), nucleation (1/m3/s), the birth and death due to aggregation (1/m3/s), and the birth and death due to breakage (1/m3/s), respectively. The particle size distribution was determined using the discrete method, with which particles are arranged inside prescribed bins of specified sizes. Nucleation only occurs in the smallest size bin (i = 0) in which there is also no breakage, and growth and aggregation do not take place in the largest size bin.
rgrowth,i =
(cAM − cAM,int)
Sh = 2 + 1.10Re1/2Sc1/3
(9) (10)
The rate of aggregation may be written in the form of the Abrahamson model.31,32 This model was chosen due to its applicability for the turbulences of high intensity, generated in suspensions being pumped, and mixed under normal industrial conditions. Nb is the number of bins, Ni and Nj (1/m3) and Di and Dj (m) represent the numbers and diameters of aggregating AM solid particles, vi and vj (m/s) are their velocities, V stands for the corresponding volume of either aggregating (death) (V = Vi + Vj) or aggregated (birth) (V = Vi) AM solid particle, and Vsolution is for the volume of the solution. Other quantities originate from the empirical capture efficiency of the turbulent collision between interacting colliding particles introducing liquid viscosity μ (Pa s), Hamaker constant term (C (J m6) is the coefficient in particle−particle pair interaction, and nAM (1/ m3) is solid AM number density), and deformation rate term (ε (m2/s3) is the average rate of the dissipation of the turbulence kinetic energy per unit mass, and ν (m2/s) is the liquid kinematic viscosity). xj,k is the correction for the contribution to the aggregate bin (Vag/Vi, subscripts ag and i refer to aggregate and ith bin), since an aggregated particle is positioned in the bin with the closest particle size, and ξj,k is 0 for the largest bin size (no aggregation), while otherwise it is 1. Nb
rB,aggregation,i =
Nb
∑ ∑ NN j k a j,k x j,kξj,k (11)
j=1 k=1 Nb
rD,aggregation,i =
(7)
∑ NiNaj i,j (12)
j=1
The rate of nucleation may be written in power law form (eq 8),24−26 where An (1/m3/s), Ean (J/mol), and nn (unitless) represent the pre-exponential factor, activation energy, and order of nucleation and cAM and cAM * stand for a given and equilibrium AM concentration (g/L). The kinetic parameters were determined by regression analysis of the laboratory scale measurements. * ⎞ ⎛ −E ⎞⎛ c − cAM rnucleation = A n exp⎜ an ⎟⎜ AM ⎟ * ⎝ RT ⎠⎝ cAM ⎠
ρAM (1 − ϕ)
n * ⎞g ⎛ −Eag ⎞⎛ cAM,int − cAM ⎟⎟ = Ag exp⎜ ⎟⎜⎜ * ⎝ RT ⎠⎝ cAM ⎠
∂(Nirgrowth,i) ∂Ni + 0irnucleation + rB,aggregation,i =− ∂Di ∂t − rD,aggregation,i + rB,breakage,i − rD,breakage,i
2φkc,i
⎛ V 40Cπ 2nAM 2 a i,j = solution 0.732⎜⎜ 3 V ⎝ 6πμ(Di + Dj) (4ε)/(15πv) 23/2 π
nn
(Di + Dj)2 4
vi 2 + vj2
⎞0.242 ⎟ ⎟ ⎠ (13)
The rate of breakage may be written in the similar form of the Abrahamson model, 31,32 where V stands for the corresponding volume of either breaking (death) (V = Vi + Vj) or broken (birth) (V = Vi) AM solid particle. Breakage frequency f (defined as CbDi5/3vi2; Cb (s2/m11/3) being the constant of breakage) represents the number of AM solid particles, which are formed from particle i upon its collision with particle j and vice versa. The number 2 in eq 14 represents the birth of daughter particle-size distribution. The 2 particles with half the volume of parent particle were considered for the simulations.
(8)
The rate of growth may also be written in power law form,24−26 where Ag (m/s), Eag (J/mol), and ng (unitless) represent the pre-exponential factor, activation energy, and order of growth and cAM,int stands for the interface AM concentration (g/L). Furthermore, the rate of growth is determined by mass transfer as well, with kc,i representing the mass transfer coefficient in the liquid film (m/s), which is unique for each bin size, ρAM is the density of solid AM (kg/ m3), and ϕ is the volume fraction of the liquid (unitless). Mass transfer can therefore indirectly affect growth kinetics via its influence on the interface concentration. The mass transfer coefficient kc,i was calculated with the Frossling equation for solid−liquid interface, where Sh, Re, and Sc represent the dimensionless Sherwood, Reynolds, and Schmidt numbers, respectively.
Nb
Nb
rB,breakage,i = 2 ∑ ∑ NN j k bj,k x j,k j=1 k=1
(14)
Nb
rD,breakage,i =
∑ NiNbj i,j j=1
10765
(15)
dx.doi.org/10.1021/ie501572h | Ind. Eng. Chem. Res. 2014, 53, 10762−10774
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Figure 1. (a) The chemical structure of amlodipine maleate. (b) Tetramer structure of synthon of amlodipine maleate composed of −N+−H···O−− and −N+−H···O interactions. (c) Schematic representation of experimental and FTIR measurement setup. (d) FTIR spectra of amlodipine maleate (AM) samples during complete dissolution of increasing AM amount and ethanol reference spectrum as baseline; magnification of FTIR spectral region between 650 and 1800 cm−1 and 2400 and 4000 cm−1; dotted gray lines are at characteristic wavenumbers between 1019 and 3532 cm−1. (e) Calibration curves constructed from absorbance values at 1212 cm−1; error bars represent deviation. (f) van’t Hoff plot for the anhydrous form of AM (x*AM, T, and R2 denote equilibrium solubility of AM, temperature, and coefficient of determination).
bi,j =
(Di + Dj)2 1 3/2 f2 π vi 2 + vj2 4 V
(shown for the aliphatic C−N group for different temperatures in Figure 1e). While the concentration of AM (e.g., in Figure 1e) was presented as gAM/Lethanol at 20 °C, the concentrations acknowledging the thermal expansion of ethanol (e.g., for mass transfer coefficient calculation) were utilized in the model. It was observed that, within different low concentration ranges, the specified absorbance of AM solutions increased to a certain level. After that, the absorbance of AM solutions started to level, which was caused by the solid phase crystallization of AM. For example, for AM at 70 °C, the absorbance of AM in the solution increased until about 70 g/L and remained unchanged until 100 g/L, where the absorbance started to level due to crystallization. From this data, the solubility curve (thermodynamic equilibrium) was determined (Figure 1f), which was further used for population balance modeling. 4.2. Molecular Modeling. The chemical structure of AM is shown in Figure 1a. It has the molecular weight of 525 g/mol, pKa of 8.79, and logPn‑octanol/water of 2.36 (Table 1). The threedimensional figure of amlodipine was created using ChemBio3D from the structure, optimized using molecular modeling (Figure 1b). The molecular modeling results for AM are reported both to elucidate its optimized structure, which was previously determined only for amlodipine besylate and other salts by NMR, XRD, and molecular modeling, and to evaluate the realistic AM unit diameter, needed to calculate the mass transfer coefficient from the appropriate correlation (eq 10).
(16)
4. RESULTS 4.1. Concentration Measurements. The concentration inside the laboratory-scale crystallizer (Figure 1c) was measured online with an FTIR probe. The FTIR spectra of increasing AM concentrations and the baseline of the solvent are shown in Figure 1d. All liquid phases have the notable characteristic peaks on the FTIR spectra in the wavenumber range, shown in the figure. The FTIR spectra of the solutions, shown in Figure 1d, exhibit the highest peak at 1212 cm−1, corresponding to the aliphatic C−N group. It can be seen from Figure 1d that the FTIR spectra of different concentrations of amlodipine maleate do not exhibit any major peaks in the wavenumber range of 1800−3000 cm−1, and therefore, the FTIR spectra within that wavenumber range were selected to predominantly setup baseline models (beside end points), to predict the composition, using the spectra, taken from the solutions and suspensions of AM with ethanol. Since the FTIR spectra of amlodipine maleate show the significant peaks in the wavenumber range of 650−1800 cm−1, the heights of five AM peaks were monitored, using the spectra in this wavenumber range, to predict the composition of the liquid phase in the solutions and suspensions of AM with ethanol 10766
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Table 1. Selected Salient Physico−Chemical and Spectroscopic Data, and Properties of Active Pharmaceutical Ingredient (API) Amlodipine Maleate in Its Anhydrous Crystal Form, Used in This Study, Its Water Content, Parameters of Structure Refinement, Hydrogen Bond Lengths and Solubility name
marketed product
amlodipine
trade name
Amlodipine besylate, mesylate, and maleate
preparation route
Norvasc (besylate)
disease treated
crystallization from organic solvents
angina pectoris, hypertension, and coronary artery disease
structural formula
content of water (wt %)
formula weight (g/mol)
heat of formation (kJ/mol)
gradient (kJ mol−1 Å−1)
(C20H26ClN2O5) (C4H3O4)
