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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5980_Библиотеки_им_академика_М_И_Перельмана.pdf
36 Cocrystals in Pharmaceutical Sciences
oral bioavailability is only 65% to 80% due to poor aqueous solubility. A
screening of CBZ with dicarboxylic acids as coformers using solid-state
NMR identied malonic acid as forming strong O-H∙∙∙N and C-H∙∙∙O
hydrogen bonds based on chemical shi perturbations. X-ray crystal-
lography of the CBZ-malonic acid cocrystal conrmed the presence of a
reinforced synthon consisting of two N-H∙∙∙O hydrogen bonds and one
C-H∙∙∙O interaction. Dissolution rate studies showed a 400% increase in
IDR compared to CBZ due to improved wettability imparted by the syn-
thon. Oral administration of the cocrystal to rats resulted in a 30% increase
in bioavailability compared to CBZ alone [41]. ese experimental nd-
ings demonstrate how identifying a robust synthon through molecular rec-
ognition principles can yield a cocrystal with enhanced solubility and oral
absorption. Felodipine (FDP) is an antihypertensive drug limited by poor
aqueous solubility. Cocrystals were designed and synthesized between
FDP and nicotinamide (NAM) or isonicotinamide (INAM) using solvo-
thermal methods. X-ray studies showed FDP formed π-stacked dimers
that were further associated through N-H∙∙∙O hydrogen bonds with NAM
or INAM molecules. Dynamic vapor sorption experiments indicated a
twofold increase in aqueous solubility for the FDP-NAM cocrystal com-
pared to FDP alone. Permeability studies across a Caco-2 monolayer also
demonstrated a 1.5-fold enhancement for the cocrystal [42]. ese molec-
ular recognition-directed cocrystals led to improved solubility and perme-
ability proles governed by self-assembled supramolecular synthons. Such
properties indicate the propensity for enhanced oral absorption through
cocrystal formation.
2.2.2 Hansen Solubility Parameters (HSPs)
HSPs help understand and predict solubility, dispersion, and formulation.
ey explain the thermodynamics of substance dissolution and are based
on the idea that similar chemicals dissolve each other [36]. HSP character-
istics are useful for studying solubility, including pharmaceutical cocrys-
tals. When assessing solvent-solute compatibility, dispersion forces, polar
interactions, and hydrogen bonding must be considered. ese aspects are
vital to assessment. is approach allows for more advanced solvents that
dissolve the API and coformer, which is necessary for cocrystal formation.
Researchers use HSPs to estimate solubility and miscibility, which are essen-
tial for synthesizing cocrystals with specied features [37, 38]. e HSP
includes three main components: δD (dispersion), δP (polarity), and δH
(hydrogen bonding). e δD value measures van der Waals force strength
and describes interactions between nonpolar compounds. Chemistry
Design and Characteristics of Pharmaceutical Cocrystals 37
relies on polarity to characterize dipole moments and polar interactions.
e δH value expresses [39] hydrogen bonding capability. HSP oers a
more whole explanation since it anticipates solubility events outside of
“polar” and “hydrophobic.” Unlike LogP [40, 41], HSP factors several solu-
bility variables. HSP claries solvent-polymer interactions, guiding formu-
lation for useful applications. It inuences patent strategies and nds use in
numerous contexts. HSP oers a whole paradigm for solubility prediction
[42]. Forecasting cocrystal development calls for knowledge of HSPs. HSPs
and miscibility depend on a knowledge of solvent-solute compatibility. e
heat of solution parameters of medicine and coformer should match to
show compatibility and mixing. Miscibility ensures that both components
dissolve in the same solvent, which is essential for cocrystal formation
[43]. HSP analysis helps researchers choose coformers by predicting medi-
cation compatibility. is forecast helps choose coformers before screening
cocrystals. By selecting coformers with drug-compatible HSP, the selection
procedure is simplied [44]. HSPs are essential for rational cocrystal design
because they identify compatible coformers. Scientists can make informed
selections about prospective cocrystal partners, improving screening e-
ciency and precision.
2.2.3 Coformers Selection and Combinatorial Approaches
e selection of an appropriate coformer is one of the most critical steps
in the rational design and development of cocrystals. e coformer must
be able to form supramolecular heterosynthons with the API through
favorable noncovalent interactions like hydrogen bonding. It should also
improve the physicochemical properties of the API like solubility, disso-
lution rate, and bioavailability without compromising stability and safety.
A combinatorial approach involving the screening of multiple coformers
can help identify the most suitable candidate for further development [35].
2.2.3.1 eoretical Methods
Advances in crystal structure databases and computational modeling tech-
niques have enabled the application of a structure-based selection of poten-
tial coformers. Tools like the Cambridge Structural Database (CSD) allow
the identication of structural moieties that can serve as complementary
hydrogen bond donors/acceptors for a given API. Density functional the-
ory (DFT) calculations can provide insights into relative binding anities
and interaction energies of dierent coformer:API complexes. Such in silico
screening helps prioritize candidates for experimental evaluation [35].
38 Cocrystals in Pharmaceutical Sciences
2.2.3.2 GRAS Coformer Libraries
Combinatorial screening typically utilizes libraries of FDA-approved
Generally Recognized as Safe (GRAS) coformers. Common classes of
coformers evaluated include carboxylic acids, amides, amines, alcohols,
sugars, and carbohydrates. Commercial databases containing characteri-
zations of >100 approved ingredients facilitate the selection of coformers
with desired physicochemical properties like solubility and pKa. Multiple
coformers are also evaluated in combination to discover multicomponent
frameworks [43].
2.2.3.3 High-roughput Experimentation
Automated platforms allow rapid evaluation of large coformer sets under
identical conditions. Methods like slurry mixing, liquid-assisted grinding,
and thermal treatments are adapted for parallel synthesis of hundreds of
cocrystal samples in microtiter plates [44]. Analytical techniques like ther-
mal analysis and PXRD are miniaturized for direct evaluation in multi-
well formats. Data mining identies formulation-property relationships to
guide the selection of lead coformer candidates.
Combining theoretical predictions with high-throughput synthesis and
screening provides a powerful approach for the rational design of cocrystals
with optimized therapeutic potential. Identication of leading coformer
candidates through such combinatorial strategies helps focus subsequent
optimization eorts on the most promising systems.
2.2.3.4 Coformer Selection
Rational selection of a suitable coformer is one of the most critical steps
in the design of pharmaceutical cocrystals. e coformer must be able to
form favorable noncovalent interactions like hydrogen bonds with the API
within the crystal lattice. It should improve key properties of the API, like
solubility, dissolution, and bioavailability, without compromising stability.
A systematic approach to coformer selection can facilitate the design of
cocrystals with optimized therapeutic potential (Figure 2.3) [35].
2.2.3.4.1 Molecular Compatibility
Coformers are selected based on their ability to serve as complementary
hydrogen bond donors/acceptors for the functional groups on the API.
Tools like the CSD can identify structural motifs from existing crystal
Design and Characteristics of Pharmaceutical Cocrystals 39
forms that are likely to interact favorably. Physical properties like pKa are
also considered to guide the choice of acidic/basic/neutral coformers [35].
2.2.3.4.2 Intermolecular Interaction Energy
Computational tools enable the evaluation of interaction energies between
possible coformer:API complexes. DFT calculations provide insights into
relative binding anities to guide prioritization for experimental screening.
Strongly bound complexes are more likely to form stable cocrystals [35].
2.2.3.4.3 Physicochemical Properties
Selected coformers should improve the solubility, dissolution, or permeabil-
ity of the API without compromising stability. eir own physicochemical
Regulatory
Solid State
Characterisation
H
H
2
3
4
5
1
Coformer
Selection
API Problems
SCXRD
PXRD
FTIR
DSC
TGA
SEM
Solubility
Dissolution
Rate
Permeability
Bioavailability
Stability
Cambridge
Structural
Database
·
Hydrogen
Bonding
·
pKa Rule
·
We are the best!
We are more
commercial
Fumaric
acid
Oxalic
acid
Citric
acid
Succinic
acid
Tmax
Figure 2.3 Schematic representation of the coformer selection process for the
development of cocrystals to improve therapeutic eciency. e process starts with the
identication of the API problems that need to be solved, followed by coformer selection
based on the CSD and literature data, and then solid-state characterization. e most
promising coformers are then selected for regulatory approval. API: active pharmaceutical
ingredient, CSD: cambridge structural database. Adopted from (Singh et al., 2023,
published under CC4 license) [35].
40 Cocrystals in Pharmaceutical Sciences
properties, like solubility and melting point, are considered to inuence
the properties of the cocrystal formed.
2.2.3.4.4 Coformer Safety
Coformers approved for use in food, medicines, and neutraceuticals by
regulatory agencies are preferred. is allows leveraging of existing non-
clinical safety data to speed up development. Toxicity risks associated with
non-GRAS coformers need careful evaluation [43]. Combining computa-
tional modeling with consideration of experimental factors like intermo-
lecular interactions, physicochemical matching, and safety facilitates the
rational selection of coformer candidates most likely to form pharmaceuti-
cally favorable cocrystals [35].
2.2.4 Combinatorial Approaches
A powerful design strategy for developing new cocrystal forms with
enhanced properties is the use of combinatorial or high-throughput
approaches. is allows the screening of a large number of potential
coformer molecules systematically to explore the cocrystal landscape. By
increasing the molecular and supramolecular diversity evaluated, rarer and
higher energy forms may be isolated, which confers improved performance
[45]. A key advantage of combinatorial methods is the ability to rapidly
screen coformer libraries in parallel using automated crystallization tech-
niques such as solvent-drop or thermal-gradient cocrystallization. is
enables the evaluation of hundreds or even thousands of coformer-drug
combinations to map out the structural landscape. Potent coformers can
then be identied more eciently for follow-up optimization.
Molecular diversity can be achieved by choosing coformer librar-
ies containing a wide range of functional groups and architectures able
to participate in multiple hydrogen bonding interactions with the drug.
Supramolecular diversity results from the ability of a given drug to adopt
multiple conformations interacting with coformers in dierent orienta-
tions. Together, this molecular and supramolecular variability allows for an
expansive cocrystal landscape to be sampled [35]. e key principle under-
lying combinatorial crystal synthesis is competitive intermolecular interac-
tions between suitable molecular components in solution. When multiple
molecules possessing potential recognition sites like hydrogen bonding or
π-π stacking functionality are combined in solution, they can engage in
a dynamic equilibrium of reversible interactions. By tuning experimental
parameters such as solvent composition, temperature, and stoichiometry,
Design and Characteristics of Pharmaceutical Cocrystals 41
certain interacting subsets can be selectively amplied to direct formation
of a stable crystalline phase [46].
is competitive selection mimics Darwinian evolution concepts, with
the system itself choosing an interaction pattern or “ttest” supramolecular
synthon based on relative interaction strengths in a given environment. It
bypasses the need for rationally predetermining a step-wise buildup route
based on interaction hierarchies. Instead, a library of molecular compo-
nents and potential binding sites are provided, allowing the experimental
conditions to guide supramolecular assembly A key requirement is that
the competing interactions be marginally reversible near room tempera-
ture, permitting proof-correction toward low-energy conglomerates. is
competitive dynamic helps avoid kinetic traps and optimizes the accom-
modation of multiple components. By systematically varying molecular
precursors and crystallization protocols, a broad array of novel multicom-
ponent crystals with diverse structures and properties can be accessed.
All the computational techniques described in Table 2.1 help narrow
down large molecular libraries to high-priority combinations for physical
screening in the laboratory [47–51].
Table 2.1 Various techniques required for the combinatorial approach to
cocrystal synthesis.
S. no. Technique Description
1. Compound
libraries
Libraries of pharmaceutically relevant drug
molecules and coformers with diverse chemical
functionalities must be available.
2. Liquid-assisted
grinding
Technique used to intimately mix and grind
drug and coformer mixtures in the presence
of a small amount of solvent. Allows rapid
screening.
3. Solvent
diversity
Ability to crystallize mixtures from a wide range
of solvents and solvent mixtures increases the
likelihood of crystallization and diversity of
products
4. Crystallization
equipment
Tools like evaporation plates, sealed vials, etc.
required to rapidly crystallize mixtures from
various solvent conditions.
(Continued)
42 Cocrystals in Pharmaceutical Sciences
Table 2.1 Various techniques required for the combinatorial approach to
cocrystal synthesis. (Continued)
S. no. Technique Description
5. Automated
systems
For high-throughput handling, mixing,
crystallization, and data collection from a large
number of experiments.
6. Crystal
screening
Techniques like microscopy for rapid evaluation
of crystal formation in mixtures.
7. Powder XRD For identifying new crystalline phases and purity
assessment of cocrystals.
8. Solubility
measurement
To screen for formulations with enhanced
therapeutic properties like improved solubility.
9. ermal
methods
TGA and DSC useful to understand the
crystallinity and stability of cocrystals.
10. Single-crystal
XRD
Gold standard for determining molecular
conformations and supramolecular synthons in
cocrystals.
11. Computational
modeling
To predict favorable intermolecular interactions
and guide cocrystal synthesis. Some common
in silico and computational tools that can be
used for the selection of candidate molecules
for cocrystal synthesis via a combinatorial
approach include the following:
i Database
searching
Screening crystal structure databases like CSD to
nd molecules with similar functional groups
that have formed heterosynthons in previous
crystal structures. is indicates recognition
potential.
ii Docking
simulations
Molecular docking methods like Autodock can
be used to predict favorable intermolecular
interactions and binding poses between
candidate drugs and coformer molecules.
Provides insight into recognition patterns
(Continued)
Design and Characteristics of Pharmaceutical Cocrystals 43
Fu et al. applied a combinatorial screening approach to discover new
cocrystal forms of the poorly soluble antiepileptic drug carbamazepine
(CBZ). e researchers selected four aromatic carboxylic acids as coform-
ers: 2,3-dihydroxybenzoic acid (DBA), 1-naphthoic acid (NA), anthra-
cene-9-carboxylic acid (AC), and systematically combined each with CBZ
in 1:1, 2:1, and 1:2 molar ratios. rough liquid-assisted grinding of the
mixtures with a small amount of solvent, they were able to rapidly crys-
tallize and isolate four new CBZ cocrystals: CBZ-DBA (1:1), CBZ-DBA-
CH
3
OH (2:1), CBZ-NA-H
2
O (1:1), and CBZ-AC (1:1). Single-crystal X-ray
diraction (SCXRD) revealed that their structures contained dierent
Table 2.1 Various techniques required for the combinatorial approach to
cocrystal synthesis. (Continued)
S. no. Technique Description
iii Crystal
structure
prediction
Methods like CrystalPredictor and ELPASO can
calculate lattice energies of putative cocrystal
structures to identify thermodynamically stable
cocrystal forms even before synthesis.
iv H-bond
propensity
calculation
Tools like COSMOtherm allow the calculation
of hydrogen bond donor/acceptor strengths
of functional groups to guide the selection of
complementary molecules.
v Conformational
searching
Methods like AutoDockTools and RaptorX are
used to generate low-energy conformations
of exible molecules to capture important
recognition conformation in cocrystals.
vi Solubility
prediction
Correlations with physicochemical properties
allow in silico screening of cocrystal
formulations with desired improvements in
solubility/dissolution rate over the original
drug form.
vii Polymorph
prediction
Predicting stable polymorphs of candidate drugs/
coformers helps reduce experimental search
space for cocrystal synthesis.
viii Interaction
energy
calculation
Quantum chemical methods like DFT
provide estimates of interaction strengths
between molecular fragments for screening
supramolecular synthons.
44 Cocrystals in Pharmaceutical Sciences
supramolecular heterosynthons, including amide-acid, amide-amide,
and amide-acid-H2O motifs. Solubility measurements found CBZ-NA-
H
2
O displayed a 1.9-fold increase in aqueous solubility (304 μg/ml) com-
pared to CBZ alone (161 μg/ml). Additionally, neat grinding experiments
demonstrated that CBZ-DBA (1:1) could be reversibly transformed to the
more stable CBZ-DBA-CH
3
OH (2:1) form upon the addition of CBZ or
solvent [52].
is case study illustrates how systematically varying drug:coformer
ratios in a combinatorial manner allows for rapid discovery and optimiza-
tion of new cocrystal forms with improved properties through modulating
their supramolecular assembly.
2.3 Structural Characteristics of Pharmaceutical
Cocrystals
e eectiveness and usefulness of pharmaceutical cocrystals heavily rely
on their unique characteristics.
2.3.1 Crystal Structure Analysis
In order to comprehend the formation process and characteristics of
medicinal cocrystals, it is essential to investigate their crystal structures.
Determining the molecular packing in crystalline structures and estab-
lishing the constitution of cocrystals are important activities that must
be accomplished by employing SCXRD or powdered X-ray diraction
(PXRD). An understanding of the molecular arrangement in cocrystals is
important, especially since it provides sucient information on the posi-
tions of atoms in the given crystal structure and the nature of the bonds
between these atoms. X-ray crystallography is an inalienable asset in this
process. e arrangement of the molecules as they are packed in the crystal
lattice inuences such properties as density, hardness, and solubility. e
measurements of the unit cell width of the crystal give insight into crystal
symmetry and lattice nature thereby providing an understanding of the
repetitive structural unit of the crystal [53–55].
2.3.2 A Perspective on Cocrystal Hydrogen Bonding
Hydrogen bonding is the major factor that contributes to the stability and
structure of cocrystals. e phenomenon of hydrogen bonding between a
Design and Characteristics of Pharmaceutical Cocrystals 45
donor and an acceptor aects the solubility and dissolution mechanisms
of therapeutically active substances. e formation of cocrystals is due to
hydrogen bonding and solubility, leading to the formation of stable struc-
tures, and eciency. Related to this denition, hydrogen bonding relates to
the attractive forces existing between a hydrogen atom and an electroneg-
ative atom, such as oxygen or nitrogen in the other molecule. e stability
of cocrystals is dened by the contact of hydrogen atoms of the rst com-
pound with the oxygen or nitrogen atoms in the second compound. at
is due to the fact that the strength and organization of chemical connec-
tions have an impact on the features of cocrystals. Improved bond strength
improves the stiness of the structure while a weaker bond improves the
exibility of the structure [10, 56, 57].
2.3.3 Characterization Techniques
e dierent instrumental analytical techniques used in the cocrystal anal-
ysis are shown in Figure 2.4.
A number of methods provide detailed information about the structural
features of pharmaceutical cocrystals. e equipment used in this study is
SCXRD (single-crystal X-ray diraction), PXRD (powder X-ray dirac-
tion), FTIR (Fourier transform infrared spectroscopy), DSC (dierential
Cocrystals
Characterization
Techniques
FTIR
DSCNMR
FESEM
SCXRD/
PXRD
Figure 2.4 Methods for characterizing pharmaceutical cocrystals.