ARTICLE
Received 5 May 2015 | Accepted 10 Jun 2015 | Published 22 Jul 2015
Combined crystal structure prediction and
high-pressure crystallization in rational
pharmaceutical polymorph screening
M.A. Neumann1, J. van de Streek2, F.P.A. Fabbiani3, P. Hidber4 & O. Grassmann5,w
Organic molecules, such as pharmaceuticals, agro-chemicals and pigments, frequently form
several crystal polymorphs with different physicochemical properties. Finding polymorphs has
long been a purely experimental game of trial-and-error. Here we utilize in silico polymorph
screening in combination with rationally planned crystallization experiments to study the
polymorphism of the pharmaceutical compound Dalcetrapib, with 10 torsional degrees of
freedom one of the most flexible molecules ever studied computationally. The experimental
crystal polymorphs are found at the bottom of the calculated lattice energy landscape, and
two predicted structures are identified as candidates for a missing, thermodynamically more
stable polymorph. Pressure-dependent stability calculations suggested high pressure as a
means to bring these polymorphs into existence. Subsequently, one of them could indeed be
crystallized in the 0.02 to 0.50GPa pressure range and was found to be metastable at
ambient pressure, effectively derisking the appearance of a more stable polymorph during
late-stage development of Dalcetrapib.
DOI: 10.1038/ncomms8793 OPEN
1 Avant-garde Materials Simulation Deutschland GmbH, Merzhauser Strasse 177, D-79100 Freiburg, Germany. 2 Department of Pharmacy, University of
Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark. 3 Department of Crystallography, Georg-August-Universita¨t Go¨ttingen, GZG,
Goldschmidtstrasse 1, D-37077 Go¨ttingen, Germany. 4 F. Hoffmann-La Roche Ltd, Pharma Technical Development, Grenzacherstrasse 124, CH-4070 Basel,
Switzerland. 5 Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124,
CH-4070 Basel, Switzerland. w Present address: F. Hoffmann-La Roche Ltd, Pharma Technical Development, Grenzacherstrasse 124, CH-4070 Basel,
Switzerland. Correspondence and requests for materials should be addressed to M.A.N. (email: marcus.neumann@avmatsim.eu) or to F.P.A.F.
(email: ffabbia@gwdg.de).
NATURE COMMUNICATIONS | 6:7793 | DOI: 10.1038/ncomms8793 | www.nature.com/naturecommunications 1
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T
he ability of many chemical compounds to form different
crystal structures is known as polymorphism1. The key
physicochemical properties such as density, morphology,
solubility, dissolution rate, electric conductivity, colour,
birefringence, magnetic susceptibility and nonlinear optical
properties are strongly influenced by the crystal packing.
Polymorphism provides a chance for fine-tuning materials’
properties, but also has important implications for
manufacturing processes. For pharmaceuticals, polymorphism
must be tightly controlled and is subjected to regulatory
procedures, mainly because the crystal form can have a strong
impact on the bioavailability of a drug and ultimately its
therapeutic performance. In addition, novel polymorphs that
show improved properties may be patented. A particular threat to
the pharmaceutical industry is the phenomenon of ‘disappearing
polymorphs’2. If the thermodynamically stable form has
unfavourable crystallization kinetics, years may pass after initial
synthesis before the first nucleation event; however, once the
stable form has occurred it may prevent the production of the
metastable form used in the drug formulation that is brought to
market. A variation of this theme was experienced by Abbot3 in
the Ritonavir case. Ritonavir was already marketed as a soft gel
formulation, when an unexpected crystal form started to appear
in 1998 with respect to which the chosen formulation turned out
to be highly supersaturated. Subsequently, Ritonavir had to be
reformulated at substantial cost and effort.
In response to the abovementioned risks and opportunities,
experimental polymorph screening has become a standard
procedure in pharmaceutical development. In numerous trial-
and-error experiments carried out manually or with the help of
robotic equipment, the key crystallization parameters such as
solvent choice, antisolvent choice, evaporation rate and cooling
rate are varied and the outcome is characterized by spectroscopic
and thermoanalytical techniques, as well as diffraction measure-
ments. However, there is no guarantee that a stable form with a
high nucleation barrier will be obtained this way. The first
nucleation event of such a form may require a special surface, the
presence of an impurity or simply many repetitions of a certain
crystallization experiment. The right conditions may not be
encountered during the short time period of the experimental
screening, but be matched accidentally after years of industrial
manufacturing. An alternative approach would consist in
mapping potentially stable polymorphs first by computational
techniques, followed by a small number of well-targeted crystal-
lization experiments to bring into existence potentially threaten-
ing crystal forms that have not yet been observed experimentally.
Tremendous progress has been achieved in the past decade in
the field of crystal structure prediction (CSP) for both inorganic4–9
and organic compounds10–12. Both branches develop rather
independently, because, despite many similarities, they involve
different challenges and address different questions. For instance,
in inorganic CSP the term ‘high pressure’ will frequently refer to
conditions found in a planet’s interior, up to ca. 350GPa at the
centre of the Earth, or to conditions required to profoundly
change the bonding and electronic properties of inorganic
materials (for instance, sodium becomes transparent and
insulating at ca. 200GPa (ref. 8)), whereas in organic CSP it
refers to a much narrower and more modest pressure range,
typically 0.1–10GPa, where most structural changes and phase
transitions take place. Here we are exclusively concerned with CSP
of organic compounds. The state-of-the-art in this field has been
well documented by a series of blind tests13–17. Of the two main
computational challenges, the complete sampling of the
configurational space and the accuracy of the energy ranking,
the first has to a large extent already been solved for structures
crystallizing with one molecule per asymmetric unit. Energy
ranking is still problematic when some low-energy structures are
strongly stabilized by entropic contributions or when competing
low-energy structures feature very different interactions such as
dissimilar hydrogen-bonding schemes. However, the most
important remaining challenge is probably the elaboration of
clear crystallization recipes to cross the divide between the
computational world (in silico) and the real world (in vitro). Since
the 2010 blind test CSP studies of substantially flexible
pharmaceutical molecules have started to appear in the scientific
literature, with blind test compound XX as a model
pharmaceutical18.
CSP has been shown to be a useful tool when it comes to
rationalizing experimental observations involving pharmaceutical
molecules, but further evidence needs to be built up to prove that
it can deliver on its two most important industrial promises: lead
experimentalists to new crystal forms and help to decide when it
is safe to stop screening. In this article, we describe a real-life
example of the pharmaceutical development compound Dalce-
trapib, where both goals have been achieved to a large extent.
A comprehensive CSP study for Dalcetrapib shows that in
addition to the experimentally observed polymorphs, two
predicted structures are candidates for a missing, thermodyna-
mically more stable polymorph. The results of pressure-
dependent stability calculations indicate that high-pressure
conditions would favour the appearance of these high-density
structures, thereby providing the recipe for a well-targeted
crystallization experiment. Indeed, by following this recipe one
of the two polymorphs can be crystallized in the 0.02 to 0.50GPa
pressure range. This crystal is metastable at ambient pressure,
effectively derisking the appearance of a more stable polymorph
during late-phase development of Dalcetrapib. This study
illustrates how CSP and high-pressure crystallization can provide
elements for rational pharmaceutical polymorph screening and in
doing so bridge the divide between the computational and
experimental worlds.
Results
Experimental polymorph screening at ambient pressure. Dal-
cetrapib19 (Fig. 1) was originally discovered by Japan Tobacco
Inc., which reported in 2000 that the molecule inhibited
cholesterol ester transferase protein activity. Dalcetrapib was in
clinical development at Roche until 2012. It has been recently
NH
S
O
O
Figure 1 | Molecular structure of Dalcetrapib. Chemical structure of
Dalcetrapib highlighting the 10 torsional degrees of freedom.
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8793
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& 2015 Macmillan Publishers Limited. All rights reserved.
demonstrated that the drug compound has significant potential in
treatment of cardiovascular diseases for a genetic subgroup20.
Extensive experimental crystal polymorph screens were
performed to identify the relevant polymorphs of Dalcetrapib.
In numerous solvent-based crystallization trials only one crystal
polymorph, form A, was observed at ambient pressure and
temperature. Differential scanning calorimetry and X-ray powder
diffraction experiments reveal that at about  87 C form A
undergoes a reversible order–disorder phase transition to another
polymorph, form B, that has been reported previously21 (see
Supplementary Fig. 1). The crystal structures of forms A and B
are almost identical, with the exception of the aliphatic side
chains that are fully ordered in form B and highly disordered in
form A (Supplementary Notes 1 and 2). The phase transition
between forms A and B does not present a development risk
because of its reversibility and the low phase-transition
temperature.
CSP of Dalcetrapib. The CSP method employed here, imple-
mented in the computer programme GRACE, stood out in the
last two blind tests11,16,17,22 in terms of success rate. It uses
dispersion-corrected density functional theory (DFT-D)
calculations23,24 for the final lattice energy ranking and for the
generation of reference data to which a tailor-made force field25 is
fitted. The tailor-made force field is used in a Monte-Carlo
parallel-tempering algorithm with statistical convergence control
to generate several thousand low-energy structures, which are
then further processed at the DFT-D level. In terms of flexibility,
the previous record in publicly available studies was held by blind
test compound XX (ref. 17) with eight rotatable single bonds not
counting terminal methyl groups. Here the limit is pushed further
to 10 rotatable single bonds and an additional flexible six-
membered ring for the pharmaceutical compound Dalcetrapib.
An in silico polymorph screen with GRACE is conducted for
Dalcetrapib in all 230 space groups with one molecule per
asymmetric unit. Figure 2 shows an energy-density plot for the 30
most stable computer-generated crystal structures (see also
Supplementary Table 1). Energy-density plots are commonly
used as a graphical representation of the energy landscape. Each
filled symbol corresponds to a local DFT-D lattice energy
minimum. The computer-generated structures are numbered in
the order of increasing lattice energy. Many of the structures are
unique; however, there are also two large families of similar
crystal structures. Within each family, the structures differ only
with respect to the conformation of the alkyl chains. Structure 1
belongs to one of these families, and structure 2 to the other. The
crystal structures in both families have P21/c space-group
symmetry, form almost identical unit cells and exhibit similar
one-dimensional hydrogen-bonded chains; however, subsequent
molecules in a chain are related by a twofold screw rotation for
the structure 1 family and by a glide plane for the structure 2
family.
The two experimental forms A and B both belong to the
structure 1 family. The ordered low-temperature form B actually
matches structure 1. Figure 3 shows an overlay of the two
structures that is representative for the excellent agreement
between experimental low-temperature structures and computer-
generated structures at the DFT-D level. The atomic coordinates
of the disordered high-temperature form A are compatible with a
mixture of structure 1 and structure 22; however, lattice energy
calculations presented in the Supplementary Note 1 suggest that
the true nature of the disorder in form A is probably much more
complex. The relative stability of crystal forms is determined by
their free energies, to which the lattice energies reported here are
only an approximation. In addition, various flavors of DFT-D
yield somewhat different energy-ranking results. When Perdew-
Burke-Ernzerhof (PBE)–Neumann–Perrin is used instead of
BLYP-D3 (see Supplementary Note 1), structure 1 is predicted
to be less stable than structures 2 and 3, which were therefore
perceived as potential candidates for the true thermodynamically
stable form. Pressure-dependent lattice energy calculations (see
Fig. 4) indicate that at high pressure a form belonging to the
structure 2 family would be significantly more stable than the
experimentally observed forms A or B, thus providing a
straightforward recipe for the crystallization of a new crystal
form to be verified experimentally.
Crystallization and stability of Dalcetrapib at high pressure.
Indeed, such a form C was readily obtained by in situ high-
pressure crystallization from solution26. The strength of this
experimental technique for exploring the structural landscape of a
compound at moderately high pressures (o1GPa) is that any
kinetic barrier associated with a molecular rearrangement in the
solid state (as encountered in a polymorphic transformation by
direct compression of the crystal) is bypassed by crystallization
from solution directly under high-pressure conditions.
At conditions of ambient pressure, crystallization of Dalce-
trapib is known to be kinetically hindered and solutions can be
easily supersaturated. A 0.82M tetrahydrofuran solution was
loaded in the diamond-anvil cell (DAC) and crystallization of
10
8
6
4
2
0
–2
–4
–6
–8
Experimental form A Experimental form B Experimental form C
Structure-1 family Structure-2 family Structure-4 family
Unique structures
R
el
at
iv
e 
la
tti
ce
 e
ne
rg
y 
(kJ
 m
ol–
1 )
1.261.241.221.21.18
Density (g cm–3)
Figure 2 | Energy-density diagram generated from the crystal structure
prediction of Dalcetrapib. Energy-density diagram for the 30 computer-
generated and three experimentally observed crystal structures of
Dalcetrapib. Two of the experimental crystal forms are disordered and
match several similar computer-generated structures. The computer-
generated structures are numbered 1–30 in order of increasing lattice
energy and families of similar structures are named according to their
member with the lowest lattice energy. The average lattice energy was
calibrated to zero.
Figure 3 | Structural overlay of experimental and computer-generated
Dalcetrapib form B. Overlay of the experimental crystal structure of
Dalcetrapib form B at 100K (red) with the computer-generated crystal
structure 1 (blue).
NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8793 ARTICLE
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& 2015 Macmillan Publishers Limited. All rights reserved.
polycrystalline material was observed after ca. 24 h from initial
loading, at a pressure of ca. 0.45GPa. A single crystal suitable
for single-crystal X-ray diffraction was grown by pressure
and temperature cycling below ca. 0.1GPa. Gentle heating
(323–333K) was applied to avoid compound decomposition.
Stages of crystallization and crystal growth are depicted in
Supplementary Fig. 3. During crystal growth the pressure inside
the chamber drops significantly, indicating that the solid is
considerably denser than the solution. The final pressure inside
the chamber after crystal growth was ca. 0.02GPa.
The structure solved from and refined against in situ single-
crystal X-ray diffraction data matches the computer-generated
structure 3 (Supplementary Figs 4–6 and Supplementary Table 2),
which is the second lowest-energy structure in the structure 2
family. The experimentally observed disorder of the aliphatic side
chains is consistent with a model of thermally populated
molecular conformations, taken from structures 9 and 13 (and
to a lesser extent 2 and 12, see Supplementary Tables 2–3 and
Supplementary Fig. 6) of the structure 2 family, in the ordered but
relaxed crystalline environment of structure 3. Lattice energy
calculations for various disorder models show that structure 2 is
less affected by thermodynamic disorder than structure 3.
Structure 3 is observed experimentally instead of structure 2
because of the contribution of disorder to the free energy.
For some chemical compounds the crystal forms obtained at high
pressure are sufficiently stable to be recovered at ambient pressure,
as testified by the numerous examples of novel inorganic materials
obtained through high-pressure synthesis27–29. In the case of
molecular organic materials, recovered crystals can additionally be
used as seeds for further crystallization experiments. This was
recently demonstrated for the analgesic acetaminophen30 and the
neurotransmitter g-aminobutyric acid31. Successful recovery and
seeding experiments are of particular interest for industrial
applications, especially when high pressure is the sole or most
reliable route for obtaining a particular solid form, as is the case for
Dalcetrapib form C. Therefore, several attempts were made to
recover form C at ambient conditions (see Supplementary Note 2
and Supplementary Figs 7–11 for full details). When crystallized
from solution in the 0.02 to 0.50GPa pressure range, form C
instantly converts to form A in a solution-mediated transformation
on opening of the diamond anvil cell. When form C is crystallized
from the melt at high pressure and the pressure is released without
opening the diamond anvil cell, form C can be obtained at ambient
pressure but converts to form A on a timescale of hours. Both
experiments prove that form A is more stable than form C at
ambient conditions.
Rational crystallization experiments from energy landscapes.
Abramov32 provided an assessment of the usefulness of CSP to
support solid-form selection. The energy landscape of the still
rather rigid pharmaceutical olanzapine was used by Bhardwaj
et al.33 to rationalize some of the observed crystallization
behaviour, including the low packing efficiency of the
unsolvated forms and the role of solvent in stabilizing the
solvate structures. Two out of three experimental unsolvated
polymorphs were identified among the computer-generated
crystal structures. Four structures were predicted to be more
stable than all of the experimental polymorphs; however, the
crystallization of a new polymorph using knowledge of the energy
landscape was not reported. Ismail et al.34 were successful in
finding the only known polymorph of a compound named
GSK269984B, previously in development at GlaxoSmithKline, as
the most stable polymorph in their prediction. GSK269984B is
only slightly less flexible than the compound studied here. The
energy landscape revealed many crystal packings with lattice
energies close to the experimentally observed one, featuring a
variety of molecular conformations. On the basis of this
knowledge new crystallization experiments were designed to
generate new crystal forms; however, no additional polymorphs
could be observed experimentally. The authors noted that unlike
the known polymorph many computer-generated structures did
not match the most stable conformation of the molecule
computed in isolation. The inability to obtain new polymorphs
was rationalized in terms of expected poor crystallization
dynamics because of the necessity for conformational change
during the crystallization process. The aforementioned studies
and the work presented here have in common that in the relevant
energy window for polymorphism there are far more computer-
generated structures than observed polymorphs. Price35 has
proposed a comprehensive analysis of this observation.
It is not new that additional crystal polymorphs of organic
molecules may be obtained by high-pressure crystallization, or
that high-pressure forms are likely to be found in CSP studies to
have higher densities than ambient-pressure forms. In a
collaborative effort between experimentalists and computational
scientists carried out under blind test conditions, Oswald et al.36
experimentally obtained both a low-density form at ambient
pressure and a high-density form at high pressure for each of the
molecules 2-chlorophenol and 4-fluorophenol. All experimental
polymorphs were found in the CSP studies with the correct
density relationships. However, the CSP studies did actually not
correctly predict the appearance of the high-density polymorphs
at high pressure because in both cases many computer-generated
structures were computed to be more stable than the
experimentally observed ones at the crystallization pressure. For
2-chorophenol, the calculations did not show a significant
stabilization with pressure of the high-density polymorph in
comparison with the low-density polymorph. In another case,
Day et al.37 obtained and characterized a previously unknown
polymorph, form II, of maleic acid serendipitously by dissolution
of the 1:2 cocrystal between maleic acid and caffeine in
chloroform, but were unsuccessful to obtain the new
polymorph a second time. In a subsequent CSP study published
with the experimental work, the authors found both polymorphs
correctly among the most stable computer-generated structures,
with form II being predicted to have higher density in agreement
with experimental findings. Later, Oswald et al.30 demonstrated
that form II can be reproducibly obtained by high-pressure
12.5
10
7.5
5
2.5
0
–2.5
–5
–7.5
–10
–12.5
0 0.2 0.4 0.6 0.8 1
R
el
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la
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ce
 e
ne
rg
y 
(kJ
 m
ol–
1 )
Pressure (GPa)
Figure 4 | Relative lattice energies as a function of pressure. Relative
lattice energies as a function of pressure for computer-generated structure
1 (green dashed line), structures 2 and 3 (red dotted lines) and all other
computer-generated structures (continuous grey lines) of Dalcetrapib.
Lattice energy optimizations were carried out from 0.0 to 1.0GPa in steps
of 0.2GPa. For every pressure the average lattice energy was calibrated to
zero.
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms8793
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& 2015 Macmillan Publishers Limited. All rights reserved.
crystallization. While highly correct, the CSP study on maleic
acid provides a postdiction, rather than a prediction of a high-
density polymorph obtained at high pressure. 2-chorophenol,
4-fluorophenol and maleic acid are all very small molecules by
pharmaceutical standards. One novel aspect of our work is to
demonstrate that even for highly flexible pharmaceutical
molecules, crystal energy landscapes and their pressure
dependence can be calculated with high-enough accuracy to
convince industrial crystallization scientists to deviate from their
experimental standard protocols and invest additional resources
to obtain a specific predicted crystal structure experimentally,
through a high-pressure crystallization experiment at a pressure
suggested by theory.
With the structure 2 family having been observed experimen-
tally at high pressure, our computational results for Dalcetrapib
show no indication for having missed the thermodynamically
stable form at ambient conditions. Within each family, cross-
nucleation and low-energy barriers for solid–solid phase transi-
tions make it unlikely to encounter a metastable form that does
not readily convert to the most stable form in the family;
therefore, none of the structures in the two observed families
presents a danger regardless of potential computational errors.
The structure 4 family and structure 5 exhibit the same hydrogen
bonding and a similar molecular conformation as the experi-
mental structures. Hence, there is in principle no apparent reason
why their nucleation or growth should be hindered compared
with the observed forms. If any of them were the truly stable
form, they should have been observed in the experimental
screening experiments, whereas only forms A and B, which are
thermodynamically the two most stable forms, were repeatedly
isolated. Interestingly, this argument also applies to form C;
however, this low-energy form could be isolated experimentally
by changing another thermodynamic variable, namely pressure,
in the crystallization experiments, and effectively moving to and
probing another portion of the compound’s phase diagram. Once
more experience with interpreting crystal energy landscapes has
been built up, it may well turn out that form C should never have
been considered a candidate for a missing thermodynamically
stable form at ambient conditions. For an unobserved low-energy
structure to be flagged as a threat after thorough experimental
screening, it should probably also present a structural feature
suggesting a high-nucleation barrier, such as an unlikely
molecular conformation according to the statistics of the
Cambridge Structural Database. Some of the unique structures
feature other molecular conformations; however, they are all
predicted to be less stable than structure 1 by more than
2 kJmol 1 and cannot benefit from a reduction in the
configurational free energy by disorder because they are not part
of a family. For Dalcetrapib the calculated lattice energy ranking
yields a reliable description of the relative stability because of the
strong structural similarity between the computer-generated low-
energy structures.
Discussion
The reader may wonder why high-pressure crystallization should
not simply be added to the experimental trial-and-error screening
protocols without the need to computationally generate a crystal
energy landscape. While there are signs that the rules of the game
are slowly changing and high-pressure experiments on pharma-
ceuticals are attracting some industrial interest in their own right,
the answer still is that it is always easier to find something when
you know what you are looking for. High-pressure experiments
need the intervention of an academic specialist, are time-
consuming and usually require diamond anvil cells as crystal-
lization vessels, limiting the choice of crystallization conditions
and capability of parallel screening compared with crystallization
at ambient conditions. In the case of Dalcetrapib, initial
experiments gave no indication of crystallization from the melt
under pressure 1 month after having initially loaded the diamond
anvil cell (see Supplementary Note 2). It would be unlikely that a
crystallization experiment had continued for such a long time in
an industrial context without knowing that there was something
to look for. High-pressure crystallization from solution of form C
occurred after only a day; however, even in this case no
crystallization event might have been observed in an industrial
laboratory without prior, time-consuming optimization of high-
pressure crystallization conditions. In the case that another high-
density form had crystallized first and repeatedly so, an expensive
high-pressure screen might have been stopped after a few
attempts. The computed crystal energy landscape is not perfect;
however, it roughly tells the experimentalist in which pressure
range new forms can be expected, how stable these forms will be
compared with other known or predicted structures and whether
they are stable enough at ambient conditions to be likely
candidates for the thermodynamically most stable form. The
energy landscape may also help to get the crystallization
conditions right. If the molecular conformation in a predicted
high-density form matches a known form, the high-pressure form
is likely to crystallize from solvents from which the known form
could be obtained. Of course, the crystallization recipe obtained
from computer simulations is still limited. Which form, if any,
results from a specific high-pressure crystallization experiment
may depend on subtle conditions such as the rate of compres-
sion38,39 and ultimately remains a question of trial-and-error,
even though the likelihood of success is high. In addition, only an
experimental investigation will show if a new form can be
recovered at ambient conditions. If so, further investigations will
typically be required to find other crystallization conditions under
which the new form can be obtained reproducibly and in large
quantities.
The art of bringing into existence predicted crystal structures
for physical characterization is only in its infancy. A toolbox of
specific techniques will have to be developed that can be used to
crystallize virtually any predicted structure not too far away from
the global energy minimum. In that toolbox, crystallization under
pressure will be the method of choice for high-density structures.
The knowledge of the predicted crystal structures may help to
choose solvents that favour certain molecular conformations or
associations40. Another versatile route that offers much promise
is the use of tailor-made additives41. Removing hydrogen-bond
acceptors from the molecule to be crystallized or replacing
hydrogen atoms with halogen atoms, it should be possible to
design additives that are easily incorporated in a candidate
form, but do not fit into the experimentally observed forms and
thereby act as crystal growth inhibitors42. Or why not search
computationally among thousands of commercially available
compounds with known crystal structures for a crystal surface
that would be the ideal substrate for the heterogeneous nucleation
of a candidate form43? Crystallization in electric fields44,
ultrasound fields45 or laser beams46 provides further avenues
for exploration, provided that the effect of these experimental
conditions on the growth of specific crystal structures is
understood.
Methods
General. Detailed information on the computational, experimental and crystal-
lographic methods is provided in the Supplementary Notes 1 and 2, Supplementary
Figs 12–15 and Supplementary Table 4.
Energy calculations. All DFT-D lattice energy optimizations have been carried
out with the GRACE programme. For the calculation of DFT energies and forces,
GRACE calls the ab initio total-energy and molecular-dynamics programme
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Vienna Ab initio Simulation Package (VASP) developed at the ‘Institut fu¨r
Materialphysik’ of Vienna University47–50. The dispersion correction is
implemented in GRACE. The energy calculation method BLYP-D3 combines the
BLYP functional, implemented in VASP, with the dispersion correction according
to ref. 24, implemented in GRACE. The energy method PBE–Neumann–Perrin
combines the PBE functional with the dispersion correction according to ref. 23.
DFT calculations use a plane wave cutoff energy of 520 eV and a k-point spacing of
roughly 0.07Å 1. All lattice energy minimizations have been converged to within
at least 0.003 Å for atomic displacements, 0.001 kJmol 1 per atom for energy
changes, 1.7 kJmol 1 per Å for atomic forces and 0.0125 kbar for cell stress. The
lattice energies of the 30 most stable computer-generated crystal structures
according to BLYP-D3 are listed in Supplementary Table 1 both for BLYP-D3 and
PBE–Neumann–Perrin. On average, the lattice energies calculated with both
methods deviate from each other by 1.9 kJmol 1 per molecule. The 30 structures
resulting from the BLYP-D3 optimization are provided as Supplementary Data.
Considering the possibility of disorder significantly complicates the tasks of CSP.
Therefore, the blind test compounds have always been selected as to avoid
disordered structures and typically compounds with ordered crystal structures are
chosen for CSP validation studies. However, disorder is a commonly observed
phenomenon in molecular crystals and can have a strong impact on the relative
stability of crystal forms because of its contribution to the crystal free energy.
Modelling and rationalization of structural disorder has been shown to be
amenable to CSP, as demonstrated in three recent examples on pharmaceuticals51–
53. With two disordered crystal polymorphs out of three, Dalcetrapib exhibits a
particularly high degree of disorder and the energy ranking presented here would
have been incomplete without an attempt to quantify the configurational
contribution to the crystal free energy by means of lattice energy calculations. Full
information on the treatment of disorder in the calculations is detailed in the
Supporting Note 1 and Supporting Fig. 2. A rigorous treatment of disorder as
applied to caffeine54 is still out of scope at the DFT-D level for a molecule such as
Dalcetrapib because of the high CPU time requirements.
The field of dispersion-inclusive DFT is rapidly evolving, and it is appropriate to
mention some recent developments that were not used in the present work.
Various ways of treating van der Waals dispersion forces in DFT have recently
been classified according to ref. 55. A particularly promising approach that
combines DFT with multibody dispersion interactions was shown to reproduce the
lattice enthalpy differences between the polymorphs of glycine and oxalic acid with
an accuracy of B1 kJmol 1 (ref. 56). For the assessment of these and other
methods, a benchmark for non-covalent interactions in solids derived from
sublimation enthalpies is now available57. Quantum mechanics-based fragment
methods provide a systematically improvable approach to make predictions in the
condensed phase for the crystal structures of small organic molecules58 and may
become a reliable source of theoretical benchmark data.
High-pressure experiments. A modified Merrill–Bassett DAC59 equipped with
800-mm culet diamonds mounted on WC seats and Inconel steel gaskets of 300-mm
diameter was used for all experiments. The opening angle of the cell for X-rays was
84. Single-crystal diffraction data were collected at 295K on a Bruker Apex II
diffractometer equipped with Mo-sealed tube radiation. A standard data collection
strategy that aims at optimizing data redundancy and completeness was used.
Recovery experiments were performed on single-crystal and polycrystalline
samples of form C and the obtained material analysed using X-ray diffraction.
Single crystals were grown in situ from solution in the DAC; polycrystalline
samples were grown in situ either from solution or from the melt in the DAC.
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Acknowledgements
F.P.A.F. thanks the DFG for funding, Emmy Noether project FA 9649/1-1. J.v.d.S.
gratefully acknowledges the Villum Foundation for funding (project No. VKR023111).
We thank Karsten Faehnrich for performing Differential Scanning Calorimetry Analysis
and Andre´ Alker for crystal structure analysis of Form B.
Author contributions
H.P. and O.G. conceived and advised on the project, M.A.N. and J.v.d.S. designed
and performed the computational work, F.P.A.F. designed and performed all high-
pressure and recovery experiments, F.P.A.F. and O.G. designed and performed the
ambient-pressure X-ray experiments, M.A.N., J.v.d.S., F.P.A.F. and O.G. performed
data analysis, M.A.N. wrote the manuscript with input from F.P.A.F., H.P., O.G.
and J.v.d.S.
Additional information
Accession codes: Crystallographic data deposition. The X-ray crystallographic coordi-
nates for structures reported in this study, C (295 K and 0.02GPa), A (295 and 223 K)
and B (100K) have been deposited at the Cambridge Crystallographic Data Centre
(CCDC), under deposition numbers 1024144–1024147. These data can be obtained free
of charge from The Cambridge Crystallographic Data Centre via www.ccdc.cam.ac.uk/
data_request/cif.
Supplementary Information accompanies this paper at http://www.nature.com/
naturecommunications
Competing financial interests: M.A.N. is the founder, owner and director of the
company Avant-garde Materials Simulation that develops the GRACE software for
crystal structure prediction. The remaining authors declare no competing financial
interests.
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How to cite this article: Neumann, M. A. et al. Combined crystal structure prediction
and high-pressure crystallization in rational pharmaceutical polymorph screening.
Nat. Commun. 6:7793 doi: 10.1038/ncomms8793 (2015).
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