Control and Prediction of the Organic Solid State
A Basic Technology project of the Research Councils UK
Computational Prediction of
Pharmaceutical Crystal Structures a severe test of modelling
supramolecular assembly
Sarah (Sally) L Price
Department of Chemistry, UCL
www.cposs.org.uk
Contrast Crystals - geological
 Durable &
hard as
strong
forces
between
atoms
 Grown on
geological
timescales2cm
10 to 1000
years
Organic/pharmaceutical and
protein crystals
 Often very difficult (impossible?) to get even the
very small crystals needed for solving structures
by diffraction
 Compromise strong covalent bonds & weak
intermolecular forces
 many
Protein crystals in 1-2 ml drop
Large crystals
parabanic acid
~ 3-5mm
Paracetamol form II
Electron micrograph
X-ray diffraction gives the atomic
scale model
Much greater resolution in
organics than proteins
No or limited water
Protons often located from
diffraction data
Solving structures from powder
samples increasing
The Cambridge Crystallographic Database of
organic crystal structures has >500,000 entries
Most are the crystal structure of the first crystal found that
was suitable for using X-ray diffraction, as chemists used
to be only interested in the molecular structure
Principles of crystal packing
small molecules to proteins
 Close packed
 solvent may fill small voids
dynamic water surrounds most protein molecules
 Forms hydrogen bonds, p-p stacking, X...X
Intermolecular, more diversity
Intramolecular, amino acids
 Conformation vital
 ~ isolated molecule (Y), some torsions vary
 dominant issue & major constraint
 Emphasis on inter - vs intra- molecular forces differ
Exercises in prognostication:
Crystal structures and protein folding
JD Duntiz & HA Scheraga, 2004 PNAS 101, 14309
global optimisation problems to identify the
structure(s) of lowest potential (or free)
energy
Search challenge
Accuracy of energy evaluation
Kinetic factors ~ preferred pathways to
assembly, may be involved
Objective blind tests “need to be maintained
so they can continue to document progress
and monitor excessive claims”
Polymorphism - a common
phenomenon??
Polymorphism - the ability of a substance to adopt
more than one crystal structure
since different physical properties, now a major
cause for concern when products transform from one
polymorph to another.
L. Yu et al.
•Pigments - change colour.
•Chocolate - need polymorph of
cocoa butter that melts at 37 oC.
• Explosives - change of
polymorphic form leads to
different detonation properties &
industrial accidents.
2000, J. Am.
Chem. Soc.
122, 585.
Pharmaceuticals must be
marketed in one controlled
polymorphic form
Change of polymorph changes effective
dose
Want to choose the crystalline form for
optimum properties & control production
Regulatory requirement for
pharmaceuticals that all reasonable
experiments are performed in order to
identify the maximum number of crystalline
forms
Difficulty in establishing that all
polymorphs are known
McCrone (1963) “the number of
polymorphs of a material depends
on the amount of time and money
spent in research on that
compound”
- Some appear after decades of
crystallisation work on compound
- Some “disappear” after a more stable
polymorph is discovered.
Which drugs may have
undiscovered polymorphs?
 1998 Abbott Laboratories anti-HIV drug
Ritonavir produced new polymorph during
manufacture after 2 years
 Problem affected plants in different countries
 Required reformulation
 “ Unfortunately, there is nothing we can do today to prevent
a hurricane from striking any community or polymorphism
from striking any drug” Sun, Abbott Laboratories, press conference.
Can we computationally predict whether the drug is
in the polymorphism equivalent of Louisiana or
Hertfordshire, Herefordshire or Hampshire ?
Why calculate crystal energy landscapes?
~ the thermodynamically feasible crystal structures
 to confirm that most stable polymorph is known
 to design new molecular materials prior to synthesis
 to see what structures are plausible undiscovered
polymorphs
 Thermodynamics vs. crystallization conditions
(T, P, solvent, supersaturation, impurities, …..)
 to help solve structures from powder XRD or other
experimental evidence
 as a complement to polymorph screening and “Quality
by Design” crystallization processes in pharmaceutical
development.
2010 5th CCDC Blind Test results –
can we predict a crystal structure?
O 2N
O
O
-
+
N
NO 2
N
COOH
O
O
S
CH3
+
COO-
N
Cl
Cl
-
2/13*
OH
N
OH
SO2
HOOC
NH
OH
Polymorphs 3 and 4
2/10*
x/y
H2O
S
O
O
+
2/11
1/13
CH3
N
H
A salt
N
Cl
2/15
N
CH3
0 or 2 excl H* /10
x = # correct within 3 submitted
y = # groups submitting *own success
Main issue is accuracy of calculating relative energies of
different crystal structures
Successful approaches to calculating
lattice energy (biological force-fields rarely adequate)
 Plane wave density
functional theory
(i.e. crystal Y)
supplemented by
empirically damped
-C6/R6 dispersion
 Elatt=Eelectronic+Edisp
 Model for intermolecular
forces with electrostatic
model derived from isolated
molecule Y
 DEintra from Y
 Elatt = Uinter+ DEintra
 Non-spherical atoms
 developed by fitting to
 Use theory of intermolecular
crystal structures
forces, moving toward nonNeumann, M. A.; Perrin, M. A. J.Phys.Chem.B 2005, 109, 15531
empirical models
Success in 4th for C6Br2ClFH2
with no experimental input
Misquitta AJ, Welch GWA, Stone AJ, Price SL 2008.Chem Phys Lett 456
Rarely only one feasible crystal
structure
H3C
Requires a uniquely
favourable close packing
defining all 3 dimensions
O
H
N
N
N
O
H
O 2N
O
CH3
Example with energy gap of
~12 kJ mol-1
Unique close packed plane
Unique stacking from
electrostatics
MU Schmidt 1999 Erice
Pigment Yellow 74
O
CH3
More typical
from 2007 blind test
Cl
Br
Br
H
H
F
Landscapes will show the
expected hydrogen bond
motifs defining
ribbons/layers
BUT different
•packings of ribbons
•stackings of layers
More predicted
structures than known
polymorphs
Relative energies
sensitive to method
Basic method for crystal energy landscapes
~ thermodynamically feasible crystal structures
 Use quantum mechanics to predict molecular structure and
represent the charge distribution within the molecule
(repeat with multiple conformers for flexible molecules, using
intramolecular energy penalty DEintra)
 Use search method to generate plausible crystal structures
(~3000 MOLPAK or ~105 CrystalPredictor for each rigid
conformation, or >106 for flexible CrystalPredictor) for Z’=1,...
 Use advanced models of the intermolecular forces (distributed
multipoles to represent lone pair & p electron density) to minimize
the intermolecular lattice energy Uinter of each crystal structure.
 Refine conformation within crystal to minimize Elatt= Uinter + DEintra
> Basic Crystal (Lattice) Energy Landscape
 Estimate lattice modes, elastic tensor & harmonic free energies
for rigid molecules and confidence in relative stabilities.
 Calculate other properties: PXRD, morphologies
Karamertzanis PG, Kazantsev AV, Issa N, Welch GWA, Adjiman CS, Pantelides CC, Price SL 2009. J Chem
Theory Comput 5, 1432
Price SL, Leslie M, Welch GWA, Habgood M, Price LS, Karamertzanis PG, Day GM
2010. Phys Chem Chem Phys 12:8478-8490.
Why do we overpredict polymorphism ?
1 Neglect of thermal motion
Cyclopentane
C5H10
MD 30K ~ form III
MD 160K ~ form I
Plastic phases
Free energy landscape for benzene has ~ a minimum
for each known form in a metadynamics study
Both have many lattice energy minima, and ~ only the
observed structures when thermal motion modelled.
Solid state transitions unusually facile for these hydrocarbons
Torrisi A, Leech CK, Shankland K, David WIF, Ibberson RM, Benet-Buchholz J, Boese R, Leslie M, Catlow CRA,
Raiteri, P. et al. Angew.Chem.,Int.Ed. 2005, 44, 3769
Price SL 2008. J Phys Chem B 112:3746
Contrast solid state of 5-fluorouracil,
with no polymorphic transitions
-94
Form I
Z’=4
Lattice Energy / kJ mol-1
-96
C2/c
P-1
-98
-100
-102
75% of
these
structures
are free
energy
minima at
310 K
P2/c
P21
P21/c
P212121
Pbcn
In two
solvates
Pc
Pca21
Pna21
Form I
Form II
-104
1.55
1.6
1.65
1.7
-3
Density / g cm
1.75
1.8
Form II found experimental search from dry nitromethane
Form II &
solvate
Hulme AT, Tocher DA, SLP, 2005 J. Am Chem Soc, 127, 1116
Karamertzanis PG, Raiteri P, Parrinello M, Leslie M, SLP 2007 J Phys Chem B 112:4298.
Do we need to do Molecular
Dynamics to model thermal motion?
Only if expect facile phase transitions.
Dynamics of nucleation & growth will
determine which structures are observed
hydration of
uracil in
water gives
close F···F of
form I
Hamad, S, Moon, C, Catlow, CRA, Hulme, AT, SLP, 2006 J. Phys. Chem. B, 110 3323
in
nitromethane
get R22 (8) of
form II
Solid-State Forms of b-Resorcylic Acid:
How Exhaustive Should a Polymorph Screen Be?
Braun DE, Karamertzanis PG, Arlin J-B, Florence AJ, Kahlenberg V, Tocher DA,
Griesser UJ, Price SL 2011 Cryst Growth Des 11: 210-220.
New polymorph I predicted,
Added confidence to PXRD
solution and evidence for proton
disorder
Similar
structures,
unlikely to be
distinguishable
polymorphs
How?
Relative stability?
Catemer polymorph?
Why do we overpredict polymorphism ?
2 The right crystallization
experiment has yet to be performed
Huge range of crystallization methods
which have generated new polymorphs
– deliberate to failed cocrystallization
Experimental conditions vary kinetics of
nucleation & growth
Can we use crystal energy landscapes to
find the right crystallization conditions?
The right crystallization experiment has not yet
been performed on carbamazepine ?
Early predictions of a chain structure
 Better methods, modelling flexibility, induction etc
– chains still competitive, also for related molecules
Florence AJ, Johnston A, Price SL, Nowell H, Kennedy AR, Shankland N 2006. J Pharm Sci 95:1918-1930.
Exptal searches are productive
N
O
dimers
chains
isostructural
relationships
N
NH2
O
NH2
O
NH2
O
NH2
DHC
CYH
CYT
CBZ
form I
form I
form I
form I
1992
2007
2008
2003
form II
form II
form II
form II
2006
2008
2008
1987
form III
form III
2007
1981
form IV
form IV
2010
2002
1:1 CBZ:DHC solid solution
form V
2006
In prepn
Success of catemeric CBZ V
required seeded sublimation
CBZ form V
CBZ form V
DHC form II (seed)
CBZ form V
Arlin J-B, Price LS, Price SL, Florence AJ, in prepn
Pbca
a/Å
b/Å
c/Å
Expt
9.1245(5) 10.4518(5)
24.8224(11)
Rigid
prediction
9.3124
10.5979
24.8819
Flex
prediction
9.4816
10.3426
24.7227
Finding the right crystallization
conditions may be even harder
Racemic crystal could not be
formed without racemization
- or obliging synthetic chemist
Challenge: what about cases where barrier is high but no so high?
e.g. Changing to an unfavourable conformation – c.f. ritonavir
Lancaster, RW; Karamertzanis, PG; Hulme, AT; Tocher, DA; Covey, DF; Price, SL, Chem.Commun., 2006, 47, 4921
(Dis)Appearing polymorphs
 Only need to nucleate more stable form
once to get seeds
Develop other routes to most stable form
May lead to loss of control of crystallisation
of metastable form
Other forms of seeding/templating
 May need impurities to producing a polymorph
1 mol% ethamindosulphathiazole stabilizes form I sulphathiazole
 Attempts to reproduce form 2 progesterone failed
– could only get moderately unstable samples when
crystallised in presence of pregnenolone
Lancaster RW, Karamertzanis PG, Hulme AT, Tocher DA, Lewis TC, Price SL 2007. J Pharm Sci 96:3419-3431.
N. Blagden, R. J. Davey, R. Rowe and R. Roberts, Int. J. Pharm., 1998, 172, 169-177.
50 year old samples from
Innsbruck
Liquid Chromatography-Mass Spec
Form 2 11 impurities total 4.85%
Form 1 3 impurities total ~1.5%, Aldrich 1.3% different impurities
irreproducible cocktail of impurities needed for long-lived form 2?
Lancaster RW, Harris LD, Pearson D CrystEngComm, ASAP
Why do we overpredict polymorphism ?
3 The right crystallization
experiment cannot be performed
 Crystal may be unstable relative to other products,
inherent in possible range of crystallization
experiments
 Solvates may form
 Proton transfer – salt or cocrystal if 0< DpKa <3
 Cocrystal may be less stable than components
Why do we overpredict polymorphism ?
4.Plurality of possible structures is
hindering crystallization
Crystallization is difficult
“Commonly found that when good quality
large crystals of a substance cannot be grown,
the small crystals are poor in quality with
substantial mosaic spread”
Harding, M. M. J. Synchrotron Radiat. 1996, 3, 250
i.e. structures solved from very small crystals
(synchroton) are more likely to be disordered
Can crystal energy landscape can warn of
possibilities of disorder = combinations of low
energy structures?
From Eniluracil Crystal Energy Landscape
H
H
H
N
Non-polar ribbons
Polar ribbons
O
N
H
-114.9
kJ mol-1
-115.5
kJ mol-1
Parallel
ribbons
PXRD_1
-116.1
kJ mol-1
PXRD_2?
Anti-parallel
ribbons
-116.4
kJ mol-1
Also little energy discrimination for the stacking variations for C4O C6H interchange
Stacking & interdigitation errors hard to avoid & barrier to correction
O
Experimental: variable disorder in single XRD on
4 crystals
Single crystal analysis could be
interpreted as polymorphism.
Powder patterns are very similar
Variable disorder challenging for
devising robust production process
P21/n disordered anti-parallel non-polar
0.742(3) 0.705(3) 0.738(3) 0.841(3)
Simulated PXRD
Crystal 4 better R1 P21 Z’=2 minor polar
Copley RCB, Barnett SA, Karamertzanis PG, Harris KDM, Kariuki BM, Xu MC, Nickels EA, Lancaster RW, Price SL 2008. Cryst
Growth Des 8:3474
Where are we now?
Crystal energy landscapes complement
experiment, providing the alternatives
likely motifs in solid forms
range of possible target structures
possible types of disorder
Can be calculated with “good enough” accuracy
for increasing range of molecules & multicomponent systems
from aspirin / paracetamol to modern
pharmaceuticals
H2N
O
N
O
Database of
computed
crystal
structures
O
H
O
O
>150 molecules
H3C
N
N
N
H3C
N
H
S
H
H
+
N
H
-
O
O
H
What are the challenges?
Improving accuracy of relative energies
periodic electronic structure DFT+D
 non-empirical anisotropic atom-atom potentials
 free energies
Understanding limitations of thermodynamic
predictions ~ kinetic factors that lead to
polymorphism
Move to modern pharmaceuticals
Computational efficiency
Grateful Thanks to
 Matthew Habgood, Doris Braun, Nizar Issa, Gareth Welch, Sharmarke Mohamed
 Derek Tocher, Louise Price, M Leslie (ex-CCLRC) Bob Lancaster (ex-GSK) (UCL)
 Andrei Kazantsev, Panos Karamertzanis, Costas Pantelides, Claire Adijman (IC)
 Alastair Florence, Andrea Johnston, Jean-Baptiste Arlin, Phillipe Fernandes (SU)
 Other coworkers in CPOSS and many collaborators
 Other Programs AJ Stone (Cambridge), H Ammon (Maryland), CCDC
 Computing infrastructure: National Grid Service (database), HPC(x), UCL
 CCDC & CSP community for blind tests
 Funding EPSRC (including E-Science)
 Basic Technology Program of RC UK for funding Control and Prediction of the Organic
Solid State www.cposs.org.uk, including “Translation” funding for Knowledge Transfer
in CPOSS Industrial Alliance from April 2008.
CPOSS Open Day, UCL
Wednesday 30 March 2011
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10.00, Coffee and registration in the South Cloisters
Introduction and welcome,
Progress in the fifth International Test of Crystal Structure Prediction,
Industrial problems from polymorphism and how we might avoid them, Dr Colin Groom, CCDC
Mapping Crystallization Processes Using In-Situ SSNMR, Dr Colan Hughes, Cardiff University
First and Second Order Transitions: A Re-appraisal, Dr Terry Threlfall, University of Southampton
12.30, Lunch and poster session
2.00, The role of transformations in pharmaceutical crystallization, Prof. Kieran Hodnett, University of
Limerick
GIPAW: a "Bragg's Law" for solid state NMR, Prof. Chris Pickard, UCL
Experimental screening and characterization of solid forms, Prof. Alastair Florence, University of
Strathclyde
3.45, Coffee and poster session cont.
5.00, Removal of posters
Sponsored by CPOSS Industrial Alliance – visit www.cposs.org.uk to register