Designing for solubility when lowering log P isnt enough

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Designing for solubility - when lowering log P
isnt enough

• A lot of modeling is how much crap you can
  take.Lauren Hutton
• Logic is useful for proof, but almost never for
  making discoveries.
• Vilfredo Pareto
• a model, like a good cartoon, captures
  important features of the reality it is meant to
  portray.
• Norbet Muller

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Many facets of solubility
-Bergström, et al. Eur. J. Pharm. Sci. 22 (2004)
387-398.
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Solubility model development schema
Iterative approach brings significant risk of
overfitting.
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Intrinsic Solubility Model

• Data selection
• Non-ionizable compounds from PhysProp
• 250 MW lt 750
• Reasonable structures only selected by hand.
• 199 training cmpds, 20 test cmpds
• Structures
• OEChem Canoncial Smiles, Omega conformer,
  minimized with OPLS2005/water using Bmin.
• Descriptors
• clogP,Volsurf, H-bond acceptors donors
• Feature Selection
• Simulated annealing with MLR/PRESS

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Intrinsic Solubility Model(Solubility of neutral
form outside of crystal lattice)

• Training Set R20.88, RMSe0.61, N199
• Validation Set R20.93, RMSe0.50, N20
• - constant not used when Xtal packing effects
  included

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Intrinsic Solubility Model(Solubility of neutral
form outside of crystal lattice)
Pharmaceutically relevant range

• Training Set R20.77, RMSe0.59
• Validation Set R20.87, RMSe0.50
• - constant not used when Xtal packing effects
  included

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Crystal Lattice Stability

• Hypothesis The extent of disorder of the unit
  cell in response to increasing energy is
  indicative of the stability of a crystal lattice.
• Ansatz Effect is non-linear, with functional
  form

Griseofulvin
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Crystal Packing Melting Point
Mult. Crystal forms 10 crystal forms of same
compound Project 1 5 compounds from three
chemotypes Project 2 6 compounds from two
chemotypes
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Error model for pH-solubility curve

• Prediction errors for various terms in model
• Uses 90 confidence interval of intrinsic
  solubility
• 0.5 pKa units from ACD/pKa or Epik. (arbitrary)
• Std. dev. of 3 runs for crystal packing effect.
• 0.2 error for std. dev. of ionization slope.
  (arbitrary)
• Monte Carlo error simulation
• Each error term is considered independent
  normally distributed with the error limits
  (either 90 conf interval or std dev.) defined
  above.
• Predicted solubility generated 1000 times at each
  pH, report median 90 interval.

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Intrinsic Solubility Predictions

• RMSe0.83, Median err0.63

RMSe0.86 Median err0.41
Intrinsic solubility data from Wassvik, et al
(Euro. J. Pharm. Sci., 29, 2006, 294305) (N25)
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Solubility Prediction Glyburide

• Crystal packing simulation based on CSD entry
  DUNXAL
• Predicted Xpack1.30.26, log So-5.90.35,
  pKa4.70.5
• Measured log So-7.1, pKa5.4

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Project Example

• Early members of lead chemotype are potent and
  selective antagonists
• Characterized by poor solubility that is not
  tightly coupled to high logP
• In vivo efficacy established

• 313 compounds with measured solubility
• 30 cmpds sol. gt 1 ?g/ml
• 2 with Ki lt 50 nM

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Cmpd-1 Solubility Profile

• Model highlights logP size as major factors
• Other parameters have important impact as well
• Lack of significant HPLC LogP correlation hinted
  that crystal packing may play significant role as
  well.

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Cmpd-1 Solubility Profile
HPLClogP gt 7 Exp. Sol lt 0.1?g/mL Pred. Sol
0.0005 ?g/mL

• Small molecule X-ray shows tight packing into the
  pocket formed by aromatic rings.
• MD simulations show this crystal form to be
  highly stable.

Xpack1.97
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Cmpd-2
EWG replaced by aliphatic group
HPLClogP3.8 Measured 4 ?g/mL Predicted 0.4
?g/mL

• Xpack simulation used Cmpd-1 x-ray structure as
  a template.
• Xpack 1.4
• Head group leaves aryl pocket in simulation at
  higher T
• Intrinsic solubility pred. 2.5 log units
  improved over cmpd-1

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Cmpd-7

• Heterocycle replacement for phenyl leads to
  unsymmetrical pocket
• Simulation using modeled structure of Cmpd-7
  based on Cmpd-1 shows that EWG not as stable in
  the modified pocket

HPLCLogP5.2 Exp. Sol 0.2?g/mL Pred. Sol 0.1
?g/mL
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Cmpd-8

• Solubility _at_pH6.5
• 3.8 - 55 ?g/mL depending on salt/crystal form.

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Solubility Estimation

• General solubility prediction including
  solvation, ionization, and local crystal packing
  simulation.
• Crystalline material only
• Most 1.0 ?g/mL 0.1 ?g/mL were recorded as soft
  numbers (e.g. lt 1.0 ?g/mL)

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Trends in Solubility Potency
50-compound moving geometric mean
Cmpd-8 registered
Cmpd-7 X-ray supports strategy
Crystal packing strategy proposed

• Chemistry took knowledge from modeling and
  derived structures to disrupt key crystal
  interaction.
• Improved solubility apparent, with maintained
  potency.

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Primary Assumptions

• Crystal packing effect falls off with ionization
• Untrue possibly fall off as ionization state
  differs from ionization state of crystal? At
  what rate?
• Crystal packing effect is independent of the free
  energy of solvation.
• Crystal packing can limit aqueous solubility by
  up to 2 orders of magnitude. (arbitrary)
• Ionization effect limit set to 4.25 log units for
  single acid or base, 5.0 for multiple ionizable
  centers. (incorrect)
• Crystal form of a new analog is similar to that
  of solved X-ray of a previous similar analog.
  (very risky)

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Major sources of error

• Sensitive to quality logP estimate.
• Comparability of crystal packing effect
  simulation is unclear - only relevant compared to
  other compounds in a series?
• No consideration of crystal rearrangement on
  melting
• Hemihydrate water leaves crystal (50 oc) prior
  to melting at 174 oc. Simulation shows this
  structure as unstable at low T.
• Better for compounds with known x-ray unit cell.
• Most common source of error (by far!) are poor
  pKa estimates
• Jaguar calculated pKas can somewhat mitigate
  this at significant added compute time.
• 4-10 cpu hours typical vs. 1 min. for Epik or ACD

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Summary

• Reasonable performance over pH-solubility curve
  when viewed in entirety, but
• Point estimates of solubility at pH6.5 are often
  dramatically off, usually due to errors in pKa
  estimate
• Individual components of the model can be
  interpreted to provide predicted information on
• Molecular features implicated in intrinsic
  solubility
• pKa
• Influence of crystal packing on limiting
  solubility.
• Complicated, but generally interpretable, model.

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Acknowledgements

• Collaborators
• Olafur Gudmundsson (Pharmaceutics/PCO)
• Xue-Qing Chen (Pharmaceutics/PCO)
• Denette Murphy (ARD)
• Chemistry
• Numerous colleagues
• Lexicon
• Terry Stouch

• Analytical RD
• Jack Gougoutas
• Mary Malley
• CADD
• Malcolm Davis
• Brian Claus
• Andy Pudzianowksi
• Arthur Doweyko
• Doree Sitkoff
• Stan Krystek
• Dan Cheney

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Solubility Prediction Algorithm
Effect of Ionization
Effect of Crystal Packing Forces
Solubility at a given pH
Aggregation Number
Intrinsic Solubility
Ionization effect Range
FI is the fraction ionized at pH
Where DT are the diffusion coefficients from an
escalating temperature molecular dynamics
simulation.
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Solubility Prediction Haloperidol

• HCl salt HALDOL01
• Mesylate modeled on YANMUW

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If we had a crystal structure

• we wouldnt need to predict solubility.
• Simulate crystal packing by overlaying molecule
  of interest on known crystal structure of related
  compound
• Less reliable as compounds become less related.
• Only suggests if new compound can form the same
  crystal form as the known crystal structure.