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Using COSMOtherm.A Pharmaceutical Industry Perspective
Simone Tomasi5th COSMO-RS Symposium
Pharmaceutical Technology & Development
Macclesfield site (UK)
Pharmaceutical Development
• How to formulate the product?
• How to deliver the product to the patient?
• How to manufacture the product?
• How to package the product?
3
• Identify preferred chemical route
• Develop ways of achieving route
• Provide process understanding
• Define ranges within which process is robust
Milling Mixing Granulation
Compaction
Packaging
Device
M&DFilling
Tablet
DPI
There is more to it than
tablets and dry powder
inhalers, but ...
Starting with the target pharmaceutical
profile, Product Development is about
Chemical Development is about designing and
developing processes to enable supply of API
that performs in the product and in the patient
A
B
C
API
Route Design
Process Design
Process
characterisation
and optimisation
S AFETY
E NVIRONMENTAL
L EGAL
E CONOMICS
C ONTROL
T HROUGHPUT
Route
Starting material
Intermediates
Co
ntr
ol str
ate
gy
Other applications•Solid state predictions
•Spectra simulations in the NMR, IR and UV-vis
•....
▪ Process Understanding
• Mechanistic studies
• Answer the question “what happens and why?”
Computational Chemistry in Chemical Development
▪ Route design
• Predictive catalysis/ligand screening
• Fast regioselectivity predictions
• pKa predictions (aqueous and organic)
▪ Process design
• Solvent selection (reaction,
work-up & isolation)
• Solvent swaps
• Extraction design
• Impurity rejection
• Crystallisations
Quantum Mechanics calculations for...
E2
E1
G
Reaction coordinate
R+ E
R
EH
+
EH
R
+
R
E
ER
Aromatic substitutions
-2
0
2
4
6
8
10
12
14
-0.03 -0.02 -0.01 0 0.01 0.02 0.03
FU (a)
Sigma-profile (QM)
Reaction coordinateReactants
DABCO-catalysed
TS1
MI-
DABCOH+-catalysed
TS2 (F- elimination)
Non-catalysed
TS2 (F- elimination)
Products
VLE simulations
Solubility profiles
or NRTL/UNIFAC parameters
Partition equilibria
Aqueous
Organic
BCME BCMS
BCME BCMS
SO42-
HCO3-
Na+ K+
Cl-
Rig-D
Rig-D
logP=3.9 logP=2.4 logP=3.6
Other applications•Solid state predictions
•Spectra simulations in the NMR, IR and UV-vis
•....
▪ Process Understanding
• Mechanistic studies
• Answer the question “what happens and why?”
Computational Chemistry in Chemical Development
▪ Route design
• Predictive catalysis/ligand screening
• Fast regioselectivity predictions
• pKa predictions (aqueous and organic)
▪ Process design
• Solvent selection (reaction,
work-up & isolation)
• Solvent swaps
• Extraction design
• Impurity rejection
• Crystallisations
Quantum Mechanics calculations for...
E2
E1
G
Reaction coordinate
R+ E
R
EH
+
EH
R
+
R
E
ER
Aromatic substitutions
-2
0
2
4
6
8
10
12
14
-0.03 -0.02 -0.01 0 0.01 0.02 0.03
FU (a)
Sigma-profile (QM)
Reaction coordinateReactants
DABCO-catalysed
TS1
MI-
DABCOH+-catalysed
TS2 (F- elimination)
Non-catalysed
TS2 (F- elimination)
Products
VLE simulations
Solubility profiles
or NRTL/UNIFAC parameters
Partition equilibria
Aqueous
Organic
BCME BCMS
BCME BCMS
SO42-
HCO3-
Na+ K+
Cl-
Rig-D
Rig-D
logP=3.9 logP=2.4 logP=3.6
6
Solvent selectionTasks of solvents in a process:
• Dissolve reagents in a reaction
• Remove impurities and co-products
during work-up
• Isolate pure solid product with form
and particle control
• Clean reactor for re-use
Useful data:
• Solubility (main product; other solutes when possible)
• Water/organic partition coefficients of all product and impurities
• Acid dissociation constants
• LLE and VLE behaviour of candidate solvents
• In-house database of 272 solvents to consider
Reaction solvent(s)
Solvents for work-up (extractions)
Solvents for isolation (crystallisations)
Plant cleaning solvents
Reaction solvent selection
compatible
functional
groups
Melting
point
Boiling
point
ICH class
other
properties
Constraints
Subset of
compatible solventsReaction
Type of
chemistry
Nature of
reagents
Required
T
Input information
Process
impurities
The Solvent Selection Tool
8
• Solvent Selection is complex process.
– Selecting the ‘right’ solvent early on can have huge benefits.
• The tool allows for the consideration of multiple criteria (Graphical Approach).
• Focus on the needs of the process solvent shortlist.
Shortlist
Process
needs
Solvent
toolSolvent
tool
Solvent list
Experimentation
And
Simulation
Solute
specifics
Org. Process Res. Dev., 2016, 20, 760–773 DOI: 10.1021/acs.oprd.6b00015 David Hose
9
Solvent selection for work-up & isolation
same
diffe
rent
no
yes
compatible
functional
groups
cost
availability
ICH class
other
properties
Constraints
yes
noSubset of
compatible solventsSolvents short list
Isolation
solventsExtraction
solvents
Partition
coefficients,
pKa’sSolubilities VLE
Check
water
miscibility
Check
viable
process
volume
Make sure
solvent swap
is possible
Impurities
present?
Isolate
solid
product?
Solvent in
next
stage?
same
diffe
rent
no
yes
compatible
functional
groups
cost
availability
ICH class
other
properties
Constraints
yes
noSubset of
compatible solventsSolvents short list
Isolation
solventsExtraction
solvents
Partition
coefficients,
pKa’sSolubilities VLE
Check
water
miscibility
Check
viable
process
volume
Make sure
solvent swap
is possible
Impurities
present?
Isolate
solid
product?
Solvent in
next
stage?
10
Solvent selection for work-up & isolation
Partition
coefficients,
pKa’sSolubilities
COSMOtherm
CH3CN
Et3N
pKa = 3.9pKa = 4.9
11
Process design example: extraction solvent selection
Aims
1. Remove Et3NH+Cl-
2. Remove 2-regioisomer
3. Carry through to next
stage as solution
Constraints
1. Organic solvent immiscible with
CH3CN or water/CH3CN
2. Enabling an efficient extraction
3. Higher boiling than CH3CN
Mark Graham
12
LogP of main product vs LogP
LogP
Ma
in p
rod
uct L
ogP
All solvents LogP values
COSMOtherm 2016
BP-TZVPD-FINE
Mark Graham
13
Choosing solvent for extraction into acidic aqueous phase
LogP
Ma
in p
rod
uct L
ogP
LogP values without
• ICH Class 1 solvents
• Some solvent classes
• Tboil < 200 °C
MTBE
Toluene
Alkanes
CPME
TAME
Mark Graham
14
Two work-up strategies
End of reaction
CH3CN mixture
Add water
Extract into
organic solvent
Extract into
acidic aqueous
Neutralise &
extract into
organic solvent
Swap to
organic solvent
Extract into
acidic aqueous
Wash with
water
Neutralise &
extract into
organic solvent
Organic solution for next stage
Reject Et3NH+Cl-
to aqueous phase
Reaction products
stay in organic phase
Product in aqueous phase
Regioisomer in organic phase
TolueneHeptane
Chosen Heptane.
Reaction solvent changed
from CH3CN to DMSO.
Final extraction with MTBE.
Distil off CH3CNRequired for Toluene only
TolueneHeptane
End of reaction
CH3CN mixture
Mark Graham
• What is the best way to predict solubility with COSMOtherm?
• How accurate are the predictions?
15
Solubility predictions
Approximation:
Justified only near to Tm
→error estimating Gfus!
How does COSMOtherm predict solubility?
16
Solute(s)
Gfus
SGmix
Solute(sol)
Solute(l) log10ሺ𝑥S) =mxx − mS
x − ∆Gfusx
RTln10
RTln10 ∙ log10ሺ𝑥S) = mxx − mS
x − ∆Gfusx
= m𝐒ሺ𝐬𝐨𝐥𝐢𝐝)𝒙 − m𝑺
𝒙 = 𝑹𝑻𝒍𝒏ሺ𝒙𝑺)
• Gfus from DSC data (standard approach)
• Gfus from reference solubility
∆𝐶𝑝𝑓𝑢𝑠~0
∆Gfusx = mx
x − mSx − RTlnሺ𝑥S)
∆𝑆𝑓𝑢𝑠= ∆𝐻𝑓𝑢𝑠/𝑇𝑚
Gfus known at the T of the reference solubility
No knowledge of T dependence
∆𝐺𝑓𝑢𝑠= ∆𝐻𝑓𝑢𝑠 − 𝑇∆𝑆𝑓𝑢𝑠 − ∆𝐶𝑝𝑓𝑢𝑠 𝑇𝑚 − 𝑇 + 𝑇∆𝐶𝑝𝑓𝑢𝑠𝑙𝑛𝑇𝑚𝑇
Effect on predictions of experimental variation in DSC data
17
• COSMOtherm16, BP-TZVPD-FINE, absolute solubility (iterative), Gfus from DSC
• Not interested in a comparison with experiment!
• Variation of predictions exclusively due to different input Hfus and Tm
• Single AZ compound; 9 measured Hfus/Tm
values
• 9 predicted values for each solvent; 259
solvents
• For each solvent plot distribution of
Ln(w_solub)
• Std Dev values from each solvent similar but
not identical
• Distribution plot of all Std Dev values gives an
average Std Dev
• Average Std Dev = 0.66 Ln units
• Due only to variation in DSC data
Variation of experimental DSC data caused a
factor of ~2 variation in predicted solubility
# Hfus
(kJ/mol)
Tm
(°C)
1 45 207
2 48 208
3 34 207
4 40 209
5 38 206
6 42 205
7 36 206
8 39 207
9 39 205
MeOH
Not all reference solvents are made equal!
18
• Previous internal AZ work: ACETONITRILE on average appears to provide
the best experimental reference solubility data for COSMOtherm solubility.
• The expected model error is a factor of ~3 (assuming no experimental error).
BP/TZVPD-FINE COSMOtherm16Zachary Lockhart
ACN
FINE_16 Log(Predicted) vs Log(EXP) by reference
19
ACN RMSE = 0.53Acetone RMSE = 0.76
DSC RMSE = 0.78 QSPR RMSE = 1.41
RMSE = 0.44
(H2O and Heptane
outliers removed)
MeTHF RMSE = 0.60
H2O RMSE = 1.77
RMSE = 0.65
(H2O and Heptane
outliers removed)
COSMOtherm16 vs COSMOtherm17
20
For other reference solvents the mean also varied
THF iPrOH
Reference solvent: ACN
The 2016 parameterisation performed better!
AZ Solubility prediction decision tree
Best possible approach First choice alternative
approach
Second choice
alternative approach
Choose as a last
resort
1.
Multiple solubilities
from internal thermodynamic
solubility screening
available?
2.
Are other
thermodynamic solubility
data in multiple solvents
available?
3.
Is the solubility in
ACN* known?
4.
Can it be
measured?
7.
Can a DSC from a
sufficiently pure sample
(>98% assay) be
obtained?
6.
Is the DSC data usable? (no solid state transformations /
desolvation / decomposition obscuring
the main melt)
5.
Is DSC data from a
sufficiently pure sample
(>98% assay)
available?
Absolute solubility
calculation with
Gfus estimate from
best reference
solvent
Absolute solubility
calculation with
Gfus estimate from
DSC
Absolute solubility
calculation with
Gfus estimate from
ACN reference
solvent
Absolute solubility
calculation at 25 °C
with Gfus estimate
from QSPR
yes
no
yes
no
no
no
yes
yes
yes
no
no
noSTART
* other solvents may
also be suitable.
• What is the best way to predict solubility with COSMOtherm?
• How accurate are the predictions?
22
Solubility predictions
• All following conclusions need to be confirmed with a larger data set.
• BP-TZVPD-FINE (2016 parameters) was the “flavour” of COSMO-RS that performed best.
• Variation of DSC experimental values has a strong influence on solubility predictions.
• Solubility predictions with COSMO-RS often work better using reference solubility data.
− COSMO-RS TZVPD-FINE predictions (2016 parameterization), acetonitrile reference
solubility data: RMSE = 0.53 Log units (0.44 excluding outliers).
− Using DSC as input: RMSE = 0.78 Log units (0.65 excluding outliers).
• Not yet clear if a single default solvent can work well enough as a reference for all solutes.
Development challenges
23
• Effects of ions in solution
– Ion supermolecules with optimal number of waters
– Implementation of COSMO-RS-PDHS into COSMOtherm
• Oiling out
– Fast and reliable way to compute and plot SLLE for ternary systems
• Interaction Energy Indices
– Great concept, necessary for treating well dimerization problems
– How could its use be made easier?
• Solubility of salts of pharmaceutical compounds
– Currently inaccurate even for salts of simple organics
Models for ions in solution
Ion-water supermolecule approach
• How many waters?
• “Easy” for metal cations and
monoatomic anions
Searchlight for water # optimization:
balance s-profiles not exceeding much
the s range span by water vs complexity
Larger anions (CO32-, SO4
2-, PO43-)
are more difficult
• More highly charged
• Multiple conformations of the
ion-water(s) supermolecule
Chem Eng Res Des, 2014, 92, 2873-2883
Can COSMOtherm predict salting out?
25
Effect of electrolytes on:
• Number of liquid phases
• Amount of water in organic phase
• Partition of solute
Process relevant conditions
Aqueous
Organic
SO42-
Na+
?Org. Process Res. Dev., 2017, 21,1355–1370
COSMOtherm
BP-TZVPD-FINE 2016
Dihydrated Na+, monohydrated SO42-
Water content in the organic phase
y = x
Experimental
Pre
dic
ted
Conditions:
• 35°C
• 14% w/w sodium sulfate (1 molal)
• 33-100% v/v MeTHF in DME
Org. Process Res. Dev., 2017, 21,1355–1370
COSMOtherm predictions:
• Correct trend
• Water in the organic phase
overpredicted by a factor of ~2
Salting out effect (Dm)
y = x
Experimental
Pre
dic
ted
Dm(Exp)
% vol
MeTHF
in DMECOSMOtherm predictions:
• Correct trend
• Salting out overpredicted
by a factor of ~2.3.
Org. Process Res. Dev., 2017, 21,1355–1370
wt%
Na2SO4
Change of Dm at 35 °C with wt% Na2SO4 (aqueous phase)
and vol% 2-MeTHF (organic phase). Vorg/Vaq = 2.
Oiling out (SLLE behaviour)
28
Why it is important:
• Oil phase is often a good solvent for impurities, which will lower the purity of the final product
• May stick to vessel walls/agitator/probes
• Slows crystallisation rate as the meta-stable liquid phase hinders primary and secondary nucleation
• Uncontrollable morphology of crystals
What it is:
“A liquid-liquid phase boundary below the liquidus, but inside
the metastable zone, where a supersaturated solution may
be prone to liquid-liquid phase separation before the onset of
crystal formation”Davey et al, CHEM. COMMUN. , 2003, 698–699
“From a thermodynamic point of view, oiling out is supposed
to be caused by a superposition of liquid–liquid demixing
and solid–liquid phase equilibrium (solubility curve).”Sadowski et al, Journal of Crystal Growth 2008, 310, 4163– 4168
Thank you!
29
AstraZeneca
David Buttar
David Hose
Lucie Miller-Potucka
Anna Jawor-Baczinska
Andy Phillips
Simon Yates
Simon Black
Mark Graham
Emerging Technologies Consortium
Solubility Working Group
Yuriy Abramov (Pfizer)
Jacob Albrecht (BMS)
Rahul Sangodkar (Amgen)
Mike Lovette (Amgen)
Frank Ricci (BI)
Jeff Tan (Lilly)
Alex Chin (Merck)
Confidentiality Notice
This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and remove
it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the
contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 1 Francis Crick Avenue, Cambridge Biomedical Campus,
Cambridge, CB2 0AA, UK, T: +44(0)203 749 5000, www.astrazeneca.com
30