Utilization of ReactIR in fit for purpose process enablement

Article abstract of DOI:10.1021/op5003165

An efficient four-step synthesis of 1 is described in which utilization of ReactIR was key to efficient processing and reaction monitoring. Key chemical steps included (i) nucleophilic aromatic substitution, iron reduction of aromatic nitro group to anili

Full text of DOI:10.1021/op5003165

Article
pubs.acs.org/OPRD
Utilization of ReactIR in Fit for Purpose Process Enablement
Shane A. Eisenbeis,* Raymond Chen, Ming Kang, Mark Barrila, and Richard Buzon
Pharmaceutical SciencesResearch API, Pfizer Global Research & Development Eastern Point Road, Groton, Connecticut 06340,
United States
ABSTRACT: An efficient four-step synthesis of 1 is described in which utilization of ReactIR was key to efficient processing and
reaction monitoring. Key chemical steps included (i) nucleophilic aromatic substitution, iron reduction of aromatic nitro group
to aniline, (ii) decarboxylation, and (iii) ester formation.
Scheme 1. Original synthesis of (1)
INTRODUCTION
We recently required multikilogram quantities of amide (1,
Figure 1) for use in toxicological studies. Several challenges
■
Figure 1. Structure of amide (1).
were associated with the target, including formation of the
chiral center, process monitoring at elevated temperatures, and
the final form of 1.
The original preparation of 1 (Scheme 1) was conceptually
straightforward but suffered from a relatively lengthy linear
sequence of reactions, multiple solvent systems, and the
inability to isolate final amide (1) in a usable form. The
route provided access to 10 g quantities of 1, but with modest
overall yields (∼23%), it became clear that further scale-up
would require significant process enabling.
DISCUSSION
■
Synthesis of (10). Initial efforts focused on a more
convergent process, eliminating multiple catalyst charges,
solvents, and unnecessary protection schemes. The processing
was broken down into three components which would serve as
key building blocks.
Scheme 2. Synthesis of intermediate (13)
Diethyl malonate was selected over dimethyl malonate for
the nucleophilic aromatic substitution, providing a significantly
cleaner conversion of (2) to (12) in 2-MeTHF (Scheme 2).
Reduction of crude nitrobenzene (12) to aniline (13) was
achieved under Fe−HOAc conditions.1 This resolved the issue
of multiple catalyst charging, thus significantly improving
processing safety. The aniline (13) was readily isolated from
the mixture as a solid which could be further purified by
triturating in heptanes if needed. This process was outsourced
to multiple vendors who successfully prepared 13 to support
the manufacturing campaign described later herein.
Special Issue: Process Analytical Technologies (PAT) 14
Received: October 9, 2014
© XXXX American Chemical Society
A
dx.doi.org/10.1021/op5003165 | Org. Process Res. Dev. XXXX, XXX, XXX−XXX

Organic Process Research & Development
Article
Limited access to larger quantities of acid 7 through
commercial sources necessitated the need to quickly develop
a process to 7 (Scheme 3). Standard Suzuki coupling of aryl
scaling the hydrolysis and decarboxylation (20 → 10), it was
noted that significant amide hydrolysis occurred. The
decomposition of 20 was presumably due to the increased
solubility of acid (10) in 2-MeTHF exposed to strongly basic
conditions. A variety of bases and solvents were investigated to
determine optimal conditions (Table 1 and 2). Once K2CO3
had been determined to be an acceptable base for converting
the ester (20) to the acid (10), we next looked into reducing
overall processing time.
Scheme 3. Synthesis of intermediate carboxylic acid (7)
Table 1. Base effects on hydrolysis of 20 in refluxing 2-
MeTHF
bromide (14) and boronic acid (15) followed by hydrolysis in a
single pot afforded 7 as the crude acid.2 The acid was purified
via recrystallization from ethanol and water affording the acid
(7) in excellent purity and yield. This process was sourced to
multiple vendors who successfully prepared 7 in order to
support the manufacturing campaign also described later
herein.
entry
base
time (hr)
yield
1
2
3
4
1 N LiOH
1 N NaOH
sat. NaHCO3
sat. K2CO3
1
decomposition
decomposition
N.R.
1
24
18
>99%
Table 2. Solvent effects on hydrolysis of 20 with 2.5 equiv
K2CO3(aq) at reflux
The final component (11) was prepared utilizing a procedure
similar to Othman and co-workers (Scheme 4).3 Treatment of
entry
solvent
time (hr)
yield
Scheme 4. Synthesis of intermediate lactam (11)
1
2
3
4
THF
1
1
3
1
>99%
>99%
>99%
>99%
MeOH
EtOH
2-MeTHF/MeOH
Although both THF and MeOH provided acceptable
reaction times they brought with them processing complica-
tions. Ethanol avoided the formation of mixed esters and
allowed for easy isolation by distillation of the solvent.
Treatment of the product rich aqueous layer with HCl
precipitated the desired acid 10 from solution. Thus, after
three chemical transformations and recrystallization, (10) was
isolated in 85% overall yield starting from (7).
Special care to wash 10 with excess water was required to
purge any residual HCl. Recrystallization of acid 10 from
toluene in the presence of HCl leads to the formation of 21,
presumably via activation of the dimethylamide followed by
intramolecular cyclization (Scheme 6).
lactam 17 with paraformaldehyde generated racemic 18 in 77%
isolated yield. Attempts were made to develop a classical
resolution with promising initial results, however due to time
constraints that process was not further optimized. Instead
lactam (18) was resolved via simulated moving bed (SMB)
chiral chromatography with recycling of the undesired
enantiomer (19). This process allowed for an overall 56%
conversion after one recycling protocol. With all components
now readily available, the task of preparing carboxylic acid 10
was initiated (Scheme 5).
As was previously mentioned, multiple solvents were utilized
within the original processing. Final processing was to be
carried out exclusively in 2-MeTHF; unfortunately, upon
Scheme 6. Hydrolysis and lactonization of 10
Scheme 5. Formation of core 10
All that remained was coupling of acid 10 with lactam 11.
Esterification was previously conducted utilizing EDCI as the
free base. A variety of alternatives were investigated (CDMT,
EDCI, T3P, mixed anhydride, and acid chloride) including
EDCI−HCl (Scheme 7).
While most coupling conditions provided the desired
product, ultimately EDCI·HCl was selected. While stressing
the reaction conditions, it was noted that a minor impurity
started to develop. This impurity was isolated and characterized
as the EDCI adduct (22). Formation of the impurity was
readily managed by dose-controlled addition of EDCI·HCl to a
mixture of both acid (10) and primary alcohol (11) minimizing
significant changes in reaction temperatures. Following workup,
B
dx.doi.org/10.1021/op5003165 | Org. Process Res. Dev. XXXX, XXX, XXX−XXX

Organic Process Research & Development
Article
Scheme 7. Esterification of 10 to generate 1
the crude materials were isolated in 98% purity and yield with
no detectable EDCI adducts present. Unfortunately, the crude
materials required purification via silica gel as a solid form
isolation was unknown at the time. To further complicate
isolation, the product (1) had exceptional solubility in all
common solvents aside from heptanes and water. Thus, in
order to isolate the API, the product-rich solutions were
concentrated to a low volume and charged to an excess of
water. The solids were ultimately isolated as an amorphous
powder.
Figure 2. IR spectra changes as a function of reaction progression
(time). 3-D surface plot of the spectra as a function of time and
wavelength.
the product 1 (Figure 3). The ability of ReactIR to
simultaneously track these reactants and products in real time
Reaction Monitoring. Online reaction monitoring tools
such as mid-infrared (MIR), near-infrared (NIR), Raman, and
NMR have found wider and wider use in API process
development and other pharmaceutical development·4−14 As
several processing steps required the use of hazardous reagents
(oxalyl chloride) or elevated temperatures (decarboxylation),
ReactIR monitoring was extensively utilized to minimize
worker exposure and reduce cycle time during the development
and scale-up. In the lab-scale experiments, a REACT IR iC10
by Mettler Toledo AutoChem with a 6.5 mm AgX DiComp
Fiber Conduit probe was used in reaction monitoring. Samples
were also collected for off line UPLC end-point determination
and for comparison to the ReactIR results. The ReactIR
monitoring data were collected for major steps described in an
early process development scheme (Scheme 1).
The reactions of formation of acid chloride (converting 7 to
8), the subsequent coupling reaction (8 and 13 to 20), and the
hydrolysis of 20 to 10 were all successfully monitored by
ReactIR (Scheme 5). Since there were distinct IR absorption
band(s) that can be assigned to either reactant or product in
these reaction steps, three separate univariate models by iC IR
software were established that can describe both consumption
of a reactant and buildup of the product in each reaction. The
ReactIR results correlated with off-line UPLC analysis results
well.
Furthermore, monitoring the transformation of 10 and 11 to
final product 1 highlights the power of ReactIR as a process
monitoring tool (Scheme 7). In this specific step, there are
multiple distinct carbonyls involved in the transformation,
extracting the reaction progression information from the
presence, formation, and or disappearance of these carbonyls
is quite daunting (Figure 2). Early LC methods were
complicated by overlapping peaks which relegated the team
to letting the reaction progress for 18 h to ensure completion.
The ReactIR monitoring data for this transformation were
processed by iC IR software (ConcIRT module) to successfully
build a multivariate model. This model simultaneously
monitors the decrease of the key reactant 10 and increase of
Figure 3. Overlay plot of the spectra at selected time points.
continuously allowed the team to determine that the reaction
was ca. 75% complete within the first hour and >98% complete
within 6 h (Figure 3), thus affording the team greater
confidence in scaling.
In the subsequent process optimization experiments, ReactIR
was continuously used to acquire online IR spectra along with a
few samples for offline UPLC analysis. For the optimized
reaction process (Scheme 5), we confirmed that reaction
monitoring by ReactIR is still feasible for the reactions of
formation of acid chloride (converting 7 to 8) and the
subsequent coupling reaction (8 and 13 to 20). Two univariate
models were established for the two reactions. However,
because of the changes in reagents and solvent that introduced
spectrum interference, reaction monitoring by ReactIR was no
longer possible for the conversion of 20 to 10.
Monitoring the transformation of 10 and 11 to product 1 in
the optimized process was still successful despite the change in
solvent for the reaction. A careful examination of the ReactIR
spectrum changes over time revealed that the subtle changes,
mostly in the range of 1660 cm−1 to 1800 cm−1 that are related
to band changes of the carbonyls, closely related to the reaction
progression (Figure 2, bottom plot). Therefore, the online IR
spectrum changes in this range were correlated to correspond-
ing offline UPLC analysis results to build a quantitative
multivariate model for accurately monitoring the reaction
progression (Figure 4). The model was built in iCQuant
module of the iC IR software. A multivariate mathematical
techniquepartial least squares (PLS)15was used to relate
the online IR measurements (e.g., spectra after applying second
C
dx.doi.org/10.1021/op5003165 | Org. Process Res. Dev. XXXX, XXX, XXX−XXX

Organic Process Research & Development
Article
Experimental Section. All reactions were run in standard
air-dried glassware with magnetic stirring under a static
atmosphere of nitrogen unless otherwise noted. Mass spectral
data were obtained on a Micromass ZMD mass spectrometer
with flow injection analysis and atmospheric pressure chemical
ionization (APCI). Reactions were monitored by Bruker 400
MHz 1HNMR, Agilent 1290 UPLC, and REACT IR iC10 with
6.5 mm AgX DiComp fiber conduit probe by Mettler Toledo
AutoChem. The REACT IR data were processed by iC IR
version 4.0 by Mettler Toledo AutoChem. Commodity
reagents were purchased from reputable vendors and used as
received.
2-(3-(Dimethylcarbamoyl)-4-(6-methyl-4′-(trifluorometh-
yl)-[1,1′-biphenyl]-2-carboxamido)phenyl)acetic Acid (10). A
200 L glass lined tank equipped with ReactIR Probe (Mettler-
Toledo Dicomp AgX probe (9.5 mm O.D. × 29 in. long, 2 m
AgX fiber)) and scrubber was purged with nitrogen and
charged with 2-methyltetrahydrofuran (80.0 L, 10 L/kg) and 6-
methyl-4′-(trifluoromethyl)-[1,1′-biphenyl]-2-carboxylic acid
(7) (8.0 kg, 28.6 mol, 1.0 equiv) followed by initiating stirring.
After 20 min of stirring at 20 5 °C, DMF (0.02 L, 0.29 mol,
0.02 equiv) was charged followed by addition of oxalyl chloride
(3.99 kg, 31.4 mol, 1.10 equiv) while maintaining a temperature
Figure 4. Reaction progression trends for the reactant and the product
(1) in Scheme 5. The trends were obtained from ConcIRT
multivariate analysis in iC IR software using a spectrum range of
900−1900 cm−1.5,6
derivative) from a set of spectra over time in a reaction to the
property value of interest − % conversion (reactant or product)
obtained for the same reaction from offline LC testing. This set
of sample was called the training set, and the resulting PLS
model is described in Figure 5 in blue for the PLS model-
of 20
5 °C. After 2 h the trending plot of the ReactIR
spectrum changes over time (univariate model) indicated that
the reaction is essentially complete with an IPC confirming
<2% residual 7 present. Excess oxalyl chloride was purged by
distillation/replacement of 2-MeTHF (12.0 L total). The tank
was cooled to 0 °C followed by the addition of diethyl 2-(4-
amino-3-(dimethylcarbamoyl)phenyl)malonate (13) (9.29 kg,
28.8 mol, 1.01 equiv) over 15 min while maintaining a
temperature of 5 5 °C. Diisopropylethylamine (7.42 L, 42.5
mol, 1.49 equiv) was charged such that the internal temperature
remains at 10 15 °C. Upon complete addition, the reaction
mixture was warmed to 20 °C. After 1 h the trending plot of the
ReactIR spectrum changes over time (univariate model),
indicating that the reaction is essentially complete with an
IPC confirming <2% residual 6-methyl-4′-(trifluoromethyl)-
[1,1′-biphenyl]-2-carbonyl chloride (8) present. 1 N Hydro-
chloric acid (60.0 L) was charged to the slurry followed by 30
min of agitation. Stirring was stopped where upon the layers
separated. The heavy aqueous layer was disposed of followed by
washing the organic layer with water (40.0 L) and an additional
30 min of agitation. The scrubber was removed from the
reaction train followed by concentration of the organic layers
containing diethyl 2-(3-(dimethylcarbamoyl)-4-(6-methyl-4′-
(trifluoromethyl)-[1,1′-biphenyl]-2-carboxamido)phenyl)-
malonate (20) to ca. 50.0 L under vacuum while maintaining a
Figure 5. Quantitative multivariate model for accurately monitoring
the reaction progression (product 1 formation) using the spectrum
data in range of 1660 cm−1 to 1800 cm−1. Blue data points were used
to build the model from one set of online IR and corresponding offline
UPLC data; the green data points were used to verify the validity of
the model from another independent set of experiment.
predicted % conversion (predicted) vs the LC measured %
conversion (actual). The blue points were the experimental
points, and the blue line is the model-predicted linear
correlation. Then, another set of data from reaction monitoring
from another independent experiment was used to check the
validity of the model. This set of data was described in the same
plot in green for the PLS model predicted % conversion
(predicted) vs the LC measured % conversion (actual). The
agreement of the two sets of data is very good.
temp of 25
10 °C. Once distillation was complete, the
temperature was set to 20 5 °C followed by addition of 1 N
potassium carbonate (80.0 kg) and ethanol (40.0 L). The entire
mixture was heated to reflux (75 10 °C) over 2 h to avoid
any potential excessive off-gassing. The mixture was held for 15
h with the IPC confirming <2% residual 20 present. The
mixture was cooled to 20 °C followed by removal of the heavy
aqueous phase. The product rich organic layer was concen-
trated to ca. half the initial volume (50.0 L) under vacuum
The model was successfully used to guide the process scale-
up from lab scale all the way to a >10 kg scale in a pilot plant.
Finally, the transformation of 10 and 11 to final product 1 in
the pilot plant was monitored using a special online IR
instrument: MonARC with an extended length IR probe from
Mettler Toledo AutoChem. MonARC is designed for mid-
infrared (FTIR) based process monitoring in classified area
environments.
while maintaining a 35
10 °C. The displaced solvent was
In conclusion, we have developed a six-step synthesis in 72%
overall yield of (1) from three key components. Key
developments include (i) simplified solvent scheme, (ii)
improved processing and yields, (iii) elimination of multiple
catalyst loadings, and (iv) ReactIR monitoring minimizing
worker exposure and side products.
then replaced with additional 2-MeTHF (65 L) via constant
volume displacement under vacuum while maintaining a 35
10 °C. Once the ethanol levels were acceptable (<5%), the
temperature was adjusted to 20 °C. To the cooled organic
solution was charged 80.0 L of 1 N NaOH followed by 5 min of
D
dx.doi.org/10.1021/op5003165 | Org. Process Res. Dev. XXXX, XXX, XXX−XXX

Organic Process Research & Development
Article
agitation and settling. The product-rich aqueous layer was
collected followed by disposal of the top organic layer. To the
product rich aqueous layer was added 2 N HCl until the pH
was 1−2. The product precipitated from solution when the pH
reached ∼4; however, additional HCl was charged to increase
product recovery. The solids were isolated via filtration
followed by rinsing with water (160.0 L). After 24 h of drying
over forced air, crude 10 (13.0 kg) was isolated. The crude
materials were subsequently recrystallized from toluene (15.0
L/kg), affording 11.8 kg of 10 in 85% yield over three steps.
Ethyl-(R)-1-((2-(3-(dimethylcarbamoyl)-4-(6-methyl-4′-(tri-
fluoromethyl)-[1,1′-biphenyl]-2-carboxamido)phenyl)-
acetoxy)methyl)-2-methylisoindoline-1-carboxylate (1). A
200 L glass lined tank equipped with ReactIR probe was
purged with nitrogen and charged with 2-methyltetrahydrofur-
an (65.0 L, 15 L/kg), ethyl (R)-1-(hydroxymethyl)-2-methyl-3-
oxoisoindoline-1-carboxylate (11) (4.3 kg, 17.3 mol, 1.0 equiv),
carboxylic acid 10 (9.2 kg, 19.0 mol, 1.1 equiv), and DMAP
(0.4 kg, 3.45 mol, 0.2 equiv). The initial slurry was held at 20
5 °C for 30 min or until the solids had completely dissolved. To
the solution was charged in 5 portions EDCI·HCl (4.1 kg, 21.6
mol, 1.25 equiv) while maintaining a batch temperature of 20
5 °C. After 7 h the trending plot of the ReactIR spectrum
changes over time (multivariate model, Figure 2) indicated the
reaction was complete. To the vessel was charged 1 N HCl
(70.5 L) followed by 30 min of agitation. The heavy aqueous
layer was removed followed by charging 70.5 L of sat. NaHCO3
(caution should be used to avoid any excessive off-gassing).
The heavy aqueous layer was removed followed by a second
wash of NaHCO3 (75.0 L). The biphasic mixture was agitated
for 30 min followed by removal of the heavy aqueous layer. The
remaining product-rich organic layer was concentrated to a
lowest stirrable volume followed by dilution with toluene (10
L/kg).
ACKNOWLEDGMENTS
■
The authors gratefully acknowledge Jeff Sperry, Roger Ruggeri,
and Edward Conn for helpful discussions, as well as Barb Sitter
for assistance with DoE studies in support of the conversion of
10 to 1 and Ling Zhang for data analysis by PLS modeling.
REFERENCES
■
(1) Handbook of Green Chemistry, Vol. 2 Green Catalyst; Anastas, P.
T., Ed.; John Wiley and Sons: New York, 2012.
(2) Suzuki, A.; Miyaura, N. Chem. Rev. 1995, 95, 2457−2483.
(3) Othman, M.; Decroix, B. Syn. Comm. 1996, 26 (12), 2803.
Othman, M.; Decroix, B.; Pigeon, P. Tetrahedron 1998, 54 (30), 8737.
Roche, B.; Conn, E.; Eisenbeis, S.; Ruggeri, R. Tetrahedron Lett. 2012,
53 (41), 5467−5470.
(4) Chen, R.; Bowles, D.; Antosz, F.; Xiang, Y.; Li, S.; Barrila, M.;
Coutant, M. Practical Approaches in Applying Process Analytical
Technology (PAT) Tools for Early API Development. Pharmaceutical
Outsourcing, August/September 2011, 28−33.
(5) Zhou, G.; Guenard, R.; Ge, Z. Infrared and Raman spectroscopy
for process development. In Applications of Vibrational Spectroscopy in
Pharmaceutical Research and Development; Pivonka, D. E., Chalmers, J.
M., Griffiths, P. R., Eds.; Wiley: New York, 2007; pp 185−211.
(6) Chanda, A.; Daly, A. M.; Foley, D. A.; Lapack, M. A.; Mukherjee,
S.; Orr, J. D.; Reid, G. L.; Thompson, D.; Howard, W. Industry
Perspectives on Process Analytical Technology: Tools and Applica-
tions in API Development. Org. Process Res. Dev., 10.1021/op400358b.
(7) Sistare, F.; Laurie, P. B., St.; Mojica, C. A. Process Analytical
Technology: An Investment in Process Knowledge. Org. Process Res.
Dev. 2005, 9 (3), 332−336.
(8) Lin, Z.; Zhou, L.; Mahajan, A.; Song, S.; Wang, T.; Ge, Z.; Ellison,
D. Real-time endpoint monitoring and determination for a
pharmaceutical salt formation process with in-line FT-IR spectroscopy.
J. Pharm. Biomed. Anal. 2006, 41 (1), 99−104.
(9) Conlon, D. A.; Izzo, B.; Collins, P. Mid-infrared monitoring
applications during development of the vinyl ether formation step in
the preparation of aprepitant. Process Chemistry in the Pharmaceutical
Industry; Gadamasetti, K., Braish, T., Eds.; CRC Press: Boca Raton,
FL, 2008; pp 349−360.
(10) Smith-Goettler, B.; Bakeev, K. A. On-line PAT applications of
spectroscopy in the pharmaceutical industry. In Process Analytical
Technology, 2nd ed.; Wiley: New York, 2010; pp 439−461.
(11) Carter, C. F.; Lange, H.; Ley, S. V.; Baxendale, I. R.; Wittkamp,
B.; Goode, J. G.; Gaunt, N. L. ReactIR Flow Cell: A new analytical tool
for continuous flow chemical processing. Org. Process Res. Dev. 2010,
14 (2), 393−404.
(12) Csontos, I.; Pataki, H.; Farkas, A.; Bata, H.; Vajna, B.; Nagy, Z.
K.; Keglevich, G.; Marosi, G. J. Feedback Control of Oximation
Reaction by Inline Raman Spectroscopy. Org. Process Res. Dev. 2014,
10.1021/op500015d.
The toluene mixture was submitted to large-scale silica gel
purification where the desired materials were isolated from
acetone/toluene. The product rich material was concentrated
to lowest stirrable volume followed by dilution in EtOAc
(azeatrope acetone) followed by EtOH (azeatrope EtOAc/
toluene) To a 200 L glass lined reactor charged with 151 L of
water (2 2 °C) was added the product-rich EtOH solution
(∼15 L) through a 5 μ in-line filter over an hour. After an hour
of granulation, 1 (10.8 kg, 15.1 mol, 88%) was isolated by
filtration.
Data: 1H NMR (700 MHz, MeOD d4): 7.74 (d, 2H, 7.5 Hz),
7.68 (d, 1H, 7.5 Hz), 7.55 (m, 4H), 7.47 (m, 4H), 7.10 (d, 1H,
8.0 Hz), 6.97 (s, 1H), 6.93 (d, 1H, 8.0 Hz), 4.91 (d, 1H, 12
Hz), 4.78 (d, 1H, 12 Hz), 4.20 (m, 1H) 4.12 (m, 1H), 3.44 (s,
2H), 3.04 (s, 3H), 3.02 (s, 3H), 2.84 (s, 3H), 2.15 (s, 3H), 1.17
(t, 3H, 7.3 Hz); 13C NMR (700 MHz, MeOD d4): 171.45,
171.41, 170.76, 170.74, 168.77, 144.65, 142.20, 139.23, 138.45,
137.97, 134.84, 133.60, 133.07, 132.64, 132.32, 131.85, 131.45,
131.21, 130.95, 130.45, 129.59, 129.19, 126.18, 126.00, 125.94,
125.79, 124.56, 123.43, 72.72, 64.22, 63.97, 40.73, 40.10, 35.51,
27.18, 20.64, 14.30; HRMS (ESI C39H37F3N3O7) calc 716.2478
u, found 716.2582 u.
(13) Foley, D. A.; Wang, J.; Maranzano, B.; Zell, M. T.; Marquez, B.
L.; Xiang, Y.; Reid, G. L. Online NMR and HPLC as a Reaction
Monitoring Platform for Pharmaceutical Process Development. Anal.
Chem. 2013, 85 (19), 8928−8932.
(14) Calow, A. D. J.; Carbo, J. J.; Cid, J.; Fernandez, E.; Whiting, A.
Understanding α,β-Unsaturated Imine Formation from Amine
Additions to α,β-Unsaturated Aldehydes and Ketones: An Analytical
and Theoretical Investigation. J. Org. Chem. 2014, 79 (11), 5163−
5172.
(15) Esbensen, K. H. Multivariate Data Analysis - In Practice An
Introduction to Multivariate Data Analysis and Experimental Design, 5th
ed.; CAMO Software: Woodbridge, NJ, 2010.
AUTHOR INFORMATION
■
Corresponding Author
*E-mail: Shane.a.Eisenbeis@pfizer.com.
Notes
The authors declare no competing financial interest.
E
dx.doi.org/10.1021/op5003165 | Org. Process Res. Dev. XXXX, XXX, XXX−XXX