Nicholas A Weires1, Daniel D Caspi2, Neil K Garg1. 1. Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, United States. 2. Research & Development, Center for Reaction Engineering, AbbVie, Inc., 1 N. Waukegan Rd., North Chicago, Illinois 60064, United States.
Abstract
Nickel-catalyzed coupling reactions provide exciting tools in chemical synthesis. However, most methodologies in this area require high catalyst loadings, which commonly range from 10-20 mol % nickel. Through an academic-industrial collaboration, we demonstrate that kinetic modeling can be used strategically to overcome this problem, specifically within the context of the Ni-catalyzed conversion of amides to esters. The successful application of this methodology to a multigram-scale coupling, using only 0.4 mol % Ni, highlights the impact of this endeavor.
Nickel-catalyzed coupling reactions provide exciting tools in chemical synthesis. However, most methodologies in this area require high catalyst loadings, which commonly range from 10-20 mol % nickel. Through an academic-industrial collaboration, we demonstrate that kinetic modeling can be used strategically to overcome this problem, specifically within the context of the Ni-catalyzed conversion of amides to esters. The successful application of this methodology to a multigram-scale coupling, using only 0.4 mol % Ni, highlights the impact of this endeavor.
New synthetic methodologies
have the potential to greatly impact pharmaceutical manufacturing,
which, in turn, can have a positive effect on human health. Although
there is no shortage of new chemical transformations being reported
each year, the likelihood of any of these being adopted in a pharmaceutical
manufacturing process remains low. Indeed, process chemists often
rely on a handful of common transformations that proceed reliably
and efficiently, and, as such, the barrier for adopting a new methodology
in a large-scale pharmaceutical manufacturing process can be substantial.[1] A key hurdle lies in practical gaps between the
typical academic methodology and an economical manufacturing process.
For instance, the pressures of manufacturing deadlines may prohibit
industrial optimization of published academic methodologies. As such,
the earlier a methodology can be rendered scalable and efficient,
the more likely it is to be implemented in drug synthesis.One
burgeoning area of academic research that is, in principle,
well-suited for large-scale manufacturing is the field of nickel-catalyzed
cross-couplings. This is not only because of the high natural abundance,
low cost, and low CO2 footprint of nickel, but also because
of its unique ability to effect novel or challenging transformations
(Figure ).[2] However, nickel-catalyzed cross-couplings reported
by academic laboratories often employ high catalyst loadings. For
example, as shown in Figure , upon surveying >80 manuscripts published in selected
top
journals since 2015 involving nickel-catalyzed cross-couplings, we
found that the vast majority of methodologies use ≥5 mol %
nickel, with greater than half of those methodologies employing 10–20
mol % nickel.[3] Indeed, examples
that require <5 mol % nickel are uncommon. In our own experience,
the high catalyst loadings in part stem from the desire to identify
broadly applicable reaction conditions and pressures to publish before
potential competitors. Although these burdens are not likely to subside,
the greater attention to developing process-friendly variants of nickel-catalyzed
couplings by academic laboratories could only lead to better chances
of such methodologies being adopted industrially.
Figure 1
Features of nickel catalysis
and the most frequently employed catalyst
loadings in nickel-catalyzed cross-coupling reactions published January
2015–April 2017.
Features of nickel catalysis
and the most frequently employed catalyst
loadings in nickel-catalyzed cross-coupling reactions published January
2015–April 2017.Prompted by discussions with industrial colleagues, we established
a collaboration targeted at rendering a recently developed nickel-mediated
coupling more catalytically efficient. The reaction that we chose
to pursue is the nickel-catalyzed conversion of amides to esters,
which represents a unique and challenging transformation.[4−9] An example of this reaction is depicted in Figure , wherein benzamide 1 is coupled
with (−)-menthol (2) to furnish ester 3 in 88% yield. Notably, this reaction proceeds at 80 °C using
both 10 mol % Ni(cod)2 and 10 mol % SIPr
in toluene (0.66 M).[4,10] At the time this reaction was
developed, initial reaction optimization efforts to lower the catalyst
loading were unsuccessful. We sought to revisit this challenge through
an academic/industrial collaboration that relied on a combination
of experiments and kinetic modeling, the latter of which is a tool
commonly employed industrially, but less often in academic pursuits.[11−13] In this manuscript, we describe the success of these efforts, which
allow for amide esterification to occur using catalyst loadings as
low as 0.4 mol % Ni.
Figure 2
Previously reported nickel-catalyzed coupling
of benzamide 1 with (−)-menthol (2) to furnish ester 3 using 10 mol % Ni.
Previously reported nickel-catalyzed coupling
of benzamide 1 with (−)-menthol (2) to furnish ester 3 using 10 mol % Ni.To initiate our studies, we identified
the coupling of benzamide 1 with (−)-menthol (2) as a practical
reaction choice for several reasons, including (a) the high purity
to which (−)-menthol (2) can be obtained by recrystallization,
(b) the robustness of the reaction, and (c) the low volatility of
all reagents under the reaction conditions. Initial attempts to reduce
the reaction temperature from the reported 80 °C revealed that
the coupling had reached >90% conversion after ∼8 h at 40
°C
(Table , entry 1). DynoChem software[14] was used
to derive rate information from this coupling, and roughly one dozen
further exploratory experiments were then designed to probe the sensitivity
of the observed reaction rate to changes in several reaction variables.
Parameters that were examined included (a) the ligand-to-metal ratio,
(b) equivalents of (−)-menthol (2), (c) presence
of product/byproduct spikes, (d) length of time holding the catalyst
at a given temperature prior to substrate addition, (e) catalyst loading,
and (f) reaction concentration.[15] With
the guidance of the software used, it was determined that only a small
number of these experiments involved changes to kinetically relevant
reaction variables (Table ). It was demonstrated that changes in temperature, concentration,
and catalyst loading had a marked impact on the reaction rate (entries
2–5 in Table ).[16] However, the stoichiometry of the
alcohol, in addition to numerous other variables, did not influence
the reaction rate.
Table 1
Experiments Used To Train the Kinetic
Modela
entry
Ni(cod)2 content (mol %)
temperature
(°C)
concentration
(M)
maximum conversionb (%)
time (h)
1
10.0
40
0.66
92
8
2
10.0
33
0.66
70
6
3
10.0
50
0.66
91
4
4
0.5
65
1.16
77
8
5
0.1
80
1.16
13
1
All reactions were
performed on
a 0.50–1.00 mmol scale, with respect to amide 1, using 1.2 equiv (−)-menthol (2) and a 1:1 ratio
of Ni(cod)2:SIPr in toluene.[10]
Conversion was determined
by SFC
analysis, using biphenyl as an internal standard.
All reactions were
performed on
a 0.50–1.00 mmol scale, with respect to amide 1, using 1.2 equiv (−)-menthol (2) and a 1:1 ratio
of Ni(cod)2:SIPr in toluene.[10]Conversion was determined
by SFC
analysis, using biphenyl as an internal standard.The data in Table were utilized to build a kinetic model,
and a simplified reaction
pathway was constructed based on prior computational studies from
the Houk laboratory, as well as extensive literature precedent (Figure ).[4,17] The
fitted model supports three fundamental steps, which are in agreement
with the literature:[4] oxidative addition
(k1), ligand exchange (k2), and reductive elimination (k3). The model fitting implicates oxidative addition as the
rate-determining step (k1), which is consistent
with previously reported computational predictions (23.0 kcal/mol DynoChem vs 26.0 kcal/mol DFT calculations).[4] In addition, the presence of a catalyst degradation pathway
(k4) was also found. These degradation
kinetics (k4) were represented by a simplified
first-order pathway from the catalyst resting state (NiL). Although
details of the catalyst degradation pathway are unknown, NiL was selected
as the most abundant catalyst species in the reaction, as oxidative
addition is rate-limiting. The regressed rate constants and associated
activation energies are depicted in Figure . Since the rate of ligand exchange (k2) and reductive elimination (k3) were not found to be rate-limiting, an arbitrary fast
rate was used for fitting. Further independent experiments were then
conducted under atypical reaction conditions in order to verify the
model prediction capabilities, and such experiments were found to
be successful in validating the model.[18]
Figure 3
Simplistic
reaction pathway, calculated rate constants, and energies
of activation for the esterification reaction. [Footnotes in figure: Rate constants are reported at 40 °C;
the ± values represent the 95% confidence interval obtained from
the DynoChem fitting of the data to the kinetic model. For comparison, the corresponding values in
kcal/mol are as follows: Ea1 = 23.0 ±
0.5 kcal/mol, Ea4 = 36.1 ± 1.0 kcal/mol. This reaction is fast and not rate-limiting;
therefore, an arbitrary fast rate of 10 was selected for subsequent
fitting. Reaction rate was a weak function
of temperature within the explored temperature range.]
Simplistic
reaction pathway, calculated rate constants, and energies
of activation for the esterification reaction. [Footnotes in figure: Rate constants are reported at 40 °C;
the ± values represent the 95% confidence interval obtained from
the DynoChem fitting of the data to the kinetic model. For comparison, the corresponding values in
kcal/mol are as follows: Ea1 = 23.0 ±
0.5 kcal/mol, Ea4 = 36.1 ± 1.0 kcal/mol. This reaction is fast and not rate-limiting;
therefore, an arbitrary fast rate of 10 was selected for subsequent
fitting. Reaction rate was a weak function
of temperature within the explored temperature range.]With a working kinetic model in hand, thousands
of in silico simulations were performed in a matter
of minutes in order to visualize
the multidimensional relationships between concentration, temperature,
and catalyst loading (Figure ). Based on these calculations, 2.0 mol % Ni catalyst
at 60 °C in toluene (∼1.04 M)[10] was chosen as an optimal set of conditions that would provide a
balance between reaction conversion and catalyst degradation. These
conditions were then used to further probe the generality of the coupling.[19]
Figure 4
In silico simulations of reaction pass
time (95%
conversion) as a function of Ni catalyst (mol %) and temperature
(°C) for overall reaction concentrations of 1.00–1.30
M.[10] Contour plot depicts the result of
several thousand simulations.
In silico simulations of reaction pass
time (95%
conversion) as a function of Ni catalyst (mol %) and temperature
(°C) for overall reaction concentrations of 1.00–1.30
M.[10] Contour plot depicts the result of
several thousand simulations.Having projected suitable conditions that would require only
2.0
mol % Ni, efforts turned to verifying this prediction (Figure ). These conditions
were found to be broadly applicable to several amide substrates 4 and alcohol coupling partners 5 to furnish
ester products 6 with high efficiencies. For example,
methyl benzoate (7) could be obtained in good yields
from benzamide derivatives possessing either N-Me,Ph
or N-Bn,Boc nitrogen substitutions. In addition,
extended aromatic systems were tolerated, as demonstrated by the formation
of 8 in 92% yield. Notably, the conditions were found
to be tolerant of heterocycles, as suggested by the preparation of
isoquinoline derivative 9 in 66% yield. The alcohol coupling
partner was also varied, permitting the generation of interesting
ester products such as cyclopropane 10 in 75% yield.
Moreover, secondary alcohol nucleophiles were found to be competent
in the coupling, allowing for the formation of 11 and 3 in quantitative yields. Finally, an ester derived from a
tertiary alcohol could also be accessed, as demonstrated by the production
of adamantyl ester 12. As shown, yields were generally
comparable to those reported in the literature using 10 mol %
Ni.[4]
Figure 5
Exploration of scope in the esterification.
[Footnote in figure: All reactions were
performed on 0.50 mmol scale
using 1.2 equiv alcohol, 2.0 mol % Ni(cod)2, and
2.0 mol % SIPr in toluene (1.04 M) at 60 °C for 16 h.
Yields determined by 1H NMR analysis using hexamethylbenzene
as an external standard. Coupling performed
with the corresponding N-Bn,Boc benzamide. 97% isolated yield obtained after silica gel chromatography.]
Exploration of scope in the esterification.
[Footnote in figure: All reactions were
performed on 0.50 mmol scale
using 1.2 equiv alcohol, 2.0 mol % Ni(cod)2, and
2.0 mol % SIPr in toluene (1.04 M) at 60 °C for 16 h.
Yields determined by 1H NMR analysis using hexamethylbenzene
as an external standard. Coupling performed
with the corresponding N-Bn,Boc benzamide. 97% isolated yield obtained after silica gel chromatography.]With the aim of minimizing the
catalyst loading further, additional
simulations were performed using <1.0 mol % Ni.[18] The simulation results predicted that the esterification
of benzamide 1 with (−)-menthol (2) could reach nearly full conversion within <56 h if performed
at 45 °C with 0.4 mol % Ni in toluene at high concentrations
(1.52 M)[10] (see Figure ).[20] These predicted
reaction conditions using only 0.4 mol % Ni were thus attempted
on a 5 g scale to test the scalability of the coupling. To our delight,
this effort afforded ester 3 in almost-quantitative yield.[21] Compared to our original disclosure, this reaction
uses 25-fold less Ni(cod)2 and >10-fold less of the
SIPr
ligand. If each reaction variable had been tested independently, this
result would have likely been discovered in a much less concise manner,
if at all. However, by employing a kinetic model, a catalyst degradation
pathway was identified that informed the careful tuning of the reaction
conditions, in turn permitting an efficient coupling to happen. This
example, which showcases the rare use of <0.5 mol % Ni in
a catalytic coupling, underscores the value of kinetic modeling and
bodes well for the increasingly widespread adoption of nickel catalysis
in industry.
Figure 6
In silico simulations of reaction pass
time (95%
conversion), as a function of Ni catalyst (mol %) and temperature
(°C) for overall reaction concentrations of 1.44–1.74
M[10] and 5 g scale coupling of benzamide 1 with (−)-menthol (2) using 0.4 mol %
Ni. [Footnote in figure: Contour plot
depicts the result of several thousand simulations. Conditions: 5.00
g amide 1, 1.2 equiv (−)-menthol (2), 0.4 mol % Ni(cod)2, and 0.8 mol % SIPr
in toluene (1.52 M) at 45 °C for 51 h. Yield refers to isolated
yield after column chromatography.]
In silico simulations of reaction pass
time (95%
conversion), as a function of Ni catalyst (mol %) and temperature
(°C) for overall reaction concentrations of 1.44–1.74
M[10] and 5 g scale coupling of benzamide 1 with (−)-menthol (2) using 0.4 mol %
Ni. [Footnote in figure: Contour plot
depicts the result of several thousand simulations. Conditions: 5.00
g amide 1, 1.2 equiv (−)-menthol (2), 0.4 mol % Ni(cod)2, and 0.8 mol % SIPr
in toluene (1.52 M) at 45 °C for 51 h. Yield refers to isolated
yield after column chromatography.]In summary, we have developed a kinetic model that allowed
for
the optimization of the nickel-catalyzed esterification of amides.
The model-predicted reaction conditions, involving a 5-fold reduction
in catalyst loading to 2.0 mol % Ni, were tested and deemed
suitable for a variety of coupling partners. Further simulations using
the kinetic model predicted the coupling of benzamide 1 and (−)-menthol (2) could then occur using as
little as 0.4 mol % Ni. This forecast was validated, as demonstrated
by a multigram scale coupling that proceeded in an almost-quantitative
yield. Thus, guided by reaction kinetics, the esterification of amides
was optimized in a concise manner and was rendered substantially more
efficient. These studies are expected to facilitate the adoption of
kinetic modeling as a powerful tool in academic methodology design
for the expedited translation of those methodologies into industry.