Photoredox catalysis has emerged as a powerful and versatile platform for the synthesis of complex molecules. While photocatalysis is already broadly used in small-scale batch chemistry across the pharmaceutical sector, recent efforts have focused on performing these transformations in process chemistry due to the inherent challenges of batch photocatalysis on scale. However, translating optimized batch conditions to flow setups is challenging, and a general approach that is rapid, convenient, and inexpensive remains largely elusive. Herein, we report the development of a new approach that uses a microscale high-throughput experimentation (HTE) platform to identify optimal reaction conditions that can be directly translated to flow systems. A key design point is to simulate the flow-vessel pathway within a microscale reaction plate, which enables the rapid identification of optimal flow reaction conditions using only a small number of simultaneous experiments. This approach has been validated against a range of widely used photoredox reactions and, importantly, was found to translate accurately to several commercial flow reactors. We expect that the generality and operational efficiency of this new HTE approach to photocatalysis will allow rapid identification of numerous flow protocols for scale.
Photoredox catalysis has emerged as a powerful and versatile platform for the synthesis of complex molecules. While photocatalysis is already broadly used in small-scale batch chemistry across the pharmaceutical sector, recent efforts have focused on performing these transformations in process chemistry due to the inherent challenges of batch photocatalysis on scale. However, translating optimized batch conditions to flow setups is challenging, and a general approach that is rapid, convenient, and inexpensive remains largely elusive. Herein, we report the development of a new approach that uses a microscale high-throughput experimentation (HTE) platform to identify optimal reaction conditions that can be directly translated to flow systems. A key design point is to simulate the flow-vessel pathway within a microscale reaction plate, which enables the rapid identification of optimal flow reaction conditions using only a small number of simultaneous experiments. This approach has been validated against a range of widely used photoredox reactions and, importantly, was found to translate accurately to several commercial flow reactors. We expect that the generality and operational efficiency of this new HTE approach to photocatalysis will allow rapid identification of numerous flow protocols for scale.
The
past decade has witnessed exponential growth in the development
of photoredox catalytic methods for organic synthesis. Photocatalysis,
in which photon-harvesting molecules convert light energy to chemical
energy, offers many useful advantages. In addition to being ecofriendly
and sustainable,[1,2] photocatalytic methods are uniquely
capable of promoting challenging bond formations[3][4] and novel chemical transformations[5−7] due to their ability to access high-energy intermediates in a controlled
and selective manner. Photoredox catalysis is now used in the synthesis
of agrochemicals, fine chemical intermediates, active pharmaceutical
compounds (APIs), and finished dosage forms (FDFs).[8] While photocatalytic methods have found increasing industrial
application, one remaining hurdle to widespread adoption of this platform
is the inherent complexity in adapting photochemical reactions to
large-scale settings, such as those required for process chemistry.[9−13] A critical outcome of the Beer–Lambert Law, with respect
to the scale-up of photochemical transformations, is that photon-flux
penetration decreases exponentially with depth in a given reaction
medium, ultimately leading to attenuation in the transfer of photons.[14] Thus, visible-light-mediated reactions take
place only in the proximal area (within 2 mm) of the vessel wall.[15−17] As such, a decrease in the diameter of the reaction vessel should
lead to an increase in photon flux throughout the reaction medium
and improved reaction efficiency. This observation has inspired recent
efforts to develop (i) laser-based reaction platforms that employ
high-intensity photon sources, which in combination with continuous
stirred tank reactors (CSTRs) provide powerful improvements with respect
to photon penetration in a batch-flow setting, and (ii) continuous-flow
photoreactors, which naturally permit better light penetration due
to the narrow tubing diameter; such systems have been shown to permit
gram- and kilogram-scale transformations.[18,19] In general, flow reactor platforms offer many advantages over batch
chemistry[20−26] with respect to photon efficiency, reproducibility, scale-up, safety,
waste generation, and productivity regarding both yield and reaction
time (Figure a). Along
these lines, a number of research groups have adopted flow photochemistry
strategies for the synthesis of molecules of pharmaceutical interest
(Figure b).[27−29] Despite these advantages, the optimization of a flow chemistry process
typically can be an onerous task for several reasons: (i) it is traditionally
not possible to perform parallel optimization experiments in the context
of a flow system; (ii) the optimal reaction conditions are highly
dependent on the size of the individual reactor; and (iii) each flow
chemistry experiment requires significant amounts of material compared
to the analogous reaction conducted in batch.[30,31] A number of strategies have been pursued to streamline optimization
of flow-based photoredox methods, including reducing the reaction
vessel size,[32−37] leveraging mathematical equations[38] and
algorithms,[36,39,40] and adapting new technologies (segmented[41,42] or microflow[43−46] and industry 4.0[47]).
Figure 1
(a) Photoredox reactions
can take place in batch, which normally
requires a small scale, or in flow, for more efficient light penetration.
However, general optimization methods in flow systems remain elusive.
(b) Continuous-flow systems have been used for the synthesis of many
active pharmaceutical ingredients (ref (28)). (c) We disclose a general approach to the
optimization of any photoredox reaction from batch to flow using a
microscale parallel experimentation to simulate the flow conditions.
(a) Photoredox reactions
can take place in batch, which normally
requires a small scale, or in flow, for more efficient light penetration.
However, general optimization methods in flow systems remain elusive.
(b) Continuous-flow systems have been used for the synthesis of many
active pharmaceutical ingredients (ref (28)). (c) We disclose a general approach to the
optimization of any photoredox reaction from batch to flow using a
microscale parallel experimentation to simulate the flow conditions.Over the past decade, high-throughput experimentation
(HTE) methodologies
have been successfully employed in the optimization of numerous catalytic
transformations.[48−51] Such technology has been adopted within both academic and industrial
settings to allow the evaluation of reaction parameters while minimizing
economic and waste constraints. Recently, the optimization of photoredox
protocols has also been conducted using HTE technology.[34,35] Using such strategies, it has been possible to build foundational
results from which reaction optimization can be examined thereafter
in continuous-flow systems. However, a limitation of existing optimization
platforms is the difficulty in translating HTE outcomes to continuous-flow
platforms, a feature that often relates to the change in vessel, light
intensity, and light path-length considerations.[49,51−55] A complementary approach was beautifully described by the Stephenson
group[56] at the outset of the preparation
of this manuscript, demonstrating a flow-based HTE platform by developing
a droplet microfluidic system for the development of photochemical
reactions. This study is focused on the generation of compound libraries,
ultimately increasing the chemical space with great time and material
efficiency. Notwithstanding, to the best of our knowledge, a general
HTE strategy for the translation of optimized photoredox reactions
seamlessly to similar outcomes on a flow platform remains undeveloped
and would be of a great interest to both discovery programs and process
chemistry alike.With this in mind, we sought to design an HTE
platform that mimics
the conditions of a flow reactor.[48−55] A requisite goal would be that the optimization data collected via
this HTE platform should be directly transferrable to a flow system,
permitting the rapid translation of small-scale batch-vessel photoredox
reactions to large-scale flow systems. Thus, the HTE setup should
allow us to perform miniaturized reactions while simulating continuous
photonic flow chemistry protocols.A compelling benefit of such
a system is the ability to simultaneously
explore numerous reaction variables, including the catalyst, photon
intensity, base, solvent, and so on, in parallel while employing short
residence times. We describe herein the development of this HTE platform
and its validation in the context of four representative photoredox
transformations.
FLOSIM Platform Design
Design Plan of an HTE Platform
to Simulate Continuous-Flow Systems
Successfully modeling
photochemical flow reactions in a high-throughput
setting requires designing a system that adequately captures the distribution
of photonic energy present throughout the entire protocol employed
within the flow apparatus.[57,58]In a photoredox-catalyzed
transformation, wherein the approximations of the Beer–Lambert
law operate, the photon absorption is described as a function of the
incident radiation and the absorption coefficient.[59] Given the angular and spatial dependence of the spectral
specific intensity and the complex geometricconsiderations required
to accurately describe irradiation in flow, we recognized that determining
the specific spectral intensity to enable design of a corresponding
high-throughput setup would prove to be challenging at best. Importantly,
however, we recognized that the key components of spectral intensity
could be appropriately accounted for by selection of a light source
that results in the same radiant flux for both systems.[60] Furthermore, the incident radiation could now
be approximated by ensuring the same path length of irradiation under
both flow and high-throughput batch conditions. With this in mid,
we sought to accomplish a path-length matching feature by the operationally
simple step of varying the volume in a standard 96-well plate to generate
a solution height matching the internal diameter (ID) of the transparent
fluorinated ethylene propylene (FEP) tubing chosen of the flow system
(Figure a, see Supporting Information for details).
Figure 2
Simulation
process and sequential optimization method. (a) By using
the inner diameter of the reactor-coil tubing as the height on the
plate, we can calculate the required reaction volume. (b) To simulate
the flow reactor, a reflected FLOSIM device was built and validated
across various parameters, such as the position, lights, and cooling
system. The FLOSIM device was optimized to obtain both high reactivity
in conjunction with homogeneity across the plate. (c) Workflow: Selection
of the optimal wavelength for the reaction is followed by optimization
in the 96-well glass plate FLOSIM device. After the reaction, the
sample is diluted and analyzed by UPLC. The selected conditions are
then validated through transfer into the commercial flow system.
Simulation
process and sequential optimization method. (a) By using
the inner diameter of the reactor-coil tubing as the height on the
plate, we can calculate the required reaction volume. (b) To simulate
the flow reactor, a reflected FLOSIM device was built and validated
across various parameters, such as the position, lights, and cooling
system. The FLOSIM device was optimized to obtain both high reactivity
in conjunction with homogeneity across the plate. (c) Workflow: Selection
of the optimal wavelength for the reaction is followed by optimization
in the 96-well glass plate FLOSIM device. After the reaction, the
sample is diluted and analyzed by UPLC. The selected conditions are
then validated through transfer into the commercial flow system.Next, in order to simulate the flow-system environment
in the context
of a photochemical reaction, it would be crucial to recreate the reactor-coil
element. Accordingly, we assembled a multienvironment 96-well plate
glass device that enables a high level of light exposure (Figure b). This platform
was equipped with two Kessil LEDs (PR160) and two ThorLabs concave
lenses (see Supporting Information for
details), while temperature control was maintained through air convection
methods. The use of a glass 96-well plate allows complete penetration
and reflection of the light inside the device in all directions, and
the uniformity of photon dispersion is accomplished across the platform
using a ThorLabs concave lens and several high-density reflection
mirrors.In order to evaluate the system’s ability to
facilitate
photoredox reactions with satisfactory consistency within the plate,
we conducted a series of simple test reactions using different materials
at different positions along the plate (see Supporting Information).[61] In Figure c, we outline the general workflow
for the translation of a photoredox reaction from batch to flow using
a multiscreening platform. Route scouting to identify optimal reaction
conditions begins with validation of the reaction, in batch, across
different wavelengths. Next, reaction optimization is performed on
microscale using the flow simulation (FLOSIM) HTE setup. Briefly,
the 96-well glass plate is loaded inside a nitrogen-filled glovebox,
sealed with transparent film, and placed in the benchtop HTE device,
where it is exposed to light irradiation for a short period of time
equivalent to the desired residence time in the flow system. Following
completion of screening, the crude reaction mixtures are analyzed
by ultraperformance liquid chromatography (UPLC). This two-step process,
HTE screening of different conditions, and analysis of results via
UPLC, can be performed iteratively until the desired results are obtained.Last, the optimal conditions, as determined from the HTE microscale
platform, were directly reproduced in the commercial flow system using
the preferred wavelength, light intensity, substrate/reagent concentrations,
residence time, solvent, base, and so on. As described below, the
optimized conditions identified at the 60 μL scale in the glass
plate system were found to be directly transferrable to a UV-150 Vapourtec
E-Series system equipped with a 2 mL or 10 mL reactor coil. We have
demonstrated the utility and generality of this FLOSIMHTE optimization
protocol in the context of four representative photocatalytic reactions
widely employed in medicinal chemistry.
Results and Discussion
Optimization
of Decarboxylative Arylation for Flow
In 2014, we reported
a novel decarboxylative arylation,[62] wherein
amino acids are transformed into benzylic
amines under synergistic photoredox and nickelcatalysis (Figure a). In optimizing
this transformation for a flow system, we selected N-Boc-Proline (Boc-Pro-OH)
and 1-bromo-4-(trifluoromethyl)-benzene as model substrates. We first
validated the reaction using a bench setup: under published conditions
with a 26 W CFL light bulb and Cs2CO3 base,
the desired product was isolated in 88% yield after 36 h. We began
optimization studies by evaluating the efficiency of the decarboxylative
arylation across a variety of wavelengths (PR160 Kessil LEDs); these
investigations revealed 427 nm to be the optimal wavelength for the
transformation. An important consideration in developing flow reactions
is the need to avoid heterogeneous conditions,[63−65] which often
clog the tubular flow reactors. With this criterion in mind, we set
out to optimize the transformation using the HTEFLOSIM–UPLC
setup, with an eye toward identifying suitable organic bases and solvents
to ensure a homogeneous solution (see Supporting Information). Approximately 300 “flow-type” reaction
conditions were tested in short order to examine the effect of residence
time, solvent, concentration, organic base, photocatalyst, catalyst
loading, as well as the nature of the transition metalcomplex (see Supporting Information). As shown in Figure b, these studies
led to the identification of homogeneous conditions that afforded
the desired transformation in only 45 min with 79% yield. We next
sought to transfer these conditions to a flow platform: a UV-150 Vapourtec
E-Series system equipped with a 2 mL reactor coil and 420 nm LED.
We were pleased to find that the HTE-optimized reaction conditions
were directly translatable to the Vapourtec, delivering the desired
product with comparable levels of efficiency (74% yield) using the
same conditions including 45 min of residence time (Figure b). In order to be confident
that the HTE platform offers an accurate simulation of the Vapourtec
flow system, we sought to determine the consistency of data between
both systems using a variety of reaction conditions. As shown in Figure b, we selected two
sets of conditions that gave mediocre and poor results respectively
with the HTE setup (i.e., 50 and 7% yield). Indeed, when these suboptimal
conditions were transferred to the Vapourtec reactor, we again found
a remarkable level of consistency between the HTEFLOSIM batch reactors
and the flow efficiencies (56 and 6% yield, respectively). These results
suggest that the optimization data obtained in the context of the
HTE platform are, indeed, indicative of performance in flow. Moreover,
time studies conducted for both the HTE setup and the flow setup under
optimal conditions reveal a strong correlation between the two systems
with respect to conversion as a function of reaction time (see Supporting Information).
Figure 3
C–C and C–N
coupling via decarboxylative protocols.
(a) The reaction between N-Boc-proline with 1-bromo-4-(trifluoromethyl)-benzene
was evaluated with a variety of light sources using standard conditions;
superior results were obtained with the 427 nm LEDs (see Supporting Information). (b) A range of results
have been obtained for several conditions, with high, moderate, or
low yield being replicated between the FLOSIM device and the commercial
flow setup (see Supporting Information).
(c) The reaction was successfully scaled using a Vapourtec E-Series
with a 10 mL reactor coil (1.3 mm ID). (d) Reaction between activated
carboxylic acid iodonium salts and 3-chloro-indazole as the N-nucleophile
via dual-photoredox copper catalysis. Superior results were obtained
with a 390 nm Kessil LED light source. (e) A range of results have
been obtained for several conditions, with high, moderate, or low
yield being replicated between the FLOSIM device and the commercial
flow setup (see Supporting Information).
(f) The reaction was successfully scaled at a 40 mmol level affording
7.6 g of the desired product (69% yield) using a Vapourtec E-Series
with a 10 mL reactor coil (1.3 mm ID). PC corresponds to 4CzIPN.
C–C and C–Ncoupling via decarboxylative protocols.
(a) The reaction between N-Boc-proline with 1-bromo-4-(trifluoromethyl)-benzene
was evaluated with a variety of light sources using standard conditions;
superior results were obtained with the 427 nm LEDs (see Supporting Information). (b) A range of results
have been obtained for several conditions, with high, moderate, or
low yield being replicated between the FLOSIM device and the commercial
flow setup (see Supporting Information).
(c) The reaction was successfully scaled using a Vapourtec E-Series
with a 10 mL reactor coil (1.3 mm ID). (d) Reaction between activated
carboxylic acid iodoniumsalts and 3-chloro-indazole as the N-nucleophile
via dual-photoredox coppercatalysis. Superior results were obtained
with a 390 nm Kessil LED light source. (e) A range of results have
been obtained for several conditions, with high, moderate, or low
yield being replicated between the FLOSIM device and the commercial
flow setup (see Supporting Information).
(f) The reaction was successfully scaled at a 40 mmol level affording
7.6 g of the desired product (69% yield) using a Vapourtec E-Series
with a 10 mL reactor coil (1.3 mm ID). PCcorresponds to 4CzIPN.Next, we aimed to demonstrate the feasibility of
this flow-optimized
method in processes of different scale. As shown in Figure c, when the reaction was conducted
at the 60 mmol level using the optimized conditions with a larger
coil size reactor (10 mL), the desired product was isolated in 70%
yield. Moreover, 13.2 g of product was isolated after an 11.7 h total
flow reactor time using the Vapourtec system. In comparison to the
laboratory vial reactor procedure, which provides 111 mg of desired
product in 36 h, we were able to demonstrate a 366-fold increase in
efficiency by way of this rapid, flow optimization protocol.
Optimization
of C–N Arylation Coupling for Flow
In 2018, our group
reported a new transformation that allows the
decarboxylative alkylation of N-nucleophiles via the merger of photoredox
and coppercatalysis.[66] Among a large scope
of valuable alkylation substrates, there has been growing interest
in the incorporation of rigid bicyclic structures, such as [1.1.1]-propellane
(BCP) scaffolds, into medicinal compounds, owing to their capacity
to act as bioisosteres of alkynes or para-substituted benzene rings.
With this consideration in mind, we sought to optimize a flow method
for the rapid production of molecules containing the BCP scaffold
via our C–Ncoupling platform. We selected 3-(methoxycarbonyl)bicyclo[1.1.1]pentane-1-carboxylic
acid and 3-chloro-indazole as the model coupling partners. Using our
previously published conditions, the C–Ncoupling adduct was
obtained in a vial batch in 80% yield after 1 h. After a subsequent
survey of reaction efficiencies as a function of LED wavelength, it
became apparent that the coupling proceeds well across a variety of
light sources, and 390 nm was selected for further HTE studies (see Supporting Information). As shown in Figure e, following a short
HTEFLOSIM–UPLC optimization campaign that involved the assessment
of ∼300 reactions (evaluating different reaction times, solvents,
concentrations, catalysts and catalyst loadings, see Supporting Information), we identified optimal flow conditions
that provided comparable efficiency (89% yield) within only an 8 min
reaction time.These conditions were then directly transferred
to the continuous-flow system (Vapourtec E-Series, 2 mL reactor coil),
and a similar result was obtained (87% yield, 8 min residence time).
As shown in Figure e, a time study showed comparable levels of conversion between the
HTE and commercial flow setups for a variety of conditions that were
examined, lending further support to the predictive power of the HTE
setup (Figure e).Finally, the decarboxylative alkylation was performed on a 40 mmol
scale using our optimized FLOSIMconditions on a Vapourtec reactor
(385 nm LEDs, 10 mL reactor coil). The reaction was conducted in the
heated mode at 35 °C to prevent solvent freezing. Under the conditions
shown in Figure f,
7.6 g of the desired product was isolated in good yield (69%) after
only 10 h, representing a 6.5-fold increase in reaction efficiency
over the vial batch setup.
Optimization of Cross-Electrophile Coupling
for Flow
In 2016, we developed a cross-electrophile coupling
that has found
broad application across a variety of medicinal chemistry campaigns.[67] As such, the development of a simple protocol
by which to translate small-scale cross-electrophile couplings to
commercial flow systems would have significant benefit for the scale-up
of critical building blocks and drug-like fragments or products. Under
our standard vial batch setup, the model substrates, 4-bromotetrahydropyran
and methyl-4-bromobenzoate, underwent cross-coupling to afford the
desired product in 79% yield over the course of 6 h. Moreover, irradiation
at 427 nm was observed to be optimal for this transformation (see Supporting Information). Given that HBr is generated
as the main byproduct in this coupling protocol,[17] we undertook an evaluation of various soluble organic bases.
While initial FLOSIM studies revealed that 2,6-lutidine appeared to
be an effective acid scavenger and compatible with high coupling yields,
the resulting side product, a lutidinium bromide salt, has poor solubility
and ultimately causes the flow system to clog. As such, we were unable
to translate this initial set of HTE-optimized conditions beyond an
8 mmol scale using the commercial flow reactor (Figure c; also see Supporting Information) due to the need to incorporate frequent wash cycles
to remove salt byproducts.
Figure 4
Optimization platform for cross-electrophile
coupling. (a) The
reaction takes place between 4-bromotetrahydropyrane and methyl-4-bromobenzoate
via silane-mediated metallaphotoredox catalysis using 427 nm Kessil
LEDs as the optimal light source (see Supporting Information). (b) HTE optimization allows the desired product
in the flow system (77% yield) to be obtained in 45 min of residence
time instead 6 h of reaction time using a standard setup. Several
conditions were evaluated for both setups (see Supporting Information for exact experimental conditions).
(c) Lutidinium bromide was detected during the course of the reaction
obstructing the flow reactor coil by accumulation. The use of thicker
tubing allows the reaction to be scaled up to 8 mmol. (d) The effectivity
of this reaction has been proved using a 60 mmol scale affording 10.3
g of the desired product (78% yield).
Optimization platform for cross-electrophile
coupling. (a) The
reaction takes place between 4-bromotetrahydropyrane and methyl-4-bromobenzoate
via silane-mediated metallaphotoredox catalysis using 427 nm Kessil
LEDs as the optimal light source (see Supporting Information). (b) HTE optimization allows the desired product
in the flow system (77% yield) to be obtained in 45 min of residence
time instead 6 h of reaction time using a standard setup. Several
conditions were evaluated for both setups (see Supporting Information for exact experimental conditions).
(c) Lutidinium bromide was detected during the course of the reaction
obstructing the flow reactor coil by accumulation. The use of thicker
tubing allows the reaction to be scaled up to 8 mmol. (d) The effectivity
of this reaction has been proved using a 60 mmol scale affording 10.3
g of the desired product (78% yield).Given the broad interest in this coupling protocol across the industrial
sector,[68−70] we undertook a second optimization campaign using
the HTEFLOSIM device, with the goal of identifying homogeneous conditions
that would provide improved properties for scale-up. In this regard,
we performed approximately 1000 experiments via HTEFLOSIM to evaluate
a variety of reaction components (bases, solvents, concentrations,
reaction times, metalcomplexes, catalyst loadings, additives, and
cosolvents; see Supporting Information).
Through this process, we determined that (i) decreasing the amount
of base from 2 to 1 equiv, (ii) switching to a more polar solvent
[N,N-dimethylacetamide (DMA)], and
(iii) extending the reaction time to 45 min provided optimal efficiency
without issues related to salt precipitates. Moreover, with these
conditions in hand, we were able to achieve high efficiency in both
the HTE setup (77% yield) and the commercial flow system (77% yield)
(Figure d). Most importantly,
as shown in Figure d, we were able to scale this reaction to 60 mmol using the Vapourtec
E-Series (10 mL reactor coil and 420 nm LEDs) to obtain 10.3 g of
the coupled product in 78% yield after 23 h.In comparison to
the initial vial batch protocol (87 mg obtained),
this result represents a 30.9-fold improvement in efficiency.
Optimization
of Visible-Light-Mediated C–O Arylation
Coupling for Flow
Our photocatalyticC–O coupling
reaction[71] has emerged as a versatile strategy
for the synthesis of alkyl aryl ethers. Under the standard bench setup,
using a relatively complex protected pyranose model substrate and
an aryl bromide, the etherification generated the desired product
in 82% yield after 24 h. Irradiation at 456 nm was found to provide
optimal reaction efficiency (see Supporting Information). Optimization studies with the HTEFLOSIM platform (∼450
experiments to evaluate all the components in the reaction, see Supporting Information) revealed the inexpensive
organic photocatalyst, 2,4,5,6-tetra(9H-carbazol-9-yl)isophthalonitrile
(4CzIPN), to be the ideal catalyst, generating the coupling product
in 80% yield after 35 min (Figure b). Translating these optimal HTEconditions to the
commercial flow system yielded similar results (75% yield), and time
studies demonstrated a strong correlation between these two platforms.
Once again, the results generated from the HTE system were consistent
with those obtained from the flow system across a variety of optimal
and nonoptimal conditions (Figure b).
Figure 5
Application for C–O coupling reaction. (a) The
reaction
takes place between protected pyranose and 4-bromo-acetophenone merging
nickel and photoredox catalysis. (b) With the workflow shown using
456 nm Kessil LEDs, followed by HTE optimization and the corresponding
UPLC analysis, we could obtain in a flow system the desired product
(75% yield) in 35 min of residence time instead 24 h of reaction time
using a standard setup. Optimization using our HTE protocol provides
a range of conditions, which we could translate successfully to the
flow system. (c) The efficiency of our protocol was also proved by
using a powerful continuous-flow system (PhotoSyn). Using the 25%
light intensity, we could observe a correlated result with our HTE
setup. Furthermore, increasing the light intensity, we were able to
reduce the reaction time with no changes on the reactivity. (d) The
effectivity of this reaction has been proved for both continuous-flow
systems affording the same reactivity (72% yield), resulting in a
higher efficiency for the more powerful flow system (26.6 g/day for
Vapourtec and 56.3 g/day using PhotoSyn.
Application for C–O coupling reaction. (a) The
reaction
takes place between protected pyranose and 4-bromo-acetophenone merging
nickel and photoredox catalysis. (b) With the workflow shown using
456 nm Kessil LEDs, followed by HTE optimization and the corresponding
UPLC analysis, we could obtain in a flow system the desired product
(75% yield) in 35 min of residence time instead 24 h of reaction time
using a standard setup. Optimization using our HTE protocol provides
a range of conditions, which we could translate successfully to the
flow system. (c) The efficiency of our protocol was also proved by
using a powerful continuous-flow system (PhotoSyn). Using the 25%
light intensity, we could observe a correlated result with our HTE
setup. Furthermore, increasing the light intensity, we were able to
reduce the reaction time with no changes on the reactivity. (d) The
effectivity of this reaction has been proved for both continuous-flow
systems affording the same reactivity (72% yield), resulting in a
higher efficiency for the more powerful flow system (26.6 g/day for
Vapourtec and 56.3 g/day using PhotoSyn.
Translation of the HTE FLOSIM Platform to Multiple Commercial
Flow Reactors
Throughout most of this project, we employed
a UV-150 Vapourtec E-Series as a representative flow reactor for scale-up.
In order to demonstrate the generality of this approach for practitioners
in this field, we sought to test our protocol in a second, commercial
flow system. In this context, we evaluated the PhotoSyn flow photoreactor
as developed and manufactured by Uniqsis Ltd. This photoreactor is
equipped with a 10 mL reactor coil (ID = 1.0 mm) and more powerful
LEDs (455 nm LEDs, 700 W total power, approximately 200 W output power)
compared to the Vapourtec system. According to literature precedent,[33] flow reactors that incorporate high-powered
photonic sources may offer numerous benefits, including faster reaction
rates, shorter reaction times, and amenability to nonhomogeneous conditions.
On this basis, we evaluated the efficiency of the above-mentioned
C–O coupling protocol in the PhotoSyn flow system using various
light intensities as determined via our HTEFLOSIM platform. As shown
in Figure c, using
25% light intensity, we were able to achieve satisfactory yield (76%
yield in HTEFLOSIM vs 79% in PhotoSyn) with a residence time of 35
min. Moreover, by increasing the light intensity to 75%, we obtained
a comparable 79% yield with a much shorter reaction time of 13.75
min (Figure c, also
see Supporting Information). Finally, we
attempted a gram-scale synthesis of the product with each continuous-flow
system (Figure d).
Under optimized conditions, the Vapourtec system provided 12.2 g of
final product in 11 h (72% yield), while the PhotoSyn system is able
to generate 26.2 g of the same product in the same time frame (72%
yield). Thus, compared to a batch setup, which provides 310 mg of
product in 24 h, the flow system can lead to an 86-fold efficiency
acceleration using the Vapourtec system and 185-fold efficiency enhancement
using the PhotoSyn photoreactor. More importantly, we have demonstrated
that our HTEFLOSIM optimization strategy can be applied across various
commercial flow reactors.
Conclusion
In
summary, we have designed an HTEFLOSIM device that can simulate
a continuous-flow setup to enable the optimization and direct translation
of small-scale photoredox methods to large-scale flow reactors. This
system permits the reproduction of the same reaction pathways in both
an HTE setup and a continuous-flow setup and therefore serves as a
general platform to rapidly optimize any photoredox reaction at microscale.
We have evaluated this optimization platform in the context of four
prominent photocatalytic transformations, and in each case, we have
been able to significantly improve the efficiency of these methodologies
at large scale compared to standard batch conditions. Moreover, the
generality of this platform with regard to different flow reactors
has been demonstrated. Considering the widespread interest in photoredox
catalysis across the pharmaceutical industry, we expect this optimization
platform to be widely adopted in both medicinal and process chemistry
settings.
Authors: Alexander Buitrago Santanilla; Erik L Regalado; Tony Pereira; Michael Shevlin; Kevin Bateman; Louis-Charles Campeau; Jonathan Schneeweis; Simon Berritt; Zhi-Cai Shi; Philippe Nantermet; Yong Liu; Roy Helmy; Christopher J Welch; Petr Vachal; Ian W Davies; Tim Cernak; Spencer D Dreher Journal: Science Date: 2014-11-20 Impact factor: 47.728
Authors: Daniel A Dirocco; Kevin Dykstra; Shane Krska; Petr Vachal; Donald V Conway; Matthew Tudge Journal: Angew Chem Int Ed Engl Date: 2014-03-26 Impact factor: 15.336
Authors: Zhiwei Zuo; Derek T Ahneman; Lingling Chu; Jack A Terrett; Abigail G Doyle; David W C MacMillan Journal: Science Date: 2014-06-05 Impact factor: 47.728
Authors: Hatice G Yayla; Feng Peng; Ian K Mangion; Mark McLaughlin; Louis-Charles Campeau; Ian W Davies; Daniel A DiRocco; Robert R Knowles Journal: Chem Sci Date: 2015-12-07 Impact factor: 9.825
Authors: Alberto Luridiana; Daniele Mazzarella; Luca Capaldo; Juan A Rincón; Pablo García-Losada; Carlos Mateos; Michael O Frederick; Manuel Nuño; Wybren Jan Buma; Timothy Noël Journal: ACS Catal Date: 2022-09-01 Impact factor: 13.700