Parallel Batch (Microtiter Plates)

Traditionally, chemical synthesis is conducted using the standard batch reactor because of its simplicity and versatility. These advantages are then bolstered through parallelisation.

Parallelisation has enabled a considerable decrease in the time necessary for the screening of biologically active compounds and chemical processes. One of the most popular devices is the microtiter plate, which provides a large number of identical reaction wells (standard array sizes of 96, 384 and 1536 wells). Pairing these plates with automatic pipetting systems facilitates high throughput screening. Vibration of the plate is the preferred choice for mixing.

However, generally this can lead to poor mixing at the base of the reaction wells, leading to mixing times of seconds to minutes [161]. This is because the Reynolds number is limited by the small scales, and the exclusion of baffles for easier loading/cleaning prevents the primary tangential flow from being disturbed [9]. However, this is usually not problematic as optimising the reaction is not the concern of these devices [4]; ‘hit’ detection is usually the primary objective with minimal focus on the scale-up aspects.

Although this methodology is suitable for the investigation of different reagent combinations in different molar ratios, screening the effects of temperature is more challenging.

Nonetheless, some parallelised temperature screening strategies are reported in the literature.

For example, to optimise the ring-opening polymerisation of 2-ethyl-2-oxazoline using DMAc as a solvent, Hoogenboom et al [162] used an automated synthesiser capable of running 16 reactions at different temperatures in parallel. The polymerisation reactions were run in 13 mL vessels fitted with separate heating mantels at temperatures of 50–130 °C, with several duplicated for repeatability. Time profiles of monomer concentration and polymer molecular weight (obtained via off-line GC/GPC analysis) showed strong temperature dependence, with an optimum of 100 °C found.

To control the temperature in of a 96-well plate, Zakhartsev et al [163] used a spectrophotometrically transparent heat exchanging fluid in the void beneath the wells. Here, a 50% mixture of ethylene/glycol enabled a usable optical wavelength range of 300–900 nm.

The absorption by the heat exchange fluid ranged from 0.6–1.5% of the optical source at 4–60

°C, and a temperature variation of ±0.1°C was observed across the plate. To study the kinetics

49

of enzymes extracted from the tissues of Atlantic cod (Gadus morhua), temperature was used as the ‘inter-assay’ variable and other operating variables as the ‘intra-assay’ variables.

A superior method for high-throughput temperature screening using a 96 microtiter plate was realised by Kunze et al [164]. By supplying separate heating and cooling streams to opposite sides of an aluminium block, a steady-state temperature gradient could be established (figure 21a). This profile was then supplied to each reaction well (200 µL) using radiator fins. The authors achieved usable temperature gradients varying from 17.7 °C to 30.3 °C, limited by the interaction between the heating and cooling streams and the need to shake the apparatus for mixing (removing the stagnant boundary layer). Repetition of the thermal profiles between rows also allowed repeatability to be established in a single experiment. This repeatability could also be theoretically used to screen the effects of other operating conditions. Kunze et al [164] applied this system for simple cultivation of E. coli and observed temperature dependent behaviour (figure 21b).

Figure 21 – (a) Example temperature profile across a microwell plate, (b) online monitoring of E. coli BL21 growth using fluorescence measurements [164]

The temperature screening system developed by Kunze et al [164] has several advantages over the use of separately controlled parallel reactors. Principally, the need for multiple separate control systems is removed, which reduces the complexity and cost of the set-up.

Additionally, the radiator fins minimise the obstruction to the reaction wells, enabling in-situ monitoring by light scattering, fluorescence measurements or infrared emission.

(a) (b)

50 2.5 Batch vs Continuous Screening

Process/product development is increasingly competitive, making it increasingly desirable to minimise the time from product inception to market [1, 8]. One of the major bottlenecks is the process screening stage. This is exemplified in the pharmaceutical industry, where very high numbers of candidate chemicals must be characterised [1] and the more promising synthesis routes optimised. Process screening can be sub-divided into two phases. Primary phase screening is focussed on the synthesis and identification of new compounds through trialling combinations of many reagents, and is a common methodology for the development of pharmaceutical products and catalysts. Secondary phase screening is associated with the determination of kinetics parameters as well as optimisation of a particular reaction or process.

Historically, batch processes are widely adopted in screening applications because of their high flexibility and versatility. A single batch reactor can serve countless reactions with no change required in the reactor configuration. At lab-scales, simple batch flasks can be used in multi-stage work-ups of a process, being applicable as reactors, distillation units, crystallisers, etc. [4, 5]. Similar work-up has been integrated with a microreactor system. Hartman et al [165] performed a Heck reaction and subsequent liquid-liquid extraction through segmented flow and micro-distillation through gas-liquid segmented flow with the gas and liquid separated using a membrane. However, microreactors are often specialised towards a target process, meaning the development of these one-off microchannels can be expensive [166].

Thus, drivers for flow fall onto performance. It has been shown that flow chemistry is desirable for minimising the materials requirement compared to batch, but it is reasoned that flow systems are not a universal solution for all reactions. Hartman et al [4] summarised a large number of case studies and proposed a basic selection guide based on the reaction class and importance of mixing/heat transfer on reaction rate. In summary, they concluded that discovery operations do not usually necessitate optimised conditions because the primary objective is usually independent of the final yield. Valtchev et al [167] agree, with the sentiment that simple ranking of primary screening results is sufficient; parallel routes such as the microwell plate are the preferred choice. This is approach is common in the pharmaceutical industry because of the ability to catalogue and track individual batches through a processing chain. It is recognised however that it is difficult to control the temperature in such devices [164]. Moreover, batch-screening throughputs can be limited by the data collection rates of off-line analysis tools such as HPLC [168]. Roberge et al [5]

51

describe three classes of reaction that would all benefit from synthesis in flow (shown in the points below). The more detailed guide of Hartman et al [4] states that continuous operation is suitable when mixing, heat transfer or dispersion are rate limiting (Da > 1, β > 1 or Pe < 1), as shown in figure 22.

 Type A reactions: very fast reactions (typically less than 1 s) that are mixing limited.

Controlling the temperature and mixing precisely can increase the yield for these reactions

 Type B reactions: fast reactions (order of 1 s to 10 min) that are kinetically limited. The benefit of flow chemistry is improved thermal control for the removal of thermal gradients that may reduce by-product formation. Additionally, tight control of residence time can suppress unwanted by-products by quenching at the optimum product concentration [90]

 Type C reactions: slow reactions (greater than 10 min) that involve hazardous compounds (high toxicity, thermally unstable, etc.) that are historically conducted in batch. These reactions are benefitted by minimal accumulation of the hazardous material, and higher temperatures and pressures can be realised to intensify the reaction

Figure 22 – Batch vs. continuous selection guide proposed by Hartman et al [4]

In figure 22, a series of dimensionless groups are used to evaluate if a flow reactor would be beneficial. The first of these groups is the Damköhler number, which is defined as the ratio of

52

characteristic mixing time to the characteristic chemical time. When Da > 1, concentration gradients may exist to the detriment of the process. Ideally for process screening, the Damköhler number should be less than one to ensure the true underlying mechanism is observed. The use of enhanced mixing in flow is thus warranted for reactions when Da > 1.

This was illustrated in a very fast Friedel-Crafts reaction, where poor mixing led to reduced selectivity of the monoalkylation product of 1,3,5-trimethoxybenzene in batch, and no selectivity issues using a micromixer [169]. Nagy et al [170] defined the Damköhler number using equation 19 and plotted the result as a function of residence time and tube diameter at different values of χ. Here, χ is a reaction rate-dependent parameter, D the tube diameter and Df the diffusivity. Their results generally show that higher reaction rates and larger tube equation 20 has been suggested [4]. Here, rAΔHrxn is the product of reaction rate and enthalpy, ΔTad is the adiabatic temperature change and h is the heat transfer coefficient. It is obvious that if β > 1, then the reaction may be insufficiently cooled resulting in ‘hot spots’ that can lead to by-products. The ability to remove heat from a reaction is also heavily dependent upon the ability to remove heat from the reactor itself. The Biot number, Bi, provides a suitable framework for addressing the ratio of external to internal heat transfer resistances (equation 21). For adequate heat transfer, it is desirable that Bi > 1. Ensuring this condition also means better control over the reaction temperature can be achieved for more efficient screening.

𝛽 = ℎ𝑒𝑎𝑡 𝑜𝑓 𝑟𝑒𝑎𝑐𝑡𝑖𝑜𝑛

The final characteristic used by Hartman et al [4] for assessing the potential of flow chemistry is the amount of axial dispersion (equation 22). Improper plug flow can lead to a range of residence times emerging from the reactor outlet that may lead to inaccurate kinetic data. For the meso-OBR, a wide range of operating conditions for plug flow has been established and this used for conducting screening in flow [46, 41], and for the microreactor almost perfect plug flow can be achieved using an immiscible carrier solvent [114]. Generally, the use of flow chemistry for screening distils down to a compromise between maximising the number

53

of conditions and maximising the speed in which these experiments are performed. Design of experiments employing feedback search algorithms can be incorporated in flow and reduce the number of experiment conditions needed to achieve robust kinetic models [152].

𝑃𝑒 =𝑐𝑜𝑛𝑣𝑒𝑐𝑡𝑖𝑣𝑒 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡 𝑑𝑖𝑓𝑓𝑢𝑠𝑖𝑣𝑒 𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡 = 𝑢𝐿

𝐷_𝑓 22

Reactor performance aside, one of the disadvantages of batch screening is the difficulty of scale-up. For batch processes, mixing is often realised through the promotion of turbulence through external agitation of the fluid, usually by an impeller. For standard stirred vessels, the power number, Np, can be defined (equation 23). Where Pw is the power supplied to the stirrer (W), ρ is the fluid density (kg/m³), ns is the stirrer speed (Hz or s^-1) and dim is the impeller diameter (m). Stirred batch vessels at laboratory scale can achieve ‘perfect’ mixing due to their high power densities; it is easy to supply very high stirrer speeds. However, when scaled up the power number decreases inversely proportional to the impeller diameter to the 5^th power. It is not possible to achieve this same high power density at large scales making it highly impractical and non-cost effective to achieve the same intensity of mixing.

Consequently, scale-up of stirred tanks is often conducted under constant impeller tip speed leading to decreased circulation time and increased residence/turnover times for the vessel.

Additionally, due to the different surface area to volume ratios between scales, mass and heat transfer inconsistencies are often observed, unless addressed with robust control models and re-optimisation [3, 11].

𝑁_𝑝 = 𝑃_𝑤

𝜌𝑛_𝑠³𝑑_𝑖𝑚⁵ 23

Thus, flow chemistry could instead address the challenges of scale-up, potentially removing the development bottleneck altogether. However, Valera et al [10] argue for ‘scale-transparency’. The intrinsic kinetics need not be studied in the same device as that used for commercial production. Valera et al [10] also argue that flow chemistry screening is slower than batch parallelisation simply because hundreds of data points can be obtained in one experiment. This is the same argument addressed by Hartman et al [4], who state that design of experiments can remove the need entirely for large numbers of experiments that may otherwise be prone to robustness problems.

Another important consideration regarding the batch vs continuous argument is fouling, whether an issue of materials compatibility or the robustness to handling solids. Corrosion of

54

common construction materials (stainless steel, hastelloy, glass, silicon, etc.) used in microreactors is usually quoted at macro-scales in mm/yr [171]. An industrially operated microreactor therefore potentially faces replacement at a rate that could make it cost-ineffective. The ability to handle solids is also critical because there are a wide range of processes in pharmaceuticals and fine chemicals synthesis that produce insoluble compounds [4, 5]. Roberge et al [5] for example conducted a survey of the chemistry conducted by Lonza in 2005 and determined that 63% of the reactions identified as suitable for flow chemistry (Type A-C reactions) contained some form of solid. The main disadvantage of the microreactor is the ease at which the channels are blocked. One approach to this problem could be to regularly purge the channels [171]. Better, Poe et al [172] synthesised solid indigo particles in a monodisperse droplet flow by introducing the reagents into an inert carrier solvent (mineral oil). Similarly reported are sheath flows and segmented flows for inorganic nanoparticles [173, 174] and slug flows for protein crystallisation [175]. Also, a microreactor with gas-liquid slug flow and ultrasonic mixing reportedly did not clog by the precipitate formed from the photodimerisation of maleic anhydride [176]. However, these methods are dependent upon the individual channel-reaction combination: therefore, timely implementation of the most suitable approach may reduce the time benefits saved in adopting microreactor technology.

Although mixing is far from the ideal plug flow model, the issue of clogging is completely removed when using a larger standard continuous stirred tank reactor (CSTR). Case studies include a solid magnesium catalysed Barbier reaction for the synthesis of a pharmaceutical ingredient [177] and the synthesis of LY573636∙Na using the Schotten-Baumann reaction [178]. The reasons for using CSTRs in these case studies instead of tubular plug flow reactors (PFRs) were: evolved CO2 gas could collect in the headspace without impacting upon mixing, solid catalysts could be used with no clogging and shorter residence times could be used because mixing was independent of the net flow.

Other flow chemistry platforms include conventional plug flow reactors (PFRs) and modified PFRs (containing inserts). Typically, a PFR is a tubular reactor where plug flow is generated via a flat velocity profile due to fluid turbulence. Unlike the OBR where the mixing is controlled using the fluid oscillation, the mixing in a PFR is controlled by the fluid velocity.

This makes scale-down difficult, as there is a minimum necessary throughput in order to achieve plug flow. Adding pipe inserts (e.g. baffles or meshes) lowers the Ren number required for the onset of turbulence and consequently reduces the flow rate required.

55

However, the mixing is still dependent on the fluid velocity (provided the scale is sufficient such that diffusion is not important). As a consequence, such reactors are seldom used for flow screening, and would be very difficult to envisage for long residence time processes.

Perhaps the final consideration of the application of flow chemistry screening is the analysis tools available. Off-line analysis methods can be time consuming and discrepant, especially if reaction samples are not appropriately quenched [168]. It is therefore desirable when monitoring a reaction to use non-destructive methods, where applicable, in order to preserve as close as possible the underlying mechanism. Although real-time monitoring is readily applicable to single batch processes, parallelised batch synthesis often requires the use of simpler off-line sampling methods. Whereas, real-time monitoring of flow reactors in the context of continuous process screening has been conducted using a wide variety of spectroscopic methods, including: NMR [155, 179, 180], UV [181], Raman [168], HPLC [149], MS [182], FTIR [148, 46] and fluorescence. A review of the use of these methods used with flow reactors was recently reported [154].

To summarise, flow chemistry can be used to improve the reaction rate providing the intrinsic kinetics are on faster time scales than mixing and the heat transfer rate. Additionally, flow chemistry screening could improve the intrinsic safety of hazardous processes by eliminating the significant accumulation of toxic or hazardous intermediates. The application of flow chemistry to primary phase screening is unlikely to yield any advantages, because the main objective (e.g. hit detection) is independent of the yield. With the combination of design of experiments methodologies, flow chemistry is instead likely to be more advantageous to secondary phase screening applications. Here, achieving good quality plug flow is important to maintain batch equivalency (narrow RTD) so that reliable kinetic data is produced. In this regard both the meso-OBR and microreactor seem ideal candidates for kinetics modelling and optimisation. However, the meso-OBR is generally a more ubiquitous screening platform than the microreactor because of its simpler construction and operation. The niche of the meso-OBR is to allow the screening of long residence time processes with multiple phases (if present) with minimal need for the optimization of the control/mixing strategies. Table 6 lists the attributes of the screening platforms discussed in this literature review.

56

Table 6 – Comparison of screening platforms

Meso-OBR Microreactor Microtiter Plate

Operation Batch/Continuous Continuous Batch

Mixing Strategies Fluid Oscillation +

≤60 Conditions per Hour ≤60 Conditions per Hour 96, 384 and 1536 Conditions per Batch

Scaling Methods Scale-up or Scale-Out Scale-Out N/A

Solids Handling Catalyst Particle

Gas-Liquid Gas Sparger at the Inlet, High Oscillation Intensity

Gas-Liquid-Solid Integral Baffles/SPC Taylor Flow in a Monolithic Channel

2.6 Meso-OBR Technology Outlook