Article pubs.acs.org/OPRD
Economic Considerations for Selecting an Amine Donor in Biocatalytic Transamination Par̈ Tufvesson,† Mathias Nordblad,† Ulrich Krühne,† Martin Schürmann,‡ Andreas Vogel,§ Roland Wohlgemuth,∥ and John M. Woodley*,† †
Department of Chemical and Biochemical Engineering, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark DSM Innovative Synthesis BV, NL-6167 RD Geleen, The Netherlands § c-LEcta GmbH, D-04103 Leipzig, Germany ∥ Sigma-Aldrich Chemie GmbH, CH-9470 Buchs, Switzerland ‡
ABSTRACT: The industrial implementation of biocatalysis for production of pharma and fine chemicals has grown substantially over recent years. An upcoming application is that of chiral synthesis of optically pure amines, a technology known for many years but that is now seeing a renewed and wider interest in industry. The technology has been demonstrated in a few selected cases, but widespread implementation and for a broader range of target molecules requires a deeper understanding of the underlying thermodynamic as well as economic constraints for the different choices that can be made in designing the process, in particular the choice of amine donor. This paper discusses these constraints and demonstrates, through simple thermodynamic and economic models, the process targets that need to be set and achieved for a process dependent on allowed process costs and quality targets.
■
INTRODUCTION Biocatalysis, the use of isolated enzymes, resting cells or parts thereof, to catalyze chemical reactions is well-established in the fine-chemical industry.1−3 Applications include many different chemistries such as chiral ketone reduction, hydrolysis, hydroxylation, Baeyer−Villiger oxidation, and more.4−6 In this paper the applications of biocatalytic transamination for the synthesis of optically pure chiral amines will be discussed. This is an area that has grown substantially over the past few years.7 The main motivation for using biocatalysis in this application is the excellent stereo and regioselectivity and the potential for high yield in a single step (compared to resolution strategies).8,9 A limited number of examples have demonstrated the possibility of developing processes that can reach high product titers, productivities, and yields.10−12 However, there remain a number of challenges related to the implementation of biocatalytic transamination processes, including the thermodynamic equilibrium of the reaction, product inhibition, low activity for the desired transformation, and low productivity/ stability of the catalyst.13 These factors are also linked to the choice of amine donor and reaction conditions and ultimately to the feasibility and competitiveness of the process. One important goal in order to simplify downstream processing and product purification is to bring the transaminase-catalyzed reaction to completion.14,15 Many different technologies have been investigated with the objective of overcoming the unfavorable equilibrium, including using a stronger or excess amine donor, removal of volatile coproduct by stripping, enzymatic cascades, and in situ product removal.8,12,16,17 Scheme 1 shows the reaction for the most common amine donors, with α-methylbenzylamine (MBA; also referred to as phenyl ethyl amine, or PEA) and alanine (ala) visualized as racemic forms. For MBA and alanine, the © XXXX American Chemical Society
equilibrium constant (Keq) relative to 2-propylamine has been estimated based on the change in Gibb’s free energy for the partial reaction of converting each donor into it corresponding ketone form. The most common way to shift the equilibrium for each donor is also indicated in the scheme. The use of MBA or alanine a racemic or an enantiomerically pure form is chosen as amine donor, is not only dependent on the donor costs (racemic MBA is much less expensive than a pure MBAenantiomer, while racemic alanine is more expensive than Lalanine), but also on the biochemical properties of the transaminase systems used. Different target molecules vary in their properties (Gibbs free energy of formation, volatility, solubility, etc.), and therefore, there is not a single universal process solution. Thus, developing a process for a new target amine remains demanding since it involves a number of choices (as discussed above) about how to run the reaction. These choices will determine not only the technical feasibility of the process but also the process costs. In many cases the biocatalyst itself will need to be developed to fit the specific target molecule, cosubstrate, and process conditions to achieve the required process intensity and biocatalyst yield (kg product per kg biocatalyst), for example by protein engineering.18 However, since the outcome of the biocatalyst development depends on the conditions used in the screening (i.e., “you get what you screen for”), ideally the targets for the process should be set, and also many of the process choices should be made, prior to starting the development. Hence, it is important to have an understanding of both the underlying physicochemical constraints such as reaction equilibrium and the economic Received: March 31, 2015
A
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
Scheme 1. Reaction Scheme for Biocatalytic Transamination Using One of the Most Common Amine Donors: αMethylbenzylamine (MBA), 2-Propylamine (IPA), or Alanine (ala)a
a
The equilibrium is given in relation to the reaction where acetone is converted to 2-propylamine.
• Biocatalyst costs, as a function of biocatalyst yield (kg product kg biocatalyst−1) and biocatalyst production cost • Amine donor and cofactor costs. Process development costs and, often more importantly, process development time can also be critical in establishing a new process. This situation is often met, particularly in industrial environments when processes are developed for application-oriented products such as pharmaceuticals, agrochemicals, flavors, and fragrances as well as other industrial products in the development phase.22 The development time is less important for second generation processes where the manufacturing cost becomes the key factor. The time and effort for implementation of a given technology also has to be estimated. By their nature, these estimates are rather uncertain but could serve as a starting point for a cost-benefit analysis for a particular strategy. In order to support the assessments carried out in this study, a number of assumptions have been made regarding the cost of equipment, labor, materials, and so forth, as well as the scale of a base case. These assumptions are presented in Tables 1 and 2. Furthermore, for the sake of simplicity, a general assumption used in this study is that the target amine has a molecular weight of 100 g/mol. Capital Costs for Process Equipment. In the base case of the cost assessment we have assumed a 10 m3 production vessel and a standard recovery by stepwise extraction, back-extraction, and evaporation in a multipurpose contract manufacturing organization (CMO) facility (see Scheme 2). (No recycling of solvent was considered.) To calculate the capital cost per production batch and per kg product, the investment cost was converted to an equivalent annual (and subsequently to an hourly) cost by multiplying the capital investment with an annuity factor, k (see eq 1) using an interest rate (i) of 6% and an economic lifetime (t) of 8 years, which can be considered typical for the chemical industry but varies with, among other things, the risk of the project.
constraints, including both the allowable cost (for example those determined by competing technology) and approximate process costs for the suggested process.19 This kind of approach is rarely used in academic research, which brings the risk that processes developed are not always the most cost-effective or in the worst case not scalable due to physicochemical constraints. The aim of this article is to add quantitative cost data and suggest a feasibility range for the various technologies to assist in selecting the most suitable and competitive system in the conceptual phase of process synthesis and design. Moreover, the study highlights the impact of key process metrics on the cost structure and suggests development targets that can be used to design suitable screening conditions for protein development.
■
METHODOLOGY AND ASSUMPTIONS The present study uses a simplified approach for estimating the cost of different process scenarios suitable for conceptual (early development phase) studies. The analysis is useful to evaluate process feasibility and to identify the economic “hot-spots”. It should be emphasized that the results obtained do not give absolute values but rather serve as guidelines and as a starting point for a more detailed evaluation.20 Although a detailed assessment will only be possible when the precise application, scale, and location of the facility is known, the general case discussed in the present study sets the stage for more detailed evaluations. The costs associated with transaminase-catalyzed processes can be broken down into different subcategories. It is customary to categorize processing costs as operating costs (OpEx) or capital costs (CapEx). The calculation and use of these are well-described in chemical engineering textbooks.21 For the purpose of analyzing the effect of different key performance indicators for biocatalytic reactions, in this paper we have also chosen to group the costs into categories which are analyzed separately. These categories are • Reaction and recovery CapEx, labor, and solvent costs, costs that change with process intensity, i.e., space time yield (g L−1 h−1) and product titer (g L−1)
k= B
i 1 − (1 + i)−t
(1) DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
analysis a high value of 30 € m−3 h−1 and a low value of 20 € m−3 h−1 was used. Operating Costs. The operating cost (OpEx) includes the cost of raw materials, utilities, waste management, and operating labor. Indirect and fixed operating costs are usually calculated from the direct labor cost and/or annual capital investment cost. The amount of raw material consumed is obtained from the process mass balances, and the cost of the most common chemicals can be obtained from the suppliers or by consulting trade journals (e.g., European Chemical News or Chemical Marketing Report).21 Raw material costs associated with the current process are given in Table 2. Process water and buffer make only a negligible contribution to the total cost and were therefore excluded from the model for the sake of simplicity. Utility requirements, including heating and energy needed for agitation, can be obtained from mass and energy balances. The cost of utilities can then be calculated based on prices obtained from suppliers or purchasing agents. In biocatalytic processes, the dominating energy-consuming operations are often mixing and potentially sterilization. The energy necessary for mixing can be calculated using rule-of-thumb values,26 whereas the heat required for sterilization can be obtained using the heat capacity for water. Waste disposal costs should also be included, and typical wastewater treatment costs are 0.5−2 € m−3 (depending on location). However, our preliminary calculations on the base case indicate that utility costs contribute only marginally to the overall cost of the process, and they were therefore excluded for the sake of having a less complicated cost model. Labor costs were estimated from the process flow sheet by assuming a total labor requirement of two operators to operate the entire process during 3 days (including preparation and cleaning). Labor rates were obtained from Eurostat (ec.europa.eu/eurostat). Material costs were based on personal communication with vendors. The cost of chemicals is highly dependent on sales volume and quality and can furthermore fluctuate in time depending on supply and demand among other factors. To reflect this, a range of costs has been given in Table 2 and used for subsequent calculations. Other operating costs were calculated based on the direct labor costs and from the annual capital investment and is described in Table 2.
Table 1. Economic Parameters and Costs for the Calculation of Process Costs equipment cost data source Lang factor annuity, based on i = 6% and t = 8 years cost of 10 m3 reactor purchase cost total installed cost (TIC) yearly capital cost (annuity) operating hours per year (∼50% utilization) fixed OpEx annual maintenance hourly cost of operation
reaction time DSP time
Matche Inc. (www.matche.com), Process design software, SuperPro Designer (Intelligen, NJ) 5.0 (typical for fluid processing units)24,25 k = 0.161 (based on eq 1)
1.000.000 € 5.000.000 € 805.000 ca. 4.000 h 15% of the annual capital investment cost 10% of the annual capital investment cost base case: 250 €/h (25 €/m3·h) high: 300 €/h for a 10 m3 reactor low: 200 €/h for a 10 m3 reactor 24 h 10 h
Table 2. Estimated Operational and Material Costs raw materials
amine donor L-alanine 2-propylamine rac-MBA optically pure MBA (R- or S-) PLP NAD+ ion exchange resin for ISPR solvent costs
process water cost solvent use
labor supervision cost and indirect OpEx
estimation price range
amount per batcha
10−20 €/kg 2−5 €/kg 0.5−2 €/kg 100 150 €/kg
2.3 tonnes 1.5 tonnes 6 tonnes 3 tonnes
1000−2115 €/kg 2.5 kg 1500−3000 €/kg 0.7 kg 100 €/kg base case: 1 €/kg high: 2 €/kg low: 0.75 €/kg 190 €/m3 base case: 1× reaction vol. high: 1.5× reaction vol. low: 0.5× reaction vol. 30 €/h (Eurostat) 2 operators 100% of the direct labor
■
RESULTS AND DISCUSSION Process and Recovery Costs. In the first step of the analysis the costs associated with the equipment capital costs, labor, operational cost, and auxiliary raw materials (reaction buffer, cofactor, and solvent for recovery) was estimated. The base case assumes a 24 h batch reaction and subsequent for recovery (10 h), as described above. In the extractions a high distribution coefficient of the targets was assumed with a yield of >99% recovery in each step. It can be seen in Figure 1 that the costs in the base case are dominated by the solvent use (44%) (recycling was not considered in the calculations), whereas the rest was distributed between CapEx for reaction (27%), labor (18%) and CapEx for DSP (11%). A sensitivity analysis was carried out where the end product concentration was varied at a fixed process (reaction and separation) time and the costs were plotted as a function of this concentration (see Figure 2). In this way the space−time yield
a
Based on a product concentration of 0.5 mol/L and 5 times amine donor excess; CPLP = 1 mM; CNAD+ = 0.1 mM.
The capital cost for a given production site can vary greatly dependent on its location and degree of utilization. Utilization of equipment is often low (30−60%), which is a problem for the overall economy of the plant. This is a very important aspect when considering the use of specialized equipment. For example, CMO sites in Europe and US are typically twice as expensive per volume/hour, relative to their Indian or Chinese counterparts.23 According to Pollak et al., the space time cost varies between 40 $ m−3 h−1 for 4 m3 reactors in a Western CMO facility down to 6 $ m−3 h−1 in a Chinese CMO facility in a 10 m3 reactor. In this study, a cost of 25 € m−3 h−1 (ca. 34 $ m−3 h−1) has been used in the base case. In the sensitivity C
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
Scheme 2. Process Flow Chart for the General Synthesis and Recovery of Chiral Aminesa
a
Reaction is carried out in a reactor vessel, and subsequently residual ketone is extracted at low pH. Tthen the product amine is recovered by basic extraction and evaporation of solvent. The addition of acid and base have been left out for simplicity.
production costs for API or fine chemicals production. The cost contribution of the biocatalyst is related to the cost of its preparation as well as the catalyst yield (the mass of product that can be produced per kg of biocatalyst). The cost for preparing the biocatalyst is in turn dependent on a number of factors, the most significant being the production volume (scale), fermentation titer, and also the form of the catalyst (i.e., whole cell, immobilized or free, or crude, enzyme). Furthermore, the biocatalyst yield is a function of the activity, stability, and recyclability of the biocatalyst. Thus, while the latter aspects are more difficult to capture in a simple screening procedure, screening solely based on specific activity does not necessarily select the most economically viable biocatalyst. The costs associated with preparing the biocatalyst were previously analyzed in detail and indeed can span several orders of magnitude.20 In the analysis in this study we have assumed a cost for whole cells in the range of hundreds of € kg−1 and for free enzymes in the range of a few thousands of € kg−1 (1500−5000). The costs are largely dependent on production scale (for API and fine chemical conversions usually around 10 m3 or less) and the degree of development of the process, e.g., biocatalyst titer. The cost of immobilized enzymes varies widely dependent on the preparation technique, but always adds to the cost per activity. This is mainly due to loss of activity, operational costs, and to some extent the cost of auxiliary materials such as functionalized resins or cross-linkers. Typically nonfunctionalized resins cost in the range of 40−100 € kg−1, whereas functionalized resins are more costly. However, also the downstream cost need to be considered when choosing biocatalyst form: although whole-cells usually are cheaper per activity, the post reaction separation could be more challenging and thus add additional cost. Figure 3 shows how the biocatalyst adds to the total cost of the product as a function of biocatalyst yield and cost of the biocatalyst, using typical values for whole-cell (100 €/kg), crude enzyme (500 €/kg), and an expensive, purified biocatalyst (2000 €/kg). Many times the aim for high process intensity (i.e., high substrate loading and rates) will conflict with the need for a high biocatalyst yield, due to a decreased stability of the biocatalyst at higher loadings and/or temperatures. Indeed, in the most economical process, a balance needs to be struck between high process intensity and high catalyst yield. All transamination reactions use PLP as cofactor. Reported concentrations normally span in between 0.1 to 1 mM, which in the base case adds up to a few € per kg product. It should be noted that this cost also scales with process intensity (in a
Figure 1. Distribution of process cost (CapEx and OpEx) excluding biocatalyst and amine donor costs.
Figure 2. CapEx, labor, and operating costs (including water and solvent) as a function of process intensity. The solid line represents the costs using the base case assumptions, whereas the lower and upper dashed lines indicate the lower and higher cost assumptions.
of the process (which acts as a modifier on the CapEx and labor) was covaried with the product concentration (which has a direct effect on the solvent cost). It is clear from Figure 2 that at product concentrations beneath 25 g/L the costs for processing increase rapidly and alone exceed 100 €/kg, which would likely be prohibitive for most processes. It should be emphasized that the output from the analysis is highly dependent on the efficiency of the recovery as this makes up half of the processing costs. This highlights the need to investigate the DSP recovery strategies early on in the project life-cycle in order to set the targets for the upstream process development (e.g., which product concentration need to be achieved). Biocatalyst and PLP (Cofactor) Costs. The cost of the biocatalyst usually contributes significantly to the overall D
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
obtained also depends on the amine donor/acceptor ratio and if the product or coproduct can be selectively removed from the reaction. In cases where MBA is used as a donor it can be difficult to find a method that can selectively remove the product without removing the substrate simultaneously due to similar molecular properties of the species (see Table 4). Figure 4 shows the dependence of the thermodynamic yield on amine donor ratio in the case where no selective ISPR takes place. In the figure, yields below 50% are disregarded since in these cases a process strategy based on kinetic resolution (where the nondesired enantiomer is degraded) would be more effective. Likewise, an excess of more than 10-fold would probably be infeasible, not only due to the added cost but because of the limited amount that can be put in the reactor due to solubility constraints, and because of the harsh chemical environment this would create for the biocatalyst. A yield above 75% (preferably >90%) and an amine donor ratio less than 2 (one time molar excess) is probably required in most cases. It can be seen that in the cases where Keq is close to 1, it is unclear whether the process will be feasible; it will have to be evaluated in each case. For the cases where Keq is around 30, the process is likely to be feasible. However, the best process option will be determined in comparison with other process alternatives. As seen in Table 3, the cost of using MBA as an amine donor is very dependent on whether optically pure or racemic MBA is used. A molar excess of 10-fold rac-MBA would add a cost of ca. 25−100 €/kg product, whereas optically pure R-(+)-MBA would add more than 1500 €/kg product. One of the main considerations for using MBA as the amine donor is the complex downstream recovery resulting from presence of an excess of a hydrophobic amine (the donor). This will be discussed in the latter part of this paper. Using 2-Propylamine as the Amine Donor. 2-Propylamine (IPA) is a commonly used amine donor in transamination.10,11 Although the donor is less strong (thermodynamically) than MBA, acetone is formed as the byproduct of the reaction which can be removed by evaporation to shift the equilibrium.28 Another attractive feature is that IPA is achiral and thus all of the amine can be utilized for transamination unlike chiral racemic amine donors where only half of the molecule will be incorporated in the ketone acceptor. It is also cheaper than L-alanine or optically pure MBA by one to 2 orders of magnitude, respectively (Table 3). The use of 2propylamine as a donor for transamination has been extensively discussed in Tufvesson et al.,28 where a coupled enzyme and acetone removal model was used to show the feasibility window of using 2-propylamine as amine donor based on the substrate volatility (loss of substrate) and Keq of the reaction (limited by acetone removal rate). Selectively removing also the amine product in situ, while running the reaction, e.g., by adding a membrane that selectively retains the ketone while allowing acetone to permeate, would expand the range of feasibility, as was reported by Rehn et al.29 Another way of expanding the scope of this amine donor for amination of more volatile ketones would be selectively reacting the acetone further. Acetone could for instance be reduced to 2-propyl alcohol using an alcohol dehydrogenase,15 although the selectivity between the substrate ketone and acetone would also in this case be crucial. Further, the added cost of the cascade enzyme and cofactor would need to be considered. The raw material cost of using a 5-fold excess of 2propylamine would add between 7 and 18 €/kg product. It can
Figure 3. Added cost of the biocatalyst per kg of product as a function of biocatalyst yield (mass of product (P) per mass of biocatalyst (B)) for three levels of biocatalyst cost.
process where a higher product concentration is reached less PLP is needed per kg product). Considerations for Choosing the Amine Donor. The choice of the amine donor is critical, because it determines the thermodynamic equilibrium of the reaction,16 as well as the feasibility for separation of the products and reactants, either in situ or post reaction, and also as the cost for the donor. The most commonly used amine donors reported in the scientific literature as well as used in industry are 2-phenylethylamine (MBA), 2-propylamine (IPA), and L-alanine (Ala). In the following section the feasibility of using each of these donors and their cost contribution to the overall process will be discussed. As can be seen in Table 3, depending on the choice of donor and the excess added, the cost of the amine donor varies from a few to above 100 euro per kg product. Table 3. Added Cost of the Amine Donor to Product Cost at No Excess and 10 Times Excess, Using Different Amine Donors amine donor cost added cost per kg product no excess 10× molar excess
2-propylamine
L-alanine
Rac-MBA
R-(+)-MBA
2−5 €/kg
10−20 €/kg
0.5−2 €/kg
125 €/kg
1.2−3 € 13−33 €
9−18 € 100−200 €
2.4−10 € 27−110 €
150 € 1670 €
Recycling of excess amine donor post reaction has been suggested as one way to reduce the cost of the donor. However, currently there are no published reports on the feasibility of this approach. The savings would obviously need to be weighed against the costs for the recovery and recycle. Using MBA as the Amine Donor. The main motivation for using MBA as an amine donor is that it is a strong donor, i.e., the resulting K equilibrium (Keq) of the reaction becomes more favorable.16,27 Using MBA as an amine donor the ΔG of the reaction (compared to 2-propylamine) is negative, which means that the Keq for the reaction between MBA and acetone to form acetophenone and 2-propylamine is in favor of the products (Keq =30). Scientific literature data indicates that Keq for molecules with similar structures (aliphatic amines) would also be similar, whereas transformation of ketones with a phenyl group in the α-position would probably result in a Keq between 0.5 and 2 depending on the substitution of the aromatic ring.16,28 The maximum reaction yield that can be E
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
Table 4. Composition and Component Properties of Reaction Mixtures for Reaction Systems charge amine donor alanine
MBA
IPA
a
main components product amine substrate ketone alanine pyruvate lactate glucose gluconate product amine substrate ketone MBA acetophenone product amine substrate ketone IPA acetone
hydrophobic a
>50 g/L ∼0−5 g/L >100 g/L 50 g/L ∼10 g/L ∼100 g/L >50 g/L ∼1−5 g/L >100 g/L >50 g/L >50 g/L ∼1−5 g/L >100 g/L 1−25 g/L
yes yesa no no no no no yesa yesa yes yes yesa yesa no no
pH 2
pH 7
pH 10
volatile
+ve neut. +ve neut. neut. neut. neut. +ve neut. +ve neut. +ve neut. +ve neut.
+ve neut. neut. −ve −ve neut. −ve +ve neut. +ve neut. +ve neut. +ve neut.
neut. neut. neut. −ve −ve −ve −ve neut. neut. neut. neut. neut. neut. neut. neut.
a, b a no no no no no a a yesb yes a, b a yesb yes
Depends on target product properties. bDeprotonated state.
MBA,12 see Scheme 3. However, using alanine can also make the biocatalyst more prone to product inhibition, and therefore a combination with in situ removal of the product may be necessary as shown in the case by Truppo et al. 12 Unsurprisingly the added cost of two extra enzymes and cofactor is significant. The added cost of NAD+ varies between about 3 €/kg to 50 €/kg depending on the added concentration of NAD+ (0.1 mM to 1 mM NAD+ at a product concentration of 50 g/L) and amount of cascade enzymes (available LDH and GDH enzymes are very efficient and are only required in very low amounts in our experience, ∼0.1 g/L). It is obvious from the potentially high added cost that the added concentration of cofactor is critical to the competitiveness of this option. It should also be noted that the cost of NAD+ (as well as PLP) cofactor scales (inversely) with the concentration of the process, meaning that higher product concentrations also help to reduce the cost for the cofactor per kg of product. The cost of L-alanine would add from ∼10 to >200 € per kg of the product dependent on the excess used (0−10-fold) and the purchase price of L-alanine. Downstream Recovery Considerations. As mentioned above, one driver for the implementation of biocatalytic processes is simpler downstream recovery due to a more selective reaction. Interestingly, in transaminase-catalyzed processes the simplicity of the recovery is also highly dependent on the choice of amine donor. Table 4 shows the composition of the reaction mixture that enters recovery. As can be seen, the systems and potential for simple recovery vary greatly. Using alanine as a donor creates a very simple system if the product is hydrophobic (which is normally the case) as all cosubstrates and products are hydrophilic. Using MBA conversely creates a relatively complicated system since the cosubstrates are also hydrophobic. Volatility could potentially be used to remove excess MBA and coproduct. In the IPA case, volatility can be exploited both in situ for shifting the equilibrium and also for removing excess amine donor in the cases where the substrate is nonvolatile. Process Targets. The targets that need to be set for a given process ultimately depend on the cost of competing technologies. Although typical conversion costs for fine chemicals are inelastic and quite low, in the range of 20−50 $/kg,23 and highly dependent on location and type of chemistry
Figure 4. Thermodynamic yield as a function amine donor ratio for Keq of (from the top down): 30, 10, 2, 1, and 0.5.
be noted that this span can be critical for the competitiveness of the process, and therefore an up-to-date cost quotation from a vendor should be obtained when considering using 2propylamine as the amine donor. The cost for sweeping or stripping the reactor would depend on the process intensity but would not add a significant cost compared to other costs. Foaming while sparging gas through the reaction liquid (stripping) may pose a problem when combining high loadings of biocatalyst with a hydrophobic substrate. This could be overcome by immobilization and/or operating the catalyst in an external packed bed, but only at the expense of added catalyst cost as discussed above. Using Alanine as the Amine Donor. When using alanine as the amine donor the thermodynamic equilibrium becomes very unfavorable; the Keq for the reaction between alanine and acetophenone to yield pyruvate and 2-phenylethylamine (MBA) is 4 × 10−5. Remarkably, it is possible to shift the unfavorable equilibrium by coupling the transamination reaction to an enzymatic cascade reaction to degrade the pyruvate. For example, a cascade using lactate dehydrogenase (LDH) to degrade pyruvate to lactic acid coupled to glucose dehydrogenase (GDH) to regenerate the NADH cofactor (while converting glucose to gluconate) has been shown to effectively assist in converting 50 g/L of acetophenone to F
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
Scheme 3. Transaminase-Catalyzed Reaction of Acetophenone to MBA Using Alanine As Amine Donor and Lactate Dehydrogenase (LDH), Glucose Dehydrogenase (GDH), and NADH as Means to Shift the Reaction Equilibriuma
a
Due to the gluconic acid production, a method for pH-control is necessary. The deprotonation of the acid is a thermodynamic sink and drives the equilibrium.
Table 5. Development Targets for Different Scenarios for Amine Donor Excess, Process Intensity (Assuming 24 h Reaction and 12 h Recovery as Described Above) and Biocatalyst Yield target cost
a
process intensity (g/La)
max amine excess (fold)
biocatalyst yield (kg P/kg B)
€/kg
IPA
Ala
Rac-MBA
in 10 m3
WC (500 €/kg)
FE/Imm. (2000 €/kg)
30 50 100 500
2−5 5−10 10 10
no excess 1−2 2−5 10
0−2 5 10 10
>150−200 >80−125 >50−75 >10−20
>50 >25 >10 >2.5
>200 >100 >50 >10
Given the reaction and recovery times above.
For any given process it does not matter from which category (e.g., biocatalyst cost) the cost originates, but for the sake of setting the process targets the allowable cost contribution has been divided between amine donor, process costs, and biocatalyst costs in the ratio 1:2:2. The targets for the four scenarios are compiled in Table 5. As can be seen in the table, the required process metrics in Scenario 1 (30 €/kg) and 2 (50 €/kg) are very challenging. As can be seen in Figure 2, where cost is plotted against process intensity, in order to achieve the targets, product concentrations need to exceed 150 g/L. Likewise, the catalyst needs to be very effective; a biocatalyst yield of 50−100 kg/kg would be required, corresponding to using less than 1−2 g/L biocatalyst (without recycle), and the amine donor needs to be used and in a very moderate (or no) excess. The use of optically pure R(+)-MBA is not feasible in any of the cases due its high cost. Racemic MBA could be suitable in the cases where economic constraints are tighter; however it would depend on the cost of recovery. It should be noted that, even where the economic constraints have been relaxed (scenario 3 and 4), the requirements on process intensity (>10 g/L, i.e., 100 mM)
carried out, conversion costs for more complex target compounds offer much more flexibility (and thus greater opportunities for enzyme-catalyzed conversions). Given this span of conditions, it is not possible to come with one target value. Instead we have considered four different scenarios to which the targets are related (relevant for fine chemical and pharmaceutical processes): (1) Competing with simple technology at conversion costs of 30 €/kg. (2) Competing with standard technology at conversion costs of 50 €/kg. (3) The process telescopes one or more existing chemical steps, or competes with difficult technology-allowed conversion cost 100 €/kg. (4) The process telescopes several existing chemical steps, unique chemistry, or where implementation speed is the primary target-allowed conversion cost 500 €/kg. The boundary conditions for the conversion costs as well as the development targets can however be changed if there are no competing routes toward the target compounds. G
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
target metrics. To decrease biocatalyst development costs, more generally applicable, off-the-shelf catalysts or pre-evolved “templates” would be very desirable to expand the applicability of transaminase technology. This also shows the need for tools for a faster and cheaper biocatalyst and process development. Automated and miniaturized screening and development platforms that can accelerate development hold much promise in this direction.30,31
are still relatively high in relation to the majority of published reaction conditions used in transamination,13 which are often in the 10 mM range (corresponding to 1 g/L assuming the molecular weight of the product is 100 g/mol). Even so, it is clear from the development work done by Codexis and Merck in the Sitagliptin case (which uses IPA) that given sufficient development it is indeed possible to achieve the numbers required for scenario 1 and 2.10
■
■
CONCLUSIONS To find the most suitable and cheapest process option a number of parameters need to be considered. Different amine donors have different application ranges and carry different cost structures. The above analysis shows the need to understand this in order to select the most promising strategy based on the physicochemical properties of the target substrate and product. It is clear from this study that it is not possible to come with a definitive conclusion on which amine donor is the better one or set absolute values for the cost of each option. The costs are dependent on a number of variables, such as scale, location, degree of utilization of equipment, requirements on return on investment, the variation of market prices for the different donors (and other materials) over time, and so on. Nevertheless, the analysis can serve as a starting point for making a more detailed study and to help make more informed choices and exclude some inappropriate options at an early stage. Potentially the cheapest technology, using IPA, is (presently) limited to nonvolatile compounds where the Keq is not too unfavorable. Using racemic MBA could possibly provide a relatively quick and easy implementation for those amines that are volatile but where Keq is still higher than 1 (with MBA as donor). Nevertheless, the recovery of the product is more complex and should probably be developed prior to, or in parallel with, the development of the biocatalytic reaction. LAlanine should be considered in those cases where it is infeasible to work with other donors, as the associated costs are higher and implementation is more difficult due to the expensive donor, additional enzymes, and cofactors. It can also be concluded that, when doing research, suitable model substrates have to be selected dependent on the application; the generally studied conversion of acetophenone to MBA is thus not always the most representative system (model reaction systems spanning the full spectrum of Keq, volatility and hydrophobicity should be considered). The use of IPA as donor and the downstream challenges when using racemic MBA also merit further investigation. In most cases the cost of the biocatalyst will be significant and therefore the activity (and yield gP/gB) of available biocatalysts will be one of the main considerations also for choosing the amine donor, if it is found that either donor is feasible. Process targets (intensity, etc.) depend on competing technology and the economic constraints. Process concentrations of at least 50 g/L will normally be required but even higher when competing with standard technologies. The development cost of a fine chemical usually normally comprises 5−10% of sales.23 Depending on the sales volume of the product and also the development phase of the project (early stage projects run a higher risk of being discontinued) more or less resources will be available for the development work. Whereas process development costs using a pre-existing biocatalyst are not likely to contribute very much to the overall product costs, many times developing the biocatalyst through several rounds of directed evolution is required to meet the
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS The support from BIOINTENSE financed through the European Union 7th Framework Programme (Grant agreement no.: 312148) is acknowledged.
■
REFERENCES
(1) Huisman, G. W.; Collier, S. J. Curr. Opin. Chem. Biol. 2013, 17, 284−292. (2) Wohlgemuth, R. Curr. Opin. Biotechnol. 2010, 21, 713−724. (3) Enzyme Catalysis in Organic Synthesis: A Comprehensive Handbook, 3rd ed.; Drauz, K., Gröger, H., May, O., Eds.; Wiley-VCH Verlag & Co, KGaA: Weinheim, Germany, 2012. (4) Ma, S. K.; Gruber, J.; Davis, C.; Newman, L.; Gray, D.; Wang, A.; Grate, J.; Huisman, G. W.; Sheldon, R. A. Green Chem. 2010, 12, 81. (5) Strohmeier, G. A.; Pichler, H.; May, O.; Gruber-Khadjawi, M. Chem. Rev. 2011, 111, 4141−4164. (6) Clouthier, C. M.; Pelletier, J. N. Chem. Soc. Rev. 2012, 41, 1585. (7) Kroutil, W.; Fischereder, E. M.; Fuchs, C. S.; Lechner, H.; Mutti, F. G.; Pressnitz, D.; Rajagopalan, A.; Sattler, J. H.; Simon, R. C.; Siirola, E. Org. Process Res. Dev. 2013, 17, 751−759. (8) Koszelewski, D.; Tauber, K.; Faber, K.; Kroutil, W. Trends Biotechnol. 2010, 28, 324−332. (9) Ward, J.; Wohlgemuth, R. Curr. Org. Chem. 2010, 14, 1914− 1927. (10) Savile, C. K.; Janey, J. M.; Mundorff, E. C.; Moore, J. C.; Tam, S.; Jarvis, W. R.; Colbeck, J. C.; Krebber, A.; Fleitz, F. J.; Brands, J.; Devine, P. N.; Huisman, G. W.; Hughes, G. J. Science 2010, 329, 305− 309. (11) Martin, A. R.; DiSanto, R.; Plotnikov, I.; Kamat, S.; Shonnard, D.; Pannuri, S. Biochem. Eng. J. 2007, 37, 246−255. (12) Truppo, M. D.; David Rozzell, J.; Turner, N. J. Org. Process Res. Dev. 2010, 14, 234−237. (13) Tufvesson, P.; Lima-ramos, J.; Jensen, J. S.; Al-haque, N.; Neto, W.; Woodley, J. M. Biotechnol. Bioeng. 2011, 108, 1479−1493. (14) Schell, U.; Wohlgemuth, R.; Ward, J. M. J. Mol. Catal. B: Enzym. 2009, 59, 279−285. (15) Cassimjee, K. E.; Branneby, C.; Abedi, V.; Wells, A.; Berglund, P. Chem. Commun. 2010, 46, 5569−5571. (16) Tufvesson, P.; Jensen, J. S.; Kroutil, W.; Woodley, J. M. Biotechnol. Bioeng. 2012, 109, 2159−2162. (17) Fesko, K.; Steiner, K.; Breinbauer, R.; Schwab, H.; Schürmann, M.; Strohmeier, G. A. J. Mol. Catal. B: Enzym. 2013, 96, 103−110. (18) Bornscheuer, U. T.; Huisman, G. W.; Kazlauskas, R. J.; Lutz, S.; Moore, J. C.; Robins, K. Engineering the third wave of biocatalysis. Nature 2012, 485, 185−194. (19) Tufvesson, P.; Lima-Ramos, J.; Haque, N.; Al; Gernaey, K. V.; Woodley, J. M. Org. Process Res. Dev. 2013, 17, 1233−1238. (20) Tufvesson, P.; Lima-Ramos, J.; Nordblad, M.; Woodley, J. M. Org. Process Res. Dev. 2011, 15, 266−274. (21) Peters, M. S.; Timmerhaus, K. D. Plant design and economics for chemical engineers, 4th ed.; McGraw-Hill: New York, 1991; p 910. H
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Article
(22) Meyer, H.-P.; Eichhorn, E.; Hanlon, S.; Lütz, S.; Schürmann, M.; Wohlgemuth, R.; Coppolecchia, R. Catal. Sci. Technol. 2012, 29−40. (23) Pollak, P.; Badrot, A.; Dach, R. Contract Pharma 2012, 14, 55− 66. (24) Lang, H. J. Chem. Eng. 1948, 55, 112. (25) Farid, S. S.; Washbrook, J.; Titchener-Hooker, N. J. Comput. Chem. Eng. 2007, 31, 1141−1158. (26) Villadsen, J.; Nielsen, J.; Lidén, G. Bioreaction Engineering Principles; 3rd ed.; Springer: New York, NY, 2011. (27) Rios-Solis, L.; Bayir, N.; Halim, M.; Du, C.; Ward, J. M.; Baganz, F.; Lye, G. J. Biochem. Eng. J. 2013, 73, 38−48. (28) Tufvesson, P.; Bach, C.; Woodley, J. M. Biotechnol. Bioeng. 2014, 111, 309−319. (29) Rehn, G.; Adlercreutz, P.; Grey, C. J. Biotechnol. 2014, 179, 50− 55. (30) Bareither, R.; Pollard, D. A review of advanced small-scale parallel bioreactor technology for accelerated process development: Current state and future need. Biotechnol. Prog. 2011, 27, 2−14. (31) Krühne, U.; Heintz, S.; Ringborg, R.; Rosinha, I. P.; Tufvesson, P.; Gernaey, K. V.; Woodley, J. M. Green Process Synth. 2014, 3, 23− 31.
I
DOI: 10.1021/acs.oprd.5b00100 Org. Process Res. Dev. XXXX, XXX, XXX−XXX