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LCA-based environmental performance comparison of batch and continuous processing: A case of 4-D-Erythronolactone synthesis Cher Kian LEE, Hsien Hui KHOO, and Reginald B. H.TAN Org. Process Res. Dev., Just Accepted Manuscript • DOI: 10.1021/acs.oprd.6b00275 • Publication Date (Web): 18 Oct 2016 Downloaded from http://pubs.acs.org on October 19, 2016

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Organic Process Research & Development

LCA-based environmental performance comparison of batch and continuous processing: A case of 4-DErythronolactone synthesis Cher Kian LEE*,‡, Hsien Hui KHOO†, Reginald, Beng Hee TAN‡ ‡

Department of Chemical and Biomolecular Engineering, Faculty of Engineering, National

University of Singapore, 4 Engineering Drive 4, Singapore 117576 †

Process Science and Modelling, Institute of Chemical Engineering Sciences, 1 Pesek Road,

Jurong Island, Singapore 627833

1 ACS Paragon Plus Environment


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TABLE OF CONTENTS GRAPHIC


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KEYWORDS Life cycle assessment, LCA, batch and continuous processing, primary pharmaceutical manufacturing, production campaign. ABSTRACT Continuous processing, as a form of process intensification, is one of the keys of green engineering research and development in the pharmaceutical industry. It has the potential to reduce solvent use and cost of production as well as increase production quality and operational safety. In light of the increased research interest surrounding continuous processing, the goal of this work is to compare the environmental performances of batch (BP) and continuous (CP) processing of 4-D-Erythronolactone (4-DEL) at pilot plant scale as case study. The processing systems are evaluated using green chemistry metrics and a cradle-to-gate life cycle assessment (LCA). The processing serves as the case study for this article’s goal. The LCA system boundary includes raw material extraction, transportation, synthesis of 4-DEL (as part of primary pharmaceutical manufacturing), equipment cleaning, plant utilities and off-site waste management. In order to obtain life cycle inventories to support the LCA study of the BP and CP systems, a modular approach is taken to address their differences. As part of a modular approach, theoretical production campaigns are constructed for the production scale of 49.6 kg 4-DEL within 5 days, the campaigns account for the time-bounded activities which affects the overall rate of production. The analysis shows that, under the assumptions used, using continuous processing for 4-DEL production has a lower environmental burden compared to batch mainly due to less equipment cleaning and a smaller plant footprint. This is reflected in a 30.1% lower cumulative mass intensity and reductions of various life cycle impacts such as global warming potential (-57.5%), human toxicity (-9.37%) and water depletion index (-41.7%). Sensitivity



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analysis on equipment cleaning and the consideration of various end-of-life waste treatment options illustrates the need to include them in the system boundary for a fair comparison between batch and continuous.


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1. Introduction Traditionally, the pharmaceutical industry has manufactured its products mostly by batch processing (BP) involving sequential and distinct unit operations. However, there has been an increased interest in continuous processing (CP). The Pharmaceutical Roundtable, which was founded by the American Chemical Society (ACS), Green Chemical Institute (GCI) and several pharmaceutical companies, voted CP as the top research area of green engineering1 as part of the goal to increase the use of green chemistry2, 3 and green engineering4 in the pharmaceutical industry5-13. While CP presents a range of advantages, cost and waste reduction, safety, chemical and process operability were amongst the stronger drivers1, 14, 15. CP can also offer flexibility, faster time-to-market, lower supply chain inventory and higher overall equipment effectiveness (OEE, i.e. the fraction of time when the equipment is actually processing material)12, 13, 16. The typical OEE in the pharmaceutical industry is 30%13. In the pursuit of sustainable engineering, the Pharmaceutical Roundtable has adopted the Process Mass Intensity (PMI) as a green metric to serve as an industry benchmark that emphasizes the optimal use of material inputs and also developed a PMI calculator with the aim of having a standardized methodology to calculate PMI industry-wide17, 18. Along with CP, the application of life cycle assessment (LCA) is also identified as a research area to evaluate green engineering practices by the Pharmaceutical Roundtable. The LCA methodology is internationally recognized as a system-wide approach to quantify the potential environmental impacts of products or processes and to identify opportunities for improving environmental performances throughout its supply chain elements (e.g.extraction of raw materials, transportation, production, usage and disposal)19-22. Depending on the goal and scope, life cycle impacts can be evaluated at different system boundaries. A life cycle inventory (LCI)



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accounts the resource and material consumption as well as emissions to the environment for each life cycle stage. It is typically followed by a life cycle impact assessment (LCIA) which can measure specific midpoint impact such as global warming potential. Although LCA have been used in the pharmaceutical industry, only a few case studies have applied LCA to compare the use of batch and continuous processing23-35. Ott et al. highlighted the tradeoffs in switching from batch to continuous manufacturing in the production of a low-volume, high-value API at Sanofi 27

. The authors explained that although continuous operation required more solvent and higher

energy input, the increase in yield along with a change in catalyst lessened the overall environmental impact compared to the existing technology. The work by De Soete et al. and and Van der Vorst et al. demonstrated a decrease in overall resource consumption by switching from batch to continuous processing of an analgesic and anti-Alzheimer drug respectively28, 34. Comparing the BP and CP methods can be challenging from an LCA perspective; the differences between the processing stages involved need to be addressed in order to construct a robust LCA model for justifiable comparison. For instance, the adoption of CP potentially results in smaller equipment size (and hence, a smaller plant footprint) as well as less cleaning1. It would also require the inclusion of startup/shutdown procedures. Given that most CP development are still in the lab- and pilot-scale while BP has been commercialized for decades, scale-up and learning effects need to be accounted for36. Such effects have been addressed using power-law relationships to predict fuel consumption in energy conversion equipment, wind power electricity generation and exergetic resource consumption for the secondary drug manufacturing of PREZISTA®25, 37, 38. Alternatively, the LCA comparison can be carried out at the similar production scale as exemplified by Van der Vorst et al.34. It is also important to consider waste treatment as different manufacturing technologies produces waste streams of


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differing amount and composition which affect the choice of waste treatment (e.g. incineration, wastewater treatment and solvent recovery) and the extent of environmental impacts27, 34, 39. Lastly, the comparison between BP and CP entails two delivery systems of a product rather than the product itself. Hence, the functional unit (FU) of both delivery systems should define the same amount of product as well as the time required to produce it (i.e. production lead time). The objective of this paper is to compare the environmental performance between BP and CP using a time-bounded production campaign for the synthesis of 4-D-Erythronolactone (4-DEL) as a case study. The comparison takes into account differences in equipment size (and hence occupied floor space) and the extent of equipment cleaning, CP startup/shutdown procedures, the production lead time and waste treatment. Scale-up and learning effects are either absence or negligible, and hence not accounted for, as the same type of equipment is used for both BP and CP. 4-DEL, a pharmaceutical intermediate, was synthesized at the pilot plant in the Institute of Chemical Engineering Sciences (ICES), Singapore in the effort to demonstrate the conversion of an existing batch process to a continuous process design11. The synthesis begins with Disoascorbic acid (DIAA) as the primary raw material. DIAA undergoes three chemical transformation steps to form 4-DEL as shown in Figure 1. It is then followed by a concentration step which remove excess water from the reaction mixture to obtain a final 4-DEL concentration of 12.8 %wt. More details about the process can be found in the Supporting Information. The BP and CP primary manufacturing systems are evaluated using green metrics and a cradle-togate (CtG) LCA.



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Figure 1. 4-DEL synthesis scheme comprising 3 chemical reactions: salt formation [1 to 2], oxidation [2 to 3] and cyclisation [3 to 4]11.

2. Methodology Green metrics and LCA are adopted to compare the potential environmental performances of BP and CP systems quantitatively. Simplified metrics provide a quick estimation on the “greenness” of the product/process while LCA is able to provide a more holistic assessment of the systems under investigation. A modular approach, described in Section 3.3, is applied to aid in constructing the LCA model. Central to the approach is a module herein termed the production campaign module (PCM) that generates hypothetical time-bounded production campaigns for both BP and CP. 2.1. Green metrics This paper uses PMI (eq 1) as it is the pharmaceutical industrial benchmark as a green metric. PMI is defined as the mass of materials used to synthesize a product. It includes reactants, reagents, solvents and water. Given its simplicity, PMI can be easily measured from most forms of production records. The pharmaceutical industry uses highly purified water which results in


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higher life cycle impacts than the process water used in the petrochemical and bulk chemical industries. Since water is used as the solvent in this case study, this places solvent intensity (eq 2) (also known as PMI Solvents in the PMI Calculator) as another important metric for comparison. Beyond the synthesis steps, wash mass intensity (eq 3) provides the mass contributions for cleaning activities and supplier mass intensity (eq 4) accounts for mass intensities of the processes involved in supplying raw materials required for both BP and CP. The last metric, supplier mass intensity, is in line with “driving more efficient and sustainable practices throughout the supply chain”17. An industry-wide study showed that pharmaceuticals have a median PMI of 120 with water and solvent contributing 77% of PMI40. =

() ()

! = $%ℎ '% ! =

"# () ()

## () ()

()) * '% ! = ∑(' ) − ∑ '

(1) (2) (3) (4)

2.2. LCA investigations 2.2.1. System boundaries and functional unit In order to quantify potential life cycle impacts of the BP and CP systems, a CtG boundary is chosen which includes all upstream manufacturing, transportation to the processing site and ends with 4-DEL production with a smaller gate-to-gate (GtG) pilot plant boundary. The latter encompasses 4-DEL synthesis, equipment cleaning and the usage of indirect plant utilities such as air conditioning and ventilation (HVAC) and lighting. The comparison also considers off-site waste management. The contributions from the manufacture of capital equipment are not within the scope of the LCA system boundary.



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To ensure a reasonable and justifiable LCA, the functional unit is defined as the capacity to produce a reaction mixture containing 49.6 kg of 4-DEL within 5 days. The final crude mixture of 4-DEL has a concentration of 12.8 %wt and is prepared for purification downstream. This definition comprises both the product (amount and purity) and processing capacity (time constraint) aspects of the BP and CP systems. More details about the production campaign are given in the following section. 2.3. Modular Approach and Production Campaign The modular approach which consists of 7 modules is used for inventory analysis of the various parts of the supply chain. The process module translates experimental records and literature data11 into GtG LCI data relating directly to the 4-step synthesis of the 4-DEL crude intermediate for both the BP and CP systems. While experimental records, provided most of the GtG LCI, data gaps such as gaseous emissions and energy estimates were addressed using MATLAB process simulation and theoretical power consumption. Unavailable information was supplemented by personal communication with the pilot plant scientists and engineers (Table SI11). The GtG LCI associated with cleaning is generated using the wash module. It is mainly based on the guidelines from the pilot plant and a 5-step cleaning procedure provided in the experimental records as solvent and energy use for cleaning were not measured. The procedure begins with line washing, followed by gross decontamination, aqueous boil-up, solvent cleaning and ends with inspection. There are two types of cleaning – full wash and repeat wash. Based on existing practices at the pilot plant, a full wash is done prior to any usage of equipment while repeat wash is done in between batches. A summary of data used in the wash module is shown in Table SI-1. Similar to the process module, energy use for the wash module is estimated using theoretical power consumption. In addition to GtG LCI data, the process and wash module also


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determines the production of 4-DEL per batch run (PBP,run), the rate of production of 4-DEL for CP (P- CP,ss ), the small fixed amount of 4-DEL produced during shut down (PCP,sd) as well as the durations for each batch run (tBP,run), start-up (tCP,su), shutdown (tCP,sd) repeat wash (tBP,rw) and full wash (tBP,fw and tCP,fw) which are required as inputs for the production campaign module (PCM). The hypothetical production campaigns are constructed using the PCM. The outputs of the module are the following: •

For both BP and CP systems: the schedule of the campaign, the number of setups (nBP,setup, nCP,setup), full washes (nBP,fw, nCP,fw) and the actual duration of the campaign (tBP,cam, tCP,cam). A setup is defined as a set of equipment that can independently process in either batch or continuous. For instance, a BP system with 2 setups produces 4-DEL with two batch reactors in parallel.

•

For BP system only: the number of batch runs (nBP,run) and repeat washes (nBP,rw). Repeat washes are conducted after a number of batch run to meet cleaning standards.

•

For CP system only: the required duration of the steady state operation (tCP,ss,req).

Figures 2 and 3 illustrate the relationships between the functional unit, system boundaries, the PCM, the process and wash modules. Due to the time constraint established by the functional unit, nBP,setup is calculated by taking the ratio of cumulative duration of batch runs and washes over the campaign time constraint (Tcam) (eq 5). nBP,run is calculated by dividing the quantity of the final product as defined by the functional (D) by PBP,run (eq 6). A modelling parameter nwashcycle describes the frequency of washes and is used to determine the number of washes in the BP system, nBP,wash (eq 7). For instance, nwashcycle = 1 implies that there is a repeat wash after every batch run. A value less than 1 indicates a repeat wash is carried out every few runs while a value greater than 1 indicates that multiple washes are required after every batch run. From the



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experiments conducted by Wong et al., a single repeat wash was sufficient in between batch runs (nwashcycle = 1)11. With nBP,wash, the number of full and repeat washes can then be calculated (eq 8). The batch campaign duration, tBP,cam, is assumed to be equal to the duration of the longest operating batch setup. This assumption is based on a simplified hypothetical production campaign in which all the equivalent batch setups are utilized to produce a single product (4DEL) without operational constraints such as storage capacity and manpower schedules. nBP,setup=roundup 1T

A

5

cam 3B

(5a)

A = nBP,run tBP,run + nBP,wash tBP,rw

(5b)

B = (tBP,fw − tBP,rw ) · roundup(nwashcycle )

(5c)

67,# =roundup 9P

D

BP,run

;

(6)

67, < = *(=()>67,# ×

Life Cyle Assessment Based Environmental ... - ACS Publications

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