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I’m here to talk about this challenge to adapt the technical solution to face the growing demand for large volume of peptides. 

 
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Just a few words about PolyPeptide to start. 

 
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We are leading CDMO organisation focused on peptide manufacturing. 

 
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With more than 70 years of experience 1200 employees worldwide on 6 sites in Europe, US, India. 

 
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A strong development expertise as well as a long manufacturing experience for the manufacturing of around 1/3 of all commercial therapeutic peptides. 

 
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The main goal of this lecture is to talk about the evolution of the peptide market. 

 
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We have very strong impact of the current development pipeline, in particular the booming demand for the metabolic diseases generating very large-scale demand, much larger than what we had in the past. 

 
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And it's very important to look at the technology platform and see how to manage a scale up of the existing technology, easy existing technology compatible with this demand and how can we improve it in order to face this challenge, taking into account both the cost aspect, but also the sustainability considerations. 

 
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So the technology platform needs to evolve in order to be able to deliver both sustainable and cost-effective solution. 

 
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And I will introduce you to the different initiatives we have within the Polypeptide group to tackle this challenge. 

 
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So, I will divide my talk into three parts. 

 
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The first part is related to the scale up consideration. 

 
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How should we design the infrastructure and the manufacturing line in order to cope with this large scale demand? 

 
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And what are the technical constraints behind this? 

 
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The second point will focus much more on the sustainability consideration. 

 
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How do we ensure that we can propose a sustainable solution and how can we improve the environmental impact of our technology? 

 
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And as a Third Point, I will introduce something new today related to a research programme ongoing to improve the throughput of our SPPS reactor. 

 
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So let's start with the scale of consideration. 

 
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The key question is of course we need to get larger quantities. 

 
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So the first thing is to consider a very large reactor. 

 
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But is a large reactor size always the best solution? 

 
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There are also consideration to take and just like the example of Airbus with these A380s that was stopped few years ago. 

 
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It was a fantastic plane. 

 
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Probably some of you already took this plane. 

 
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It was very nice, very comfortable, but unfortunately they have to stop based on several considerations. 

 
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So technical constraints can reduce process throughput. 

 
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When you scale it up, at a certain scale you get some technical limitations that may at some point impact the linear evolution of your throughput and we need to take it into account. 

 
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The second key point is financial risk. 

 
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When you scale it up, the value of your batch in the reactor is becoming quite large and the financial impact of any failure may be quite critical for the process. 

 
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The third point is the flexibility. 

 
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Having a very large reactor is maybe good for a given application, but sometimes in term of manufacturing organisation, it can limit the flexibility of the process and could generate a risk in term of supply chain. 

 
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If a technical failure occurs, your reactor stops and everything stops. 

 
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So let's see how to consider this in in the design of the manufacturing lines. 

 
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If we specifically look to the solid phase reactor, let's look at the process rules in order to scale it up. 

 
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Typically when we consider a standard reactor, when we want to increase the capacity, we increase the volume of the reactor. 

 
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When we talk about solid phase chemistry, the situation is slightly different because we are using a resin which is soft and if you increase the volume and increase in particular the height of the resin inside the reactor, it can have a detrimental impact on the draining time. 

 
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And draining can take quite a significant time in particular when you increase the bed height, you may have some resin collapsing effects on soft gel that can be very can have a very strong impact on this time and can impact your process throughput. 

 
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So ideally speaking, if you look at the design of your SPPS reactor, the best solution, the ideal solution would be to keep the same height, whatever the size of the reactor, meaning that if you start with a small reactor and you increase it in term of scale, you should get something like this. 

 
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So that's the ideal consideration for the design of the circuit phase reactor. 

 
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If we look at this impact, if we start with, let's say the, typical shape of let's say a 100 litre reactor. 

 
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And when we scale it up, we see that very quickly the ideal reactor shape is becoming extremely flat and you reach a certain technical limitation in the design of your reactor to keep a linear scale up of your process, keeping the same performance all over the scale up. 

 
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So it's very important to take it into account in order to set, let's say, the optimal size of the reactor and avoid the technical constraint that may appear with a very large scale reactor. 

 
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So our approach to tackle this is instead of using single large scale manufacturing line, the strategy is to go more to a modular strategy and promote the use of, let's say, an optimal size of the assets in order to keep the performance. 

 
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But also getting the advantage of this multiple reactors in term of agility security. 

 
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If anything fails on one reactor, everything is not stopped in term of risk, lower value of product within each reactor and capacity management. 

 
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So the planning organisation for the production team is also easier with these type of things. 

 
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The last point is also very important time to implement when we have an increasing demand. 

 
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Using this modular approach allows us to adapt the capacity to the demand in the fastest way. 

 
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The goal is to design a module with a standard setup and to duplicate it in term of engineering cost and time. 

 
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It is far more efficient than designing a single line. 

 
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Also the engineering study is completed upfront and the lead time to get the reactor available is much shorter. 

 
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So let's move to the second point, sustainable solution. 

 
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It's a key challenge in the peptide manufacturing. 

 
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We know that the process mass intensity characteristics of our process are pretty large, and it is probably the major challenge we face with this large scale manufacturing demand. 

 
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Our green agenda is focused on 4 main points, reduction, recycle, replace and avoid. 

 
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And I will go through this agenda in in order to show where we stand today and what are the key achievements and the current situation in term of both development and manufacturing. 

 
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The first point is reduction. 

 
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Let's be very pragmatic and take the SPPS technology as it is today. 

 
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Our consideration was to look at the solvent consumption and where do we consume most of the solvent volume in an SPPS process, most of the volume is consumed during the washing steps between the coupling and the protection steps. 

 
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And we paid a lot of attention to revise the process and see how to reduce this volume keeping exactly the same performance, meaning we keep the same washing criteria. 

 
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The remaining amount of reagents in the reactor should be should be the same, but we just try to optimise the washing practises. 

 
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Typically with a steel reactor, in order to wash the resin, we tend to perform what is called batch washing. 

 
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We add a certain portion of solvent, we stir it, we drain, and we repeat it several time to reduce the the quantities of reactions in term of process engineering using a solid support. 

 
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So best way to wash a solid support would be to have a fixed bed approach. 

 
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While for the reaction we use a steel reactor. 

 
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So we have at some point we are constrained by the steel bed technology which is most likely the optimal solution for the coupling and the protection step. 

 
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While for the washing step we should have a fixed bed design. 

 
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So we try to look at the design of our steel bed reactor to see if we could apply a fixed bed strategy to wash the resin. 

 
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So we if we stop the stirrer, if we let the bed fixed in the reactor, can we perform a simple percolation wash in order to drain the reagent out of it with an efficient concept? 

 
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We made it first in silico. 

 
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You see some modelling, so computerised free dynamics modelling to design the system and from this concept we move to a pilot scale before implementing it at large scale. 

 
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The challenge is to do this plug flow stream on the resin and try to be as efficient as possible. 

 
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So the focus of this is not only to get an efficient solution, but also secure the robustness of the technology, which is key for GMP application. 

 
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Theoretically, it's quite easy to make percolation, but when you are using industrial reactor, it's very important to have a reliable solution that will be repetitive from batch to batch. 

 
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So the distribution of the fluid from the top needs to be very good, not to disturb the surface of the resin. 

 
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We need to clean also the wall of the of the reactor on the top. 

 
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And to do this, the best way we found is to use a discontinuous approach. 

 
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Meaning we feed the reactor in a discontinuous manner while the output stream is continuous and with let's say the optimal velocity to get a good mass transfer within the resin. 

 
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So this technology has been optimised quite intensively, first in the lab, in silico on the pilot scale before being deployed on our industrial assets today. 

 
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The benefit is summarised here. 

 
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Of course it depends on the peptide and can change a bit from peptide to peptide, but typically what we observe is at least 50% reduction of the solvent consumption compared to a batch washing. 

 
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The second point which is key is at the same time we managed to reduce the time for washing by more than 60%. 

 
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So you have not only a greener solution with a lower solvent consumption, but at the same time you reduce the time spent for washing, so you increase your throughput on the reactor. 

 
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This solution has been developed is routinely used on the group and the number for 2023 in the PolyPeptide group is that 84% of our SPPS capacity in manufacturing are using this percolation technology. 

 
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This generated more than 500 cubic metres of DMF saved within a year thanks to this technology. 

 
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Recycling is also a very important point to consider when scale up. 

 
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Recycling is already applied for our large-scale site in in in Belgium with acetonitrile used in the downstream area and more than 90% of our waste is recycled in this case. 

 
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The interest of recycling is of course to reduce the CO2 footprint and have a positive environmental impact compared to burning the solvent. 

 
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It also has a potential cost advantage; getting something cheaper than buying a fresh solvent. 

 
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And what is also key for this large-scale demand is the supply chain going for recycling reduce the pressure to buy a fresh solvent, which can be sometimes quite challenging. 

 
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The example of acetonitrile is pretty clear, we had a shortage back in 2009 I think. 

 
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So these types of things may happen. 

 
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And when we go for very large demand recycling is clearly a solution to consider. 

 
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So we are also working now on the development of DMF recycling for large scale manufacturing. 

 
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I would say two things are under consideration. 

 
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The first one is circular economy. 

 
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Can we find a way to use our waste DMF for other needs? 

 
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And the second one is recycling. 

 
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Can we use it back on the process with the challenge associated regarding the presence of formic acid, regarding nitrosamine? 

 
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So there are some process and analytical challenges in this aspect, but the proof of concept is done and it looks very promising for the design of the future manufacturing lines. 

 
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Third Point, replacement of DMF, it is a hot topic for the peptide community. 

 
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A lot of things have been made over the last years to replace DMF with greener solvent. 

 
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There are a lot of publications in this area. 

 
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And it's clear that the evolution goes for binary solvent mixtures, mainly DMSO Ethyl acetate and NBP ethyl acetate. 

 
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We were very active in this, several publications have been made in the past by PolyPeptide. in order to support this this research programme, the goal is to search for solvent alternative, which is as good as DMF and remains cost efficient as well. 

 
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The selection of the solvent is important. 

 
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It's important to look at the performance of the process with this green solvent. 

 
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A lot of publications compare the HPLC purity of the crude material obtained, which is quite important. 

 
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But it's also important to look much deeper on the side product specifically generated by this green solvent in order to ensure that we have a full control and understanding of the impact of this green solvent. 

 
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We are moving from, I would say DMF platform that was used over the last 2-3 decades to something new. 

 
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And it's very important to generate the experience and to secure the side impurities that we can have. 

 
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Another point when we scale up this green solvent is to consider other aspects. 

 
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Solubility is key, the solubility of the amino acid but also the solubility of the other reagents. 

 
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One key point that is known by the peptide chemist is related to the use of the coupling agent. 

 
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DIC, DIC is generating urea after the coupling. 

 
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This urea has a poor solubility in DMF, but the situation is even worse in the green solvent. 

 
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And when we intend to scale it up, it can be a really detrimental to the process. 

 
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So we worked on this and identified that TBEC which is known to be good in term of yield racemisation also HCN formation has a better solubility in DMF. 

 
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So urea of TBEC has a better solubility in DMF but also has a much better solubility in the green solvent. 

 
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This is a definitively an interesting option for the industrialization of the green solvent 

 
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Alternative technology, we have this partnership signed last year with Numaferm to look at biochemical production platform as an alternative to chemistry that can offer also some interest for specific sequences with natural amino acids. 

 
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But let me move now to the, the third Point, unlocking the SPPS throughput, because this is something new that I want to share with you today. 

 
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One of the challenges when we look at solid phase chemistry is when we want to scale it up, we can multiply the volume of the reactor. 

 
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But it is better to consider the throughput of a certain reactor volume and see if we can maximise the volumetric capacity of the reactor? 

 
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Can we produce more peptide within a certain reactor volume? 

 
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The capacity is driven by the resin capacity and the sweating of the resin at the end of the of the assembly. 

 
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So it's important to look at the how can we potentially maximise the volumetric capacity of the resin. 

 
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Instead of talking about millimole per gramme that we typically consider for the capacity of the resin, let's talk about millimole per millilitre. 

 
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Typically when we optimise the capacity of the resin for a certain peptide sequence. 

 
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We tend to increase the loading of the resin and increase the density of the reactive site on the resin in order to optimise the capacity. 

 
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So problem is that if you increase it too much you get steric hinderance that will disturb you. 

 
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One alternative that we have investigated is to work on the branching approach, meaning that instead of increasing the capacity by the density of the active site, we’re implementing some branching agents on the on the resin. 

 
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And with the first reaction of our peptide chemist was that it makes no sense. 

 
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You add some complexity on the resin, you will generate additional steric hinderance. 

 
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So it does not make sense. 

 
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Surprisingly, we got quite promising results. 

 
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Here is an example of a 15mer that I’ll share with you today. 

 
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We made also some examples with other peptide sequence up to 15mer. 

 
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Starting with 400 milligramme of resin. 

 
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You see the final weight of the protected peptide resin is growing from the initial resin with resin that has 2 branching, 4 branching, 8 branching. 

 
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What is quite interesting is the amount of crude that we get after cleavage moving from 200 milligramme to 500 milligramme. 

 
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It's quite obvious you have higher capacity, you produce more, but what is more surprising is the volume of the final protected peptide resin which is driving the size of your reactor. 

 
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We produce 2.5 times more, more or less, while the volume of the protected peptide resin remain is even decreased in this approach. 

 
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Meaning that if you look at the volumetric capacity of the reactor, you go from 30 gramme per litre to 95 gramme per litre, keeping more or less the same purity profile. 

 
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So it's early results, its the first time we’ve presented them, but it has a great potential to debottleneck the throughput of the SPPS reactor not only by increasing the volume or multiplying the reactor, but getting more peptide out of a certain reactor capacity. 

 
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The other point is that the solvent consumption is also reduced at the same time you have the same amount of resin and you consume yet less solvent based on this approach. 

 
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So to conclude, the process consideration is significantly impacted by this large-scale demand and modular design is for us the preferred option to answer this demand in a in a cost efficient way. 

 
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Sustainable solutions are available to reduce the solvent usage in the PolyPeptide group. 

 
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We reduce by 23.5% the relative solvent consumption, meaning the solvent per kilo of peptide produce in 2023 compared to last year. 

 
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DMF recycling is an option for the design of the large-scale manufacturing and greener solvents are becoming more and more involved in the development project. 

 
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We have now in 2023 around 12.5% of the development programme using green solvents. 

 
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And this branching SPPS regime offers a new technology platform that could help to unlock the capacity of peptide manufacturing. 

 
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So I would like to thank you, and I would like to thank my team involved on this programme within the PolyPeptide group.