Mettler-Toledo International Inc. (MTD) Earnings Call Transcript & Summary

Hello, everyone, and welcome to today's Chemical Process Research and Development Online seminar. I am Jennifer Allen, a principal technology and applications consultant at Mettler-Toledo based here in the U.S. I'm very excited about today's talk and would like to thank you and the presenters for your participation in today's event. A little bit of housekeeping before we get started. Please submit your questions via the question-and-answer chat function. That's a little Q&A there on the team's bar. We will address them in the order in which they come in. Any questions that aren't addressed in today's session will be given to the presenter and answer directly after the event. Our first presentation today is from Dr. Matthias Balsam -- Dr. Matthias's main fields are online spectroscopy and chemical development of APIs in pharma and chemical processes, AI as well as seeds in crop science. He has been employed at Bayer since 2018. He also teaches online analytic lectures at the University of Applied Science in Fresenius. He received his PhD at the University of Applied Science in Cologne, Germany in the field of PhD. Matthias also has a Master's degree in analytical and bioanalytical chemistry at the University of Applied Science Fresenius. It's my pleasure to welcome Dr. Balsam. And Dr. Balsam, I'll turn it over to you.

Hello, everyone. Welcome to my presentation. Bayer's approach to bring spectroscopy from the lab into the process. My name is Matthias Balsam. I'm working for Bayer in the global PAT group. And today, I show you example of our work for the pharmaceutical division in [ Pupatel ] and the API development. Let's have a look onto the -- our agenda for today. First, I'll start with the PAT concept in the early-stage and late-stage API development in the pharmaceutical industry. After that, I will show you 3 different PAT examples started by middle infrared for an amidation. After that, I'll show you a Raman for crystallization and at the end, I show the whole new infrared concept with an example from distillation process. And at the end, we got the benefit of PAT. So way from a chemical substances to pharmaceutical product is quite long. We took here from roughly 15 to 16 years from the first idea to the final product. In general, we can divide that whole process into 4 major parts; the foils part is the drug discovery, of Mettler. We have screened a lot of substances and only a few of them come to the next stage, the so-called chemical process or chemical development. We will have a closer look to chemical development in a few seconds. The next part is the submission where all the regulatory documents are submitted and approved from the FDA or from the EMA or other regulatories. And of course, the last steps of production. We, SPG Group and the work I will show today is focused on chemical development. So chemical development can be also divided into 2 parts: early-stage process research and late-stage process development. Let's have a look into early stage. The task of the process research is to find the synthetic route and start to optimize the synthetic route. But it has also the goal to make a fast API supply because we want to support preclinical studies in Phase I studies with API. Therefore, we need material only a limited amount of material, but we need material, and that material has to be supplied quite fast and in a good quality and has to be safe. Let's look on the PAT challenges we have during early stage. So in early stage, we have quite small volumes only a few milliliter up to 100 milliliters of reactors. So a low -- really low volume could be quite challenging, but general normal volume like 100 milliliter after 1 liter is, yes, more or less easy to implement, but there are the conditions in conditions we have here. Furthermore, we have no ATEX regulatories on only limited ATEX regulatories in the laboratory environment, and our reactors are flexible. And for the reactors, we have often non-GMP regulatory. So if you want to change something, we do not have to make a change request or something like that. We are -- they're more flexible, and we have no process control. So everything we bring into the process that get our new information could be helped to find information about the process. And from the measurement, we have the challenge, our first shot will be in a blind flight because that's the first time we go with a probe into the process. So we do not know anything. How the spectrum looks if the message is the right one and so on. Also, our reference analysis is quite limited because the reference analytics like an HPLC or GC is still under development. Our evaluation will be, yes, always ratio perspective. So we make a batch to batch evaluation, and we have a high number of batches. A few , yes, to 100 -- up to 100 batches to optimize the synthetic route. And of course, in all batches there are changes in the conditions because we're under development. What can PAT achieve during early stage because we are in the process. We have a fast response. We don't have to wait for reference analogies. We can make decisions based on our datas. By that, we can increase efficiency and reduce trails because we can make decision faster and don't need that much try and error trails. We start to understand our process derived from the beginning. And by that, we can be fast and the scale up as a message transfer. Let's see the late-stage process development. In the late stage, we have the task to find the final production route. So the production route how it is later in the -- for the normal production routine reduction. Therefore, we will deliver high-quality APIs for later clinical Phase II and Phase III studies and sometimes also small volumes for the market supply. The focus here is not all about speed, but to have a process that is high, stable. So that's a process then also able to submit later on and of course, with good quality and low cost. For the basic technical conditions, we are now talking about large volume under up to 1,000 liters or more. We are in an arctic environment so that makes it more complicated to bring a probe or an instrument in that environment. We are here totally in GMP production. So if you want to change something in your reactor vessels, that could be quite challenges. Therefore, for our concept we used bypass systems that makes it more easier. You will see that in a minute. But also here, we have low information during the process. And we have, of course, developed Atlan Analytics that is used for release, but also the PAT could be really useful for that process scale-up. The measurement challenge is that we have online evaluation. We need so an evaluation model. When we are at that stage of the process development, we don't have the time and possibility to develop a PAT model or PAT method. At that stage, our PAT has to be already quite close to -- and yes. So if you are here, you have to be sure that the message you use is correct and that the model is already developed and perfectly would be to have a direct evaluation on the process control system and see is the values so that the operator already see how the process is running. And the early stage we had a high number of batches. Here, we only have a few batches scale up and the late stage has only batches roughly under 10, but are already well developed. And of course, as I already mentioned, we have basic information by Atlan process status, and that is all ready and reference analytics for release or just for in process control. The part achievement at that state is to confirm the process understanding and show just a developed process was and the scale-up was successful. And by that, it means that we also increase our efficiency. And all over that, we have a smarter process development. Coming to the spectroscopy method that we use. So we use, RAMAN often for crystallization to show the polymer of the crystallization. But also, we use RAMAN for reaction monitoring and look for [ Ident ] byproducts and products. And that is often evaluated by a simple peak tracking and iodine method univariate collaboration. Furthermore, of course, middle infrared, also that is used for reaction monitoring for [ Ident ] products and byproducts. And the evaluation is often done by peak tracking also hard modeling and univariate or sometimes multivariate calibration. Also middle infrared to use that in the gas phase also for a reaction. And then often for the byproducts and the byproducts can indicate the states of direction. And for that, we often use peak tracking or just a simple iodine method. And new infrared that has a totally different approach. The new infrareds are often used for distillation, audio filtration and only in rare cases, we use that for reaction monitoring and the evaluation is always this multivariate calibration, which has a high effort we could see that as also in a minute. Here, you can see our 3 devices we currently use in chemical development at Bayer. That is our middle infrared. It's MATLAB system. It's an ATEX version from MATLAB. We -- it's engineering to make the spectrometer more mobile so that we can use it in different reactor vessels. Then we have a RAMAN system from another supplier, which we introduced in an ATEX box and also make that mobile. And we have a near infrared system, which was also from another company where they sell it as a system like you see in the picture here. How does that looks in the process? So as mentioned before, and the process development with the higher amount of vessels we use a bypass. That was more easy to implement because the bypass already exist for sampling. And what we did, we designed different types of bypass vessels where we could introduce 1 or more than 1 probe and pump the solution through our bypass. And here, you see the middle infrared spectrometer direct close to the reactor, the light fiber of the probe for in general or in general, 4 meters. That is the maximum distance you could -- or you can achieve for that instruments. Yes, as mentioned, it's a thoroughly assessment as assembly so that you are mobile, you have here your spectrometer, which is -- again writer -- to have -- obviously have a process computer and a small gaming that we are working on is a remote control via Wi-Fi. So all this area is, of course, ATEX, but it's also cleaning area. So with Wi-Fi and remote control, we could or can support SPT Group, the operator from outside and don't have to go into the cleaning area. Let's now come to the 3 examples, the amidation to crystallization and the distillation. Here, we see the reaction of an intermediate step of the amidation with [ Pteroic acid ] that was monitored this middle infrared as the pilot plant process. The method and ph was more or less in peak tracking, which is done by the reactor a software for MATLAB, and that is a really quite a simple to use peak tracking method, that was already tested and developed during the lab and then used in the scale-up in the pilot plant. Here you see our primary mean that has a peak that is easily to detect. And by the reaction of [ sulfur pteroic acid, ] we get a secondary [ amine ] and that has shown a peak shift and these peak shifts can be detected. Here, we see the result of the signal from the primary [ amine ] I mean, which decreased and we have the secondary [ amine ] which increased. And by that, we could also have some findings during the scale up, we could show that the reaction was much faster in the larger scale than the lab trials. We have here a post steering time or steering time that was overestimated because the reaction was already finished quite faster. Coming to the crystallization that was analyzed by Raman. Actually, that is the same reaction or same product and test we had seen for middle infrared. Here is our secondary aiming and the crystallization was the step after that, and that was in the different vessel direct by side of the reactor you have seen on the picture before. The crystallization can take place and has 2 different polymeric forms and the polymeric forms, pattern 1 and pattern 2 can be detected. [ Gova ] to have a crystallization, only pattern 2 accrues and Pattern 1 does not accrue. Sequestration was developed in the laboratory of course. And we have to show that the scale up has the same effect so that no pattern 2 accrual. For that we could show there was no pattern 1, but we could also show that there was different to the laboratory. So if you see here, that was a seeding point developed from the laboratory. But the crystallization started already 45 minutes before the seeding. The crystallization actually started doing the -- there was a dosing of water. And during that time, the crystallization already started. And we could also show that crystallization was completed. So in general, the scale up worked quite well, but was different to the laboratory. So let's come to near infrared. Near infrared is a little bit different in the story. And therefore, I would like to show the user general workflow of near infrared development. And by near infrared always starts that we make a small visibility. We get substance from one of our research labs with reference substances, and we have a look into the material and make a small calibration, which is more or less only univariate. When that works, that we will also get free of process samples and see, okay, that we can detect these seeds also in the process sample. When that works, we start to make a lab modeling. So we get references and make a design of an experiment and make a calibration, which is a multivariate calibration. When this lab modeling is complete, we start to make a small-scale feasibility or we used our near infrared probe and the model direct in line and see if that is suitable. If it's suitable, we say, okay, we can go into the process, which is maybe other lab where they develop and develop the processes, the distillation for example, also first trials in the pilot plant and so on. And we use that process metal and from the PAT group, we always start to see and evaluate the model. Do we need further improvement if we need further improves, we go always a step back -- add more spectrum based on inline spectra and reference analytics. And so we have a development of the model. And by each step, we make a model verification. If that model works, we are fine. If we see there's a space to improve, we improve it and start the circle again. And so we come from the laboratory from a small vessel to the larger scale and have always a model in hand that can be used. And then we have to decide do we -- do we need any -- near infrared for later process control? Or was it just useful for the development? It is just useful for the development, of course, we -- you know -- not further, but if we have the transfer to one of our normal plans and the process units say, okay, we want to have the near infrared information also doing routine -- routine production, then we can transfer the model into routine production, of course, then also evaluate the model and see if it's worked or do we need further process spectra and then have, of course, a life cycle and continuous model evaluation, doing routine production. And here, I have 1 example where we used our first developed lab model that was then transfer in the pilot plant as a small pilot plant or technical lab, and where we could prove that our lab model worked quite well also for the technical plant and that actually that model will be also transfer into routine production. -- and for us to measure DMSO and water. The green dots are the analytical values and the blue numbers are our online values. And you see the online spectrums, our online results looks really nice and we were able to use that in process for monitoring and we'll use that in later for process control. So at last, I would like to say something about the benefits of PAT in chemical development. It's all about datas. If you have datas you can use these datas to make a faster overall development because your decision you make are based on -- on datas on spectras and results and so on. Furthermore, these datas and PAT can -- such as fast and up the process development, it could also -- can also reduce your risk because you already know what are you doing and if you make the scale up, you are really in a good shape because you have a lot of information about your process. Has that reduced your technology risk and so on? And that comes together with datas. The PAT measurement, so the online monitoring enables you to make real-time evaluation and real-time decisions during the development and that enables you to also to reduce numbers of trades and so on. And that is also a benefit in an early-stage development. And you -- of course, you will need always Atlan analytics like the HPLC and GCs, but in a stage like early-stage development where you do not have a suitable HPCL as so far, you can already work on your process because you may have a good in line or online measurement method that brings you so much information that you can already develop your process, even if there is no one headline available at that point. So I hope I could introduce you into the work that we are doing at Bayer, and I hope you like to my presentation. If you give us any further questions, write it into the chat or please contact me by my e-mail address, [email protected]. So thank you very much.

Thank you, Matthias for your excellent presentation. I see say that we do have a number of questions. So we'll just quickly go through these. Matthias, can you see them? Or would you like for me to give them to you -- read them out to you.

I can see them, I think, yes. So the first question is, I think, from David, at what volume does your ATEX requirement starts? So we start with ATEX when we are not in the lab anymore in the mini plant laboratories. So there, we have volumes in the flask from roughly 1 liter to up to 100 liters and normal mini-plant, there would be roughly 10 liters, I would say and that is all ATEX. So in one. Second question is from Frank. Why did you decide not to put the ReactIR probe directly into the 250-liter vessels? I think there several reasons why to do so. And most simply answer on that is just because there was no free port to introduce the probe into it. And that is something you often find if you make a project on reactors that are already on existent environment, yes. So the older instruments that you do not have any free ports but also the port lengths of a problem or the steering of the reactor or DRAM or reactor. Third question, why do you think the reaction was so much faster at large scale than in the lab scale? So you always have effects during scale-up that the geometrical effects of a smaller laboratory equipment and the bigger equipment is different. You try to reduce it as much as possible. It has the same stereotype and so on. But these effects often occur and that is a nice thing about PAT because -- actually, you can see it during the scale-up phase. And maybe in the past, you was just seeing the end product and never knew about that effect. So let me see what was the next question? From Jonas, is there a one-to-one relation between the left middle infrared model and the data you see from the pilot plant? Or do you have to adapt the lab model slightly? I think for middle infrared, model or -- model transfer is not that critical compared to near infrared transfer. And we do not have to make big changes in the model. First of all, we used more or less the same instrument in the laboratory than in the process. That is also the same with the RAMAN and the infrared. And we try to use for middle infrared and for the infrared FT instruments. So the transfer of the model with FT normally works quite well. Let me see. The next question comes from Thomas. Can you explain on -- why you -- and your colleague feels, the crystallization starts 55 minutes before seeding? -- is there some relation to the water addition? Did you observe anything like this in the lab study? I think we have more or less the same question before. Yes, I think it's come from the water seeding -- from the water that the water dosing probably induce the crystallization, yes. And no, we did not see something like that in the laboratory. Can you explain why you choose near infrared over middle infrared for the distillation application? Yes, that is a really good question. I think on the slide with total approach of near infrared. You saw that near infrared is always quite challenging to make a model and to develop the model about the whole life cycle of the development. And that is a really big effort. But at the end, that effort is good because near infrared for process like distillation, it's much easier to introduce later in the field. It's a cheaper instrument and cheaper measurement. But furthermore, you can put several light fibers over a few meters up to 100 meters from your device to the column of your distillation that is not really possible within the middle infrared and to bring in -- you have seen the picture of how big an ATEX version of the middle infrared is -- bring that over a whole column a few times would be not suitable and quite expensive. So if there is a chance to use near infrared and you want to introduce near infrared later on in production that would be much cheaper and easier to install an engineer. Is there a validation procedure to follow that for each PAT implementation? The measurements you have seen here was doing development phase. Of course, these are not validated because the process is already -- is under development. So a validation would be something we need later for the routine production. These are information-only measurements for the development and not for release. So for that, we have not a validation. But of course, if we use measurements later for in process control and also for yes -- in process control offer release, we do have procedures for PAT equipment, how it is to validate. Looking for near infrareds, that is also why we have all these steps to make a life cycle from the model and use our data already with a high value doing development for later to make a faster validation because near infrared validation would be also quite challenging and took a long time, yes.

Okay. Excellent. Well, Matthias, I think there are a few other questions that I think we probably should get on to our next presentation. So we will get these questions to you, and you can certainly reach out to these people after the presentation. Again, thank you so much for your wonderful presentation. Our next presenter is Benjamin Kordes. He studied chemistry at the University of Stuttgart with a focus on polymer chemistry. And he joined a Wacker Chemie at the end of 2019 to conduct his PhD in cooperation with the University of Bayreuth. So I will now turn it over to Benjamin, and we look forward to your excellent presentation.

Hello, ladies and gentlemen, thank you very much for inviting me to this event. My name is Benjamin Kordes. I'm a PG student, my thesis, which I'm doing at Wacker Chemie AG is dealing with biodegradable polymers. Today, I would like to tell you something about my latest publication. In this study, I was able to make many useful kinetic measurements using the ReactIR and Raman, at first to the basics of my research. Starting point of my research is MDO. What is MDO? MDO Is the molecule drawn on the left side at the top, it's a monomer, in a free-radical polymerization and ester group is incorporated into the backbone of the polymer. The copolymers, for example, polyvinyl acetate with MDO are then hydrologically cleavable. I have illustrated this as a [indiscernible] symbol. So you get a biodegradable polymer. In the first step, you have a copolymer consisting of the main chain incorporated MDO units, here marked by the blue dots. In the first step, there's a hydrolysis. This first process is extracellular so without microorganisms, but purely chemically and physically induced. Thereby, the MDO affected sites are cleaved. If this results in fragments that are most between 0.5 and 1.5 kilogram per ml in size, they are small enough to be taken up by microorganisms through the cell membrane and plus to be degradated to water, carbon dioxide and biomass in the next step. This is the way of research process. There's already a lot of [indiscernible] for solution [indiscernible] of MDO and other [indiscernible] . So what is the problem? The problem was already recognized by the discovers of [indiscernible] in 1948. MDO is highly susceptible to hydrolysis. If milestone polymerization occurs, for the most part, it is not just polymerization that occurs but hydrolysis. These 2 structures look very similar. But in the upper case, you has a biodegradable polymer, but in a lower case, you has a low molecular weight compound. Without a double bond, this compound is used as in radical polymerization, already in the past, they assessed indications that the hydrolysis depends on the pH value. The slower hydrolysis in alkaline conditions. We therefore wanted to perform a precise hydrolysis study to investigate the process of hydrolysis as a function of pH and temperature. Once in aqua solution and once in emulsion. The aim was to find out whether there is a certain optimal conditions in which emulsion polymerization with MDO is possible. In this process, we faced a number of problems. MDO does not dissolve very well in water. You can see a picture of an [indiscernible] salted water into which I put the drop of MDO. You can see the nonstability. So initially the hydrolysis takes place only at a phase interface. But if you mix the 2 substances very well together, as it happens in emulsion polymerization, then even under the smooth conditions of pH7 at 40 degree Celsius, you can see how very fast exothermic reaction takes place. We're talking about seconds. Within 25 seconds, your entire MDO was gone and there a sharp temperature rise occurs. You must avoid the strong temperature rise for precise kinetic measurements, think of [indiscernible]. At the beginning, we therefore first performed [indiscernible] kinetic measurements. As you have already seen MDO does not mix with water. And once [indiscernible], you cannot achieve mixing by shaking it. So we have been looking for solvent to combine the MDO with the water in one single phase. We have tested through many solvents and mixing ratios. The solvent must be strongly pull out to combine both substances, but should not affect the pH so you cannot take protein for example. But it should also be [indiscernible] MDO also reacts with alkyls and carboxylic acids. That's why we decided to use ethylene carbonate, EC for short. These experiments worked very well. In contrast to MDO water mixtures, the dilution of the [indiscernible] with easy slows down, hydrolysis kinetics so much, so you can record good kinetics. Here, you see the overlap of several spectra each measured in a 10-minute interval. You can see nicely how the signals of MDO, Alpha decrease and the signals of the hydrolysis product Bravo and Charlie increase. You can then evaluate the spectra and obtain conversions as a time plots. On the left, hydrolysis is spotted as a function of temperature and on the right, as a function of pH. As temperature increases, the rate of hydrolysis increases, not surprisingly, and as pH decreases, the right of hydrolysis increases. This is also not surprising at first, but possibly points to protein catalysis mechanism. In fact, however, we did manage to make some rather surprising observations. When we played around a bit, we observed that the MDO was added a second time to a mixture that was already fully reacted. Hydrolysis was much faster. This was unexpected for us at first. We have the same effect shown on the right, and you already had some of the hydrolysis product for HBA at the beginning. Now this observation is not just an academic curiosity but has a direct bacterial consequence. The point after all, is to evaluate whether MDO is suitable for emulsion polymerization. In emulsion polymerization, at least those that are carried out on a larger scale, the monomers are usually added continuously. Fresh MDO would then encounter already erected MDO so that hydrolysis will become faster and faster overtime. This is a clear argument against the use of MDO in emulsion polymerization. We had already noted a pH dependence of hydrolysis. Due to the last dilution, water in excess, we can therefore assume [indiscernible] reaction. At the same time, we have autocatalytic behavior here. Autocatalysis is also always associated with a slower and catalyst reaction because you do need some initial product to get to autocatalysis. We had found that the turnover of MDO is best described by this logistic function. This function mathematically describes an S-shaped curve. As you have seen from the previous turnover curves, our turnover curves are not really distinctly S shaped. This is due to the overlapping of the different mechanisms. Now how does autocatalysis happen? Well, here are some structural formulas that explain this. So first, water adds to the double bond of the MDO in [indiscernible]. This is a very short list intermediate. Under ring-opening, it rearranged to form the hydrolysis product for HPA. Since the hydrolysis product is itself an ester and is also highly water soluble to trace [indiscernible] group. It cleaves in a subsequent step and form further molecules among others, acetic acids. Acetic acid can also add to the double bond and in turn form [indiscernible]. This in turn can hydrolyze and even release 2 molecules of acetic acids. But so far, we have only looked at hydrolysis in solution. However, our goal is to describe hydrolysis of MDO as realistic as possible. This includes kinetic studies in this version, but these versions are difficult to study by [indiscernible]. Therefore, we use the ReactIR and ReactRaman techniques. We tried a lot and found that these signals on the left for the IR and on the right for Raman, they are the best. In fact, we decided to sit on a rather unexpressive signal for the IR. You would think the largest signal would be the best. However, in this right number, we have the smallest interference with other products. So we measured our kinetics. You can see here the 3 dimensional [indiscernible] number time absorption graph. Top for the characteristic reaching of the hydrolysis product in IR, bottom for MDO in Raman. You can clearly see how the signals of MDO blue decreases and how the signals of hydrolysis product purple increases. First, we wanted to compare the ReactIR and Raman with the NMR kinetics already measured. So we examined again the MDO water EC mixtures. Since it is not possible to still doing the NMR measurements, [indiscernible] , but only to shake NMR at the beginning, but it's possible to stay all the time during the IR [indiscernible] and the Raman measurements back squares. We first wanted to check if this makes a difference. As you can see, all signals are more or less the same. The methods are comparable, and we could not see any differences. Here also the react -- in advantage of the ReactIR and Raman techniques becomes clear. You can generate much more measurement points in the same time interval compared to NMR. Next, we look at hydrolysis in heterogenous phase, which is not accessible by NMR technique. In heterogeneous phase, there is only MDO and water, as far as some [indiscernible] for final disposal of the MDO droplets. Here are, however, already some differences to be seen. It should be recognized that in heterogeneous phase that hydrolysis is once again significantly faster. Yes, now the time come our diagrams in a margin for different temperatures left and different pH values, right? You can also see here the trend that there is increasing temperature and decreasing pH, the hydrolysis proceeds faster. In addition, I have drawn the temperature curve in red here, you can see that we are almost exothermal here. This is due to the slightly alkaline conditions and the high dilution water, which can absorb the thermal energy well due to its high thermal capacity. Our big worry was that the setup penetration depth of the IR beam would make [indiscernible] for this first phase kinetic measurements. The penetration web of the IR might be too low to enter the MDO droplets and provide a reproducible image. However, we have the ATR technique, which stands for attenuated total reflection technique here. So the beam path is quite short at 7x by 2 millimeters. However, this concern is unjustified as you can see, the Raman measurements tranches are always almost congruent with the IR measurements circles. Once again, back to autocatalysis. We were also able to do some futuristic experiments on this the ReactIR. As I said before, the further reaction of hydrolysis product to acetic acid probably has a key role in the autocatalysis mechanism. We did not want to use acetic acid because all through we were working in a buffer system, we did not want to introduce problems that would favor protein catalysis. Therefore we use sodium acetate that is a weak base, one would expect that this addition would slow down the hydrolysis. Since in alkaline, the hydrolysis is slower. However, we observed the opposite at pH8 sodium acetate is in equilibrium with acetic acid and the sodium acetate addition despite the low concentration, accelerates the hydrolysis to more in a double. Since the ReactIR can be used to record a large number of data points. It can also be used to mathematically prove autocatalysis. This is how our calculations determine the order of the reaction. You see only by using the autocatalysis application, you get a straight line with a very good regression curvation over the whole time. Also, the title of my presentation was the question of which is faster hydrolysis or polymerization of MDO? We made some theoretical considerations in this regard. The polymerization kinetics are sequence of different individual steps. So first, we initiated the composition here potassium [indiscernible] effect takes place. This is KD. Then a sulfate radical reacts with a monomer to cause chain initiation. Then chain propagation occurs. This is KP. We assume a copolymerization of the new acetate is MDO. So we have to distinguish again between homo and copolymerization. Finally, chain commination, occurs due to the radical recombination. This is KT. This is opposed by hydrolysis KH. Now the individual values are not comparable with each other once you have first auto reactions, second auto reactions and autocatalysis. How do you compare them now? We have introduced a dimensional ratio [indiscernible] for this purpose. This is the question of the polymerization rate and the hydrolysis rate. If the value is greater than 1 polymerization wins, if it is less than 1 hydrolysis wins. The [indiscernible] is to be seen as a rough approximation, especially in emulsion polymerization kinetic strongly deviates from the rule [indiscernible] used here. You have homogeneous phase as well as heterogenous phase, the values are far below 1. So it's quite clear that hydrolysis wins. We now want to prove this theoretical consideration experimentally. For this purpose, we carried out the emulsion polymerization of MDO blue circles and new acetate red circles at pH8. To determine how many MDO units we have incorporated, we [indiscernible] component obtained in this way the sodium hydroxide and then we [indiscernible] with acetic anhydride. You then get putting acetate [indiscernible], each having agent with an MDO residual. The NMR analysis carried out in power shows that only a small fraction of MDO could be incorporated into the polymer. The molecular rate decreased significantly in all 3 samples, including the polynomial acetate homopolymer. The decrease in the polynomial acetate homopolymer can be explained by mechanical and thermal stress during the digestion process. In the end, however, we arrived at molecular weights that are clearly too large for intracellular uptake. The polymers produced in display are therefore very unlikely to be biodegradable. What can we learn from this study? Emulsion polymerization with MDO is always associated with a large loss of yield because it is not hydrologically stable. We have really looked at a lot of conditions in the study. However, we could not identify a sweet spot anywhere with MDO biodegradable, primary dispersions are not possible. As you could show the ReactIR is super suitable for measurements in this first phase. The low penetration depth of the IR beam has no obstacle. When determining which orders of a catalytic behavior should be also checked. If you have a strong exothermic reactions, diluted strongly. This will bring them to absorb the exothermic condition. You don't worry. Despite the high dilution, the signals are still very predictable in the ReactIR or Raman. Thank you very much for listening. If you would like to learn even more about my study, please feel free to read the article here.

Thank you, Benjamin, for your really wonderful presentation. So I believe we do have Benjamin on call yes, hello, Benjamin. So we do have -- we do have a few questions. So I will read these out for you. The question from Wes, I will answer at the end. But first, it doesn't seem so from your data, but did you observe any spectral or trend anomalies in the ReactIR emulsion data under any certain conditions?

Yes, that's a good question. I compared the right IR measurement, Mr. Raman, Director IR Measurements, and we did not see any differences between ReactIR and ReactRaman. So I think there are no problems due to the emulsions so that the penetration depth of the IR beam is sufficient enough. And we also compared the ReactIR measurements once in homogeneous solutions and in heterogenous solutions and we don't observe any differences. So I think the ReactIR is suitable for emulsion -- for measurement in emulsion polymerization, so this is no problem. I don't observe any anomalies or something like that.

Okay. All right. Excellent. Second question from Lilly. It seems the reaction is very fast. Is it possible to run the reaction at lower temperatures.

The question on the study was to evaluate if it is possible to make emulsion polymerization with MDO and water and you usually make emulsions polymerizations above room temperature. So of course, the erection speed will be slowed down at lower temperatures. But these are not the conditions which I used in emulsions polymerizations and we are in water. So we can't go under 0 degree as us because then you [indiscernible] ice. So they were very limited in the temperature range. So which has temperatures above room temperature are interesting.

Okay. Excellent. Jonathan would like to know have you evaluated the heat release of your reaction with calorimetry.

Yes, I also did some colorimetry measurements. This is described in the paper and we have served a very exothermic reaction, so there's a lot of energy released due to the ring opening of the molecule.

Okay. One further question from Andreas. Instead of MDO could a different length alkyl backbone or substitution with methyl groups helped with a limiting hydrolysis, basically a different monomer?

This is a very interesting question. I did a lot of considerations about that. And the problem is the [indiscernible] group. So this functional group is very sensitive to hydrolysis and some other substituents did not suppress the hydrolysis. I also did some experiments with other monomers instead of MDO, but I observed always a high degree of hydrolysis. On the other side, the fast -- by this hydrolysis is due to the ring opening. So if you use other monomers, which are not good in ring opening. This is slower, but then just not useful in emulsion polymerizations. So all monomers which are good in recurring [indiscernible] base also hydrolysis fast.

Okay. All right. Excellent. I believe that is all the questions we have directly for Benjamin. So again, Benjamin, thank you so much for this excellent work in this great presentation. I do have 1 question from Wes, which is an excellent question is will the -- will copies of these presentations be shared? So we do have permission from Matthias to share his presentation. So that one will be shared but the presentations have been recorded. So they are available for on-demand view and relistening too. So -- but only from Matthias will it be shared, you'll get an e-mail with a link later on this week. So I would like to close our session for today. I would again like to thank all of today's papers their really excellent presentations. And as just stated, recorded presentations from this and even past events will be available at www.mt.com/PATwebinars. Again, if you have any further questions, please submit them via the question and answer, and we will pass them to the speakers, and they will certainly be in touch with you. We also would very much appreciate your feedback on this event, so please be sure to submit that feedback once a link is provided to you. Again, thank you everyone for joining today's online seminar. I hope you enjoyed it and I wish you a wonderful rest of your day.