Webinar: Advanced Characterization on Solid State Materials | Dr. Jürgen Thun (Roche) - Part 1/3

Good morning and good afternoon to everybody, to all the participants to this webinar workshop. Today we are going to have a workshop about advanced characterization of solid material. I'm your host right now and I'm going to be one of the presenters during this workshop. My name is Damiano Cattanio. I'm a DVS product manager for DVS Adventure Resolution Endeavor here at Surface Measurement System. Our first presenter today is Dr. Jurgen Tung, principal scientist and group leader in the particle science design at Roche. And today he is going to introduce us to DBS analysis in drug development from intrinsic property to solid form control. So thank you very much and let's enjoy the presentation.

Thanks Damiano, for this kind introduction. Thanks for the possibility to present our work here. And it's not myself who did most of the work. Actually I present on behalf of the team, mainly Flavio Lak, Nikolaus Martin, Pascal Fleischmann. They did most of the work that I present today. And we have one example where we had a collaboration with research colleagues. This was Paulina Jakubiak at that time. And with this I would like to start maybe give you a first brief overview over the content of the talk. A short introduction, some information on solid form control strategy. That's actually the first case study. And the second one is how we used it for a BT surface area determination. What was at that time new for us? When I start with my presentation, we are talking today about dvs or in my talk it's about dvs. And that's a rather old and simple technique, isn't it? It's a balance, it's a humidity generator. And nowadays we talk about fancy new techniques like AFM or electron diffraction. That's the the buzzwords we hear in our community right now. So why are we investing time to learn more about dynamic wave absorption? And that's what I want to show you within the next 30 minutes. Roughly why in our development we still have such a high value creation using dynamic vaporsorption as one of our tools. And one thing is we start with a look on the solid form landscape. And on the first glance that looks rather simple. You might have some amorphous material disordered only. Short range order maybe, but no long range order. We talk about crystals and there, if we don't have any different component inside the crystal, we talk about polymorphs or different coordinations of the molecules within the crystal structure. And this means we have a long range order compared to the amorphous stuff. We could have sol weights or hydrates where we incorporate a second component into the crystal lattice, which is a liquid under ambient conditions, or which could be solid. Then we talk about CO crystals, and if we have ionic species, we talk about salts. And now the fun is that we can have all of them together. We can have mixed salt CO crystals, we can have hydrates or solvates of mixed salt CO crystals, and we can have polymorphs of these solvates of mixed salt CO crystals. And then finally you mill your material, your drug substance, and then you will have some amorphous parts on the surface of the material. So you can really have a whole variety of different combinations of those solid forms. We try to understand our material as best as we can. Before we go on, I would like to share some definitions which are rather old. When we talk about polymorphs, we mean crystals, a solid crystalline phase of a given compound resulting from the possibility of at least two different arrangements of the molecules that compound in the solid state. This is a definition by Walter macron back in 1965, but still a very valid definition of the polymorphism. If you go back, what means polymorphism? It comes from the Greek word poly, which means many, and morph, which means form, so that you have different forms. And it was first mentioned in a fashion, 1656, but then also in context of crystallography by Michelich in 1822. And when we talk about polymorphs, we need to differentiate between these polymorphs, as we have seen before, and other solid forms. Therefore, I called the picture before solid form landscape. Because if we have the definition from Walter Macron, we leave that a solid of a given compound, and if we talk about solvates or hydrates, I mean, this is not within the definition of Walter Macron, because then we have a different composition. If you compare it to an anhydrous form, sometimes it's called pseudopolymorphs. I just use the wording solvates or hydrates, but we prefer to use the wording solid form if we talk about different crystalline forms and amorphous. So this includes really the whole variety of possibilities. Why is it important to think about this? And there I have some references, literature references. This is mainly focusing on true polymorphs, but I think it's also true for solids and hydrates. Also from Walter Macron we have this quote, it's at least this author's opinion that every compound has different polymorphic forms, or in more general, we could say solid forms. And that in general, the number of forms known for a Given compound is proportional to the time and money spent in research on that compound. And from my experience in the pharmaceutical industry, in most cases that's really true. The more time you spend, the more solid forms you will find. And then also we have a quote from Joel Bernstein, who says the possibility of polymorphism may exist for any particular compound, but the conditions required to prepare as yet unknown polymorphs by. And this means, in principle, it fits to the Macron statement, you need some time and you will find something. But it's not obvious that you will find. You don't have a recipe, how to get it. So why do we think it's really necessary? And I want to share some examples from the past where you see that also, especially with transformation from an anhydrous form into a solved or hydrate is of interest for our research. Back in 1988, there was a failure of carbamazepine, because there you can see it's a conversion from an anhydrous form to an dihydrous form. And this, of course, will change the solubility and may significantly impact the bioavailability of your drug. You have another case in 1998 where we have this famous ritual navir case. Here you have a polymorph issue. So you get a more stable polymorph. This was one of the key events that triggers these polymorph screenings in our day's research departments. Then you have in 1999, there was some issues with Vermox tablets. Also here it's on polymorphs. But if you have A Look, in 2010, we have these Coumadin tablets. And here it's also that you have a solvate incorporated. So the variable isopropanol content turned out to have different crystalline forms. And if you dehydrate this sol weight, you get an amorphous formation. These amorphous parts also will have an impact on your solubility behavior. So on this page at least, we have two different two events with not only talking about polymorphs, but also about solvates and hydrates. And that brings us back to this, to my introduction, where I said, why do we still use tvs? Because we are living in a world with humidity. And if we produce our APIs, our drug substance materials or our drug product materials, we work with solvents. So it's necessary for us to understand the solid form landscape also in the presence of these solids. This brings me to the next part of this talk. It's about the solid form control strategy. There is a key requirement from the health authority departments that you perform a solid form screening. This is a more technical document. In this ICH Q6A you need to perform a polymorph screen on the drug substance. Can you define different polymorphs? If no, you're fine. If yes, you need to characterize them. I think everyone would do that in a scientific environment. Don't need to have a document for this. But then I like this statement here because it's a really philosophical question. Do the forms have different properties? Solubility, stability, melting point, yes or no? And to be honest, I always struggle with this question because I mean they have different crystalline forms, they have different crystal lattice and hence lattice energies. So of course they will have a different solubility value. It might be very similar, but it's different by definition. But if it's different, does it make an has an effect on the product safety, performance or efficacy? In some cases you would say no, and then also no action is needed. But if yes, you need to set an acceptance criteria. So why do I show this here? Because I think that's in principle only a technical document that's required if you want to get your approval on your drugs. But in principle this is a scientific workflow. We need to understand our product, we need to understand our drug substance molecule, how it behaves, and we need to find a process that robustly will deliver the desired solid form we have selected. So we need to develop a solid form control strategy. We need to understand our solid form landscape, we need to identify the transition paths between different solid forms. And this happens in our case with a close collaboration between the thermal analysis lab where the DVS instrument is located and the solid form screening laboratory. Then you need to identify the process relevant solid forms. And if you know this, you can establish some kind of a holistic control strategy based on these intrinsic properties and based on your process, because you know your parameters from the process, if it's a wet granulation in the rock product or if it's a dry granulation. And this you can incorporate into your control strategy. So you have a strong scientific and database rational that demonstrate the robustness of your manufacturing process with respect to the patient safety and which means no change of the selected solid form during production of life cycle. And we use some kind of this picture just to show this holistic view. So you have the intrinsic properties of your material, you have procedural and parametric controls in place by the adaption or the design of your process, and you have an attribute control at the End which in principle is kind of a release analytics you apply. So with this I would go further. If you think about this control strategy, it means it might be difficult to find analytical tools. So especially when we think about drug product applications, you have a very low drag load. And then you need to think you are looking for meta stable unstable polymorphs or labile hydrates and solvate. So that might be rather tricky. And that's why we think it's necessary to identify, to have an understanding of the solid form landscape of your pure material as well, because this helps you and gives you some warning signals if you think about hydrate formation or something like that. And so the idea behind the control strategy we implemented in our shop, and I think Dara is also online, who was at that time postdoc and developed a lot of tools for us here during this workflow, is not to minimize the production environment, the production equipment. The idea is to understand your solid landscape and then apply stresses that occur during your manufacturing process. So don't miniaturize your equipment, but simulate the stresses and then based on those outcomes, you can really build a scientific rationale for your control strategy. So now let's jump to some applications and case studies. And the first one is a rather simple one. You just have one solid form. When we think back to this quote from Walter Macron, maybe in that case you simply didn't have enough time to look deep into those, into this compound. But of course also we have compounds that where we only have one solid form, one crystal in solid form and it's fine. So for this product you don't have any problems with respect to the solid form at least, but we might have more complex cases. And this is also a true example that this is not just an image. What you can see here is a solid form landscape of yeah, it's already marketed product. This is the selected solid form. It's a monohcl salt, it's a polymorph, and all the lines here are transition paths. So you can see it's a rather complex landscape. And at the end we want to convince the health authorities that we are able to robustly deliver this selected solid form and without having changes to all the others seen in this diagram. Of course not all of those solid forms here are within process relevant solvents. This will limit the space. But nevertheless you need to understand the whole figure before you can minimize your rational on the process relevant solid forms. Within this graph we have kind of a hydrate family and I want to show the benefit of the DVs for the elucidation of this hydrate family here. And when we have a closer look on this, we can see that we have a polymorph which is stable at really low relative humidities. We have a hemihydrous form, we have a monohydrate, a tetrahydrate and above 90% relative humidity we have also a heptahydrate. And you see this is reversible. You see all these arrows going up and down. So this is a reversible conversion. You need to understand this because if you want submit your sample for certain analysis xrpd if you don't care about your relative humidity, you might end up with a different solid form than you originally expected. And if you know this is a, this will always be an equilibrium at your conditions you're measuring then immediately shows you that you need to take need to understand the behaviors of your hydrous forms. Maybe one Roche specific thing. We have an internal nomenclature system for our polyme or solid forms. So it's not so that every scientist can claim this is a new solid form, that's form A or form B or Form 6. So we have all the experts from X ray spectroscopy, thermal analysis and solid form screening lab that meet regularly and they discuss the data and then say okay, that's really a true solid form. We have a full understanding on this form. And then it's really designated as Form 4, for example. And this explains all the. Here you have form 2, form 4, form 5, form 6, form 7. So you see also here is it's not in order that you would have set it from the beginning, but this simply shows how you detect those solid forms. So these are five solid forms and in principle you need only one DVs run to detect all those solid forms. You see those steps and also some kind of hysteresis. You can clearly see that the stability regions of those different hydrous forms. You can see the hemihydrate, monohydrate, tetra and the heptahydrate. And that's really also in the, in the mass change plot. You can can see this quite nicely. It's rather difficult to see this hemihydrous form, but when you know that there needs to that there should be something, you clearly see this step here as well. So that's really in both cases you can see the, during this absorption and desorption cycle. This was a perfect example for us to study also the application using Raman coupled to the DVS instrument. And this was one of our test cases when we tried this, and what we did was we repeated, in principle, this cycle, we only went up to 90 degrees. So we won't see the heptahydrate here. But you can see those dots were where we measured the Raman at the end of each of those steps. And what you can nicely see that when you overlay your structures, you clearly see a difference between the monohydrate and the anhydrous form. And you can see a difference between the tetrahydrate and the monohydrate. And for me, this was really interesting to see because I haven't had experience with these Raman couplings on the DVs before. You need to take, keep in mind that during the measurement, the focus of your Raman spot is not on the sample. You don't want to burn it. We have maybe some labile solvates, hydrates, and we don't know what happens if you have the focus of your Raman probe on the probe. So your focus is a bit off, and this means that you might lose resolution and intensity. But nevertheless, we can see differences for those hydrates. And here also keep in mind these hydrates are reversible hydrates. So the binding within the crystal lattice might not be so strong. So you might only have subtle changes to your crystal structure. But nevertheless, you can see this difference between the anhydrous and the anhydrate and the monohydrate, and the monohydrate and the tetrahydrate. It's a bit more difficult for the hemihydrate. So we did some more experiments trying to elucidate this. And we used this kind of a ramping or dynamic measurement, only focusing on this first 30%. And here you can clearly see the formation of the hemihydrate as a depth. And you can also see the Raman measurements. But to be honest, on a first glance, similar. And when you have a look at the overlay, also here you can see only subtle changes. You can see that between the anhydrate and the monohydrate, the blue and the black, you can see differences, and those are significant. Also here, between the blue and the black one, you can see a clear difference. But the red one, it could, it looks like just to be a mixture. And also in our other wave number area, this seems to be rather simple. And also here you can see differences between the black and the blue, the black and the blue, but the red one, it looks just as if it would be a mixture. So for this hemihydrous form, where you really have only minor changes between the original anhydrous form and your monohydrate, this seems not to work. Nevertheless, as we work also in close collaborations with the colleagues from the X ray laboratory and on the X ray you can clearly see the formation of this hemihydrous form. We have the anhydrous form. This is a humidity dependent XRPD analysis. You can see peaks for single peaks, singular peaks for the hemihydrous form and singular peaks for the monohydrosporum. So with XRPD you are more sensitive in this case for this drug substance molecule to detect these differences. Nevertheless, I mean, with one DVS experiment we could already elucidate the transitions between those hydrates within the solid form landscape. And as I said at the beginning, you really need to understand your transition paths before you want to set your control strategy for your product. At the end, you want to convince yourself that your process is robust and also the health authorities that you have a robust process in place to produce the selected solid form. And to do so you need to understand all those arrows in this area. And DVS is one of the instruments, especially with a coupling to elucidate a lot of these transition paths. With this I want to change gears and talk about BET surface area. And to be honest, I am not an expert in BET specific surface area determinations. But at some point a few years ago, we were asked if we would have a method to determine the specific surface area for a product which is called melanin from different sources. And typically you use this classical BET measurement approaches. But for this the problem was that they want to characterize these melanin from sources from the Porchini, sepia and synthetic. The synthetic one is not an issue. You can buy it kilogram wise, that's not an issue. Also sepia can be extracted rather simple problem is the material from the porcini. And what they wanted to look at was they wanted to study the binding affinity of drugs on this melanin, because this is typically within our eyes. And if you have orphan drugs, you want to have a binding inside your eye. And so this was one thing they wanted to look at and therefore they needed to. They wanted to see the effect of the origin of the melanin source on their binding assays they developed. So the problem is from a porgin eye you get roughly around 4 milligrams, the 0.4 milligrams of melanin. And the question was, is there any possibility to determine the specific surface area with less material than Compared to these normal quantities that's typically used. Of course, this depends on the specific surface area. The, the higher the specific surface area, the less material you need. But typically for a standard BAT analysis you have 1 to 2 grams, then you can use DVS. That was one thing we thought about at the beginning, but the documentation, the applications we found were around 100 to 300 milligrams. So we tried to adapt the method and use it with smaller amounts as well. Because when you think about porcinise, this means for a standard BET analysis you would have needed 5,000 eyes. And I mentioned Paulina Yakubiak at the beginning because she was doing her PhD during this time and she really went to the slaughtery, got the protein ice and extracted this melanin from those eyes. I mean, of course you first need to have these 5,000 ice and then you need to extract it in your lab. So the standard BT, roughly 5,000. With a standard DVS method, around 250 to 750. And with our adapted method, it's around 70. So this significantly reduces the lab work for Paulina here. In that case, the question was, does it really work or not? So first of all, Flavio looked into the DVS instrument and the application nodes. And of course, when you want to compare the data from a standard BET with the measurements we performed, you need to be sure, you need to be aware that you use different probe molecules, you use octane in case for the DVs, and you have different conditions so you don't freeze your materially. It's an unbanned temperature, ambient pressure, not under vacuum. So the data might not be comparable directly to standard BET data, but the ranking between the different sample types or the samples of different origin should work also with these adapted BET methods. As I mentioned, we didn't have any clue how that works on the dbs, but we tried it with lactose just to acquire some knowledge. Then we switched to the synthetic melanin samples because there you can get grams and kilograms of material. So we tried to set up the measurement with the synthetic melanin using small sample amounts. We run several cycles every time in order to reach a plateau. And then we compared those values to the literature data that we have for these synthetic melanin. And then finally we applied it to these biologic samples because of course we didn't want to waste the biologic samples and the PhDs. You need to go back to the lab and extract from another 70 ice again because we just ruined it through our experiments. So in Principle it worked, otherwise I wouldn't have shown you the data here today. You can see the PET plot you get from the software after the runs. You can see that there is a perfect but a nice regression line and you can extract the specific surface areas for your synthetic melanin. But also it worked for the sepia melanin. Melanin and the Porcian melanin. When you compare this now with the literature values, you can see that synthetic melanin was analyzed with a standard BET measurement to be 11.8. We had 9.7. This was a triplicate determination in our case here, I don't know, but I mean it's not so far away and we need to keep in mind that we use different probe molecules and different conditions. What's nice with the DVS is that you really can see we see differences, small differences. The synthetic one has the lowest specific surface area. You can see that the fit was for all. The regression line was for all Very well. And what you also have within the BET equation is this BET constant C, which somehow gives you an idea about the adsorbent interaction strength. And to be honest, as I said, I'm not an expert in this, but what you can see here is that this constant is higher for the synthetic melanin compared to the biologic samples. And this makes absolutely sense in my opinion because I mean the synthetic one is the purest material you can get. And I would think also that the surface is much cleaner compared to the biological samples which were extracted according to a certain protocol. So I just mentioned that the data correlated well with the literature values. The constancy gives you an additional insight on the binding characteristics and this seems to be a suited technique to characterize and compare these different materials. This data is published in a paper in Molecular Pharmaceutics. And one nice thing was that one of the reviewers was really pleased to see these. For them it was a new DVS technique. He was really, really said that this is one of the major innovations in this area and this was one of the his positive aspects why this paper should be published. So for me that was very interesting to see that for us TVS as a standard technique, maybe not for bet, but as a standard technique. And in this case this was really seen as one of the innovations within this project. With that I want to conclude, I think I showed you that with this gravimetric BT determinations using the dbs, it allows you to detect the specific surface area for very small amounts of organic materials. I also want to Highlight that you analyze your sample and conditions, which means that you don't have a clean surface by vacuum or something like that. So it's really your sample you just put in your system. You need less sample amount, which is very advantage for early phase projects where you don't have so much material. And it's really ideal to compare different material qualities if you run a series and can compare your DBS data with each other. The summary for the first part on the control strategy, as I said at the beginning, a simple technique, just a balance and a humidity generator. I'm a bit kidding of course, but nevertheless this technique has still a high scientific output due to the significant improvements in the instruments, like different detectors, different these possibilities to analyze solvents and the Raman couplings. So these improvements really help us to understand our solid form landscapes. It's also written here, these coupling techniques helps us also to generate more data from one run. So we just need one experiment and get additional data by this Raman coupling. So nevertheless, old technique, but still very valuable in all our development projects. And with this I'd like to thank my colleagues from the lab for thermal analysis, especially Flavio, Nico and Pascal for their work, the colleagues from the solid state sciences department, because most of the projects come from them. As a analytical lab, you are more or less analytical app, you're not producing the samples. And finally I wanted to thank also Paulina Jacubiak and her supervisor because this was really a nice work on this bet specific surface area. And with that I want to thank you for your attention and thanks also SMS for the possibility to present today within this webinar.

Thank you very much for the great presentation. Dr. Sun was very interesting and also seeing a point of view from an industrial perspective is very useful.