Fundamentals of Solid Formulation
3rd Edition
April 6, 13, 20, 27
11:00 AM – Noon EDT
For busy professionals working in pharmaceutical solid form, we have created a 4-week webinar series to distill state-of-the-art solutions to key challenges. Each webinar will feature a leading expert who understands your daily workflow and will share his/her real-world experience in successfully supporting preclinical and clinical projects. The series will catalyze discussions aimed at ensuring a stable form is selected with optimal bioavailability and manufacturing properties.
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The particle-powder-processability interplay – powder characterization in pharmaceutical development
The particle-powder-processability interplay – powder characterization in pharmaceutical development
Carolin is a pharmacist by training with a PhD in pharmaceutical technology where she focused on solubility enhancement with amorphous solid dispersions. In 2018, she embarked on powder characterization tools by mimicking dedicated unit operations and deriving processability for oral solid dosage forms. Together with her team, the expertise acquired in this field is provided for various pipeline projects. Continuously expanding capabilities and finding customized solutions for specific challenges still inspires her. In addition, Carolin holds a position as drug product lead for a late-stage asset.In 2014, Leane et al. brought up the idea of a Manufacturing Classification System (MCS) for selection of the manufacturing process for solid dosage forms. The choice shall be made based on particle and powder properties rather than company and staff experience. As such, the presentation will focus on different powder characterization techniques that are applied at Merck Healthcare KGaA for this concept. How were they selected and standardized for getting least variability in the analytical data acquisition and enabling comparability among different projects? The final goal is to use drug substance data for selection of excipients and predicting processability of the formulation. Due to the interdependencies of certain properties, univariate correlations may not be sufficient for holistic description of manufacturability, as such multivariate data analysis is applied. In addition, more advanced methods will be presented to mimic specific unit operations and issues like fluidization in fluid bed granulation or time consolidation in a blending container during process holding times.Q1. Have any computational methods proved useful when evaluating the 1st wave drug substance batch? For example, morphology prediction calculations for calculating particle shape.
we are currently in the evaluation of complementing computational methods for predictions of morphology and in my opinion, there are already some promising approaches. Up to now, we rely on experimental data (also as PSD measurements are quite quick and do not require a huge amount of sample) and use supportive AI applications e.g. in evaluation of SEM images.
Q2. Could you comment a bit on how well the results for neat API fit for or translate into the final formulation?
This is a very important aspect and in my opinion and as depicted with the P3 cycle also a big step to take for direct correlations between API and processability. How dominating the API properties will be, is on the one hand of course depending on the drug load. On the other hand, it depends on the nature of interactions between API and excipients. So we have seen powder blends with 20% drug load, performing almost like neat API in certain aspects. But it can also be the other way around that drug loads up to 60% are still dominated by the excipient/formulation.
Q3. Did you already define limits for processability e.g. in terms of flowability? And if yes, based on which method?
Yes we did e.g. for the direct compression process. The method with highest predictability in our studies was the ring shear tester.
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Thermodynamics versus Kinetics: who wins the crystallization race?
Thermodynamics versus Kinetics: who wins the crystallization race?
After obtaining a BSc in Chemistry from the University of Jaén (2002), Aurora earned a Master's Degree in Heterogeneous Catalysis from the University of Córdoba (2004). She then spent some months at the Royal Institution in London, where she learnt about various molecular simulations techniques. Aurora then moved to the University of Cambridge where she gained a PhD in Physical Chemistry (2008) under the supervision of Dr Graeme Day and Prof. Bill Jones. Following her PhD, Aurora worked as a researcher in several pharmaceutical companies (Pfizer and Roche), the University of Amsterdam and the Cambridge Crystallographic Data Centre. In 2016, Aurora joined the Department of Chemical Engineering at the University of Manchester, where she is now a Reader in Crystallisation. Her research interests lie in the area of the organic solid-state, data analysis, molecular modelling, crystal engineering and crystallisation. Some of her best well-known work lies in the area of crystal polymorphism. Aurora has published over 80 research papers and given over 70 invited talks all over the world. She regularly serves the community as a reviewer and guest editor for various scientific journals. She is also a member of the Scientific Advisory Board for the Cambridge Crystallographic Data Centre.Crystallization of complex (and simple!) molecules can be difficult to control with its outcome sometimes dominated by molecular level processes which are difficult to underpin. In this presentation, I will share my experiences in the area of polymorphism and crystallization. I will make special emphasis on the fine balance between thermodynamics and kinetics which may give some polymorphs some advantages during crystallization. But who wins the race? The answer is complex and certainly dependent on many factors including solvent of choice, levels of supersaturation or impurity profiles.Q1. Slide 26: Have you tested other morphology prediction calculations like Attachment energy or modified attachment energy to see how it effects the subsequent rugosity calculations?
No, we have not tested other methods. We plan to do this in the future. Whilst, this will be indeed a good improvement, I would not expect to make a significant difference in the overall particle rugosity.
Q2. Slide 36: Here you show that introducing impurities can change the kinetics. Polymer additives can change crystal morphologies for some systems, do you think this is related to a change in the kinetics?
The work by Weizmann institute team has shown how different impurities, including polymers, can interact differently with different crystal faces resulting in morphological changes. So, yes, polymers may also have the potential to impact kinetics of crystal faces differently.
Q3. You have been successful in the pharmaceutical industry, the CCDC and as an academic. How would your career advice differ depending on if one wants to go to industry or pursue an academic track?
Thanks for this question, which I could discuss for hours and hours! I have personally loved working in all these three environments. For me, the most important thing is the people I work with. I have been privileged to work with great people in all these three environments. I would advice that you need to keep passionate and learn to work enthusiastically with a team to succeed in any environment. Above anything, many of my choices have been dictated by family circumstances at the time. I value family and people above everything else, and if that is right and you are passionate, brilliant science will follow.
Q4. Slide 27: Have you compared the rugosity trend between known and unobserved but themodynamically stable polymorphs from CSP landscapes? For example, molecule XXIII or Galunisertib both have stable forms that are predicted but never observed.
Rugosity work is ongoing in my group and we are now looking into further systems and applications to CSP landscapes. Please keep an eye on the literature for some more exciting work.
Q5. a water activity value can favor a certain anhydrous polymorph?
No, the water activity will determine whether the hydrate is favoured over the anhydrous forms or the other way around. It will not impact the relative stabilities of anhydrous forms.
Q6. How one can generate paracetamol less stable form in bulk knowing that impurities playing role
You need the impurities to produce form II so that form I is blocked from nucleating and growing.
Q7. Slide 16: Any dvs study or water slurry performed on anhydrous form to check the conversion?
Yes, we did slurries to determine the critical water activity, please see the paper.
Q8. would you comment on Oswald's role implying more stable polymorph nucleates slower than metastable form?
The Oswald rule of stages is just a case of many scenarios whereby the metastable form is “easier” to nucleate than the stable form. However, not all systems behave like this and there is a very large body of examples in the literature where this is not the case. For example, form II paracetamol does not follow the Oswald rule.
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Physical Properties Control in the Process of Crystallization of Ulotaront Hydrochloride
Physical Properties Control in the Process of Crystallization of Ulotaront Hydrochloride
Haitao Zhang is an Associate Research Fellow in Chemical Process R&D and has been with Sunovion since 2012. In his current role, he is responsible for in developing, and demonstrating commercially viable, multi-step, organic syntheses and crystallization for the manufacturing of small-molecule advanced intermediates and active pharmaceutical ingredients. His expertise range from the scale-up of crystallization, reaction engineering and mixing, the characterization and control of API physical properties at the bulk-pharm interface, use of high-throughput instrumentation and laboratory workflows for process development. Haitao is also responsible for the new technology platform establishment, such as continuous manufacturing, PAT application in process development, QbD, simulation and process modeling, etc.
Haitao completed his postdoctoral training at Massachusetts Institute of Technology and received his Ph.D. in chemical engineering from Tianjin University. During his stay at MIT, he was dedicated to the development and demonstration of the first end-to-end, integrated continuous manufacturing pilot plant for a pharmaceutical product sponsored by Novartis.Physical properties of pharmaceutical solid materials can have a critical impact on the material's bulk properties, drug formulation performance, processability, stability and appearance. In the drug substance manufacturing process for ulotaront hydrochloride, a novel trace amine-associated receptor 1 (TAAR1) agonist, the physical properties of final active pharmaceutical ingredient (API), including polymorphism, morphology, particle size, agglomeration, have been investigated systematically.
In the polymorphism screening and crystallization process development of ulotaront hydrochloride, two different polymorphs have been identified: Form A (plate-like crystal) and Form B (needle-like crystal). In most cases, Form A was generated (a non-solvated, non-hydrated solid-state form), which is a strong indication that Form A is the thermodynamically stable form. Crystals with a clearly different, needle-like shape (Form B) were observed in several recrystallization experiments, however the needles decomposed during isolation or even upon prolonged standing at room temperature. Additional studies demonstrated that Form B is not the thermodynamically stable form. Form B could transform to Form A in solution, or in the isolated solid state at room temperature. While the isolated Form B needles were kept at 20 oC under ambient conditions, the tracking (X-ray Powder Diffraction) XRPD patterns indicated it was slowly transferring to Form A, while the crystal shape remained as needles. The crystallization of ulotaront hydrochloride is designed as reactive crystallization by adding the HCl isopropanol solution into the ulotaront freebase solution. The addition mode and addition profile of HCl solution, mixing performance control have been demonstrated to be critical to the polymorphism control.
Form A and Form B crystals have distinct crystal habits. Crystal morphology was observed to change to cube-like (from the current hexagon face plate) when the water content is above 0.5% in the process stream, which could be addressed by controlling water content. The presence of residual R-mandelic acid in the crystallization process was observed to generate rod-like crystals.
The agglomeration issue was observed in the first current Good Manufacturing Practice (cGMP) campaign, and it has been successfully addressed by the introduction of subsurface dosing system of HCl isopropanol solution in the later manufacturing campaigns.
Regarding the Particle Size Distribution (PSD) control, a strategic crystallization mean has been developed by controlling the HCl solution dosing profiles, operation temperature, and mixing performance through the geometric configuration.
The crystallization process of ulotaront hydrochloride has been successfully developed and it could effectively control its physical properties, including polymorphism, morphology, agglomeration and PSD. The efficiency has been demonstrated in cGMP manufacturing.Q1. Slides 26 -28, the PSD control is eternal topic in crystallization. For the reactive crystallization, it becomes more complicate as the reaction kinetics, mixing and mass transfer, and crystallization kinetics all play important roles for the PSD control. Could you explain what is the current control strategy on the PSD control in manufacturing and what is the consideration behind?
The PSD control for Ulotaront Hydrochloride is quite challenging as multiple parameters are involved, especially in scale-up manufacturing. In terms of the current PSD control strategy, firstly, the mixing assessment has to be done to define the mixing regime in the reactor. This will facilitate the dosing tubing design (subsurface dosing) and configuration, and it also enables the impeller selection and helps to define agitation rate. Secondly, the parameters affect the PSD has to be defined according to the kinetics study results. The parameters include the dosing profile, temperature, and agitation rate (de to its effect on secondary nucleation). The idea is to have all the critical process parameters defined based on the current process understanding in order to have robust and reliable control over the PSD.
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Solid Formulations in Agriculture
Solid Formulations in Agriculture
Susie received her B.S. in chemistry from Butler University in 2014 and completed her Ph.D. in Inorganic Chemistry at Purdue University (2019). Immediately following her graduate work, she worked at Purdue as a Lecturer for the Chemistry Department and as a Postdoctoral Researcher. Susie joined Corteva Agriscience in 2019 as a Formulation Scientist in the Formulations R&D group and has been leading the Formulation Support and Characterization team since 2021.Solid formulations in agriculture come in many forms based on the target demographic and customers' needs. Examples of products on the market range from bait stations to water dispersible granules. Our formulation scientists are tasked with ensuring excellent product performance while balancing stability with processibility. Presented herein is a high-level overview of the considerations that are taken for our products during development such as I) scale of manufacture II) conditions of product storage and III) usability of product by the customer.
