FDA/M-CERSI Co-Processed API Workshop Proceedings.

These proceedings contain presentation summaries and discussion highlights from the University of Maryland Center of Excellence in Regulatory Science and Innovation (M-CERSI) Workshop on Co-processed API, held on July 13 and 14, 2022. This workshop examined recent advances in the use of co-processed active pharmaceutical ingredients as a technology to improve drug substance physicochemical properties and drug product manufacturing process robustness, and explored proposals for enabling commercialization of these transformative technologies. Regulatory considerations were discussed with a focus on the classification, CMC strategies, and CMC documentation supporting the use of this class of materials from clinical studies through commercialization. The workshop format was split between presentations from industry, academia and the FDA, followed by breakout sessions structured to facilitate discussion. Given co-processed API is a relatively new concept, the authors felt it prudent to compile these proceedings to gain further visibility to topics discussed and perspectives raised during the workshop, particularly during breakout discussions. Disclaimer: This paper reflects discussions that occurred among stakeholder groups, including FDA, on various topics. The topics covered in the paper, including recommendations, therefore, are intended to capture key discussion points. The paper should not be interpreted to reflect alignment on the different topics by the participants, and the recommendations provided should not be used in lieu of FDA published guidance or direct conversations with the Agency about a specific development program. This paper should not be construed to represent FDA's views or policies.

Breakage Assessment of Lath-Like Crystals in a Novel Laboratory-Scale Agitated Filter Bed Dryer.

Agitated filter bed dryer is often the equipment of choice in the pharmaceutical industry for the isolation of potent active pharmaceutical ingredients (API) from the mother liquor and subsequent drying through intermittent agitation. The use of an impeller to promote homogeneous drying could lead to undesirable size reduction of the crystal product due to shear deformation induced by the impeller blades during agitation, potentially causing off-specification product and further downstream processing issues. An evaluation of the breakage propensity of crystals during the initial development stage is therefore critical. A new versatile scale-down agitated filter bed dryer (AFBD) has been developed for this purpose. Carbamazepine dihydrate crystals that are prone to breakage have been used as model particles. The extent of particle breakage as a function of impeller rotational speed, size of clearance between the impeller and containing walls and base, and solvent content has been evaluated. A transition of breakage behaviour is observed, where carbamazepine dihydrate crystals undergo fragmentation first along the crystallographic plane [00l]. As the crystals become smaller and more equant, the breakage pattern switches to chipping. Unbound solvent content has a strong influence on the breakage, as particles break more readily at high solvent contents. The laboratory-scale instrument developed here provides a tool for comparative assessment of the propensity of particle attrition under agitated filter bed drying conditions.

A Novel Computational Approach Coupled with Machine Learning to Predict the Extent of Agglomeration in Particulate Processes.

Solid particle agglomeration is a prevalent phenomenon in various processes across the chemical, food, and pharmaceutical industries. In pharmaceutical manufacturing, agglomeration is both desired in unit operations like wet granulation and undesired in unit operations such as agitated filter drying of highly potent active pharmaceutical ingredients (API). Agglomeration needs to be controlled for optimal physical properties of the API powder. Even after decades of work in the field, there is still very limited understanding of how to quantify, predict, and control the extent of agglomeration, owing to the complex interaction between the solvent and the solid particles and stochasticity imparted by mixing. Furthermore, a large size of industrial scale particulate process systems makes it computationally intractable. To overcome these challenges, we present a novel theory and computational methodology to predict the agglomeration extent by coupling the experimental measurements of agglomeration risk zone or "sticky zone" with discrete element method. The proposed model shows good agreement with experiments. Further, a machine learning model was built to predict agglomeration extent as a function of input variables, such as material properties and processing conditions, in order to build a digital twin of the unit operation. While the focus of the present study is the agglomeration of particles during industrial drying processes, the proposed methodology can be readily applied to numerous other particulate processes where agglomeration is either desired or undesired.

Understanding stress-induced disorder and breakage in organic crystals: beyond crystal structure anisotropy.

Crystal engineering has advanced the strategies for design and synthesis of organic solids with the main focus being on customising the properties of the materials. Research in this area has a significant impact on large-scale manufacturing, as industrial processes may lead to the deterioration of such properties due to stress-induced transformations and breakage. In this work, we investigate the mechanical properties of structurally related labile multicomponent solids of carbamazepine (CBZ), namely the dihydrate (CBZ·2H2O), a cocrystal of CBZ with 1,4-benzoquinone (2CBZ·BZQ) and the solvates with formamide and 1,4-dioxane (CBZ·FORM and 2CBZ·DIOX, respectively). The effect of factors that are external (e.g. impact stressing) and/or internal (e.g. phase transformations and thermal motion) to the crystals are evaluated. In comparison to the other CBZ multicomponent crystal forms, CBZ·2H2O crystals tolerate less stress and are more susceptible to breakage. It is shown that this poor resistance to fracture may be a consequence of the packing of CBZ molecules and the orientation of the principal molecular axes in the structure relative to the cleavage plane. It is concluded, however, that the CBZ lattice alone is not accountable for the formation of cracks in the crystals of CBZ·2H2O. The strength and the temperature-dependence of electrostatic interactions, such as hydrogen bonds between CBZ and coformer, appear to influence the levels of stress to which the crystals are subjected that lead to fracture. Our findings show that the appropriate selection of coformer in multicomponent crystal forms, targetting superior mechanical properties, needs to account for the intrinsic stress generated by molecular vibrations and not solely by crystal anisotropy. Structural defects within the crystal lattice, although highly influenced by the crystallisation conditions and which are especially difficult to control in organic solids, may also affect breakage.

A machine learning framework for computationally expensive transient models.

Transient simulations of dynamic systems, using physics-based scientific computing tools, are practically limited by availability of computational resources and power. While the promise of machine learning has been explored in a variety of scientific disciplines, its application in creation of a framework for computationally expensive transient models has not been fully explored. Here, we present an ensemble approach where one such computationally expensive tool, discrete element method, is combined with time-series forecasting via auto regressive integrated moving average and machine learning methods to simulate a complex pharmaceutical problem: development of an agitation protocol in an agitated filter dryer to ensure uniform solid bed mixing. This ensemble approach leads to a significant reduction in the computational burden, while retaining model accuracy and performance, practically rendering simulations possible. The developed machine-learning model shows good predictability and agreement with the literature, demonstrating its tremendous potential in scientific computing.

Recent Advances in Co-processed APIs and Proposals for Enabling Commercialization of These Transformative Technologies.

Optimized physical properties (e.g., bulk, surface/interfacial, and mechanical properties) of active pharmaceutical ingredients (APIs) are key to the successful integration of drug substance and drug product manufacturing, robust drug product manufacturing operations, and ultimately to attaining consistent drug product critical quality attributes. However, an appreciable number of APIs have physical properties that cannot be managed via routes such as form selection, adjustments to the crystallization process parameters, or milling. Approaches to control physical properties in innovative ways offer the possibility of providing additional and unique opportunities to control API physical properties for both batch and continuous drug product manufacturing, ultimately resulting in simplified and more robust pharmaceutical manufacturing processes. Specifically, diverse opportunities to significantly enhance API physical properties are created if allowances are made for generating co-processed APIs by introducing nonactive components (e.g., excipients, additives, carriers) during drug substance manufacturing. The addition of a nonactive coformer during drug substance manufacturing is currently an accepted approach for cocrystals, and it would be beneficial if a similar allowance could be made for other nonactive components with the ability to modify the physical properties of the API. In many cases, co-processed APIs could enable continuous direct compression for small molecules, and longer term, this approach could be leveraged to simplify continuous end-to-end drug substance to drug product manufacturing processes for both small and large molecules. As with any novel technology, the regulatory expectations for co-processed APIs are not yet clearly defined, and this creates challenges for commercial implementation of these technologies by the pharmaceutical industry. The intent of this paper is to highlight the opportunities and growing interest in realizing the benefits of co-processed APIs, exemplified by a body of academic research and industrial examples. This work will highlight reasons why co-processed APIs would best be considered as drug substances from a regulatory perspective and emphasize the areas where regulatory strategies need to be established to allow for commercialization of innovative approaches in this area.

Assessment of impact breakage of carbamazepine dihydrate due to aerodynamic dispersion.

Acicular crystals are very common in pharmaceutical manufacturing. They are very prone to breakage, causing unwanted particle size degradation and problems such as segregation and lump formation. We investigate the breakage pattern of carbamazepine dihydrate, an acicular and platy crystal with cleavage planes. It readily undergoes attrition during isolation and drying stage, causing processing difficulties. We use the aerodynamic dispersion of a very small quantity of powder sample to induce breakage by applying a pulse of pressurised air. The dispersion unit of Morphologi G3 is used for this purpose. The broken particles settle in a chamber and are subsequently analysed using the built-in image analysis software. The shift in the particle size and shape distributions is quantified through which the extent of breakage is determined as a function of the dispersion pressure. The analysis reveals a change of breakage mechanism as the dispersion pressure is increased from primarily snapping along the crystal length to one in which chipping has also a notable contribution. The breakage data are analysed using a modified impact-based breakage model and the breakability index of the carbamazepine dihydrate is determined for the two breakage regimes. The method provides a quick and easy testing of particle breakability, a useful tool for assessing attrition in process plant and grindability in milling operations.

Evaluation of effects of pharmaceutical processing on structural disorders of active pharmaceutical ingredient crystals using nanoindentation and high-resolution total scattering pair distribution function analysis.

Pharmaceutical unit operations such as milling and compaction can often generate disordered regions in crystals of active pharmaceutical ingredients (APIs). This may lead to changes in a number of important pharmaceutical properties including dissolution, stability, hygroscopicity, and so on. It is therefore important for pharmaceutical industry to evaluate the effects of pharmaceutical processing on API structural orders, and to investigate and develop analytical tools that are capable of accurately detecting and assessing subtle process-induced structural disorders in pharmaceutical crystals. In this study, nanoindentation was first used to determine the intrinsic mechanical properties including hardness and Young's modulus of two API crystals, compounds 1 and 2. These crystals of different mechanical properties were then milled and compacted under various conditions. The resulting structural disorders in these crystals were subsequently evaluated using synchrotron-based high-resolution total scattering pair distribution function (TS-PDF) analysis. Furthermore, principal component analysis was applied to the PDF data to assess the relative extents of disorders in the API crystals, which showed a good correlation with the process conditions. The study demonstrates that high-resolution TS-PDF analysis coupled with nanoindentation measurement is a valuable and effective tool for detecting and assessing process-induced subtle structural disorders in API crystals.

Effect of milling on particle shape and surface energy heterogeneity of needle-shaped crystals.

PURPOSE: Milling and micronization of particles are routinely employed in the pharmaceutical industry to obtain small particles with desired particle size characteristics. The aim of this study is to demonstrate that particle shape is an important factor affecting the fracture mechanism in milling. METHODS: Needle-shaped crystals of the ß polymorph of D-mannitol were prepared from recrystallization in water. A portion of the recrystallized materials was ball-milled. Unmilled and milled sieved fractions of recrystallized D-mannitol were analyzed by dynamic image analysis (DIA) and inverse gas chromatography (IGC) at finite concentration to explain the breakage/fracture behavior. RESULTS: In the process of ball-milling, D-mannitol preferentially fractured along their shortest axis, exposing (011) plane with increased hydrophilicity and increased bounding rectangular aspect ratio. This is in contrary to attachment energy modeling which predicts a fracture mechanism across the (010) plane with increased hydrophobicity, and small change in particle shape. CONCLUSIONS: Crystal size, and more importantly, crystal shape and facet-specific mechanical properties, can dictate the fracture/cleavage behavior of organic crystalline materials. Thorough understanding of the crystal slip systems, combining attachment energy prediction with particle shape and surface characterization using DIA and IGC, are important in understanding fracture behavior of organic crystalline solids in milling and micronization.

Influence of fines on the surface energy heterogeneity of lactose for pulmonary drug delivery.

The effects of the blending of lactose fines to the overall adhesion property of coarse alpha-lactose monohydrate carrier particles were investigated. Five samples, three of them commercial samples from DOMO (Lactohale) LH100, LH210, and LH250) whilst the other two are blends of LH210 and LH250, were studied. Characterisation included particle sizing, SEM, PXRD and IGC. Dispersive surface energy gamma(SV)(d) was determined using a finite concentration IGC method to obtain a distribution profile. The gamma(SV)(d) distribution of lactose crystals was found to vary from 40 to 48mJ/m(2). The unmilled coarse crystalline lactose sample (LH100) gamma(SV)(d) was lowest and showed less heterogeneity than the milled sample (LH250). Fines (LH210) were found to have the highest gamma(SV)(d) value. The samples with loaded LH210 were found to have a higher energy than LH100. The amount of LH210 in Blend 1 was not able to decrease surface energy heterogeneity, whereas sample Blend 2 showed adequate loading of fines to obtain a relatively homogeneous surface. Addition of fines resulted in an increase in gamma(SV)(d), suggesting that coarse lactose surfaces were replaced by surfaces of the fines. Increasing the loading of fines may result in a more homogeneous surface energy of lactose particles.

Determination of surface heterogeneity of D-mannitol by sessile drop contact angle and finite concentration inverse gas chromatography.

The sensitivity of two techniques in tracking changes in surface energetics was investigated for a crystalline excipient, D-mannitol. Macroscopic crystals of D-mannitol were grown from saturated water solution by slow cooling, and sessile drop contact angle was employed to measure the anisotropic surface energy. The facet-specific surface energy was consistent with localised hydroxyl group concentrations determined by X-ray photoelectron spectroscopy (XPS), and was also in excellent agreement with the surface energy distribution of the powder form of mannitol measured via a new methodology using inverse gas chromatography (IGC) at finite concentrations. The gamma(SV)(d) was found to vary between 39.5 mJ/m(2) and 44.1 mJ/m(2) for contact angle and between 40 mJ/m(2) and 49 mJ/m(2) for IGC measurements. We report here, a high level of surface heterogeneity on the native mannitol crystal surfaces. When the surfaces of both D-mannitol samples (powder and large single crystals) were modified by dichlorodimethylsilane to induce surface hydrophobicity, both IGC and contact angle revealed a homogeneous surface due to functionalisation of mannitol crystal surface with methyl groups resulting in gamma(SV)(d) of approximately 34 mJ/m(2). It was shown that both IGC and contact angle techniques are able to detect surface chemical variations and detailed surface energetic distribution.

The use of murine embryonic stem cells, alginate encapsulation, and rotary microgravity bioreactor in bone tissue engineering.

The application of embryonic stem cells (ESCs) in bone tissue engineering and regenerative medicine requires the development of suitable bioprocesses that facilitate the integrated, reproducible, automatable production of clinically-relevant, scaleable, and integrated bioprocesses that generate sufficient cell numbers resulting in the formation of three-dimensional (3D) mineralised, bone tissue-like constructs. Previously, we have reported the enhanced differentiation of undifferentiated mESCs toward the osteogenic lineage in the absence of embryoid body formation. Herein, we present an efficient and integrated 3D bioprocess based on the encapsulation of undifferentiated mESCs within alginate hydrogels and culture in a rotary cell culture microgravity bioreactor. Specifically, for the first 3 days, encapsulated mESCs were cultured in 50% (v/v) HepG2 conditioned medium to generate a cell population with enhanced mesodermal differentiation capability followed by osteogenic differentiation using osteogenic media containing ascorbic acid, beta-glycerophosphate and dexamethasone. 3D mineralised constructs were generated that displayed the morphological, phenotypical, and molecular attributes of the osteogenic lineage, as well mechanical strength and mineralised calcium/phosphate deposition. Consequently, this bioprocess provides an efficient, automatable, scalable and functional culture system for application to bone tissue engineering in the context of macroscopic bone formation.