Unraveling the complexity of amorphous solid as direct ingredient for conventional oral solid dosage form: The story of Elagolix Sodium.

Conventional solid oral dosage form development is not typically challenged by reliance on an amorphous drug substance as a direct ingredient in the drug product, as this may result in product development hurdles arising from process design and scale-up, control of physical quality attributes, drug product processability and stability. Here, we present the Chemistry, Manufacturing and Controls development journey behind the successful commercialization of an amorphous drug substance, Elagolix Sodium, a first-in-class, orally active gonadotropin-releasing hormone antagonist. The reason behind the lack of crystalline state was assessed via Molecular Dynamics (MD) at the molecular and inter-molecular level, revealing barriers for nucleation due to prevalence of intra-molecular hydrogen bond, repulsive interactions between active pharmaceutical ingredient (API) molecules and strong solvation effects.

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers.

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities.

Snap-on Adaptor for Microtiter Plates to Enable Continuous-Flow Microfluidic Screening and Harvesting of Crystalline Materials.

Microtiter plate assay is a conventional and standard tool for high-throughput (HT) screening that allows the synthesis, harvesting, and analysis of crystals. The microtiter plate screening assays require a small amount of solute in each experiment, which is adequate for a solid-state crystal analysis such as X-ray diffraction (XRD) or Raman spectroscopy. Despite the advantages of these high-throughput assays, their batch operational nature results in a continuous decrease in supersaturation due to crystal nucleation and growth.

Proof-of-Concept in Developing a 45% Drug Loaded Amorphous Nanoparticle Formulation.

Amorphous solid dispersion (ASD) is an enabling approach utilized to deliver poorly soluble compounds. ASDs can spontaneously generate drug-rich amorphous nanoparticles upon dissolution, which can act as a reservoir for maintaining supersaturation during oral absorption. But, conventional ASDs are often limited in drug loadings to < 20 %.

A comprehensive modeling approach for polymorph selection in Lennard-Jones crystallization.

Computational predictions of the polymorphic outcomes of a crystallization process, referred to as polymorph selection, can accelerate the process development for manufacturing solid products with targeted properties. Polymorph selection requires understanding the interplay between the thermodynamic and kinetic factors that drive nucleation. Moreover, post-nucleation events, such as crystal growth and polymorphic transformation, can affect the resulting crystal structures.

An investigation of the kinetics and thermodynamics of NaCl nucleation through composite clusters.

Having a good understanding of nucleation is critical for the control of many important processes, such as polymorph selection during crystallization. However, a complete picture of the molecular-level mechanisms of nucleation remains elusive. In this work, we take an in-depth look at the NaCl homogeneous nucleation mechanism through thermodynamics.

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.

Modeling Multiphase Heat and Mass Transfer in an Agitated Filter Dryer by Integrating Experiment, Computations, and Analytical Solutions.

The drying of a wet cake consisting of an active pharmaceutical ingredient and solvent in an agitated filter-dryer is a critical and challenging unit operation in the pharmaceutical industry. The complexity of this operation is attributed to the constraints on product quality in terms of its physical properties in addition to the residual solvent content. In this manuscript, a better understanding of the drying mechanism is gained by integrating insights from three-dimensional analytical solutions and computational fluid dynamics simulations into a zero-dimensional model to explain experimental data.

Machine Learning-Driven, Sensor-Integrated Microfluidic Device for Monitoring and Control of Supersaturation for Automated Screening of Crystalline Materials.

Integrating sensors in miniaturized devices allow for fast and sensitive detection and precise control of experimental conditions. One of the potential applications of a sensor-integrated microfluidic system is to measure the solute concentration during crystallization. In this study, a continuous-flow microfluidic mixer is paired with an electrochemical sensor to enable in situ measurement of the supersaturation.

Patterned microfluidic devices for rapid screening of metal-organic frameworks yield insights into polymorphism and non-monotonic growth.

Metal-organic frameworks (MOFs) are porous crystalline structures that are composed of coordinated metal ligands and organic linkers. Due to their high porosity, ultra-high surface-to-volume ratio, and chemical and structural flexibility, MOFs have numerous applications. MOFs are primarily synthesized in batch reactors under harsh conditions and long synthesis times.

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.

Advanced continuous-flow microfluidic device for parallel screening of crystal polymorphs, morphology, and kinetics at controlled supersaturation.

A flow-controlled microfluidic device for parallel and combinatorial screening of crystalline materials can profoundly impact the discovery and development of active pharmaceutical ingredients and other crystalline materials. While the existing continuous-flow microfluidic devices allow crystals to nucleate under controlled conditions in the channels, their growth consumes solute from the solution leading to variation in the downstream composition. The materials screened under such varying conditions are less reproducible in large-scale synthesis.

A CFD Digital Twin to Understand Miscible Fluid Blending.

The mixing of stratified miscible fluids with widely different material properties is a common step in biopharmaceutical manufacturing processes. Differences between the fluid densities and viscosities, however, can lead to order-of-magnitude increase in blend times relative to the blending of single-fluid systems. Moreover, the mixing performance in two-fluid systems can be strongly dependent on the Richardson number defined as the ratio of fluid buoyancy to fluid inertia.

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.

Characterization of the Hydrodynamics in the USP Basket Apparatus Using Computational Fluid Dynamics.

Computational fluid dynamics (CFD) has been extensively used for the USP paddle apparatus II, but limited CFD studies have been conducted on the USP basket apparatus I. We expanded on past CFD basket studies to consider the presence of a tablet inside the basket, compared predictions to in vivo conditions, and confirmed observations around the complexity of nonuniform hydrodynamics. Tablets near the basket perimeter experienced near 5-fold increase in maximum velocity and surface shear stress compared to tablets placed at the center of the basket.

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.

Leveraging Lyophilization Modeling for Reliable Development, Scale-up and Technology Transfer.

Modeling of the lyophilization process, based on the steady-state heat and mass transfer, is a useful tool in understanding and optimizing of the process, developing an operating design space following the quality-by-design principle, and justifying occasional process deviations during routine manufacturing. The steady-state model relies on two critical parameters, namely, the vial heat transfer coefficient, K, and the cake resistance, R. The classical gravimetric method used to measure K is tedious, time- and resource-consuming, and can be challenging and costly for commercial scale dryers.

Continuous-flow, well-mixed, microfluidic crystallization device for screening of polymorphs, morphology, and crystallization kinetics at controlled supersaturation.

Screening of crystal polymorphs and morphology and measurement of crystallization kinetics in a controlled supersaturated environment is crucial for the development of crystallization processes for pharmaceuticals, agrochemicals, semiconductors, catalysts, and other specialty chemicals. Most of the current tools including microtiter plates and droplet-based microfluidic devices suffer from depleting supersaturation in small compartments due to nucleation and growth of crystals. Such variation in supersaturation not only affects the outcome but also leads to impediments during the scale-up of the crystallizer.

Predictive models of lyophilization process for development, scale-up/tech transfer and manufacturing.

Scale-up and technology transfer of lyophilization processes remains a challenge that requires thorough characterization of the laboratory and larger scale lyophilizers. In this study, computational fluid dynamics (CFD) was employed to develop computer-based models of both laboratory and manufacturing scale lyophilizers in order to understand the differences in equipment performance arising from distinct designs. CFD coupled with steady state heat and mass transfer modeling of the vial were then utilized to study and predict independent variables such as shelf temperature and chamber pressure, and response variables such as product resistance, product temperature and primary drying time for a given formulation.

Nanocrystal Dissolution Kinetics and Solubility Increase Prediction from Molecular Dynamics: The Case of α-, β-, and γ-Glycine.

Nanocrystals are receiving increased attention for pharmaceutical applications due to their enhanced solubility relative to their micron-sized counterpart and, in turn, potentially increased bioavailability. In this work, a computational method is proposed to predict the following: (1) polymorph specific dissolution kinetics and (2) the multiplicative increase in the polymorph specific nanocrystal solubility relative to the bulk solubility. The method uses a combination of molecular dynamics and a parametric particle size dependent mass transfer model.

Solubility curves and nucleation rates from molecular dynamics for polymorph prediction - moving beyond lattice energy minimization.

Current polymorph prediction methods, known as lattice energy minimization, seek to determine the crystal lattice with the lowest potential energy, rendering it unable to predict solvent dependent metastable form crystallization. Facilitated by embarrassingly parallel, multiple replica, large-scale molecular dynamics simulations, we report on a new method concerned with predicting crystal structures using the kinetics and solubility of the low energy polymorphs predicted by lattice energy minimization. The proposed molecular dynamics simulation methodology provides several new predictions to the field of crystallization.

Cu-catalyzed couplings of aryl iodonium salts with sodium trifluoromethanesulfinate.

A convenient method for the preparation of aryl trifluoromethylsulfones from the reactions of diaryliodonium salts with sodium trifluoromethanesulfinate in the presence of copper catalysts is described. Cuprous oxide in DMF was found to be the optimal catalyst for the reaction. The reaction conditions are tolerant of various functional groups as well as of various counteranions of the iodonium salt.

Drying process optimization for an API solvate using heat transfer model of an agitated filter dryer.

Drying an early stage active pharmaceutical ingredient candidate required excessively long cycle times in a pilot plant agitated filter dryer. The key to faster drying is to ensure sufficient heat transfer and minimize mass transfer limitations. Designing the right mixing protocol is of utmost importance to achieve efficient heat transfer.