Emerging Applications and Regulatory Strategies for Advanced Medicines Manufacturing - Towards the Development of a Platform Approach.

The last decade has seen Advanced Medicines Manufacturing (AMM) progress from isolated product developments to the creation of industry-academic centres of excellence, regulatory innovation progressing leading to new standards, and product commercialisation across multiple product formats. This paper examines these developments focusing on successful applications and strategies presented at the 2023 Symposium of the International Consortium for Advanced Medicines Manufacturing (ICAMM). Despite these exemplar applications, there remain significant challenges to the sector-wide adoption of AMM technologies.

Computational Modeling for the Oxidation Reactions of the Cysteine Residues with the Superoxide and the Organic Radical Species.

The current computational study analyzes the oxidation reactions of the superoxide and hydroxyl radicals with cysteine residues due to their importance as natural targets to neutralize the harmful reactive oxygen species. Due to the high reactivity of the hydroxyl radicals with the surrounding environment, we also studied the oxidation reactions of organic radicals with cysteine. In addition, we explored the different reaction pathways between cysteine and the superoxide radicals in both anionic and protonated forms.

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics.

Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies.

Differences in human IgG1 and IgG4 S228P monoclonal antibodies viscosity and self-interactions: Experimental assessment and computational predictions of domain interactions.

Human/humanized IgG4 antibodies have reduced effector function relative to IgG1 antibodies, which is desirable for certain therapeutic purposes. However, the developability and biophysical properties for IgG4 antibodies are not well understood. This work focuses on the head-to-head comparison of key biophysical properties, such as self-interaction and viscosity, for 14 human/humanized, and chimeric IgG1 and IgG4 S228P monoclonal antibody pairs that contain the identical variable regions.

Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters.

High viscosity presents a challenge for manufacturing and drug delivery of therapeutic antibodies. The viscosity is determined by protein-protein interactions among many antibodies. Molecular simulation is a promising method to study protein-protein interactions; however, all-atom models do not allow the simulation of multiple molecules, which is necessary to compute viscosity directly.

Machine Learning Applied to Determine the Molecular Descriptors Responsible for the Viscosity Behavior of Concentrated Therapeutic Antibodies.

Predicting the solution viscosity of monoclonal antibody (mAb) drug products remains as one of the main challenges in antibody drug design, manufacturing, and delivery. In this work, the concentration-dependent solution viscosity of 27 FDA-approved mAbs was measured at pH 6.0 in 10 mM histidine-HCl.

Machine Learning Feature Selection for Predicting High Concentration Therapeutic Antibody Aggregation.

Protein aggregation can hinder the development, safety and efficacy of therapeutic antibody-based drugs. Developing a predictive model that evaluates aggregation behaviors during early stage development is therefore desirable. Machine learning is a widely used tool to train models that predict data with different attributes.

Molecular computations of preferential interactions of proline, arginine.HCl, and NaCl with IgG1 antibodies and their impact on aggregation and viscosity.

Preferential interactions of excipients with the antibody surface govern their effect on the stability of antibodies in solution. We probed the preferential interactions of proline, arginine.HCl (Arg.

Machine Learning Models of Antibody-Excipient Preferential Interactions for Use in Computational Formulation Design.

Preferential interactions of formulation excipients govern their impact on the stability properties of proteins in solution. The ability to predict these interactions without the need to perform experiments would enable formulation design to begin early in the development of a new antibody therapeutic. With that in mind, we developed a feature set to numerically describe local regions of an antibody's surface for use in machine learning applications.

Why We Need Continuous Pharmaceutical Manufacturing and How to Make It Happen.

We make the case for why continuous pharmaceutical manufacturing is essential, what the barriers are, and how to overcome them. To overcome them, government action is needed in terms of tax incentives or regulatory incentives that affect time.

Molecular Computations of Preferential Interaction Coefficients of IgG1 Monoclonal Antibodies with Sorbitol, Sucrose, and Trehalose and the Impact of These Excipients on Aggregation and Viscosity.

Preferential interactions of formulation excipients govern their overall interactions with protein molecules, and molecular dynamics simulations allow for the examination of the interactions at the molecular level. We used molecular dynamics simulations to examine the interactions of sorbitol, sucrose, and trehalose with three different IgG1 antibodies to gain insight into how these excipients impact aggregation and viscosity. We found that sucrose and trehalose reduce aggregation more than sorbitol because of their larger size and their stronger interactions with high-spatial aggregation propensity residues compared to sorbitol.

Achieving continuous manufacturing in lyophilization: Technologies and approaches.

This paper provides an organic overview of the most interesting continuous freeze-drying concepts that have been proposed over the years. Attention has mainly been focused on the field of pharmaceuticals, but some background has also been given on the food industry. This work aims at providing a solid starting point for future research on continuous manufacturing for the freeze-drying of pharmaceuticals.

On computing the solubility of molecular systems subject to constraints using the extended Einstein crystal method.

A method to compute solubilities for molecular systems using atomistic simulations, based on an extension of the Einstein crystal method, has recently been presented [Li et al., J. Chem.

Understanding the Role of Preferential Exclusion of Sugars and Polyols from Native State IgG1 Monoclonal Antibodies and its Effect on Aggregation and Reversible Self-Association.

Purpose: To investigate differences in the preferential exclusion of trehalose, sucrose, sorbitol and mannitol from the surface of three IgG1 monoclonal antibodies (mAbs) and understand its effect on the aggregation and reversible self-association of mAbs at high-concentrations.

Methods: Preferential exclusion was measured using vapor pressure osmometry. Effect of excipient addition on accelerated aggregation kinetics was quantified using size exclusion chromatography and on reversible self-association was quantified using dynamic light scattering.

Solubility of paracetamol in ethanol by molecular dynamics using the extended Einstein crystal method and experiments.

Li and co-workers [Li et al., J. Chem.

Kirkwood-Buff-Derived Alcohol Parameters for Aqueous Carbohydrates and Their Application to Preferential Interaction Coefficient Calculations of Proteins.

The CHARMM36 carbohydrate parameter set did not adequately reproduce experimental thermodynamic data of carbohydrate interactions with water or proteins or carbohydrate self-association; thus, a new nonbonded parameter set for carbohydrates was developed. The parameters were developed to reproduce experimental Kirkwood-Buff integral values, defined by the Kirkwood-Buff theory of solutions, and applied to simulations of glycerol, sorbitol, glucose, sucrose, and trehalose. Compared to the CHARMM36 carbohydrate parameters, these new Kirkwood-Buff-based parameters reproduced accurately carbohydrate self-association and the trend of activity coefficient derivative changes with concentration.

General Method for the Identification of Crystal Faces Using Raman Spectroscopy Combined with Machine Learning and Application to the Epitaxial Growth of Acetaminophen.

Crystal morphology is one of the key crystallographic characteristics that governs the macroscopic properties of crystalline materials. The identification of crystal faces, or face indexing, is an important technique that is used to get information regarding a crystal's morphology. However, it is mainly limited to single crystal X-ray diffraction (SCXRD) and it is often not applicable to products of routine crystallizations becasue it requires high quality single crystals in a narrow size range.

Nucleation of Molecular Crystals Driven by Relative Information Entropy.

Simulating nucleation of molecular crystals is extremely challenging for all but the simplest cases. The challenge lies in formulating effective order parameters that are capable of driving the transition process. In recent years, order parameters based on molecular pair-functions have been successfully used in combination with enhanced sampling techniques to simulate nucleation of simple molecular crystals.

Demonstration of pharmaceutical tablet coating process by injection molding technology.

We demonstrate the coating of tablets using an injection molding (IM) process that has advantage of being solvent free and can provide precision coat features. The selected core tablets comprising 10% w/w griseofulvin were prepared by an integrated hot melt extrusion-injection molding (HME-IM) process. Coating trials were conducted on a vertical injection mold machine.

Tablet coating by injection molding technology - Optimization of coating formulation attributes and coating process parameters.

We developed and evaluated a solvent-free injection molding (IM) coating technology that could be suitable for continuous manufacturing via incorporation with IM tableting. Coating formulations (coating polymers and plasticizers) were prepared using hot-melt extrusion and screened via stress-strain analysis employing a universal testing machine. Selected coating formulations were studied for their melt flow characteristics.

Integrated hot-melt extrusion - injection molding continuous tablet manufacturing platform: Effects of critical process parameters and formulation attributes on product robustness and dimensional stability.

This study provides a framework for robust tablet development using an integrated hot-melt extrusion-injection molding (IM) continuous manufacturing platform. Griseofulvin, maltodextrin, xylitol and lactose were employed as drug, carrier, plasticizer and reinforcing agent respectively. A pre-blended drug-excipient mixture was fed from a loss-in-weight feeder to a twin-screw extruder.

Retracted: Molecular characterization of excipients' preferential interactions with therapeutic monoclonal antibodies.

Retraction: Molecular characterization of excipients' preferential interactions with therapeutic monoclonal antibodies by Jehoon Kim, Mark R. H. Krebs and Bernhardt L.

Preferential interactions of trehalose, L-arginine.HCl and sodium chloride with therapeutically relevant IgG1 monoclonal antibodies.

Preferential interactions of weakly interacting formulation excipients govern their effect on the equilibrium and kinetics of several reactions of protein molecules in solution. Using vapor pressure osmometry, we characterized the preferential interactions of commonly used excipients trehalose, L-arginine.HCl and NaCl with three therapeutically-relevant, IgG1 monoclonal antibodies that have similar size and shape, but differ in their surface hydrophobicity and net charge.

Development of Maltodextrin-Based Immediate-Release Tablets Using an Integrated Twin-Screw Hot-Melt Extrusion and Injection-Molding Continuous Manufacturing Process.

The combination of hot-melt extrusion and injection molding (HME-IM) is a promising process technology for continuous manufacturing of tablets. However, there has been limited research on its application to formulate crystalline drug-containing immediate-release tablets. Furthermore, studies that have applied the HME-IM process to molded tablets have used a noncontinuous 2-step approach.