Industrial application of heat- and mass balance model for fluid-bed granulation for technology transfer and design space exploration.

This work demonstrates the application of state-of-the-art modeling techniques in pharmaceutical manufacturing for fluid bed granulation at varying scales to successfully predict process conditions and ultimately replace experiments during a technology transfer of five products. We describe a mathematical model able to simulate the time-dependent moisture profile in a fluid bed granulation process. The applicability of this model is then demonstrated by calibrating and validating it over a range of operating conditions, manufacturing scales, and formulations. The inherent capability of the moisture profile to serve as a simple, scale-independent surrogate is shown by the large number of successful scale-ups and transfers. A methodology to use this 'digital twin' to systematically explore the effects of uncertainty inherent in the process input and model parameter spaces and their impact on the process outputs is described. Two case studies exemplifying the utilization of the model in industrial practice to assess process robustness are provided. Lastly, a pathway to leverage model results to establish proven acceptable ranges for individual parameters is outlined.

Modeling of pan coating processes: Prediction of tablet content uniformity and determination of critical process parameters.

We developed an engineering model for predicting the active pharmaceutical ingredient (API) content uniformity (CU) for a drug product in which the active is coated onto a core. The model is based on a two-zone mechanistic description of the spray coating process in a perforated coating pan. The relative standard deviation (RSD) of the API CU of the coated tablets was found to be inversely proportional to the square root of the total number of cycles between the spray zone and drying zone that the tablets undergo. The total number of cycles is a function of the number of tablets in the drying zone, the spray zone width, the tablet velocity, the tablet number density, and the total coating time. The sensitivity of the RSD to various critical coating process parameters, such as pan speed, pan load, spray zone width, as well as tablet size and shape was evaluated. Consequently, the critical coating process parameters needed to achieve the desired API CU were determined. Several active film coating experiments at 50, 200, and 400 kg using various pan coaters demonstrated that good correlation between the model predictions and the experimental results for the API CU was achieved.

Experimental and model-based approaches to studying mixing in coating pans.

The focus of this study was the determination of mixing patterns and rates inside a cylindrical coating pan. The research for this study was divided into two parts. The first part examined the mixing pattern and the movement of tablets inside of a coating pan experimentally. The second part consisted of using a DEM (Discrete Element Model) simulation to evaluate mixing in the coating pan in silico. Mixing was investigated as a function of the rate of rotation of the pan and the number of revolutions. Mixing rates were measured in two directions--axial--from the front of the unit to the back of the unit along its axis and radial/angular--in the plane orthogonal to its axis. Radial/angular mixing was faster than axial mixing--the coating pan was found to be well-mixed across the axis within 2-8 revolutions as compared to 16-32 revolutions needed for the pan to be well-mixed along the axis. The DEM simulation used for this study is capable of predicting how fast the tablets mix in the coating pan. It does so by explicitly modeling the motion of individual tablets in the unit. Model predictions were verified by comparing the simulated mixing in the coating pan to the experiments. The simulated mixing process is found to be slightly slower than the experimentally observed mixing, which means that the simulations give a conservative estimate of mixing rates. The model can also be used to calculate the residence time distribution of the tablets in a spray zone of a given area.

Effects of chain length on the aggregation of model polyglutamine peptides: molecular dynamics simulations.

Aggregation in the brain of polyglutamine-containing proteins is either a cause or an associated symptom of nine hereditary neurodegenerative disorders including Huntington's disease. The molecular level mechanisms by which these proteins aggregate are still unclear. In an effort to shed light on this important phenomenon, we are investigating the aggregation of model polyglutamine peptides using molecular-level computer simulation with a simplified model of polyglutamine that we have developed. This model accounts for the most important types of intra- and inter-molecular interactions-hydrogen bonding and hydrophobic interactions-while allowing the folding process to be simulated in a reasonable time frame. The model is used to examine the folding of isolated polyglutamine peptides 16, 32, and 48 residues long and the folding and aggregation of systems of 24 model polyglutamine peptides 16, 24, 32, 36, 40, and 48 residues long. Although the isolated polyglutamine peptides did form some alpha and beta backbone-backbone hydrogen bonds they did not have as many of these bonds as they would have if they had folded into a complete alpha helix or beta sheet. In one of the simulations on the isolated polyglutamine peptide 48 residues long, we observed a structure that resembles a beta helix. In the multi-chain simulations we observed amorphous aggregates at low temperatures, ordered aggregates with significant beta sheet character at intermediate temperatures, and random coils at high temperatures. We have found that the temperature at which the model peptides undergo the transition from amorphous aggregates to ordered aggregates and the temperature at which the model peptides undergo the transition from ordered aggregates to random coils increase with increasing chain length. Our finding that the stability of the ordered aggregates increases as the peptide chain length increases may help to explain the experimentally observed relation between polyglutamine tract length and aggregation in vitro and disease progression in vivo. We have also observed in our simulations that the optimal temperature for the formation of beta sheets increases with chain length up to 36 glutamine residues but not beyond. Equivalently, at fixed temperature we find a transition from a region dominated by random coils at chain lengths less than 36 to a region dominated by relatively ordered beta sheet structures at chain lengths greater than 36. Our finding of this critical chain length of 36 glutamine residues is interesting because a critical chain length of 37 glutamine residues has been observed experimentally.

Spontaneous formation of annular structures observed in molecular dynamics simulations of polyglutamine peptides.

Annular structures have been observed experimentally in aggregates of polyglutamine-containing proteins and other proteins associated with diseases of the brain. Here we report the observation of annular structures in molecular-level simulations of large systems of model polyglutamine peptides. A system of 24 polyglutamine chains 16 residues long at a concentration of 5 mM spontaneously formed large beta sheets which curved to form tube-like annular structures that resemble beta barrels. This work was accomplished by extending the PRIME model to polyglutamine. PRIME is an off-lattice, unbiased, intermediate-resolution protein model based on an amino acid representation of between three and seven united atoms depending on the residue being modeled. Our results are interesting not only because of the recent discovery of tubular protofibrils in experiments on aggregation of mutant huntingtin fragments containing expanded polyglutamine tracts but also because Perutz predicted that polyglutamine forms water filled nanotubes.

Side-chain interactions determine amyloid formation by model polyglutamine peptides in molecular dynamics simulations.

The pathological manifestation of nine hereditary neurodegenerative diseases is the presence within the brain of aggregates of disease-specific proteins that contain polyglutamine tracts longer than a critical length. To improve our understanding of the processes by which polyglutamine-containing proteins misfold and aggregate, we have conducted molecular dynamics simulations of the aggregation of model polyglutamine peptides. This work was accomplished by extending the PRIME model to polyglutamine. PRIME is an off-lattice, unbiased, intermediate-resolution protein model based on an amino acid representation of between three and seven united atoms, depending on the residue being modeled. The effects of hydrophobicity on the system are studied by varying the strength of the hydrophobic interaction from 12.5% to 5% of the hydrogen-bonding interaction strength. In our simulations, we observe the spontaneous formation of aggregates and annular structures that are made up of beta-sheets starting from random configurations of random coils. This result was interesting because tubular protofibrils were recently found in experiments on polyglutamine aggregation and because of Perutz's prediction that polyglutamine would form water-filled nanotubes.

Solvent effects on the conformational transition of a model polyalanine peptide.

We have investigated the folding of polyalanine by combining discontinuous molecular dynamics simulation with our newly developed off-lattice intermediate-resolution protein model. The thermodynamics of a system containing a single Ac-KA(14)K-NH(2) molecule has been explored by using the replica exchange simulation method to map out the conformational transitions as a function of temperature. We have also explored the influence of solvent type on the folding process by varying the relative strength of the side-chain's hydrophobic interactions and backbone hydrogen bonding interactions. The peptide in our simulations tends to mimic real polyalanine in that it can exist in three distinct structural states: alpha-helix, beta-structures (including beta-hairpin and beta-sheet-like structures), and random coil, depending upon the solvent conditions. At low values of the hydrophobic interaction strength between nonpolar side-chains, the polyalanine peptide undergoes a relatively sharp transition between an alpha-helical conformation at low temperatures and a random-coil conformation at high temperatures. As the hydrophobic interaction strength increases, this transition shifts to higher temperatures. Increasing the hydrophobic interaction strength even further induces a second transition to a beta-hairpin, resulting in an alpha-helical conformation at low temperatures, a beta-hairpin at intermediate temperatures, and a random coil at high temperatures. At very high values of the hydrophobic interaction strength, polyalanines become beta-hairpins and beta-sheet-like structures at low temperatures and random coils at high temperatures. This study of the folding of a single polyalanine-based peptide sets the stage for a study of polyalanine aggregation in a forthcoming paper.