Nonsmooth Modeling for Simulation and Optimization of Continuous Pharmaceutical Manufacturing Processes

During continuous manufacturing, there may be some out of specification tablets that need to be diverted in real time, in order to ensure the quality of the final product. Specifically, the content uniformity of each tablet must be guaranteed before it can be released to market. However, currently, no methods or tools are available that can assure the content uniformity and divert the non-confirming products in real time. The aim of this work is to develop and evaluate a strategy to divert the non-confirming tablets in real time and thereby assure drug concentration of final tablets. This work has been conducted in silico using a combination of MATLAB and Simulink. A methodology to implement a residence time distribution (RTD)-based control system for drug concentration-based tablet diversion which uses the convolution integral was developed and implemented in MATLAB. Comparisons between the performance of “fixed window” and “RTD-based” approaches for diversion have also been presented and used to assess optimal usability. In this work, two novel strategies namely, “fixed window approach” and “RTD-based approach” have been developed and evaluated for real-time diversion of non-confirming tablets. The RTD-based control system was designed, developed, and implemented in silico. A framework for its implementation in a real-time system has also been elaborated on. This methodology was compared to an alternative fixed window approach. The proposed control system is analyzed for various manufacturing scenarios, systems, and disturbances. A comparison of the two proposed strategies suggests that the “RTD-based control system” is more efficient in every simulated scenario. The relative performance is best when the disturbances in the system are characterized by short pulse-like changes.

Conventional nanoparticle manufacturing techniques remain costly, labor-intensive, and difficult to scale, while also being subject to batch-to-batch variability. These limitations hinder their clinical translation, particularly in first-in-human trials. Emerging transformative technologies such as microfluidics and three-dimensional (3D) printing offer opportunities to develop agile, continuous, and scalable manufacturing processes. This study aims to demonstrate the feasibility of continuous microfluidic production of nanoparticles using customizable 3D-printed chips, integrated with atomization technologies, to generate solid nano-enabled controlled release therapies. 3D-printed microfluidic chips were designed using computational fluid dynamics (CFD) to optimize flow characteristics. Nifedipine (NFD)-loaded nanoparticles were continuously manufactured with Eudragit L-100 and subsequently embedded into pullulan microparticles by spray-drying, yielding nano-in-microparticles (NIM). Particle size, encapsulation efficiency, solid-state properties,permeability, and release kinetics were assessed inex vivoFranz cell studies across porcine intestinal membranes. Continuous microfluidic processing produced NFD-loaded nanoparticles with 95% encapsulation efficiency. Spray-drying yielded spherical pullulan-based NIMs of ~ 10 µm, which, upon rehydration, released NFD nanoparticles of ~ 100 nm. The nanoparticles retained their amorphous state and displayed a three-fold increase in intestinal permeability compared to free drug, accompanied by a three-fold reduction in lag time. Release studies demonstrated reduced burst release and a sustained zero-order release profile over 24 h, favorable for blood pressure maintenance therapy. The integration of 3D-printed microfluidic chip design with continuous manufacturing and spray-drying enables scalable production of solid nano-enabled therapies. The NFD-loaded NIMs demonstrated enhanced permeability and controlled release, supporting the potential of this platform for the clinical translation of nanomedicines.

The pharmaceutical industry has traditionally employed batch processing as a means of synthesizing active pharmaceutical ingredients (APIs) on a commercial scale. Batch manufacturing enables API synthesis in large quantities in order to meet regulations. Yet, this strategy remains cumbersome, is labor‐intensive, and creates complex logistical networks. In recent decades, batch API processing has gradually eroded American economic competitiveness and has led to the offshoring of API manufacturing from the United States. Today it is estimated that +80% of APIs are manufactured overseas.[1] Meanwhile, disruptions from the Coronavirus Disease (SARS‐CoV‐2) have exacerbated weaknesses in the global supply chain, culminating with widespread shortages of critical life‐saving drugs.[2] These shortages have emphasized the importance of reshoring drug manufacturing to the U.S. and fostered a regulatory landscape that seeks advanced methods of API manufacturing in order to bolster America's supply chain resiliency.[3] Recently, increased attention has been directed towards continuous drug manufacturing to enable nonstop API production within modular stand‐alone flow systems. Continuous manufacturing (CM) facilitates modular automation, offers new avenues towards process intensification, and even enables in‐line analytical monitoring from raw materials to packaged products. This strategy offers better conversion, increased safety, reduced waste, and overall cost savings versus traditional batch‐style processing. The rise of advanced API manufacturing, coupled with the current regulatory landscape, offers a rare window of opportunity to convert traditional batch pharmaceutical processes into continuous, streamlined production systems to on‐shore API manufacturing and eliminate drug shortages. This review will outline the current state‐of‐the‐art in the CM of APIs and will highlight the translation of chemistry and unit operations from batch processes to modular CM systems.

A near-infrared (NIR) calibration was developed using an efficient offline approach to enable a quantitative partial least-squares (PLS) chemometric model to measure and monitor the concentration of active pharmaceutical ingredients (API) in powder blends in the feed frame (FF) of a tablet press. The approach leveraged an offline "feed frame table," which was designed to mimic the full process from a NIR measurement perspective, thereby facilitating a more robust model by allowing more sources of variability to be included in the calibration by minimizing the consumption of API and other raw materials. The design of experiment (DOE) for the calibration was established by an initial risk assessment and included anticipated variability from factors related to formulation, process, environment, and instrumentation. A test set collected on the feed frame table was used to refine the PLS model. Additional fully independent test sets collected from the continuous drug product manufacturing process not only demonstrated the accuracy and precision of the model but also illustrated its robustness to material variability and process variability including mass flow rate and feed frame paddle speed. Further, it demonstrated that a calibration can be generated on the offline feed frame table and then successfully implemented on the full process equipment in a robust manner. Additional benefits of using the feed frame table include streamline model monitoring and maintenance activities in a manufacturing setting. The real-time monitoring enabled by this offline calibration approach can be useful as a key component of the control strategy for continuous manufacturing processes for drug products, including detecting special cause variations such as transient disturbances and enabling product collection/rejection based upon predetermined concentration limits, and may play an important role in enabling real-time release testing (RTRt) for manufactured pharmaceutical products.

The wet granulation route of tablet manufacturing in a pharmaceutical manufacturing process is very common due to its numerous processing advantages such as enhanced powder flow and decreased segregation. However, this route is still operated in batch mode with little (if any) usage of an automatic control system. Tablet manufacturing via wet granulation, integrated with online/inline real time sensors and coupled with an automatic feedback control system, is highly desired for the transition of the pharmaceutical industry toward quality by design as opposed to quality by testing. In this manuscript, an efficient, plant-wide control strategy for an integrated continuous pharmaceutical tablet manufacturing process via wet granulation has been designed in silico. An effective controller parameter tuning strategy involving an integral of time absolute error method coupled with an optimization strategy has been used. The designed control system has been implemented in a flowsheet model that was simulated in gPROMS (Process System Enterprise) to evaluate its performance. The ability of the control system to reject the unknown disturbances and track the set point has been analyzed. Advanced techniques such as anti-windup and scale-up factor have been used to improve controller performance. Results demonstrate enhanced achievement of critical quality attributes under closed-loop operation, thus illustrating the potential of closed-loop feedback control in improving pharmaceutical tablet manufacturing operations.

On-line monitoring of blend uniformity in continuous drug product manufacturing process—The impact of powder flow rate and the choice of spectrometer: Dispersive vs. FT

In this paper, we propose a novel mathematical model for the integrated optimization for production planning, scheduling, and dynamic optimization of continuous manufacturing processes. With a novel approach to estimate the inventory cost, the integrated problem is first formulated as a mixed-integer dynamic optimization (MIDO) problem, which is then reformulated into a large scale mixed-integer nonlinear program (MINLP). By using metamodeling to characterize the detailed linking information between different decision layers, we develop an efficient solution method to decompose the integrated MINLP into a mixed-integer linear program (MILP) for an integrated planning and scheduling problem with flexible recipes, and a set of dynamic optimization problems for generating metamodels. We further apply a bilevel decomposition algorithm to improve the computational efficiency of solving the integrated planning and scheduling problem with flexible recipes. The proposed models and algorithms are demonstrated through case studies of methyl methacrylate (MMA) polymerization processes. The results show that the proposed methods reduce the computational time by more than 2 orders of magnitude compared with the approach of solving the entire integrated optimization problem directly.

Advances in manufacturing technology coupled with the increased potency of new biotherapeutic modalities have created an external environment where continuous manufacturing (CM) can address a growing need. Amgen has successfully implemented a hybrid CM process for a commercial lifecycle program. In this process, the bioreactor, harvest, capture column, and viral inactivation/depth filtration unit operations were integrated together in an automated, continuous module, while the remaining downstream unit operations took place in stand-alone batch mode. CM operations are particularly suited for so-called "high mix, low volume" manufacturing plants, where a variety of molecules are manufactured in relatively low volumes. The selected molecule fit this mold and was manufactured in a low-capital micro-footprint suite attached to an existing therapeutic production facility. Use of a hybrid process within an already operating facility required less capital and minimized complexity. To enable this hybrid CM process, an established fed-batch process was converted to a perfusion process with continuous harvest. Development efforts included both process changes and the generation of a novel cell line adapted to long-term perfusion. Chromatography resins were updated, and purification processes adapted to handle variable inputs due to the fluctuations in harvest titer from the lengthy production process. A novel automated single-use (SU) viral inactivation (VI) skid was introduced, which entailed the development of a robust pH verification and alarm system, along with procedures for product isolation to allow discard of specific cycles. The CM process demonstrated consistent performance, meaning it met predefined performance criteria (including product quality attributes, or PQAs) when operated within established process parameters and manufactured according to applicable procedures. Using a 75% reduction in scale, it resulted in a five-fold reduction in process media and buffer usage, a fifteen-fold increase in mass per thaw, and an overall process productivity increase of 45-fold (as measured by grams drug substance per liter per day.) The hybrid CM process also enabled increased material demand to be met with no change in cost of goods manufactured or plant capacity, due to the repurposing of existing facility space and the flexible duration of the hybrid CM harvest. Overall, the success of the hybrid CM platform represents an exciting opportunity to reduce costs and increase process efficiency in industry.

There has been a noticeable shift from pharmaceutical batch processing towards a more continuous mode of manufacture for solid oral dosage forms. Continuous solid oral dose processes would not be possible in the absence of a highly accurate feeding system. The performance of feeders defines the content of formulations and is therefore a critical operation in continuous manufacturing of solid dosage forms. It was the purpose of this review to review the role of the initial powder feeding step in a continuous manufacturing process. Different feeding mechanisms are discussed with a particular emphasis on screw controlled loss in weight (LIW) feeding. The importance of understanding the physical properties of the raw materials and its impact on the feeding process is reviewed. Prior knowledge of materials provides an initial indication of how the powders will behave through processing and facilitates in the selection of the most suitable (i) feeder (capacity), (ii) feeding mechanism, and (iii) in the case of screw feeder – screw type. The studies identified in this review focus on the impact of material on powder feeding performance.

In this work, real-time optimization (RTO) schemes are proposed and applied on a continuous pharmaceutical manufacturing process which consists of three units: synthesis unit, hot melt extrusion unit and direct compaction line. The developed RTO strategies calculate the operating conditions by optimizing the considered objective functions while satisfying the specific constraints. Moreover, the RTO schemes can cope with intentional changes in the process and unintentional changes such as disturbances. Results from simulations and experiments are presented in this work. An advantageous performance is achieved when using the developed schemes.

A systematic methodology for the design of continuous active pharmaceutical ingredient production processes

A novel manufacturing strategy based on continuous processing, integrated with online/inline monitoring tools, coupled with an advanced automatic feedback control system is highly desired for efficient Quality by Design (QbD)-based manufacturing of the next generation of pharmaceutical products with optimal consumption of time, space and resources. In this work, an advanced hybrid MPC-PID control system as well as a simpler PID controller for a direct compaction continuous tablet manufacturing process has been designed and implemented for a pilot-scale pharmaceutical process. An NIR sensor, an online NIR prediction tool, a PAT data management tool, an OPC communication protocol, a standard control platform and control hardware have been used to close the control loop. A systematic methodology to design and implement the control system has been also proposed. A control framework with features such as the option to run the plant in open-loop as well as in a closed-loop scenario has been developed. Furthermore, within the closed-loop scenario, options for a simpler PID, a dead time compensator (Smith predictor) as well as an advanced model predictive controller have been included. The feature to run the control strategy in simulation mode has been added to the control platform to facilitate virtual control system design and performance evaluation. Two case studies involving a direct compaction continuous tablet manufacturing process have been considered to demonstrate the closed-loop operation. Case Study 1 was completed at Rutgers University and constituted the use of a continuous cylindrical blender with a rotating screw. Case Study 2 was based on a continuous tumble mixer and was completed at the University of Puerto Rico—Mayaguez Campus (UPRM).

Nonsmooth differential-algebraic equations in chemical engineering

Adoption of Quality by Design (QbD) principles, regulatory support of QbD, process analytical technology (PAT), and continuous manufacturing are major factors effecting new approaches to pharmaceutical manufacturing and bioprocessing. In this review, we highlight new technology developments, data analysis models, and applications of Raman spectroscopy, which have expanded the scope of Raman spectroscopy as a process analytical technology. Emerging technologies such as transmission and enhanced reflection Raman, and new approaches to using available technologies, expand the scope of Raman spectroscopy in pharmaceutical manufacturing, and now Raman spectroscopy is successfully integrated into real-time release testing, continuous manufacturing, and statistical process control. Since the last major review of Raman as a pharmaceutical PAT in 2010, many new Raman applications in bioprocessing have emerged. Exciting reports of in situ Raman spectroscopy in bioprocesses complement a growing scientific field of biological and biomedical Raman spectroscopy. Raman spectroscopy has made a positive impact as a process analytical and control tool for pharmaceutical manufacturing and bioprocessing, with demonstrated scientific and financial benefits throughout a product’s lifecycle.

A hybrid NIR-soft sensor method for real time in-process control during continuous direct compression manufacturing operations