Sterile Drug Product Manufacturing Research Articles

Data-Driven Approach toward Long-Term Equipment Condition Assessment in Sterile Drug Product Manufacturing.

A two-stage data-driven methodology for long-term equipment condition assessment in drug product manufacturing is presented with a case study for a commercially operating aseptic filling line. The methodology leverages process monitoring data. Sensor measurements are partitioned using process information and maintenance schedules that are available on different databases. Data is processed to tackle heterogeneity in sources and formats. The data is cleaned to remove the effects of short-term variabilities and to enhance underlying long-term trends. Two approaches are presented for data analysis: first, anomaly detection using independent component analysis (ICA), where clusters of outliers are identified. The frequency and timing of such outliers yield important insights regarding maintenance schedules and actions. The second approach enables condition monitoring using principal component analysis (PCA). Long-term operational baselines are identified and shifts therein are linked with different process and equipment faults. This approach highlights the impact of equipment deterioration on shifting operational data baselines and shows the potential for the combined application of ICA and PCA for equipment condition monitoring. It can be applied within predictive maintenance applications where the installation of new specialized sensors is difficult, like in the pharmaceutical industry.

Data-driven equipment condition monitoring and reliability assessment for sterile drug product manufacturing: Method and application for an operating facility

Data-driven equipment condition monitoring is difficult to apply in operating pharmaceutical manufacturing plants. The required revalidation costs and efforts hinder the installation of dedicated sensors. This work proposes a three-step methodology to exploit the existing process monitoring infrastructure to infer equipment condition-related information. The developed methodology addresses the challenges imposed by using process monitoring data for a secondary application. In the detection step of the methodology, batch variations are separated from changes due to underlying equipment deterioration. Principal component analysis is conducted followed by slow feature analysis to extract long-term equipment variations. After identifying relevant shifts in the slow feature baselines, the sources of variations in equipment conditions are traced back to sets of installed sensors in the localization step. The identified sensor sets are used to determine the location and physical type of cause of the changes. Last, in the prevention step, tailored maintenance actions are proposed to avoid potential equipment-related failures. Two case studies are presented to demonstrate the application of the methodology with real industrial data. Data from historical maintenance records in the facility were used to verify the findings from the case study. The successful application provides lessons-learned to include maintenance as part of holistic system design and is an important step towards data-driven equipment reliability assessment and maintenance planning in pharmaceutical manufacturing.

Lead-time and risk reduction assessment of a sterile drug product manufacturing line using simulation

Digital Twins are finding their way into more and more parts of supply chains. Especially in highly regulated manufacturing processes of the pharmaceutical industry, they are becoming an increasingly valuable tool for improving processes without inducing prolonged downtimes, e.g. through virtual tests and virtual scenario analyses.Simulation can serve as a powerful foundation for digital twins, as it e. g. allows for probabilistic assessments and multi-dimensional optimization of highly complex and dynamic processes.In this study, a simulation model is developed as part of the EU research and innovation programme Horizon 2020. The goal is to explore the benefits of a simulation-based approach and quantify the potential for later adoption in a scalable Digital Twin system. The model is applied as a case study on a sterile drug product manufacturing line of the Roche Diagnostics GmbH in Mannheim, Germany.With the model, sensitivity analyses of process steps, campaign building and batch change scenarios, different shift models, scheduling approaches and delivery breakdown risk assessments were conducted. Results underlined the benefits of simulation-based analyses and the potential for adoption of digital twin technologies in the pharmaceutical industry.

Integrated Design of H2O2 Decontamination Processes and Scheduling in Sterile Drug Product Manufacturing

We explored the integrated design of H2O2 decontamination processes and scheduling in sterile drug product manufacturing, considering productivity and product quality. Models were developed that (i) deal with the scheduling of filling and the changeover of multiple batches/products and (ii) configure the aqueous H2O2 injection rate into the isolator as a process parameter. The total production time for all planned batches and the sterility assurance level of the products were defined as the objective functions for productivity and product quality, respectively. The models were applied to a multiobjective evaluation of the decontamination and scheduling options in the production of 15 batches (different products and batch sizes). Pareto-optimal solutions were obtained that indicated a trade-off between the two objectives. The inclination of the Pareto frontier increased when the product became more vulnerable to residual H2O2 after aeration and when the batch size became smaller. The quantitative results confirmed an increased impact of the configuration of the decontamination process on both productivity and product quality. The small batch-size production of H2O2-sensitive products is increasingly popular, especially for biopharmaceuticals, and the results of this study encourage the collaborative development of decontamination processes and production schedules in sterile drug product manufacturing.

Design-oriented regression models for H2O2 decontamination processes in sterile drug product manufacturing considering rapidity and sterility

We developed regression models for designing rapid and effective H2O2 decontamination processes in the manufacturing of sterile drug products such as injectables. Decontamination, which is typically performed by using H2O2, is a critical changeover process used to establish a sterile environment for filling products. In the process, there is a trade-off relationship between the duration of the process and the level of sterility assurance that needs to be considered in the design. Our model defines these two items as objective functions and the parameters describing the profile of H2O2 injection and the initial humidity as design variables. Our model also considers aeration, i.e., removal of H2O2 from the environment, as a part of the entire process. This design-oriented modeling considering the entire process is the novelty of the work. Experiments were performed using an industrial isolator to develop and validate a set of regression models that describe the relationship between the design variables and the objective functions. In the application of the model, Pareto-optimal conditions could be indicated given the target H2O2 concentration in aeration, which is useful for the makers of drugs and/or isolators for designing decontamination processes.

Erratum to: Decision-Support Method for the Choice Between Single-Use and Multi-Use Technologies in Sterile Drug Product Manufacturing

Single-use technology has been applied to sterile drug product manufacturing processes as a new technology in contrast with the conventional multi-use technology. This study proposes a decision-support method for choosing between these two technologies in sterile drug product manufacturing. The proposed method consists of four steps: create process evaluation models, calculate evaluation results, perform what-if analysis, and interpret results. We created models for evaluating the production cost and life cycle CO2 emissions of processes using either technology. “What-if” analysis quantifies the effect of the input parameters on the evaluation results, which supports more informed decision-making. Here, it is recommended that the filling speed, which was found to have a significant impact on filling accuracy—a critical quality attribute of sterile drug products—should be investigated. As a case study, the method was applied in two cases of technology selection: (i) single-batch production of a product with different batch sizes and (ii) single-batch production with different production patterns. The single-use technology showed its economic superiority in producing small batches and in producing multiple small-scale products, whereas in the environmental evaluation, it was always better than multi-use technology. What-if analyses revealed the impact of changing input parameters on the economy, environment, and quality. Our method can support the choice of single-use and multi-use technologies in plants having both technologies independently. In the case study, economic evaluation showed a critical point in each design case, whereas the environmental evaluation result was always better in single-use technology.

Process Model for Enhancing Yield in Sterile Drug Product Manufacturing

Purpose We present a process model for enhancing the yield in the manufacturing of sterile drug products, such as injectables, eye drops, or intravenous bags. The process typically consists of compounding, filtration, filling, and visual inspection and involves raw materials of active pharmaceutical ingredients, water for injection, excipients, and packaging materials.

Innovative approach for identifying root causes of glass defects in sterile drug product manufacturing

In sterile drug product manufacturing, scratched and broken glass containers (i.e., vials) cause product losses, glass particles, equipment contamination and additional cleaning efforts. However, mechanical resistance and exposure of vials to mechanical stress are not sufficiently understood, and no systematic approach for reducing glass-related losses is established. Manufacturers may tackle glass-related losses more rationally if (i) frequencies for inflicting disqualifying damages to drug product containers are known for given forces, (ii) actual exposure in industrial filling lines is quantified and (iii) process enhancements are derived based on collected information.In this work, an innovative approach for exploiting these opportunities, identifying glass defect root causes and reducing glass defects is provided. Devices for quantifying (i) damaging frequencies and (ii) actual exposure are presented and then applied in an industrial case study on sterile drug product manufacturing; finally, (iii) process enhancements are derived and implemented. In the case study, frequencies for scratching vials at given forces as well as breaking forces have been determined. Peak exposure in the investigated filling line was detected at 6 N. As a result of the case study, key machine parts were identified and adjusted.

Multicenter Study on Incubation Conditions for Environmental Monitoring and Aseptic Process Simulation.

Microbiological environmental monitoring and aseptic process simulation confirm that pharmaceutical cleanrooms are in an appropriate hygienic condition for manufacturing of sterile drug products. Guidance documents from different health authorities or expert groups differ regarding recommendation of the applied incubation time and incubation temperature, leading to variable manufacturers practices. Some recent publications have demonstrated that laboratory studies are not relevant to determine the best incubation regime and that in situ manufacturing site studies should be used. To solve any possible bias coming from laboratory studies or single-site in situ studies, we conducted a multicenter study at four manufacturing sites with a significant amount of real environmental monitoring samples collected directly from the environment in pharmaceutical production during manufacturing operations with four solid and liquid nutrient media. These samples were then incubated under four different conditions suggested in the guidance documents. We believe that the results of our multicenter study confirming recent other single-site in situ studies could be the basis of the strategy to determine the best incubation regime for both viable environmental monitoring and aseptic process simulation in any manufacturing facility.

Rigorous approach to scheduling of sterile drug product manufacturing

Abstract Optimizing the scheduling of liquid drug product manufacturing is paramount for pharmaceutical companies in their increasingly competitive environment and requires the modelling of industry-specific constraints. Such constraints include: (i) changing sequence-dependent setup times; (ii) maintaining a sterile production environment (e.g., through sterile holding times); (iii) periods with limited or no plant activity (e.g., no workforce during weekends); and (iv) demand timing (i.e., delivery deadline and release date constraints). In this work, an immediate precedence model is formulated to optimize the scheduling of liquid drug product manufacturing, considering the industry-specific constraints. The primary objective is to minimize the production makespan. Four case studies comprising up to 38 batches from a real multi-product facility illustrate the performance of the rigorous optimization approach. The makespan could be reduced by up to 7.9% compared to expert schedules.

Application of the principles of good manufacturing practices (GMP) to the design and operation of a tissue culture laboratory

Recommendations are presented for the design and operation of a tissue culture laboratory to reduce microbial contamination of cultures. These recommendations are based on practices currently used in the manufacturing of sterile drug products, certain medical devices, and in vitro diagnostic products. The recommendations depend on qualification and validation of equipment, systems, and procedures and on the control and monitoring of the laboratory environment and procedures.