Pressure Rise Test Research Articles

Improvement of a pressure rise test rig for cooling capacity inference of hermetic compressors based on ANNs

Improvement of a pressure rise test rig for cooling capacity inference of hermetic compressors based on ANNs

Model-based design of secondary drying using in-line near-infrared spectroscopy data

This article deals with the design and optimization of the secondary drying stage, via design space calculation, of a freeze-drying process. A simple and well known mathematical model was used to this purpose: the kinetic parameters of the water desorption step were determined, either off-line or in-line, using the measurement of the residual amount of water (Cs ) in one of the processed samples through Near-Infrared spectroscopy. In the first approach, three tests, at different values of heating shelf temperature, are employed: the measurement of Cs versus time allows estimating the desorption rate and, finally, the kinetic constant at the given temperature. Arrhenius plot is used to get the parameters expressing the dependence of the kinetic constant on product temperature, thus allowing the calculation of the design space. In the second approach, the kinetic parameters are estimated in-line, focusing on the first part of the secondary drying stage, where the variation of product temperature is more relevant, hence allowing to track the evolution of the desorption rate (via Cs measurement) versus product temperature. A fitting procedure is then used, looking for the kinetic parameters that provide the best fit between calculated and measured values of Cs . By this way only one test is required to get the design space. Drying of sucrose and of sucrose – arginine mixtures were used as case studies, to point out the effectiveness of the proposed method. Examples of the design spaces that can be obtained are presented and discussed, focusing on the effect of operating parameters like the heating rate and the residual water content at the beginning of the secondary drying, as well as on the constraint about the maximum allowed temperature. Abbreviations: KF: Karl-Fischer; MVA: multivariate analysis; NIR: near-infrared; NIRS: near-infrared spectroscopy; PAT: process analytical technology; PLS: partial least square; PRT: pressure rise test; RM: residual moisture; RMSE: root mean squared error

Development of an EPU vacuum system using lumped NEG-ion combination pumps

A vacuum design based on five lumped ZAO® non-evaporable getter (NEG) pumps (CapaciTorr® Z 200 × 2 and NEXTorr® Z 200 × 3) was developed to construct a vacuum system of elliptically polarized undulator (EPU). The vacuum tests, including measurements of the base pressure and the sorption capacity of CO, and the pressure-rise test on turning off the ion pumps, were performed to evaluate the vacuum performance of this design. Two such EPU vacuum systems were installed in the storage ring of Taiwan Photon Source (TPS) in 2020 and were conditioned with synchrotron radiation, but without baking. The experimental results show that their dynamic pressures achieved less than 3 × 10−12 mbar mA−1 after an accumulated beam dose 100 A h.

Automatic control of a freeze-drying process: Detection of the end point of primary drying

In freeze-drying, the detection of the end of primary drying is a crucial aspect for both the process economics and product quality. Furthermore, the extreme process conditions (low temperature, high vacuum, and sterility) require monitoring devices with a high degree of assurance. In this paper, the most promising methodologies for the detection of the end point of primary drying were investigated and compared. These devices include thermocouples, comparative pressure measurement, condenser pressure, controlled leakage, vacuum shut-off valve, microbalance, mass spectrometers, moisture sensors, and pressure rise test. Furthermore, a multi-scale model of the process was used to describe the process dynamics during the last part of drying, showing that the time difference between the onset and offset points depends on the batch heterogeneity, as well as process conditions and batch size. Ultimately, an automatic stop criterion, named EPD, has been designed and experimentally tested in a wide range of process conditions, batch size, vial size, and drug products. In particular, the experimental validation involved some of the most used excipients as model products, i.e., mannitol, dextran, lactose, and sucrose. In all the runs, the EPD drying times reasonably agreed with the comparative pressure measurement, which was the most reliable way to detect the end of primary drying. Thus, EPD can effectively be used to optimize primary drying without risking the product collapse because of a premature increase in shelf temperature for secondary drying.

Industrial leak testing of dangerous goods packagings

The Dangerous Goods Regulations currently do not include limit leakage rates or sensitivity requirements for industrial leak testing procedures that are equivalent to the bubble test, which is the prescribed test method for design type testing of dangerous goods packagings. During series production of such packagings, various methods are used, which often do not meet the requirements of the bubble test with regard to important criteria.Sensitivity, flow direction, pressure level and automatability are particularly important factors when selecting a suitable industrial leak testing method.The following methods are in principle both suitable and equally effective as the bubble test: pressure rise test (vacuum chamber), ultrasonic bubble leak detection and gas detection methods (pressure technique by accumulation and vacuum chamber technique).To ensure a uniform test level during design type testing and production line leak testing and therefore a comparable safety level as required by the Dangerous Goods Regulations, it is necessary to include a more precise specification in these regulations. This requires, on the one hand, information about the sensitivity of the bubble test and, on the other hand, the inclusion of a list of suitable, equally effective industrial test methods with their specific boundary conditions.

Tuning, measurement and prediction of the impact of freezing on product morphology: A step toward improved design of freeze-drying cycles

The control of freezing is crucial as it can influence the freeze-drying operation as well as the chemical and physical properties of the lyophilized product such as the specific surface area, dissolution rate, and drug stability. In this review article, we focus on two areas related to lyophilization in the pharmaceutical industry: (1) advances in our understanding of the relationship between the freezing conditions, product morphology and drying efficiency, and (2) the control of nucleation in solutions to be frozen. The final objective is to accelerate the transition toward a more robust design of freeze-drying cycles, based on deep knowledge of the phenomena involved rather than on empirical observations. While these topics are not new, they are areas of significant current interest to the community engaged in drying in the pharmaceutical industry.Abbreviations: FDM: freeze-drying microscope; GMP: good manufacturing practice; INA: ice nucleating agent; QbD: quality by design; PRT: pressure rise test; SSA: specific surface area, m2; UIIN: ultrasound-induced ice nucleation; VIN: vacuum induced nucleation; VISF: vacuum induced surface freezing.

Determination of the dried product resistance variability and its influence on the product temperature in pharmaceutical freeze-drying

During the primary drying step of the freeze-drying process, mass transfer resistance strongly affects the product temperature, and consequently the final product quality. The main objective of this study was to evaluate the variability of the mass transfer resistance resulting from the dried product layer (Rp) in a manufacturing batch of vials, and its potential effect on the product temperature, from data obtained in a pilot scale freeze-dryer. Sublimation experiments were run at −25 °C and 10 Pa using two different freezing protocols: with spontaneous or controlled ice nucleation. Five repetitions of each condition were performed. Global (pressure rise test) and local (gravimetric) methods were applied as complementary approaches to estimate Rp. The global method allowed to assess variability of the evolution of Rp with the dried layer thickness between different experiments whereas the local method informed about Rp variability at a fixed time within the vial batch. A product temperature variability of approximately ±4.4 °C was defined for a product dried layer thickness of 5 mm. The present approach can be used to estimate the risk of failure of the process due to mass transfer variability when designing freeze-drying cycle.

Heat Transfer Analysis of an Optimized, Flexible Holder System for Freeze-Drying in Dual Chamber Cartridges Using Different State-of-the-Art PAT Tools

The aim of this study was to determine the heat transfer characteristics of an optimized flexible holder device, using Tunable Diode Laser Absorption Spectroscopy, the Pressure Rise Test, and the gravimetric procedure. Two different controlled nucleation methods were tested, and an improved sublimation process, “preheated plate,” was developed. Tunable Diode Laser Absorption Spectroscopy identified an initial sublimation burst phase. Accordingly, steady-state equations were adapted for the gravimetric procedure, to account for this initial non–steady-state period. The heat transfer coefficient, KDCC, describing the transfer from the holder to the DCC, was the only heat transfer coefficient showing a clear pressure dependence with values ranging from 3.81E−04 cal/(g·cm2·K) at 40 mTorr to 7.38E−04 cal/(g·cm2·K) at 200 mTorr. The heat transfer coefficient, Ktot, reflecting the overall energy transfer via the holder, increased by around 24% from 40 to 200 mTorr. This resulted in a pressure-independent sublimation rate of around 42 ± 1.06 mg/h over the whole pressure range. Hence, this pressure-dependent increase in energy transfer completely compensated the decrease in driving force of sublimation. The “flexible holder” shows a substantially reduced impact of atypical radiation, improved drying homogeneity, and ultimately a better transferability of the freeze-drying cycle for process optimization.

On the use of model-based tools to optimize in-line a pharmaceuticals freeze-drying process

ABSTRACTThis article is focused on the use of model-based tools to design and optimize in-line a pharmaceutical freeze-drying process. Two control systems have been compared, a predictive one that uses the pressure rise test to monitor the state of the system and to estimate in-line the values of model parameters, named LyoDriver in the previous literature, and a controller where a soft sensor uses the temperature measurement obtained by a thermocouple to get the same information and to calculate on-line the design space of the process. In both cases, the goal of the controller is to maintain product temperature as close as possible to a limit value, without trespassing it, throughout the primary drying stage. An extended experimental campaign has been performed, where various products, with different characteristics, have been processed, namely, aqueous solutions containing sucrose, mannitol, or polyvinylpyrrolidone. Results evidence that both systems are effective in optimizing in-line the freeze-drying process, but shorter cycles can be obtained using the soft sensor. This is due to the fact that the soft sensor is not responsible for any product overheating and, thus, product temperature can be maintained very close to the limit value, while when using the pressure rise test as monitoring tool, a safety margin has to be used, because of the temperature increase during the pressure rise test. Besides, when using the soft sensor no least-square optimization problem is solved to estimate model parameters, and this can improve the robustness of the system. The main drawback is represented by the fact that this system requires thermocouples to measure product temperature, and this can be difficult in industrial-scale freeze-dryers, used to process large batches of vials in sterile conditions, but it can be performed quite easily in lab-scale units used for process design.

A New Method Based on the Regression of Step Response Data for Monitoring a Freeze-Drying Cycle

This paper deals with the problem of monitoring the freeze-drying process of thermo-labile products and particularly tracking the temperature and the position of the interface of sublimation. A novel and affordable way is proposed to estimate the vapor flow rate and, thus, retrieve the parameters of interest. This method is referred to as pressure decrease test (PDT) and is based on the shutoff of the controlled leakage valve and on the subsequent model-based analysis of the response of the process. In this paper, a detailed description of the PDT algorithm is given; furthermore, the method was tested upon two placebo formulations, that is, sucrose- and mannitol-based solutions, showing that the tool can give an accurate, complete, and noninvasive estimation of all the parameters of interest. These results also show that the method is a valid solution to various technical problems that arise when attempting to apply other techniques proposed in the literature, for example, the pressure rise test and the tunable diode laser absorption spectroscopy technology.

Monitoring of a Pharmaceuticals Freeze‐Drying Process by Model‐Based Process Analytical Technology Tools

AbstractPharmaceuticals freeze‐drying requires a careful monitoring to preserve product quality. This is a challenging task as it is not possible to measure inline the variables of interest, i.e., temperature and residual amount of ice in the product in the primary drying stage and residual unfrozen water in the secondary drying stage. Various sensors are available to estimate the state of the product, coupling experimental measures and a model of the process. Methods based on the measure of product temperature and on the pressure rise test are discussed and compared by means of experimental investigations. The former is a local intrusive method, as it requires placing thermocouples in various vials, but allows monitoring the batch taking into account its non‐uniformity, while the latter is a global and non‐intrusive method which permits a partial insight into process dynamics.

Quality by design: scale-up of freeze-drying cycles in pharmaceutical industry.

This paper shows the application of mathematical modeling to scale-up a cycle developed with lab-scale equipment on two different production units. The above method is based on a simplified model of the process parameterized with experimentally determined heat and mass transfer coefficients. In this study, the overall heat transfer coefficient between product and shelf was determined by using the gravimetric procedure, while the dried product resistance to vapor flow was determined through the pressure rise test technique. Once model parameters were determined, the freeze-drying cycle of a parenteral product was developed via dynamic design space for a lab-scale unit. Then, mathematical modeling was used to scale-up the above cycle in the production equipment. In this way, appropriate values were determined for processing conditions, which allow the replication, in the industrial unit, of the product dynamics observed in the small scale freeze-dryer. This study also showed how inter-vial variability, as well as model parameter uncertainty, can be taken into account during scale-up calculations.

Monitoring of the Secondary Drying in Freeze-Drying of Pharmaceuticals

This paper is focused on the in-line monitoring of the secondary drying phase of a lyophilization process. An innovative software sensor is presented to estimate reliably the residual moisture in the product and the time required to complete secondary drying, that is, to reach the target value of the residual moisture or of the desorption rate. Such results are obtained by coupling a mathematical model of the process and the in-line measurement of the solvent desorption rate and by means of the pressure rise test or another sensors (e.g., windmills, laser sensors) that can measure the vapor flux in the drying chamber. The proposed method does not require extracting any vial during the operation or using expensive sensors to measure off-line the residual moisture. Moreover, it does not require any preliminary experiment to determine the relationship between the desorption rate and residual moisture in the product. The effectiveness of the proposed approach is demonstrated by means of experiments carried out in a pilot-scale apparatus: in this case, some vials were extracted from the drying chamber and the moisture content was measured to validate the estimations provided by the soft-sensor.

On the Use of Mathematical Models to Build the Design Space for the Primary Drying Phase of a Pharmaceutical Lyophilization Process

The aim of this article is to show a procedure to build the design space for the primary drying of a pharmaceuticals lyophilization process. Mathematical simulation of the process is used to identify the operating conditions that allow preserving product quality and meeting operating constraints posed by the equipment. In fact, product temperature has to be maintained below a limit value throughout the operation, and the sublimation flux has to be lower than the maximum value allowed by the capacity of the condenser, besides avoiding choking flow in the duct connecting the drying chamber to the condenser. Few experimental runs are required to get the values of the parameters of the model: the dynamic parameters estimation algorithm, an advanced tool based on the pressure rise test, is used to this purpose. A simple procedure is proposed to take into account parameters uncertainty and, thus, it is possible to find the recipes that allow fulfilling the process constraints within the required uncertainty range. The same approach can be effective to take into account the heterogeneity of the batch when designing the freeze-drying recipe.

On the Methods Based on the Pressure Rise Test for Monitoring a Freeze-Drying Process

This article is focused on the methods based on the pressure rise test (PRT) used to monitor the primary drying of a lyophilization process. Details about the model-based algorithms proposed to interpret the PRT, namely, manometric temperature measurement (MTM), pressure rise analysis (PRA), and dynamic parameters estimation (DPE), are briefly summarized and various features of the models used by these algorithms, in particular the role of the vial wall and radiation on the thermal balance of the system, are investigated. The optimal selection of the sampling frequency and the time interval between two tests is discussed, and the influence of the duration of the test on the results is investigated by means of mathematical simulation: results obtained from the PRT can be significantly improved by optimizing the duration of the test. Moreover, the problem of misleading results obtained at the end of the primary drying is investigated, taking into account the problem of ill-conditioning of the algorithms. An improved version of the DPE algorithm is proposed to cope with this problem; its effectiveness is demonstrated by means of mathematical simulations and experimental runs.

In-Line Optimization and Control of an Industrial Freeze-Drying Process for Pharmaceuticals

This paper deals with the in-line optimization and control of the freeze-drying process of pharmaceuticals in vials. The proposed control system, named LyoDriver, uses a mathematical model of the process to calculate the values of the temperature of the heating fluid: the goal is to minimize the time required to get the desired amount of residual water in the dried product, and to maintain product temperature below the maximum allowed value, thus preserving product quality. The values of product temperature and residual ice content, as well as other parameters, are required to perform the calculations: these variables are estimated in-line by means of the Dynamic Parameters Estimation algorithm, an advanced tool based on the pressure rise test, but also other monitoring systems can be used. Two different control algorithms are presented and investigated by means of mathematical simulation and experiments carried out in a small industrial-type apparatus (LyoBeta 25 by Telstar). Results show the effectiveness of LyoDriver in a wide range of operating conditions, even when the process becomes mass-transfer controlled, or when the operating pressure is changed.

Model-Based Monitoring and Control of Industrial Freeze-Drying Processes: Effect of Batch Nonuniformity

This article deals with the monitoring and control of the freeze drying of pharmaceuticals in vials taking into account batch heterogeneity. Firstly, the problem of nonuniformity of the batch is addressed: the vials in the chamber of the freeze dryer can, in fact, exhibit different time evolutions due not only to radiation from the wall of the chamber, but also to temperature gradients on the heating shelf, vapor fluid dynamics, and nonuniform inert distribution, as it has been evidenced by means of computational fluid dynamics simulations. Then, the effect of batch heterogeneity on the performance of the monitoring and control system is discussed and a new tool is presented, based on an advanced algorithm, the Dynamic Parameters Estimation, that estimates the state of the system (product temperature and residual ice content) by using the results of the pressure rise test, coupled with a controller (LyoDriver) that changes the shelf temperature in order to maintain product temperature below the maximum allowed value while minimizing the duration of primary drying.

Determination of end point of primary drying in freeze-drying process control.

Freeze-drying is a relatively expensive process requiring long processing time, and hence one of the key objectives during freeze-drying process development is to minimize the primary drying time, which is the longest of the three steps in freeze-drying. However, increasing the shelf temperature into secondary drying before all of the ice is removed from the product will likely cause collapse or eutectic melt. Thus, from product quality as well as process economics standpoint, it is very critical to detect the end of primary drying. Experiments were conducted with 5% mannitol and 5% sucrose as model systems. The apparent end point of primary drying was determined by comparative pressure measurement (i.e., Pirani vs. MKS Baratron), dew point, Lyotrack (gas plasma spectroscopy), water concentration from tunable diode laser absorption spectroscopy, condenser pressure, pressure rise test (manometric temperature measurement or variations of this method), and product thermocouples. Vials were pulled out from the drying chamber using a sample thief during late primary and early secondary drying to determine percent residual moisture either gravimetrically or by Karl Fischer, and the cake structure was determined visually for melt-back, collapse, and retention of cake structure at the apparent end point of primary drying (i.e., onset, midpoint, and offset). By far, the Pirani is the best choice of the methods tested for evaluation of the end point of primary drying. Also, it is a batch technique, which is cheap, steam sterilizable, and easy to install without requiring any modification to the existing dryer.

On the Design of an In-Line Control System for a Vial Freeze-Drying Process: The Role of Chamber Pressure

This paper is focused on the design of an in-line control system for the freeze-drying process of pharmaceuticals in a vial. The goal is to minimize the duration of the primary drying, when most of the water is removed by sublimation while maintaining the product temperature below the maximum value allowed by the product. The pressure in the drying chamber and the temperature of the fluid that is used to heat (or to cool) the product can be manipulated; the pressure rise test and the DPE (Dynamic Parameters Estimation) algorithm are used to estimate the product temperature and the residual ice fraction, i.e. the controlled variables. Both an open-loop controller, using constant values of fluid temperature and chamber pressure, and a closed-loop controller, based on the in-line optimization of the fluid temperature, will be described and tested. Finally, the possibility of manipulating in-line the pressure in the drying chamber will be discussed.