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Satish K. Singh is a research fellow at Pfizer, Inc.
Arnold McAuley is scientist in formulation and analytical research at Amgen, Inc.
Nitin Rathore is a senior scientist in drug product and device development at Amgen, Inc.
Anurag S. Rathore is a professor in the Department of Chemical Engineering at the Indian Institute of Technology Delhi and a member of BioPharm International's Editorial Advisory Board, Tel. +91.9650770650, email@example.com.
How to maintain product stability and prevent particulates.
Maintaining product stability during the various drug product process unit operations is paramount to our ability to supply safe and efficacious biotech products to patients. New technologies are helping us ensure that we meet these challenges successfully and are able to embrace the Quality by Design paradigm. This article presents best practices to meet three of the significant technical challenges experienced in drug product manufacturing, namely, maintaining product stability during frozen storage, performing visual inspection of drug product vials, and controlling protein particulates.
Drug product manufacturing has its share of operational and technical challenges. The large number of stock-keeping-units (SKUs) that we typically manufacture for a single product, as well as the need for the product to move outside the manufacturer's network and be delivered to the patient, add to the operational complexity of drug product manufacturing. Further, technical challenges associated with maintaining the purity, activity, and efficacy of the final product during drug product processing must be overcome successfully.1
(Althea Technologies, Inc.)
This article is the 17th in the Elements of Biopharmaceutical Production series and presents best practices to meet three of the significant technical challenges experienced in drug product manufacturing, namely, maintaining product stability during frozen storage, performing visual inspection of drug product vials, and controlling protein particulates.
Protein stability can be affected by a multitude of factors that interplay during the manufacturing of biotech drug products. The need to examine product stability over a broad range of process parameters has been highlighted in the literature.1 Such an examination can be achieved by characterization studies at small scale using qualified scaled-down models or large-scale experiments designed to examine worst-case scenarios related to changes in operating conditions.2 The development of a design space in the context of developing, scaling up, and transferring freeze-dried products has been discussed in recent publications.3 It has been pointed out that when doing formulation and initial cycle development, the development scientist must be aware of the type of equipment to which the product will be transferred in the next stage of the product lifecycle.
Anurag S. Rathore
Freezing and thawing large volumes of bulk protein solutions has become an important step in biopharmaceutical manufacturing because the flexibility it affords makes it possible to maximize productivity and align drug product logistics with market demands.4 The stability of therapeutic proteins during long-term storage has been highlighted as a key issue for product safety and efficacy.1 Storing drug substance for periods of time in the frozen state enables a decoupling of drug substance manufacturing from drug product manufacturing. A successful operation, therefore, requires an understanding of the fundamental aspects of freezing and thawing proteins as well as the impact of the practical aspects of heat and mass transfer, along with knowledge of the technology available.
Manufacturing sterile biotech products requires visual inspection of the final drug product filled in sealed containers to ensure there is no contamination from foreign particulates.5 Such inspection can be performed by humans or through an automated inspection machine (AIM). Compared to manual inspection, automated visual inspection (AVI) offers more consistency, higher speed, and improved quality of inspection. It also is cost efficient over a longer period and for higher production volumes.
Problems arising from insoluble aggregate formation in biologics development along with approaches to detect and characterize the aggregate species have been a focus for regulators and the biotech industry lately. It has been suggested that our understanding of aggregation pathways and how to inhibit aggregation remains relatively poor and that it is challenging to characterize the whole size range of particulates for a given biologics formulation.6 The United States Pharmacopeia and the harmonized versions of the European and Japanese Pharmacopoeias set limits and cite enumeration methods for sub-visible, foreign particulate matter in parenteral products.7–9 A significant presence of particles, whether they are product-related or foreign, may not only compromise the efficacy or the drug product but also present a safety issue.10 One important factor is potential immunogenicity, which can be a result of poor quality of the protein product.11,12 The quality of a product can be affected by the presence of various degradation products such as particulates and aggregates and also by chemical modifications of the protein molecule. Protein particles typically are a result of the aggregation of structurally altered monomers and or dimers, resulting in the insolubility of the species. Aggregates or multimers can be categorized as either large or small in size.13 Small aggregates can range from dimers to multimers that can be detected by size exclusion chromatography and dynamic light scattering, with a size range of 0.1 to 1 μm. Larger aggregates can be classified as sub-visible which are 2 to 100 μm in size and detected by light obscuration methods such as the HIAC Royco liquid particle counter and microscopy. Visible particles are detected by the naked eye and can either be visible (>40 μm) or sub-visible and typically are detected by visual methods or light obscuration instruments, respectively. The size range of the protein particle can vary from <1 μm to >400 μm. In the sub-visible size range, injectable liquid formulations must comply with the pharmacopeial limit of: not <6,000 particles for the 10 μm range and not <600 particles for the 25 μm range.
Freezing biologics at large-scale is carried out in various ways, from improvised to custom-designed systems. The simplest storage method involves filling the bulk solution into bottles or carboys of appropriate size and storing in freezers. These containers are often made of polyethylene or polypropylene, although steel (e.g., SS316L) can be used for small volumes. Their advantage is simplicity. Disadvantages include a lack of active control and potential variability between containers, as well as multiple container–closures to secure against contamination. The procedure for preparation, loading, and placement in the freezer has to be well defined to reduce this variability. Thawing is generally performed by placing containers in a refrigerator or at room temperature. In the absence of an active thawing mechanism, thaw times can be quite long (possibly days) depending on the size of the container. During this period, significant concentration and temperature gradients can exist in the container if it is not actively shaken or agitated. Practical handling considerations limit the size to about 20-L carboys, although 50-L sizes are possible. The system is simple, however, and if the protein formulation is stable under a wide range of freeze–thaw conditions and can withstand cryoconcentration, the bottle or carboy system may be the preferred mode of operation.
Another solution that is available for freezing protein solutions at large scale uses stainless steel vessels (cryovessels) from Sartorius-Stedim Biotech (Aubagne, France). These cryovessels are available in multiple sizes (125-L, 200-L, and 300-L) and consist of a jacketed stainless steel tank with an internal radial finned-heat exchanger. This effectively divides the tank into six (or 10 for 125-L) longitudinal sections and has the effect of reducing the heat-transfer distance and improved heat transfer across the entire volume. Dendritic ice formation is promoted, thus avoiding the potentially damaging effects of cryoconcentration.14 The vessels are cooled and heated by an external refrigeration system that circulates heat transfer fluid through the jacket and fin system. The temperature profile of the heat transfer fluid is programmable and results in reproducible temperature profiles in the vessel. The vessel is kept stationary through the freezing process below 0 °C, but is gently agitated by rocking during the thawing process. The lack of agitation during freezing prevents solutes from moving and promotes the formation of dendritic ice. Agitation during thawing promotes rapid mixing of the thawed material, thereby removing concentration hot spots and maintaining uniform temperature in the solution with rapid thawing. The lowest working temperature for the equipment is –60 °C.
A variation on the bulk freezing technology is the FreezeContainer from Zeta Holdings (Styria, Austria). Jacketed vessels (currently limited to 300-L) are cooled or heated through an internal circulation system (mounted in the lid). Heat exchange is accomplished by an external refrigeration system by a circulating heat transfer fluid. The temperature profile is programmable. The entire container is agitated during thawing.
A large-scale bag freezing system called Celsius from Sartorius Stedim Biotech uses upright bags made of Stedim71 film (ethylene vinyl acetate product contact material) that are filled with the solution to be frozen and held with slight compression between two plates that serve as heat exchange surfaces. These plates are cooled or heated by circulating heat transfer fluid from an external programmable refrigeration unit. The slight compression provides improved contact and heat transfer resulting in a frozen bag in the shape of a pillow. The bag is kept in frames so as not to stress the material during handling and transport. The sizes of nominal bags are 16.6 L and 8.3 L, with fill volumes ranging between 4.2 L and 16 L, and 2.1 L and 8 L, respectively. Six bags can be simultaneously processed in the cryo unit.
The freeze and thaw behavior of proteins has been studied extensively, but primarily in small or microscopic volumes and often in conjunction with lyophilization. The use of these small volumes in literature studies makes the process aspects difficult to relate to the freezing and storage of bulk proteins. A few studies have, however, elucidated fundamental aspects of the impact of freezing on protein structure and interaction with ice and are reviewed by Bhatnagar, et al.15
An unavoidable feature of freezing is cryoconcentration as water converts to ice and excludes the solutes (and protein), ultimately creating a viscous glassy matrix (Figure 1). This can affect the embedded protein in a number of ways. If the buffer salts are prone to crystallization because of saturation, significant pH shifts can occur. Among the common buffers used for biologics, the sodium phosphate buffer mixture is particularly susceptible, and the pH can change from seven to near four on precipitation of the dibasic salt; the actual value is dependent on strength and rate.15 Even if the salts do not precipitate, buffer pH is sensitive to temperature, and therefore, pH shifts will occur during freezing and in the frozen state. Other excipients in the formulation can also cryoconcentrate. Although there is a complex dependence on factors such as the rate of cooling and composition, phase and state diagrams provide some insight into the cryoconcentrated system. If sodium chloride (NaCl) is present, a eutectic is formed at –21.2 °C which has a concentration of 23.3% w/w, i.e., an approximately 25-fold increase from 0.9% w/w normal saline. For most carbohydrates (including disaccharides), the concentration of solute in a maximal freeze-concentrated glass is around 80% w/w.16 Reactions that could lead to incompatibilities in the matrix are slowed down because of the low temperature, but the cryoconcentration of solutes can counteract this effect. Reactions such as oxidation can be enhanced, especially because the solubility of oxygen increases as temperature drops, while ice formation also excludes gases. Other potential incompatibilities among the solutes, including the protein, can be exacerbated. Proteins also interact with the ice surface with a consequent perturbation of their native structure. Proteins can partially denature at the ice interface through weakening of hydrophobic bonds as well as adsorption on the ice surface.17 This phenomenon is largely reversible after thawing, although some fraction of the protein may become irreversibly damaged. More importantly, depending on the storage temperature (in relation to the glass transition temperature of the cryoconcentrated mass), this loss of protein structure can result in aggregate formation because the partially unfolded molecules interact with other species around them. Storage above the glass transition temperature (Tg') of the matrix will allow greater mobility for this to occur. Similarly, other solutes (e.g., NaCl, glycine, mannitol, sorbitol) can phase separate, crystallize, or undergo phase transitions over time if frozen into nonequilibrium states during the freezing process, leading to protein destabilization.18 Maximally freeze-concentrated carbohydrate solutions relevant to biologics formulation tend to have a Tg' below –30 °C.19 Less than maximally freeze-concentrated systems have even lower Tg' levels. Proteins themselves have Tg' levels in the range of –10 to –15 °C, but freezing without cryoprotectants is generally not viable.19–20 Practical storage areas always have a degree of temperature variability within which they are controlled. Temperature fluctuations, especially in the vicinity of and above the Tg', can be especially detrimental because the rates of the processes described above will increase significantly more than would be expected based on the nominal storage temperature.
The large-scale storage systems discussed here attempt to control the rate of heat removal and thereby obtain a reproducible process. In the case of bottles or carboys, the exact pretreatment and placement of the containers and load in the freezer must be defined. Similarly, the thawing conditions and placement must be established. The active systems from Sartorius-Stedim can be programmed to provide reproducible temperature profiles in the bulk. The actual profile is determined by the load, but a range of loads (fill volumes) can be defined, qualified, and validated. During operation, after a small degree of supercooling, ice formation is generally nucleated throughout the bulk, although the growth is faster at the edges than in the center. Depending on the rate and nature of ice growth in relation to diffusion rate, solutes get trapped between growing ice crystals. Thus, concentration gradients are generated and "frozen-in" in such systems. An example of concentration gradients observed in bottles is shown in Figure 2(a). Such gradients can persevere if thawing is carried out without mixing, as shown in Figure 2(b). Our in-house observations show that proteins and other excipients cryoconcentrate to the same extent. Cryoconcentration occurs in the cryovessels and bags.21,22 Because a degree of cryoconcentration is unavoidable and the protein is most vulnerable when the solute concentration is high but the mass has not been completely immobilized, it is best to freeze as rapidly as possible. Doing so minimizes the time the protein spends in the partially frozen high concentration but still mobile transition region.
Once processed, these bulk containers must be stored for a period of time. The storage temperature is determined by the nature of the formulation as well as practical and logistical considerations. Bottles and carboys can be placed in deep freezers at any desired temperature that can be tolerated by the material of construction. The glass transition temperature of high density polyethylene (HDPE) is –145 °C for the amorphous portion (brittle temperature quoted as –100 to –70 °C), making it suitable for most applications.23 For polypropylene (PP), the glass transition temperature ranges from –15 to –10 °C requiring that such containers be handled carefully in cold storage. Similar care is required for containers based on ethylene vinyl acetate (EVA), which has a transition around –15 °C although the brittleness temperature for film-grade EVA is stated to be as low as –75 °C or below. Large stainless steel cryovessels have an operational temperature limit around –60 °C, although custom-built warehouses are required if storage below –20 °C is needed.
The process of thawing, while simple in principle, must be controlled properly to ensure that the wall temperatures at the heat transfer surfaces do not exceed allowable limits for the product. To ensure that the thawed material does not overheat while a remainder is still in the frozen state, the mass should be agitated during processing, thereby ensuring efficient heat transfer as well as preventing hot spots. Finally, a comparable system to perform long-term stability studies is required to support regulatory filings. In the case of a bottle or carboy storage, smaller units are used. Simple dimensional considerations imply that these cannot be completely representative. For the cryovessels and bag freezing systems, small-scale models are available to do process development. Their utility as stability models must be evaluated.
Various light transmission or camera-based commercial systems are currently available in the market and can be used to perform automated visual inspection (AVI) of sterile drug products.24–26 The automated inspection machine (AIM) used in this study uses a light transmission–based static division system to detect particles of foreign contaminants in vials filled with liquid product. The vial containing the product is spun at a specified speed followed by the application of brakes to stop the rotating vials. As the vial stops, the particles continue to stay in motion while being suspended in the liquid, thereby causing interference in the incident light that is detected by the sensor. The performance of an automated visual inspection system should be qualified and characterized before its usage for inspecting drug products filled in sealed containers such as vials and syringes. A Knapp study can be conducted to establish the human capability for visual inspection and to set the performance acceptance criteria for the AIM.27–28 In the case study presented here, process parameters that affect the performance of the AVI system, such as machine parameters, product formulation, and fill configuration were evaluated. A standard vial defect set was prepared by seeding filled clean vials with a single glass bead of size 70 μm, 100 μm, and 400 μm. Each seeded vial contained only one glass bead of a specific size. Two vial sets comprising 24 vials each (six clean, and six of each particle size) were run through the AVI system 32 times and the detection results (accept/reject) for each vial were recorded. At the end, percent detection rate (% DR) of the machine for each vial was evaluated as the ratio of the number of times the vial was rejected by the machine and the number of times the vial was inspected. Studies using product mimic solutions were designed to evaluate the effect of each process parameter on the defect detection rate by the machine.
Key machine parameters affecting the process performance include spin speed (how fast the vial is spun, measured in rpm), brake setting (how quickly inspection is performed after applying the brakes), sensitivity (signal to noise ratio), inspection view height (based on liquid meniscus height), and background light intensity. Sensitivity and background light settings were optimized and held constant throughout this study. Inspection view height was altered based on meniscus height. Various formulations of different viscosities were then tested by changing the brake and spin speed settings. Figure 3 shows that increasing the spin speed improves the detection rate, the impact being more significant for high viscosity products. Detection of the glass particle by the machine requires the particle to move and stay suspended in the detection window. Higher spin speeds transfer more momentum from vial to liquid and then from liquid to the glass particle, thereby resulting in larger particle movement over longer durations. Inspecting the vials quickly after applying the brakes (a higher brake setting) also seemed to help the detection rates.
In addition to machine parameters, the product formulation also can have a significant effect on the ability of the machine to detect particles. Similar to the observations in Figure 3, we observe deterioration in the detection rate as product viscosity increases. For low viscosity solutions, a spin speed of 1,600 rpm is sufficient to achieve detection rates of >80%. However, for high concentration products with viscosities >4 cP, process performance deteriorates significantly at low spin speeds. Higher spin speeds of 2,200 and 2,800 are needed to achieve the same detection rate. Other product properties such as density (relative to defect particle density) and surface tension also may affect the performance of an AVI system. Figure 4 compares the detection rate (average of 100 μm and 400 μm) of the machine for two mimic solutions of equal viscosity (2.3 cP) but different surface tensions. The formulation without polysorbate (PS-20) had a higher surface tension and was more challenging for the AIM than the one with polysorbate for the detection of 400-μm particles. The results highlight the importance of using a representative mimic solution that mimics not only a product's viscosity but other properties as well.
The fill configuration of the product SKU also affects AVI performance. The automated inspection of syringes can be more challenging than vials because the smaller radius of syringe barrels reduces the momentum imparted to particles for a given spin speed. The fill volume of the liquid in the container also can have a bearing on the ability of the machine to detect particles. Figure 5 compares the machine performance for low and high fill volumes for two different vial sizes. For both 5 cc and 10 cc, the detection rate (plotted as the average of 100 μm and 400 μm) is lower for very low fill volumes. When the fill volume is reduced, the inspection window available to the sensor becomes smaller, thereby reducing the detection rates. Intermediate fill volumes did not impede performance as much as the low fill volumes.
The automated visual inspection of biopharmaceuticals is a key process step in the fill–finish process and offers several benefits over manual inspection, including higher speed, better detection, and improved process consistency. The machine should, however, be qualified and characterized before its usage for product lot inspection. Machine parameters, product properties, and fill configuration are all important factors that determine the performance of the AVI system. In addition to actual product, appropriate mimic solutions can be used to characterize the effect of these parameters and design an AVI process that is robust and consistent.
Particles may be generated as a result of large-scale manufacture or because of an inherent property of the protein molecule. The large-scale manufacturing of protein drug products involves processing steps such as purification, formulation, freeze–thaw, filling, shipping, and storage. Stresses that are introduced during these steps can cause instabilities that can lead to aggregation and particulation.29
In this case study, we discuss some important factors that may be used to control particulation for a monoclonal antibody product. The data presented are from the formulation development of a monoclonal IgG2 antibody. A typical example of visual particulation in a biopharmaceutical liquid formulation is shown in Figure 6.
The particles in these formulations can be counted by instruments such as the HIAC Royco liquid particle counter and characterized by purifying the particles and subjecting them to protein analysis. During formulation development, screening studies are performed to study the effect of factors such as pH, buffering agents, excipients (sugars, surfactants), and protein concentration to minimize the presence of particles.
Figure 7 shows the effect of including a low amount (0.004% by weight) of Tween 80 (polysorbate 80) on the particle counts in a particular IgG liquid formulation. Samples were stored at 4 °C for three months and then analyzed for particulates. These IgG preparations were either derived from a hybridoma cell line or a Chinese hamster ovary (CHO) cell line. In the absence of Tween, the hybridoma-derived material had higher particle counts compared to the CHO-derived material. This difference may be a result of the inherent nature of the protein molecule or differences between the two processes. A size range of 2, 5, 7.5, 10, 20, and 25 μm is shown at 10 and 20 mg/mL. As evident from the graph, the 2 μm counts are orders of magnitude higher than the other size range and should be an important consideration in the particle analysis.10
Figure 8 shows the effect of varying pH on particulate counts for 10-, 20-, and 25-μm particle size. Samples were formulated in a poly buffer system with a common excipient to maintain osmolality. Samples were then stressed over 24 h using a tumbling apparatus. The tumbling action was used to represent agitation stress that may be experienced during the transportation of drug product. This particular antibody is more stable in the acidic pH range from 5 to 6. At neutral and basic pH, however, the particle counts are significantly increased. The exact reason for this particle increase as a function of pH is not known, but it may be related to changes in the surface charge distribution of the molecule as the pH is increased from 5.0 to 7.5, causing the protein to become less soluble. It was also noted that formulations containing higher particulate counts showed increased dimer levels by size exclusion chromatography (data not shown).
Recently, flow imaging technology has emerged as an orthogonal technique to measure subvisible particles, in addition to light obscuration–based techniques.30 In this setup, samples are made to flow through a microfluidic cell, and digital images of suspended particles are captured. The images are then analyzed by the software to count particles and estimate their size. In addition to being an orthogonal technique to light obscuration, flow imaging also has the advantage of making it possible to view the particle in question. The image and the aspect ratio (ratio of longer to shorter dimension) helps differentiate if the particle is an aggregate or silicon-oil droplet, some other foreign particle, or even an air bubble.
Figure 9 shows particulate analysis using microflow imaging (MFI) of a different IgG2 monoclonal antibody. Particulation behavior of this molecule stored in a glass prefilled syringe was compared to a glass vial, in a formulation that lacked polysorbate. Data are plotted as total particle counts for a variety of particle ranges (from 2 to >125 μm). Under these conditions, the prefilled syringe produced significantly more particles than the glass vial, across the different size ranges (up to >50 μm). This was most likely caused by the phenomenon of silicon-oil–induced particulation.31
Characterizing and controlling particulates through a rational formulation screening process is an important part of protein drug development. Careful analysis of particle generation through downstream processing, storage, and transportation should be an important consideration in drug development. Furthermore, particle detection and quantification using advanced techniques has become an integral part of biopharmaceutical development.
Nitin Rathore would like to thank Cylia Chen and Oscar Gonzalez of Amgen, Inc. for their support in conducting these studies and Wenchang Ji, Erwin Freund, and Ed Walls for review and useful feedback. Arnold McCauley would like to thank Sekhar Kanapuram, Hyo Jin Lee, Alexis Leuras, Lyanne Wong, and Rahul Rajan, all from Amgen Inc., for providing data, editing the manuscript, and helpful discussions.
Satish K. Singh, PhD, is a research fellow at Pfizer Inc., global biologics, Chesterfield, MO, Nitin Rathore, PhD, is senior scientist in process development and Arnold McAuley, PhD, is scientist in formulation and analytical research, both at Amgen, Inc., Thousand Oaks, CA. Anurag S. Rathore, PhD, is a consultant, Biotech CMC Issues and a faculty member in the department of chemical ?engineering at the Indian Institute of Technology, Delhi, India, firstname.lastname@example.org Rathore is also a member of BioPharm International's editorial advisory board.
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