KR102638347B1 - Reactor surface finish remediation - Google Patents

Abstract

Disclosed herein are improved biopharmaceutical processing devices, such as reactor vessels and reactor stainless steel surfaces, and methods for their differentiation. In some embodiments, a biopharmaceutical processing device may include a vessel having a surface configured to contact a proteinaceous processing material, wherein the surface has a pre-commissioning surface roughness greater than about 20 Ra Max (μin). surface roughness).

Description

Reactor surface finish correction {REACTOR SURFACE FINISH REMEDIATION}

The present invention relates to bioreactor vessels and production surfaces, and more particularly, to the cleanability of bioreactor vessels and production surfaces.

In the pharmaceutical and biopharmaceutical industry, stainless steel device surface finishes are carefully controlled to ensure a high level of cleaning performance. Prior to commissioning, this is achieved by developing robust design specifications and verifying compliance during certification testing. Once commissioned, the device should be inspected using an on-going maintenance program to determine when surfaces require repair. However, both pre-commissioning and post-commissioning, the appropriate level of surface anomaly and its effect on cleanability are not known in advance, resulting in inconsistent and uncontrolled surface characteristic requirements. This results in increased calibration between vessels and added costs in commissioning, manufacturing, and operational maintenance of the vessels.

As such, improved reactor vessels and stainless steel surfaces and methods for differentiating them are needed.

Disclosed herein are improved biopharmaceutical processing equipment, such as reactor vessels and stainless steel surfaces, and methods for their differentiation. In some embodiments, a biopharmaceutical processing device may include a vessel having a surface configured to contact a proteinaceous processing material, wherein the surface has a pre-commissioning surface roughness greater than about 20 Ra Max (μin). (pre-commissioning surface roughness). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 35 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 20 Ra Max (μin) and less than or equal to about 250 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 35 Ra Max (μin) and less than or equal to about 150 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness of greater than about 90 Ra Max (μin) and less than or equal to about 150 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness of about 150 Ra Max (μin). In some embodiments, the surface may be formed from 316L stainless steel.

In at least one embodiment, a biopharmaceutical processing device may include a vessel having a surface configured to contact a proteinaceous processing material, wherein the surface exceeds a maximum depth of surface pitting of about 2.6 mm. It has a surface finish with no surface abnormalities. Moreover, in some embodiments, the processing device surface may be free of surface abnormalities exceeding a maximum scratch depth of about 1.0 mm. In some embodiments, the surface may be free of surface abnormalities exceeding a maximum depth of surface fitting of about 1.2 mm. The surface may be formed of 316L stainless steel. In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 20 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 35 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 20 Ra and less than or equal to about 250 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness of greater than about 35 Ra and less than or equal to about 250 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 35 Ra and less than or equal to about 150 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness of about 150 Ra Max (μin). In some embodiments, the surface may have a surface finish free of surface abnormalities exceeding either a maximum depth of surface pitting of about 1.2 mm, and a maximum depth of scratching of about 1.0 mm.

In some embodiments, a method of repairing a biopharmaceutical processing device includes inspecting a surface of a vessel in contact with the processing material for the presence of a surface abnormality, measuring physical characteristics on the surface, and determining whether the surface abnormality exists. If it exceeds a predetermined threshold, it may include correcting surface abnormalities from the surface. In some embodiments, the physical characteristic may be pit depth and/or scratch depth. In some embodiments, the surface abnormality may be a pit, and the predetermined threshold is a maximum pit depth of about 2.6 mm. In some embodiments, the surface abnormality may be a pit, and the predetermined threshold may be a maximum pit depth of about 1.2 mm. In some embodiments, the surface abnormalities may be micropits and the predetermined threshold may be a maximum micropit density of about 2600 per inspection area. In some embodiments, the surface abnormality may be a scratch and the predetermined threshold may be a maximum scratch depth of about 1.0 mm. In some embodiments, the surface abnormality may be surface roughness and the predetermined threshold may be a surface finish of about 150 Ra Max (μin) or less. In some embodiments, the predetermined thresholds include a maximum pit depth of about 1.2 mm, a maximum micropit density per inspection area of about 2600, a maximum scratch depth of about 1.0 mm, and/or a surface finish of about 150 Ra Max (μin) or less. It can be included. In some embodiments, inspecting the surface of the vessel in contact with the processing material for the presence of a surface abnormality includes at least one of visually inspecting the surface of the reactor vessel and using a depth gauge instrument to measure the depth of the abnormality. may include. Correcting surface abnormalities from a surface may include buffing the surface with a buffing device sufficient to remove the surface abnormalities.

1 shows an example of a biopharmaceutical reactor vessel;
Figure 2 shows pitted coupons, scratched coupons, rough coupons, and micropitted coupons;
Figure 3 shows an exemplary method for application of BSA soil to pitted, scratched, and rough coupons;
Figure 4 shows an exemplary coupon tested with UV light;
Figure 5 shows an exemplary falling film test apparatus;
Figure 7 shows contour plots of % removal rate for pairs of factors;
Figure 6 summarizes a regression analysis illustrating multiple regression for % removal as a function of density coefficient, aspect ratio, and depth;
Figure 8 shows the visual effect of fluorescence using UV illumination captured as the percentage of coupons failing visual inspection in a two-variable matrix consisting of depth and diameter;
Figure 9 shows a linear regression analyzing "normalized % removal" and surface roughness;
Figure 10 shows a residual plot analyzing "normalized % removal" and pit density;
11 shows scratch depth v. Linear regression of mean normalized % removal rate is shown;
Figure 12 shows the percentage of fluorescent visual failure per scratch depth;
Figure 13 shows the ANOVA methods used in the analysis of the addendum study of different challenging soils and cleaning agents;
Figure 14 shows the ANOVA methods used in the analysis of the appendix study of the different test contaminants and cleaners;
Figure 15 shows multiple regression analysis for % removal as a function of density coefficient, aspect ratio, and depth;
Figure 16 shows multiple regression for % removal rate as a function of scratch depth;
Figure 17 shows multiple regression for residual TOC as a function of density coefficient, aspect ratio, and depth of fitting;
Figure 18 shows a residual plot for residual TOC as a function of scratch depth;
Figure 19 shows a graphical summary of the appendix TOC results;
Figure 20 shows the ANOVA summary of the Appendix TOC results.

As specified above, the present invention relates to bioreactor vessels and manufacturing surfaces, and more particularly to the cleanability of bioreactor vessels and manufacturing surfaces, which is now described in detail in conjunction with the accompanying drawings. Note that like reference numerals refer to like elements throughout different embodiments.

The articles “a” and “an” as used herein preceding an element or component are intended to be non-limiting as to the number of instances (i.e., occurrences) of the element or component. Accordingly, “a” or “an” should be read as including one or at least one, and the singular word form of an element or component also includes the plural, unless the number is clearly intended to be singular.

As used herein, the terms “invention” or “the invention” are non-limiting terms and are not intended to indicate any single aspect of a particular invention, but rather include all possible aspects as set forth in the specification and claims.

As used herein, the term "about" modifies the amount of an ingredient, ingredient or reactant used, e.g., through typical measurement and liquid handling procedures used to prepare concentrates or solutions. It represents a variation in a numerical quantity that can occur. Additionally, differences may arise from inadvertent errors in the measurement process, differences in manufacturing, source of origin, or purity of ingredients used to prepare the composition or perform the method. In one aspect, the term “about” means within 10% of the reported numerical value. In another aspect, the term “about” means within 5% of the reported numerical value. In another aspect, the term “about” means within 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% of the reported numerical value.

The biopharmaceutical and pharmaceutical industries use ASME BPE (the American It has primarily adopted stringent specifications based on the 2014 edition of the Society of Mechanical Engineers' Bioprocessing Equipment standard. As used herein, “surface abnormality” means any defect on a given surface, whether formed pre-commissioning or post-commissioning. For example, four types of surface defects are commonly observed in biopharmaceutical product contact surfaces - scratches, roughness, micropits, and pitting. As used herein, “pre-commissioning” means during the design and production of a reactor before the reactor is placed into operation and used in the production of product. As used herein, “post-commissioning” means after the reactor has been provided and produced the product. As used herein, a “pit” or “fitting” is a surface void of measurable depth that is generally annular, circular, oval, or rectangular in shape. As used herein, “scratch” means a surface cavity having a substantially linear shape with a measurable depth. As used herein, “vessel,” “reactor vessel,” and/or “processing device” includes tanks, pipes, filters, bioreactors, product hold vessels, WFI hold vessels, chromatography skids, and ultrafiltration. /diafiltration refers to any device or system having at least one surface that comes into contact with process materials, including but not limited to diafiltration skids, filter housings, and any process contact surfaces that are cleaned via recirculating CIP. do.

Table SF-2.4-1 of ASME BPE (2014), which is incorporated herein by reference in its entirety and reproduced in part below, provides surface roughness (as expressed in R _a Max in both microinches and microns) for the commissioned reactors. Establish guidelines for the biopharmaceutical industry. Adopting these standards poses challenges for ongoing maintenance as tanks age. Properties such as pit diameter are very difficult to measure in this area once the device is in operation. And, although other industry publications have explored the impact of surface finish on biofilm formation, none prior to this invention had shown that defects exceeding these ASME BPE specifications were detrimental to chemical cleaning (e.g. CIP) performance.

Table SF-2.4-1

Surface roughness, as used below, is R _a Max, measured in microinches (μin) (hereinafter referred to as “Ra Max (μin)”).

As detailed herein, adoption of these standards can be either extremely stringent or straightforward, thus adding to manufacturing costs because the cost of reactor materials increases as surface roughness decreases; That is, the smoother the surface, the more expensive the material. As such, aspects of the present invention include determining qualitative and quantitative thresholds for pre-commissioning and post-commissioning analysis of biopharmaceutical reactor vessels, as well as analyzing, cleaning and designing, constructing, and/or designing reactors based on the application of these thresholds. Or it provides repair methods.

As described herein, the purpose of the present invention is to better define criteria for calibration by assessing when cleaning performance is affected by aging and/or chemical degradation of product contact surfaces. . As described below, the effects of pits, scratches, and surface finish variations were explored in a laboratory setting using a wide range of contaminant types and cleaning conditions to identify the true inflection point in cleaning degradation. These studies explored a broad range of defects beyond their typical boundaries to provide a sound statistical basis for conclusions. As such, the present invention identifies a threshold or inflection point that can be used as a basis for defining surface abnormality limits as part of a visual inspection and/or maintenance program or during commissioning of new reactor vessels.

The effectiveness of cleaning surface abnormalities or defects as described herein was explored using the difficulty in removing proteinaceous contaminants of bovine serum albumin (BSA) applied to the surface via immersion in an agitated solution. As used herein, “proteinaceous” refers to fluids containing at least one protein, amino acid residues, or other organic molecules typically associated with biopharmaceutical production, including but not limited to lipids and other macromolecules. refers to any substance such as These specific proteinaceous contaminants act as surrogates that will challenge the cleaning performance with surface defects being precisely suppressed.

Taking into account all data and observations described in the examples, the following thresholds can be applied (together or separately) to determine the cleanability of the reactor surface and/or the need to correct surface abnormalities and will serve as the basis for a visual inspection program. You can:

1. Fitting does not affect cleanability as long as the pit depth remains below about 2.6 mm and, in some embodiments, below about 1.2 mm. At these depths, pit density and diameter are irrelevant.

2. Scratches do not affect cleanability as long as the scratch depth remains below about 1.2 mm and, in some embodiments, below about 1.0 mm. Scratch length and angle were independent within the ranges indicated herein.

3. Micropits do not affect cleaning performance, at least up to about 2600 per inspection area.

4. Surface finish does not affect cleaning ability at least up to about 150 Ra Max (μin).

These thresholds may be applied to commissioning of the reactor vessel and/or calibration or repair of the reactor vessel surface. That is, these thresholds can be applied when designing and constructing reactor vessels as well as during maintenance of on-line reactors. Any suitable calibration method may be used. For example, a buffing device - such as a grinder - can be used to remove surface abnormalities from the surface. In embodiments, for example, correction may include backweld to fill the abnormality followed by grinding smooth.

1 depicts an exemplary biopharmaceutical reactor vessel. As shown in FIG. 1 , reactor vessel 100 includes a reactor surface 102 configured to contact proteinaceous processing material—e.g., fermentation medium and inoculant—and a CIP device configured to clean the reactor surface 102. You can have (104). Reactor vessel 100 may include any other components necessary for the production of biopharmaceuticals, such as sensors, probes, baffles, inlets, outlets, and any other components (not shown). You can. In some aspects, reactor vessel 100 and reactor surface 102 are formed from stainless steel, such as 316L, 304, or other 18-8 stainless steel. Other metals such as Inconel, titanium alloys, etc. may be used as they are suitable for specific applications and manufacturing methods.

In some embodiments, reactor surface 102 may have a surface finish free of surface abnormalities exceeding the thresholds described herein. For example, reactor surface 102 may not have pits equal to or exceeding the maximum depth of surface pitting of about 2.6 mm. In some embodiments, surface 102 may not have pits equal to or exceeding a maximum depth of about 1.2 mm. In some embodiments, surface 102 may have no scratches equal to or exceeding a maximum scratch depth of about 1.2 mm. In some embodiments, surface 102 may have no scratches equal to or exceeding a maximum scratch depth of about 1.0 mm. In this way, cleanability of the reactor surfaces using standard CIP cleaning techniques is guaranteed.

Additionally, in some embodiments, reactor surface 102 may have a surface finish greater than about 20 Ra Max (μin). For example, the reactor surface 102 can have a surface finish of about 20 Ra Max (μin) to about 250 Ra Max (μin), and preferably about 150 Ra Max (μin). In some embodiments, surface 102 may have a surface finish greater than about 35 Ra Max (μin). In some embodiments, surface 102 may have a surface finish of about 35 Ra Max (μin) to about 250 Ra Max (μin), and preferably about 150 Ra Max (μin). Additionally, in some embodiments, reactor surface 102 may not have a density greater than about 2600 micropits per inspection area.

As described, reactor vessels can be commissioned to include less-smooth surface pre-commissioning, i.e., the reactor can be designed and constructed using tougher steel than previously practiced in industry. That is, the reactor and reactor surfaces in contact with the process fluid may have a surface roughness greater than 20 Ra Max (μin), for example, from about 20 Ra Max (μin) to about 150 Ra Max (μin). This is not to say that a surface roughness of 20 Ra Max (μin) or less is contradictory to the teachings of the present invention - that acceptable cleaning of reactor surfaces with a roughness of 20 Ra Max (μin) or less is achieved. ) Surface roughnesses above 20 Ra Max (μin) can be used, resulting in reduced initial costs of constructing the reactor and future remediation costs compared to surface roughnesses below 20 Ra Max (μin). For example, in some embodiments, prior to providing on-line or pre-commissioning, the reactor surface 102 has a temperature of about 25 Ra Max (μin), about 30 Ra Max (μin), or about 40 Ra Max (μin). , about 50 Ra Max (μin), about 60 Ra Max (μin), about 70 Ra Max (μin), about 80 Ra Max (μin), about 90 Ra Max (μin), about 100 Ra Max (μin), about 110 Ra Max (μin), about 120 Ra Max (μin), about 130 Ra Max (μin), about 140 Ra Max (μin), about 150 Ra Max (μin), about 160 Ra Max (μin), about 170 Ra Max (μin), about 180 Ra Max (μin), about 190 Ra Max (μin), and about 200 Ra Max (μin). In some embodiments, the surface may have a pre-commissioning surface roughness greater than about 35 Ra Max (μin). Preferably, in some embodiments, the reactor surface has a pre-commissioning surface roughness of about 60 Ra Max (μin) to about 150 Ra Max (μin). Preferably, in some embodiments, the reactor surface has a pre-commissioning surface roughness of about 150 Ra Max (μin).

These thresholds can be applied to any bioreactor vessel and/or manufacturing surface, such as those requiring CIP cleaning, especially those configured to contain proteinaceous materials, such as reactors for culturing cells.

Example

Various examples are included to illustrate the determination of suitable surface abnormality thresholds for biopharmaceutical manufacturing surfaces. In the examples, the effect on cleaning performance of several factors affecting tank finish observed in stainless steel processing equipment was studied. The present invention identifies an inflection point that can be used as a basis for defining surface abnormality limits as part of a visual inspection and/or maintenance program or in the commissioning of a new reactor vessel.

Exemplary Methods

Coupons were manufactured with peak, scratch, and roughness characteristics designed to bracket the recent AMSE BPE guide for new tanks and extend to the inflection point. A single-variable study was performed on scratches, roughness, and micropitting as described in more detail below. Scratches were evaluated at various depths, including the ASME BPE range, made diagonally across the coupon. Each coupon had only one scratch. Surface roughness was evaluated from 20 Ra Max (μin) to 150 Ra Max (μin). Micropits with unquantifiable depth were created using electrochemical etching. This allows evaluation of micropit density using a specification of 40 feet per inspection area and an exaggeration of 2600 feet per inspection area. Pitting defects were the largest group studied and included exploration of aspect ratio (defined as the depth of the pit divided by the diameter) and density. A half-fraction designed experimental approach was used to determine the influence and interaction (if any) of these surface defects on cleaning performance.

Surface finish studies in these experiments were performed on ¼" thick stainless steel 316L (SS316L) plates with a base finish of 20 Ra Max (μin), except where noted to represent typical pressurized vessel construction materials. This was performed using manufactured coupons. Coupons were manufactured using multiple vendors to achieve the desired defects. Coupons with pits were milled by drilling at the desired depth and diameter.

Surface roughness as measured by Ra Max (μin) was designed as a single factorial experiment. Comparison of coupons of 30 Ra Max (μin), 60 Ra Max (μin), 90 Ra Max (μin), 120 Ra Max (μin), and 150 Ra Max (μin) with baseline 20 Ra Max (μin) coupons was created in this evaluation for . The factor of scratch depth was also explored as a single factor. These were created using metal cutting discs with equal length (50.8 mm) at a 45 ^o angle across the coupon and a minimum width of 1.0 mm. Only the depth changed. Nine coupons were created with scratch depths of 0.2 mm, 0.4 mm, 0.6 mm, 0.8 mm, 1.0 mm, 1.2 mm, 2.6 mm, 4.0 mm, and 5.0 mm.

For the study of pits and scratches, it was decided to conduct the study on milled defects without exposing them to further corrosion. This was done to avoid adding additional uncontrolled variability to the study. To investigate the influence of corrosion effects, coupons with micropits were electrochemically created. A grid with evenly distributed holes perforated in contact paper was placed on the coupon. Paper was used to shield the area subjected to electrochemical etching while the holes allowed current to flow at a localized point. Etching took place in an acid/salt bath using a stainless steel probe connected to an electric current. The anode was applied to the coupon and the cathode was applied to the prod. One coupon with 40 micro-fts was created and another coupon with 2600 micro-fts.

Two full-factorial designed experiments were used for fitting. This design provides a template for a half factorial approach resulting in five (5) different density components, five (5) different pit depths, and five (5) different diameters. did. The combination of depth and diameter also resulted in a fourth implicit variable of aspect ratio (depth/diameter). For analysis, aspect ratio; depth; and density were evaluated. The selection of parameters was based on field experience and the difficulties in measuring pit diameters in actual devices.

Only one coupon of each type was created. Replicates were achieved by preparing each coupon and cleaning it at least three (3) times over the course of several days. The specific set of coupons with pits reported in this paper are detailed in Table 4 below. Figure 2 also shows coupons with pits, coupons with scratches, rough coupons, and coupons with micropits showing the different types of factors explored.

[Table 4] Coupon Factors - Density, Diameter, Depth, and Aspect Ratio

Residue contamination of coupons:

Prior to applying residue to the coupons in this design, all coupons were cleaned using a similar method to the USP <1051> Cleaning Glass Apparatus. Table 5 summarizes the cleaning process. Cleaning with CIP-100 chemicals was performed in an ultrasonic bath. CIP 100 ^® alkaline process and research cleaner is commercially available from Steris Corporation.

[Table 5] Cleaning of coupons before testing

Bovine serum albumin (BSA) was chosen as a protein surrogate to test the surface finish cleaning ability because it is a representative proteinaceous contaminant whose removal can be adjusted through heat treatment to identify beta-sheets. Because. This allowed the removal rate to be carefully controlled to evaluate the relative influence of surface finish differences. 3 shows an exemplary method for applying BSA soil to pitted coupons, scratched coupons, and rough coupons. The concentrations of BSA and fluorescein in the mixture were optimized for suitable contamination weight and fluorescence detection. Heat treatment of the coupons after drying caused denaturation of the protein, which enhanced its binding to the surface of the coupon. The temperature for heat treatment was determined empirically to optimize simultaneous dissolution of BSA and fluorescein. This was achieved by applying the residue to control coupons and heating the coupons for 60 minutes over a temperature range of 80°C to 110°C. The treated coupons were then labeled with fluorescein (gauged by testing with UV light under a flow of detergent, as shown in Figure 4, which shows an exemplary coupon tested with UV light) and BSA (coupon testing under ambient light). An experiment was conducted to determine how long it would take to remove the gases (gauged through visual inspection). The test temperature was selected based on conditions that minimize the time difference between removal of the two component contaminants while providing a test time long enough to detect differences in conditions. This turned out to be a 90°C heat treatment of the coupons for 60 minutes and a 5 minute cleaning time to completely remove the BSA contaminants.

Cleaning of contaminated coupons

Soiled coupons were cleaned in caustic commercial cleaning solution for five (5) minutes. This time was determined empirically in a screening test to completely remove the surrogate BSA/fluorescein mixture from pristine coupons. The order of coupon exposure to the cleaning schedule described below was randomized for each of the three (3) replicate runs. The direction of the coupons with respect to the detergent flow was also randomized.

Figure 5 shows an exemplary falling film test apparatus 500 used in the examples below. As shown, the test was performed on a falling film system 500 designed to generate energy of flow at 3000 Reynolds number over coupons 502 for cleaning. The Reynolds number was chosen to simulate the worst case condition of a falling film down the sidewall of the vessel. The detergent solution used was 1% CIP100® (commercially available from Steris) at 60°C. Each set of experiments used two pristine, 20 Ra Max (μin) control coupons to allow relative comparison with coupons without engineered surface defects. After cleaning, all coupons 502 were allowed to dry before being evaluated for remaining residue.

Cleanliness evaluation

Three methods were used to evaluate cleanliness: (1) Gravimetric determination was used as the main quantitative approach to evaluate the percent removal of contaminants; (2) BSA was combined with a fluorescein marker during part of the study, allowing quantitative assessment of material retention in the pit as gauged by fluorescence under ultraviolet light (UV); (3) Worst case process contaminants were evaluated with different cleaning cycle recipes to demonstrate the applicability of surface finish results obtained using BSA under simulated process conditions.

In the appendix examples, total organic carbon was also evaluated. The fluorescence method described in point (2) is intended solely for use on a laboratory scale to enhance visual inspection insofar as it provides orthogonal confirmation of the cleaning inflection point. These appendix studies using process contaminants included evaluation of residual mass and residual total organic carbon (TOC) using swab methodology. TOC testing is included to provide a link to existing cleanability validation test methods.

Gravimetric analysis was used as a quantitative measure of total contaminants removed, expressed as percent removed. Weights were obtained before contamination, after BSA/fluorescein application and heat treatment, and after cleaning and post drying schedule. Each value was normalized to the control. against scratches, roughness, and micro-pitting; Normalized controls were also included as part of the continuum of variables. The addition of fluorescein created a highly sensitive marker, which allowed assessment of remaining residues in pits and other anomalies when examined under UV light. These qualitative and quantitative measurements allowed evaluation of multiple facets of surface defects for cleaning.

Appendix Examples

The purpose of the appendix examples was to evaluate the actual cleaning process parameters and whether the significant variables that interfere with the cleaning performance of protein substitutes can be applied to worst case process contaminants. This example included two additional residues and five cleaning schemes as demonstrated in Table 6.

Cleaning conditions were chosen to represent other typical schemes within a biopharmaceutical facility. The appendix examples are designed to relate detailed analyzes performed using BSA surrogate contaminants and CIP 100® to other process contaminant and cleaner combinations. Appendix examples evaluate how different cleaning chemicals paired with each process contaminant can affect the inflection points generated during the main part of the study.

[Table 6] Cleaning conditions and contaminants for appendix examples

A subset of initial coupons was selected from the DOE consisting of pitted coupons, scratched coupons, and pristine coupon controls. These coupons are listed in Table 7.

[Table 7] Appendix coupons

Contamination was applied as before by dipping shielded coupons into a beaker of contaminant. Except for cleaning time, all other procedures outlined under Cleaning of Contaminated Coupons in this appendix study were used for evaluation. Washing time for the lysate was determined by the duration for complete washing in 1% CIP 100® at 60°C using a control coupon. Likewise, for tank ring substitutes, the time for complete cleaning of pristine control coupons was determined under the conditions listed. In addition to gravimetric analysis and testing by UV fluorescence, total organic carbon (TOC) was 500 parts per billion (ppb) as a pass/fail criterion for swab samples.

Example 1: Fitting

Statistical analysis of pit data using the BSA surrogate revealed no significant correlation between aspect ratio, depth, and density (p-value > 0.05). However, both pit depth (p-value = 0.091) and the interaction between pit depth and aspect ratio (p-value = 0.064) were close to the threshold for statistical significance. This indicates that depth versus diameter interaction may be important for residue removal.

The results of the quantitative and qualitative analyzes are summarized in Table 8 below. In this case, the % removal represents 100% removal of the control and all other results are normalized to reference this value. The value in parentheses immediately next to the pass/fail indicator for fluorescence indicates the percentage of coupons that failed inspection under UV light.

[Table 8] Normalized results for coupons with pits

To evaluate the impact of different pit variables on removal efficiency, multiple regression was used to test the hypothesis that cleanability is a function of aspect ratio, pit depth, and/or density. The aspect ratio as a function of depth to diameter is the preferred measure for a fit criterion and was therefore used in the statistical analysis of these data. Not all combinations of all four variables are appropriate because diameter, pit depth, and aspect ratio are not independent of each other. Only two of these three variables could be analyzed simultaneously within the context of this experiment, so depth and aspect ratio were chosen for evaluation. Figure 6 summarizes the regression analysis showing multiple regression for % removal as a function of density coefficient, aspect ratio, and depth.

Figure 7 shows a contour plot of % removal rate for pairs of factors. The contour plot helps highlight the areas most affected by the fitting. These plots provide a preliminary indication of the inflection point in residue removal efficiency as a function of significant variables. Light green areas in the graph represent areas with reduced removal efficiency. This would indicate that quadrants with a diameter > 2.5 mm and a depth > 3.5 mm are likely to negatively affect cleaning efficacy.

Figure 8 shows the visual effect of fluorescence using UV light captured as the percentage of coupons that failed visual inspection in a two-variable matrix of depth and diameter. Using a matrix approach, the rejections shown in Figure 8 were graphed with identified inflection points within the selected design space. Coupons were assigned pass/fail values. Coupons were considered rejected if any fluorescent residue was detected, regardless of the total number of pits on the surface. Visual inspection using fluorescent markers detected failure when the diameter was > 4.0 mm and the depth was > 2.6 mm. This result is consistent with a regression model showing a trend toward lower mass removal for higher depth and diameter combinations. The results in Figure 8 help to more definitively identify the inflection point that affects cleaning performance. The data support the results from the gravimetric analysis by demonstrating the interactive effect of depth and diameter. The conclusions are more individualized than those derived from gravimetric analysis, but point to the same general trends. That is, quadrants with diameter > 4.0 mm and depth > 2.6 mm show the greatest potential to negatively impact cleaning efficiency.

Example 2: Surface roughness

Example coupons exploring the effect of surface roughness show that surface roughnesses of about 20 Ra Max (μin) to about 150 Ra Max (μin) have comparable cleaning efficiencies. Figure 9 shows a linear regression used to show that “normalized % removal” is a function of surface roughness. Since the p-value is sufficiently large (p >0.05), it is concluded that % removal is not a function of surface roughness, at least within the limits tested here. Additionally, there were no visual failures under UV conditions.

Summary data in Table 9 shows comparable cleaning performance (i.e. > 97% mass removal) as roughness increases from 20 Ra Max (μin) to 150 Ra Max (μin). This supports the conclusions from the regression analysis.

[Table 9] Summary of normalized % removal rate by coupon roughness

Likewise, statistical analysis of the surface roughness data revealed no statistical correlation between Ra Max (μin) values and residual mass (p-value > 0.05). Additionally, no fluorescence failures were noted during the visual inspection.

Example 3: Micropits

Statistical analysis of the micropitting data revealed that there was no statistical correlation between density coefficient and residual mass, at least within the range tested in Example 3 (p-value > 0.05). Additionally, no fluorescence failures were noted during the visual inspection.

Figure 10 shows the linear regression method used to test that “normalized % removal” is a function of pit density. As shown in Figure 10, there was no significant (p >0.05) effect of pit density on % removal, at least within the range tested in Example 3. There were no appearance failures under UV.

A summary of normalized % removal rates for coupons with micropits is captured in Table 10.

[Table 10] Summary of normalized % removal rate for micropitting

Example 4: Scratch

Statistical analysis of scratch data using the BSA surrogate revealed a strong correlation between scratch depth and removal efficiency (p-value = 0.000), with removal deteriorating with increasing scratch depth. Visual inspection using fluorescent markers detected failure if the depth was > 1.0 mm.

Results for both cleanliness measurements for scratched coupons are summarized in Table 11 below.

[Table 11] Normalized results for Scratch

11 shows scratch depth v. Linear regression of mean normalized % removal rate is shown. The scratch depth examined in Example 4 was determined to be significant (p-value = 0.000) when analyzed using linear regression shown in Figure 11. The regression shows that approximately 87% of the data variability can be attributed to the model, lending credence to the finding that % removal rate decreases with increasing depth.

Figure 12 shows the percentage of fluorescence appearance failures for Example 4. Fluorescence analysis also showed a strong correlation with the increase in depth preventing removal of residues. As Figure 12 shows, as the depth increased past 1.0 mm, the amount of rejections during fluorescence testing also increased. The results show that the presence of scratches greater than 1.0 mm in depth can trap the amount of residue that can be observed by UV inspection of fluorescein.

Taking all results into account, a specification of < 1.0 mm for scratches can be used as a criterion for calibration, as scratches exceeding this depth indicated visual failure within the range tested in this study.

Appendix Examples:

The appendix examples using tank ring surrogates with process contaminants and various cleaners have a complex interpretation in that contaminant and cleaner interactions may be the overriding factor in the results. The normalized weight measurement results are shown in Table 12. The fluorescence results are shown in Table 13 and the TOC swab results are shown in Table 14. Where applicable, corresponding BSA test results are shown for the same coupon.

[Table 12] Results of % removal rate for appendix studies

[Table 13] Results of fluorescence failure for the appendix study

[Table 14] Results of TOC analysis in the appendix study

Figures 13 and 14 show ANOVA methods demonstrating that the “normalized % removal” of each contaminant combination is a function of the cleaning agent. As shown in Figures 13 and 14, the cleaning agent affects the percent removal (p-value = 0.001). As such, subsequent regression analysis was performed using the cleaner/contaminant combination as a categorical variable, as shown in Figure 15.

Figure 15 shows multiple regression analysis for % removal as a function of density coefficient, aspect ratio, and depth. This analysis shows that only the cleaning agent was a significant factor in removal (p-value = 0.007). The dominant influence of the contaminant/cleaner combination masks any underlying trends in pit behavior explored in the examples.

Figure 16 shows multiple regression for % removal rate as a function of scratch depth. Here, neither scratch depth nor cleaner were considered significant variables in predicting mass removal (p-value > 0.05). Variability in contaminant removal appeared to be related to other uncontrolled parameters, as indicated by the random distribution of removal rate values shown in Figure 13.

In these appendix examples, melt contaminants were chosen to represent worst case process contaminants. Most of the cleaning schemes tested were not necessarily targeted at worst case contaminants. This results in data variability that is incompatible with the choice of contaminant vs. cleaning scheme (e.g., lysate vs. 1% CIP100 or purified water). In operational equipment, cleaning plans must be designed to provide worst-case results within a given piece of equipment so that the variability found in the data for incompatible conditions may not necessarily reflect at-scale performance. Can be selected to target contaminants.

Although no significant variables other than the detergent could be derived from the regression analysis, the fluorescence results in Table 13 show similar trends for the behavior of the BSA surrogates. Higher depth/diameter coupons (P-05 and P-23 at 5 mm x 5 mm followed by P-16 at 4 mm depth x 1.2 mm diameter) show a greater tendency to fail inspection. Deeper scratches (S-04 at 4 mm) also show a greater likelihood of visual failure under UV light. The trend of fluorescence rejection for each coupon is consistent across contaminants and cleaners.

Finally, returning to the TOC results from the study, all cleaner combinations were able to remove lysate contaminants to the point where the average swab result was less than 500 ppb TOC. Variability in swab results was lowest with CIP 100® cleaner. Purified water was ineffective in removing the lysate with any swab recovering an average TOC result of greater than 1 ppm. To confirm, multiple regression was used to test the hypothesis that the cleaning capacity of melt contaminants is a function of aspect ratio, density, pit depth, and detergent. The detergent and purified water results, which were established as categorical variables in this analysis, were removed from the analysis due to unusually high results.

Figure 17 shows multiple regression for % removal as a function of density coefficient, aspect ratio, and depth of the fit. The regression results from the TOC evaluation of pitted coupons mirror the results from the gravimetric evaluation. This analysis shows that only the cleaning agent was a significant factor in removal (p-value = 0.006). The dominant influence of the contaminant/cleaner combination masks any underlying trends in pit behavior, at least within the range tested.

The regression results for coupons with scratches are shown in Figure 18. That is, Figure 18 shows a multiple regression for % removal rate as a function of scratch depth. Again, neither scratch depth nor cleaner was considered to be a significant variable in predicting mass removal (p-value > 0.05). The p-value for the cleaner was 0.097, indicating a weaker correlation between the cleaner and TOC removal on scratched coupons than seen in the gravimetric evaluation.

The combined TOC results for pitted and scratched coupons are compared using ANOVA in Figures 19 and 20. Figure 19 shows a graphical summary of the appendix TOC results. Figure 20 shows the ANOVA summary of the Appendix TOC results. ANOVA shows that aggregate TOC results were statistically lower for CIP-100 than any other cleaner (p-value <0.05). The results for CIP-150 and NaOH were indistinguishable (p-value > 0.05), and the purified water results showed TOC values one order of magnitude higher than any of the cleaners. This analysis supports the claim that the appendix study results were influenced by the interaction of the cleaning agent and contaminants.

Discussion of Examples

The results of Examples 1-4 and the Appendix Examples indicate that surface abnormalities smaller than the inflection point do not appear to affect the cleanability of the device at scale using standard CIP cleaning techniques and chemistries.

Pit: Statistical analysis of pit data using the BSA surrogate revealed no significant correlation between aspect ratio, depth, and density (p-value > 0.05). However, both pit depth (p-value = 0.091) and the interaction between pit depth and aspect ratio (p-value = 0.064) were close to the threshold for statistical significance and may indicate a minor effect. This indicates that depth versus diameter interaction may be important for residue removal, which was supported by the contour plot derived from the regression model data and presented in Figure 7. These graphical results indicate that quadrants with diameter > 3.5 mm and depth > 2.5 mm are likely to have a negative impact on cleaning efficiency.

Further observation of pits on the surface and fluorescent material in the material suggested an unblemished surface as well as a certain inflection point beyond which coupons were not cleaned. Specifically, the material was consistently found in pits with diameters > 4.0 mm and depths > 2.6 mm. This trend was also seen in a regression analysis of gravimetric data with diameter > 2.5 mm and depth > 3.5 mm affecting cleaning for many of the continuous scales. As such, in some embodiments, the reactor surface should not have pits with a depth greater than about 2.6 mm, and in some embodiments, greater than about 1.2 mm. These results are consistent with a regression model showing a trend toward lower mass removal at higher depth and diameter combinations.

Using melt process contaminants, no correlation was found between any pit characteristics and gravimetric or TOC removal (p-value > 0.05). However, in both cases, the detergent was found to be a significant predictor in mass removal (p-value = 0.007) and TOC removal (p-value = 0.006).

Taking all results into account, the reactor surface can be maintained at a maximum pit depth of approximately 2.6 mm, with depths greater than this value indicating an apparent failure within the range tested in this study. In some embodiments, about 1.2 mm is the basis for correction. Basing specifications solely on depth provides the fastest and most accurate field measurements. Because the data show that only depth becomes important as diameter exceeds a certain threshold, adopting a fit-check criterion for this single variable provides a conservative approach to calibration.

Scratches: Like pits, scratches can affect cleaning performance with visible failures under fluorescence that occur when deeper than approximately 1.0 mm. Scratches not only retain more tracking dye as depth increases, but also retain a statistically significant reduced percent removal by gravimetric measurements. Statistical analysis of scratch data using BSA surrogates revealed a strong correlation between scratch depth and removal efficiency (p-value = 0.000), with removal deteriorating with increasing scratch depth. Visual inspection using a fluorescent marker detected failure when the depth exceeded approximately 1.0 mm. Using melt process contaminants, the correlation between scratch depth and removal efficiency was not significant (p-value > 0.05) for both gravimetric and TOC results. However, based on the pit results, the detergent condition/contaminant interaction appears to mask the relative importance of pit depth (p-value > 0.097 for both gravimetric and TOC results). Taking all results into account, the reactor surface can be commissioned or maintained with a maximum scratch depth of approximately 1.0 mm.

Statistical analysis of the micropitting data revealed that there was no statistical correlation between density coefficient and residual mass (p-value > 0.05), at least within the range tested here. Additionally, fluorescence failure was not noted during visual inspection. Statistical analysis of the surface roughness data revealed no statistical correlation between Ra Max (μin) values and residual mass (p-value > 0.05). Additionally, fluorescence failure was not noted during visual inspection.

The appendix examples are designed to demonstrate the usefulness of these parameters using in-process soil. The study suggested that the contaminant and cleaning agent combination had a greater effect on removal than the surface defects themselves. Nonetheless, the consistent fluorescence rejection at high diameter and depth combinations, supported by similar trends in the gravimetric contour plots, shows that similar trends in removal occur under actual process conditions.

Table 15 summarizes statistical conclusions from studies on gravimetric analysis of pits, scratches, and surface roughness. A p-value <0.05 indicates that certain variables are considered statistically significant, while the R ² value indicates the percentage of data variability that can be attributed to the regression model.

[Table 15] Gravimetric conclusion from BSA test

Table 16 summarizes conclusions from the appendix examples regarding gravimetric analysis. In all cases, worst-case melt process contaminants were applied to test coupons and residual mass was evaluated as a function of different pit and scratch parameters. Regression was performed with detergent test condition included as a categorical variable.

[Table 16] Weight measurement conclusion from appendix examples

Table 17 summarizes conclusions from the appendix examples regarding residual TOC detected from swab sampling. In all cases, the TOC values obtained represent the amount of lysate contaminants that can be detected after cleaning. Regression was again performed on the data to evaluate the impact of pits and scratches on residual TOC. Cleanser test condition was included as a categorical variable. The results exclude values obtained after rinsing with purified water at 80°C because all TOC swabs exceed 1 ppm under these conditions:

[Table 17] TOC conclusions from appendix studies

The description of various embodiments of the invention has been presented for purposes of illustration, but is not intended to be exhaustive or limited to the disclosed embodiments. Numerous modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, applications, or technological improvements over techniques found in the marketplace of the embodiments, or to enable persons other than those of ordinary skill in the art to understand the embodiments disclosed herein. It has been done.

The description of various embodiments of the present invention can be used in the manufacture of pharmaceuticals and biopharmaceutical products. The devices, equipment and methods described herein are suitable for culturing any desired cell line, including prokaryotic and/or eukaryotic cell lines. Moreover, in embodiments, the devices, equipment and methods are suitable for culturing suspension cells or anchorage-dependent (adherent) cells and producing pharmaceutical and biopharmaceutical products, such as polypeptide products, nucleic acids. It is suitable for production operations configured for the preparation of products (e.g. DNA or RNA), or cells and/or viruses, e.g. those used in cell and/or virus therapy.

In an embodiment, the cells express or produce a product, such as a recombinant therapeutic or diagnostic product. As described in more detail below, examples of products produced by cells include antibody molecules (e.g., monoclonal antibodies, bispecific antibodies), antibody mimetics (which bind specifically to an antigen but are not structurally similar to an antibody). Unrelated polypeptide molecules (e.g., DARPins, affibodies, adnectins, or IgNARs), fusion proteins (e.g., Fc fusion proteins, chimeric cytokines), other recombinant proteins (e.g., glycosylated proteins, enzymes, hormones), viral therapeutics (e.g., oncolytic viruses on cancer, viral vectors for gene therapy and viral immunotherapy), cellular therapeutics (e.g., pluripotent stem cells, mesenchymal stem cells, and adult stem cells), vaccines or lipid-encapsulated particles (e.g., exosomes, virus-like particles), RNA (e.g., siRNA) or DNA (e.g., plasmid DNA), antibiotics or amino acids, It is not limited to this. In embodiments, devices, equipment and methods may be used to produce biosimilars.

As mentioned, in embodiments, the devices, facilities and methods may be used in eukaryotic cells, such as mammalian cells or lower eukaryotic cells, such as yeast cells or filamentous fungal cells, or prokaryotic cells, such as Gram- Can produce products of positive or Gram-negative cells and/or eukaryotic or prokaryotic cells, such as proteins, peptides, antibiotics, amino acids, nucleic acids (e.g. DNA or RNA) synthesized by eukaryotic cells on a large scale. . Unless otherwise specified herein, the devices, equipment, and methods may include any desired volume or production capacity, including, but not limited to, bench-scale, pilot-scale, and full production scale capacities.

Furthermore, unless otherwise specified herein, devices, equipment, and methods may be used in agitated tanks, airlifts, fibers, microfibers, hollow fibers, ceramic matrices, fluidized beds, fixed beds, and/or spouted beds. ) may include any suitable reactor(s), including but not limited to bioreactors. As used herein, “reactor” may include a fermentor or fermentation unit, or any other reaction vessel, and the term “reactor” is used interchangeably with “fermenter.” For example, in some aspects, exemplary bioreactor units may perform one or more or all of the following: supply of nutrients and/or carbon sources, injection of suitable gases (e.g., oxygen), fermentation, or Inlet and outlet flow of cell culture medium, separation of gas and liquid phases, maintenance of temperature, maintenance of oxygen and CO2 levels, maintenance of pH level, agitation (e.g., stirring), and/or cleaning/sterilization. Exemplary reactor units, such as fermentation units, may contain multiple reactors within the unit, for example, the unit may have 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, There may be 45, 50, 60, 70, 80, 90, or 100, or more bioreactors in each unit and/or the facility may contain multiple units with single or multiple reactors within the facility. In various embodiments, the bioreactor may be suitable for batch, semi-fed-batch, fed-batch, perfusion, and/or continuous fermentation processes. Any suitable reactor diameter may be used. In embodiments, the bioreactor may have a volume of about 100 mL to about 50,000 L. Non-limiting examples include 100 mL, 250 mL, 500 mL, 750 mL, 1 liter, 2 liters, 3 liters, 4 liters, 5 liters, 6 liters, 7 liters, 8 liters, 9 liters, 10 liters, 15 liters, 20 liters, 25 liters. Liter, 30 liter, 40 liter, 50 liter, 60 liter, 70 liter, 80 liter, 90 liter, 100 liter, 150 liter, 200 liter, 250 liter, 300 liter, 350 liter, 400 liter, 450 liter, 500 liter, 550 liters, 600 liters, 650 liters, 700 liters, 750 liters, 800 liters, 850 liters, 900 liters, 950 liters, 1000 liters, 1500 liters, 2000 liters, 2500 liters, 3000 liters, 3500 liters, 4000 liters, 4500 liters , 5000 liters, 6000 liters, 7000 liters, 8000 liters, 9000 liters, 10,000 liters, 15,000 liters, 20,000 liters, and/or 50,000 liters. Additionally, suitable reactors may be multi-use, single-use, disposable, or non-disposable and may be made of metal alloys such as stainless steel (e.g., 316L or any other suitable stainless steel) and Inconel. , plastic, and/or glass.

In embodiments and unless otherwise specified herein, the devices, equipment, and methods described herein also include any suitable unit operations not otherwise noted, such as operations and/or devices for the separation, purification, and isolation of such products. and/or devices. Any suitable equipment and environment may be used, such as conventional stick-built equipment, modular, portable and temporary equipment, or other suitable structures, equipment and/or layouts. For example, modular clean-rooms may be used in some embodiments. Additionally, and unless otherwise specified, the devices, systems, and methods described herein may be housed and/or practiced in a single location or facility, or alternatively, may be housed in separate or multiple locations and/or facilities and /or can be executed.

By way of non-limiting example and without limitation, the U.S. Pat. Publication No. 2013/0280797; No. 2012/0077429; No. 2011/0280797; No. 2009/0305626; and U.S. Patent No. 8,298,054; No. 7,629,167; and 5,656,491 describe exemplary equipment, devices, and/or systems that may be suitable.

In an embodiment, the cell is a eukaryotic cell, such as a mammalian cell. Mammalian cells may be, for example, human or rodent or bovine cell lines or cell strains. Examples of such cells, cell lines or cell strains include, for example, mouse myeloma (NSO)-cell line, Chinese hamster ovary (CHO)-cell line, HT1080, H9, HepG2, MCF7, MDBK Jurkat, NIH3T3, PC12, BHK (cub Hamster kidney cells), VERO, SP2/0, YB2/0, Y0, C127, L cells, COS, e.g. COS1 and COS7, QC1-3, HEK-293, VERO, PER.C6, HeLA, EBl, EB2, EB3, oncolytic or hybridoma-cell lines. Preferably, the mammalian cells are CHO-cell lines. In one embodiment, the cells are CHO cells. In one embodiment, the cells are CHO-K1 cells, CHO-K1 SV cells, DG44 CHO cells, DUXB11 CHO cells, CHOS, CHO GS knockout cells, CHO FUT8 GS knockout cells, CHOZN, or CHO-derived cells. CHO GS knockout cells (eg, GSKO cells) are, for example, CHO-K1 SV GS knockout cells. CHO FUT8 knockout cells are, for example, Potelligent® CHOK1 SV (Lonza Biologics, Inc.). The eukaryotic cell may also be an avian cell, cell line or cell strain, such as EBx® cells, EB14, EB24, EB26, EB66, or EBvl3.

In one embodiment, the eukaryotic cell is a stem cell. Stem cells include, for example, embryonic stem cells (ESCs), adult stem cells, induced pluripotent stem cells (iPSCs), tissue-specific stem cells (e.g., hematopoietic stem cells), and mesenchymal stem cells (MSCs). It may be pluripotent stem cells including.

In one embodiment, the cell is a differentiated form of any of the cells described herein. In one embodiment, the cells are cells derived from any primary cell in culture.

In an embodiment, the cells are hepatocytes, such as human hepatocytes, animal hepatocytes, or non-parenchymal cells. For example, cells include plateable metabolic quantitative human hepatocytes, plateable derived quantitative human hepatocytes, plateable Qualyst Transporter Certified ^TM human hepatocytes, suspension quantitative human hepatocytes (including 10-donor and 20-donor pooled hepatocytes), and human Liver Kupffer cells, human hepatic stellate cells, canine hepatocytes (including single and integrated Beagle hepatocytes), mouse hepatocytes (including CD-1 and C57BI/6 hepatocytes), rat hepatocytes (Sprague-Dawley, Wistar Hahn ( Wistar Han and Wistar hepatocytes), monkey hepatocytes (including Cynomolgus and Rhesus monkey hepatocytes), cat hepatocytes (including Domestic Shorthair hepatocytes), and rabbit hepatocytes (New Zealand White) White) may include liver cells. Exemplary hepatocytes are commercially available from Triangle Research Labs, LLC, 6 Davis Drive Research Triangle Park, North Carolina, USA 27709.

In one embodiment, the eukaryotic cell is a lower eukaryotic cell, such as a yeast cell (e.g., a member of the Pichia genus (e.g., Pichia pastoris, Pichia methanolica, Pichia clujberg, and Pichia Angusta), the genus Comagataella (e.g., Comagataella pastoris, Comagataella pseudopastoris or Comagataella papii), the genus Saccharomyces (e.g., Saccharomyces cerevisae, cerevisiae, Saccharomyces kluyveri, Saccharomyces uvarum), Kluyveromyces genera (e.g. Kluyveromyces lactis, Kluyveromyces maxianus), Candida genus (e.g. For example, Candida utilis, Candida cacaoi, Candida voidinii), Geotrichum genus (e.g. Geotrichum fermentans), Hansenula polymorpha, Yarrowia lipolytica, or Schizosaccharomai Seth pombeida.Pichia pastoris species is preferred.Examples for Pichia pastoris strains are X33, GS115, KM71, KM71H; and CBS7435.

In one embodiment, the eukaryotic cell is a fungal cell (e.g., Aspergillus (e.g., A. niger, A. fumigatus, A. origiera, A. nidula), Acremonium (e.g. For example, A. thermophilum), Ketomium (e.g. C. thermophilum), Chrysosporium (e.g. C. thermophilum), Cordyceps (e.g. C. Militaris), Corinascus, Ctenomyces, Fusarium (e.g. F. oxysporum), Glomerella (e.g. G. graminicola), Hypocreaa (e.g. H. zecorina), Magnaporte (e.g. M. orgier), Mycelioptora (e.g. M. thermophile), Nectria (e.g. N. haematococa), Neurospora Ra (e.g. N. crassa), Penicillium, Sporotrichum (e.g. S. thermophile), Thiellavia (e.g. T. terrestris, T. heterotalica) , Trichoderma (e.g. T. reesei), or Verticillium (e.g. V. dahlia)).

In one embodiment, the eukaryotic cell is an insect cell (e.g., an Sf9, Mimic™, Sf9, Sf21, High Five™ (BT1-TN-5B1-4), or BT1-Ea88 cell), an algae cell (e.g. For example, cells of the genera Amphora, Basilariophyceae, Dunaliella, Chlorella, Chlamydomonas, Cyanophyta (cyanobacteria), Nannochloropsis, Spirulina, Orochromonas), or plant cells (e.g. , cells from monocot plants (e.g., maize, rice, wheat, or Setaria), or dicot plants (e.g., cassava, potato, soybean, tomato, tobacco, alfalfa, Physcomitrella patens or Arabidopsis) )am.

In one embodiment, the cell is a bacterial or prokaryotic cell.

In an embodiment, the prokaryotic cell is a Gram-positive cell, such as Bacillus, Streptomyces streptococcus, Staphylococcus, or Lactobacillus. Bacilli that can be used are, for example, B. subtilis, B. amyloliquefaciens , B. licheniphormis , B. natto, or B. megaterium . In an embodiment, the cell is B. subtilis, such as B. subtilis 3NA and B. subtilis 168. Bacillus is available, for example, from the Bacillus Genetic Stock Center (Biological Sciences 556, 484 West 12 ^th Avenue, Columbus OH 43210-1214).

In one embodiment, the prokaryotic cell is a Gram-negative cell, such as Salmonella spp. or Escherichia coli, such as TG1, TG2, W3110, DH1, DHB4, DH5a, HMS 174, HMS174 (DE3), NM533, C600, HB101, JM109, MC4100, XL1-Blue and Origami, as well as well as cells derived from E. coli B-strains, such as BL-21 or BL21(DE3), all of which are commercially available.

Suitable host cells are commercially available, for example, from strain collections such as DSMZ (Deutsche Sammlung von Mikroorganismen and Zellkulturen GmbH, Braunschweig, Germany) or the American Type Culture Collection (ATCC).

In an embodiment, the cultured cells are used to produce proteins, such as antibodies, such as monoclonal antibodies, and/or recombinant proteins, for therapeutic uses. In an embodiment, the cultured cells produce peptides, amino acids, fatty acids or other useful biochemical intermediates or metabolites. For example, in embodiments, molecules having molecular weights from about 4000 daltons to about 140,000 daltons or more may be produced. In embodiments, these molecules can be of a wide range of complexity and can include post-translational modifications, including glycosylation.

In an embodiment, the protein is, for example, BOTOX, Myobloc, Neurobloc, Dysport (or other serotypes of botulinum neurotoxin), aleucosidase alpha, Daptomycin, YH-16, cryonadotropin alfa, filgrastim, cetrorelix, interleukin-2, aldesleukin, teseriulin, denileukin diftitox, interferon alpha-n3 (injection), interferon alpha- nl, DL-8234, interferon, Suntory (gamma-1a), interferon gamma, thymosin alpha 1, tasonermin, DigiFab, ViperaTAb, EchiTAb, CroFab, nesiritide, abatacept, alefacept, Rebif, eptoterminalpa , Teriparatide (osteoporosis), calcitonin injection (bone disease), calcitonin (intranasal, osteoporosis), etanercept, hemoglobin glutamer 250 (bovine), drotrecogin alfa, collagenase, cafferitide, recombinant human epidermal growth factor. (topical gel, wound healing), DWP401, darbepoetin alfa, epoetin omega, epoetin beta, epoetin alfa, desirudin, lepirudin, bivalirudin, nonacog alfa, Mononine, Eptaco He Alpha (Activated), Recombinant Factor VIII+VWF, Recombinate, Recombinant Factor VIII, Factor VIII (Recombinant), Alphnmate, Octocog Alpha, Factor VIII, Palifermin, Indikinase, Tenecteplase, alteplase, pamiteplase, reteplase, nateplase, monteplase, follitropin alfa, rFSH, hpFSH, micafungin, pegfilgrastim, lenograstim, nartogras Tim, thermorelin, glucagon, exenatide, pramlintide, iniglucerase, galsulfase, leukotropin, molgramostyrne, triptorelin acetate, histrelin (subcutaneous implant, Hydron), Slorelin, histrelin, nafarelin, leuprolide sustained-release depot (ATRIGEL), leuprolide implant (DUROS), goserelin, utropin, KP-102 program, somatropin, Mecacermin ( growth failure), enlfavirtide, Org-33408, insulin glargine, insulin gluicine, insulin (inhaled), insulin lispro, insulin deternir, insulin (oral, RapidMist), mecasermin linfabate, anakinra, Selmoleukin, 99 mTc-Abcitide Injection, Myelopide, Betaseron, Glatiramer Acetate, Gepon, Sagramostim, Ofrelbekin, Human Leukocyte-Derived Alpha Interferon, Bilive, Insulin ( recombinant), recombinant human insulin, insulin aspart, mecacenin, loferon-A, interferon-alpha 2, alphaferon, interferon alphacon-1, interferon alpha, Avonex' recombinant human luteinizing hormone, donase alpha , trafermin, ziconotide, taltirelin, divoterminalpa, atosiban, becaplermin, eptifibatide, Zemaira, CTC-111, Shanvac-B, HPV vaccine (quadrivalent) , octreotide, lanreotide, ancestine, agalsidase beta, agalsidase alpha, laronidase, fresatide copper acetate (topical gel), rasburicase, ranibizumab, Actimmune , PEG-intron, tricomine, recombinant house dust mite allergy desensitization injection, recombinant human parathyroid hormone (PTH) 1-84 (sc, osteoporosis), epoetin delta, transgenic antithrombin III, granditrophin, vitrase, recombinant insulin. , interferon-alpha (oral lozenge), GEM-21S, vapreotide, idursulfase, omnapatrilat, recombinant serum albumin, certolizumab pegol, glucarpidase, human recombinant C1 esterase inhibitor (vascular edema), lanoteplase, recombinant human growth hormone, enfuvertide (needle-free injection, Biojector 2000), VGV-1, interferon (alpha), lucinactant, aviptadil (inhalation, pulmonary disease), icatibant , Ecalantide, Omiganan, Aurograb, Pexiganan Acetate, ADI-PEG-20, LDI-200, Degarelix, Syntredelin Vesudotox, Favld, MDX-1379, ISAtx-247, Liraglutide, Teriparatide (osteoporosis), Tipacogin, AA4500, T4N5 liposome lotion, catumaxomab, DWP413, ART-123, chrysalin, desmoteplase, amediplase, corypolytropin alfa, TH-9507, teduglutide, diamide (Diamyd), DWP-412, growth hormone (extended-release injection), recombinant G-CSF, insulin (inhaled, AIR), insulin (inhaled, Technosphere), insulin (inhaled, AERx) ), RGN-303, DiaPep277, interferon beta (for hepatitis C virus infection (HCV)), interferon alpha-n3 (oral), belatacept, transdermal insulin patch, AMG-531, MBP-8298, Xerecept , Opevacan, AIDSVAX, GV-1001, LymphoScan, ranfirnase, lipoxylic acid, rusupultide, MP52 (beta-tricalcium phosphate carrier, bone regeneration), melanoma vaccine, sipuleucel-T, CTP-37, Insegia, Vitesfen, human thrombin (frozen, surgical hemorrhage), thrombin, TransMID, alfimeplase, furicase, tulipresin (intravenous, hepatorenal syndrome), EUR-1008M, recombinant FGF- I (injectable, vascular disease), BDM-E, rotigaptide, ETC-216, P-113, MBI-594AN, duramycin (inhaled, cystic fibrosis), SCV-07, OPI-45, endostatin, angiostatin, ABT-510, Bauman-Burke Inhibitor Concentrate, , Interleukin 4, PRX-321, Pepscan, Ivotadechin, Lelactoferrin, TRU-015, IL-21, ATN-161, Cilengitide, Albuferon, Biphasix, IRX-2 , omega interferon, PCK-3145, CAP-232, pasireotide, huN901-DMI, ovarian cancer immunotherapy vaccine, SB-249553, Oncovax-CL, OncoVax-P, BLP-25, CerVax-16, multi-epitope peptide Melanoma vaccine (MART-1, gp100, tyrosinase), nemipitide, rAAT (inhalation), rAAT (dermatology), CGRP (inhalation, asthma), pegsunercept, thymosin beta4, plitidepsin, GTP-200 , ramoplanin, GRASPA, OBI-1, AC-100, salmon calcitonin (oral, eligen), calcitonin (oral, osteoporosis), examorelin, capromorelin, Cardeva, belafermin, 131I-TM-601 , KK-220, T-10, ularitide, defelestat, hematide, chrysalin (topical), rNAPc2, recombinant factor V111 (PEGylated liposomal), bFGF, PEGylated recombinant staphylokinase variant, V-10153, SonoLysis Prolyse, NeuroVax, CZEN-002, islet nephrogenic therapy, rGLP-1, BIM-51077, LY-548806, Exenatide (controlled release, Medisorb), AVE-0010, GA- GCB, arborrelin, ACM-9604, linaclotide acetate, CETi-1, Hemospan, VAL (injectable), short-acting insulin (injectable, Viadel), intranasal insulin, insulin (inhaled), insulin (oral, eligen), recombinant methionyl human leptin, Fitrakinra subcutaneous injection, eczema), Fitrakinra (inhaled dry powder, asthma), Multikine, RG-1068, MM-093, NBI-6024, AT- 001, PI-0824, Org-39141, Cpn10 (autoimmune disease/inflammation), Talatoferrin (topical), rEV-131 (ophthalmology), rEV-131 (respiratory disease), oral recombinant human insulin (diabetes), RPI- 78M, Ofrelbekin (oral), CYT-99007 CTLA4-Ig, DTY-001, Balategrast, Interferon alpha-n3 (topical), IRX-3, RDP-58, Tauferon, bile salt-stimulated lipase , merispase, alanine phosphatase, EP-2104R, melanotan-II, bremelanotide, ATL-104, recombinant human microplasmin, AX-200, SEMAX, ACV-1, Xen-2174, CJC-1008, Dino Lepin A, SI-6603, LAB GHRH, AER-002, BGC-728, malaria vaccine (virosome, PeviPRO), ALTU-135, parvovirus B19 vaccine, influenza vaccine (recombinant neuraminidase), malaria/HBV Vaccine, Anthrax vaccine, Vacc-5q, Vacc-4x, HIV vaccine (oral), HPV vaccine, Tat toxoid, YSPSL, CHS-13340, PTH(1-34) liposomal cream (Novasome), Ostabolin-C, PTH analog (topical, psoriasis), MBRI-93.02, MTB72F vaccine (tuberculosis), MVA-Ag85A vaccine (tuberculosis), FARA04, BA-210, recombinant plague FIV vaccine, AG-702, OxSODrol, rBetV1, Der-p1/Der -p2/Der-p7 allergen-targeted vaccine (dust mite allergy), PR1 peptide antigen (leukemia), mutant ras vaccine, HPV-16 E7 lipopeptide vaccine, labyrinthin vaccine (adenocarcinoma), CML vaccine, WT1-peptide vaccine. (Cancer), IDD-5, CDX-110, Fentris, Norelin, CytoFab, P-9808, VT-111, Icrocaptide, Telvermin (dermatology, diabetic foot ulcer), Rupintrivir, Reticul Ross, rGRF, HA, alpha-galactosidase A, ACE-011, ALTU-140, CGX-1160, angiotensin therapeutic vaccine, D-4F, ETC-642, APP-018, rhMBL, SCV-07 (oral, tuberculosis), DRF-7295, ABT-828, ErbB2-specific immunotoxin (anticancer), DT3SSIL-3, TST-10088, PRO-1762, Combotox, cholecystokinin-B/gastrin-receptor binding peptide, 111In -hEGF, AE-37, Trasnizumab-DM1, Antagonist G, IL-12 (recombinant), PM-02734, IMP-321, rhIGF-BP3, BLX-883, CUV-1647 (topical), L-19 based Radioimmunotherapy (cancer), Re-188-P-2045, AMG-386, DC/1540/KLH vaccine (cancer), VX-001, AVE-9633, AC-9301, NY-ESO-1 vaccine (peptide) , NA17.A2 peptide, melanoma vaccine (pulsatile antigen therapy), prostate cancer vaccine, CBP-501, recombinant human lactoferrin (dry eye), FX-06, AP-214, WAP-8294A (injectable), ACP-HIP , SUN-11031, peptide YY [3-36] (obesity, intranasal), FGLL, atacicept, BR3-Fc, BN-003, BA-058, human parathyroid hormone 1-34 (intranasal, osteoporosis), F -18-CCR1, AT-1100 (celiac disease/diabetes), JPD-003, PTH(7-34) liposomal cream (Novasome), duramycin (ophthalmology, dry eye), CAB-2, CTCE-0214, GlycoPEGylated erythropoietin, EPO-Fc, CNTO-528, AMG-114, JR-013, factor (immediate release), EP-51216, hGH (controlled release, Biosphere), OGP-I, sifuvirtide, TV4710, ALG-889, Org-41259, rhCC10, F-991, thymopentine (pulmonary disease), r( m)CRP, liver-selective insulin, subalin, L19-IL-2 fusion protein, elafin, NMK-150, ALTU-139, EN-122004, rhTPO, thrombopoietin receptor agonist (thrombocytopenia disorder), AL -108, AL-208, nerve growth factor antagonist (pain), SLV-317, CGX-1007, INNO-105, oral teriparatide (eligen), GEM-OS1, AC-162352, PRX-302, LFn-p24 Fusion vaccine (Therapore), EP-1043, S pneumoniae pediatric vaccine, malaria vaccine, Meningococcal group B vaccine, Neonatal group B streptococcal vaccine, Anthrax vaccine, HCV vaccine (gpE1+gpE2+MF-59), otitis media therapy, HCV vaccine (core antigen + ISCOMATRIX), hPTH(1-34) (transdermal, ViaDerm), 768974, SYN-101, PGN-0052, Aviscumnin, BIM-23190, tuberculosis vaccine, multi-epitope tyrosinase peptide, cancer vaccine, Encasstim, APC-8024, GI-5005, ACC-001, TTS-CD3, vascular-targeted TNF (solid tumors), desmopressin (oral controlled-release), Onercept, and TP-9201.

In some embodiments, the polypeptide is selected from adalimumab (HUMIRA), infliximab (REMICADE™), rituximab (RITUXAN™/MAB THERA™) etanercept (ENBREL™), bevacizumab (AVASTIN™), tra stuzumab (HERCEPTIN™), pegrilgrastim (NEULASTA™), or any other suitable polypeptide, including biosimilars and biobetter.

Other suitable polypeptides are listed below and in Table 1 of US Patent No. 2016/0097074:

[Table 1]

In embodiments, the polypeptide is a hormone, clotting/coagulation factor, cytokine/growth factor, antibody molecule, fusion protein, protein vaccine, or peptide as shown in Table 2.

[Table 2] Example products

In an embodiment, the protein is a multispecific protein, such as a bispecific antibody as shown in Table 3.

[Table 3] Bispecific format

Claims (23)

As biopharmaceutical processing equipment,
A vessel comprising a surface configured to contact the proteinaceous processing material, and a clean-in-place (CIP) device configured to clean the surface,
wherein the surface has a pre-commissioning surface roughness of 25 Ra Max (μin) or more and 250 Ra Max (μin) or less. The biopharmaceutical processing device of claim 1, wherein the surface has a pre-commissioning surface roughness of greater than 35 Ra Max (μin) and less than or equal to 250 Ra Max (μin). The biopharmaceutical processing device of claim 1, wherein the surface has a pre-commissioning surface roughness of greater than 90 Ra Max (μin) and less than or equal to 150 Ra Max (μin). The biopharmaceutical processing device of claim 1, wherein the surface has a pre-commissioning surface roughness of 150 Ra Max (μin). The biopharmaceutical processing device of claim 1, wherein the surface is formed of 316L stainless steel. As a biopharmaceutical processing device,
comprising a container having a surface configured to contact the proteinaceous processing material,
wherein the surface has a surface finish free of surface anomalies exceeding a maximum depth of surface pitting of 2.6 mm. 7. The biopharmaceutical processing device of claim 6, wherein the processing device surface has no surface abnormalities exceeding a maximum scratch depth of 1.0 mm. 7. The biopharmaceutical processing device of claim 6, wherein the surface has no surface abnormalities exceeding a maximum depth of surface fitting of 1.2 mm. 7. The biopharmaceutical processing device of claim 6, wherein the surface is formed of 316L stainless steel. 7. The biopharmaceutical processing device of claim 6, wherein the surface has a pre-commissioning surface roughness greater than 20 Ra Max (μin). 7. The biopharmaceutical processing device of claim 6, wherein the surface has a pre-commissioning surface roughness of greater than 35 Ra and less than or equal to 250 Ra Max (μin). 7. The biopharmaceutical processing device of claim 6, wherein the surface has a pre-commissioning surface roughness of 150 Ra Max (μin). 7. The biopharmaceutical processing device of claim 6, wherein the surface has a surface finish free of surface abnormalities exceeding any of a maximum depth of surface pitting of 1.2 mm, and a maximum depth of scratches of 1.0 mm. As a repair method for a biopharmaceutical processing device,
inspecting the surface of the container in contact with the processing material for the presence of surface abnormalities;
measuring physical characteristics beyond the surface on the surface; and
If the surface abnormality exceeds a predetermined threshold, remediating the surface abnormality from the surface.
A repair method of a biopharmaceutical processing device, including a. 15. The method of claim 14, wherein the physical characteristic is pit depth and/or scratch depth. The repair method of a biopharmaceutical processing device according to claim 14, wherein the surface abnormality is a pit, and the predetermined threshold is a maximum pit depth of 2.6 mm. The method of repairing a biopharmaceutical processing device according to claim 14, wherein the surface abnormality is a pit, and the predetermined threshold is a maximum pit depth of 1.2 mm. 15. The method of claim 14, wherein the surface abnormalities are micropits and the predetermined threshold is a maximum micropit density of 2600 per inspection area. The repair method of a biopharmaceutical processing device according to claim 14, wherein the surface abnormality is a scratch, and the predetermined threshold is a maximum scratch depth of 1.0 mm. The repair method of a biopharmaceutical processing device according to claim 14, wherein the surface abnormality is surface roughness, and the predetermined threshold is a surface finish of 150 Ra Max (μin) or less. 15. The method of claim 14, wherein the predetermined thresholds include a maximum pit depth of 1.2 mm, a maximum micropit density of 2600 per inspection area, a maximum scratch depth of 1.0 mm, and a surface finish of less than or equal to 150 Ra Max (μin). Repair method for biopharmaceutical processing equipment. 15. The method of claim 14, wherein the step of inspecting the surface of the vessel in contact with the processed material for the presence of a surface anomaly comprises visually inspecting the surface of the reactor vessel and a depth gauge device to measure the depth of the anomaly. A method of repairing a biopharmaceutical processing device comprising at least one of the steps of using a depth gauge instrument. 15. The method of claim 14, wherein correcting surface abnormalities from the surface comprises buffing the surface with a buffing apparatus sufficient to remove the surface abnormalities.

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