WO2023211875A1 - Procédés et systèmes de production de flacons sans ligne de fusion - Google Patents

Procédés et systèmes de production de flacons sans ligne de fusion Download PDF

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Publication number
WO2023211875A1
WO2023211875A1 PCT/US2023/019718 US2023019718W WO2023211875A1 WO 2023211875 A1 WO2023211875 A1 WO 2023211875A1 US 2023019718 W US2023019718 W US 2023019718W WO 2023211875 A1 WO2023211875 A1 WO 2023211875A1
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Prior art keywords
flask
panel
cell culture
sidewall
rib
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PCT/US2023/019718
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English (en)
Inventor
Digvijay Singh RAWAT
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Corning Incorporated
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Publication of WO2023211875A1 publication Critical patent/WO2023211875A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
    • C12M23/00—Constructional details, e.g. recesses, hinges
    • C12M23/02—Form or structure of the vessel
    • C12M23/08—Flask, bottle or test tube
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C45/00—Injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould; Apparatus therefor
    • B29C45/17—Component parts, details or accessories; Auxiliary operations
    • B29C45/76—Measuring, controlling or regulating
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C45/00—Injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould; Apparatus therefor
    • B29C45/17—Component parts, details or accessories; Auxiliary operations
    • B29C45/76—Measuring, controlling or regulating
    • B29C45/768—Detecting defective moulding conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76003—Measured parameter
    • B29C2945/76153—Optical properties
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76344—Phase or stage of measurement
    • B29C2945/76424—After-treatment
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76494—Controlled parameter
    • B29C2945/76638—Optical properties
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76929—Controlling method
    • B29C2945/76939—Using stored or historical data sets
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76929—Controlling method
    • B29C2945/76939—Using stored or historical data sets
    • B29C2945/76949—Using stored or historical data sets using a learning system, i.e. the system accumulates experience from previous occurrences, e.g. adaptive control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76929—Controlling method
    • B29C2945/76983—Using fuzzy logic
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C2945/00—Indexing scheme relating to injection moulding, i.e. forcing the required volume of moulding material through a nozzle into a closed mould
    • B29C2945/76—Measuring, controlling or regulating
    • B29C2945/76929—Controlling method
    • B29C2945/76993—Remote, e.g. LAN, wireless LAN

Definitions

  • the present specification generally relates to methods of manufacture of flasks for use in cell culture and particularly relates to methods of flask manufacture that reduce or eliminate meld lines.
  • T flasks are traditional flasks used for cell culture. Typically, such flasks are optically clear or transparent in order to view the cell culture happening within the flask. During manufacturing of the flasks, process steps may result in meld line formation. Meld lines are undesirable, as meld lines are typically opaque, thus preventing the flask from being transparent and hindering the user in viewing the cell culture happening within the flask.
  • the present subject matter is directed to methods of designing cell culture flasks that are meld-line free.
  • a method of determining whether a design of a cell culture flask will be meld line-free comprises: training a machine learning model on cell culture flask design parameter data; inputting parameters of a flask design into a machine learning model; and determining whether the flask design will be meld line-free, based on output from the machine learning model.
  • cell culture flask design parameter data comprises data obtained by varying geometric parameters of cell culture flasks.
  • the cell culture flasks comprise U225 and U25 cell culture flasks.
  • the geometric parameters comprise ratios of geometric parameters.
  • the ratios of geometric parameters comprise: width panel (Wp) to length of panel (Lp); width of sidewall (Ws) to length of sidewall (Ls); thickness of panel (Tp) to thickness of sidewall (Ts); thickness of panel (Tp) to thickness of rib (Tr); width of rib (Wr) to length of rib (Lr); and length of panel (Lp) to length of sidewall (Ls).
  • training further comprises evaluating each design obtained by varying the geometric parameter for its meld line formation tendency by running it through a numerical model.
  • training further comprises conducting a comprehensive numerical design of experiments (DOE) to generate the data on which the machine learning model was trained on.
  • DOE numerical design of experiments
  • the cell culture flask comprises: a panel; a bottom arranged parallel to the panel; a plurality of sidewalls extending between the panel and the bottom, wherein a sidewall disposed at a first end of the flask comprises an endwall, wherein each sidewall has a sidewall length (Ls), sidewall thickness (Ts), and sidewall width (Ws); a neck portion disposed at an opposite second end of the flask; a rib disposed along at an outer perimeter of the panel, the rib extending upwards from an exterior surface of the panel; and an interior chamber defined by interior surfaces of the panel, the bottom, the plurality of sidewalls, and the neck portion.
  • the rib surrounds the entire outer perimeter of the panel.
  • the panel comprises a panel length (Lp), a panel thickness (Tp), and a panel width (Wp).
  • each sidewall of the plurality of sidewalls comprises a sidewall length (Ls), sidewall thickness (Ts), and sidewall width (Ws).
  • the rib comprises a rib length (Lr), rib thickness (Tr), and rib width (Wr).
  • the cell culture flask comprises a U-shaped flask. In an embodiment, the U-shaped flask comprises a canted neck. In an embodiment, the U-shaped flask comprises an angled neck. In an embodiment, the U-shaped flask comprises a straight neck. [0018] In an embodiment, the cell culture flask comprises a T-shaped flask. In an embodiment, the T-shaped flask comprises a canted neck. In an embodiment, the T-shaped flask comprises an angled neck. In an embodiment, the T-shaped flask comprises a straight neck.
  • the cell culture flask comprises a rectangular flask.
  • the rectangular flask comprises a canted neck.
  • the rectangular flask comprises an angled neck.
  • the rectangular flask comprises a straight neck.
  • a cell culture flask designed according to the methods described herein.
  • the cell culture flask comprises a U-shaped flask, a T- shaped flask, or a rectangular flask.
  • FIG. 1 shows perspective view of a flask according to embodiments described herein.
  • FIG. 2 shows a cross-sectional view of inset Box A of the flask of FIG. 1 according to embodiments described herein.
  • FIG. 3 shows an image of a U75 flask according to embodiments described herein.
  • FIG. 4 shows a perspective view of a U225 flask and a U25 flask according to embodiments described herein.
  • FIG. 5 shows a distribution chart of design cases, where the length ratio (Lp/Ls) is on the Y axis and the thickness ratio (Tp/Ts) is on the X axis according to embodiments described herein.
  • FIG. 6 shows a bar chart countplot of cases with thickness ratio (Tp/Ts) as 1 segregated by length ratio (Lp/Ls) according to embodiments described herein.
  • FIG. 7 shows a graph of input parameter model coefficients according to embodiments described herein.
  • FIG. 8 shows a top view of a rectangular flask according to embodiments herein.
  • FIG. 9 shows a top view of an angled neck T flask according to embodiments herein.
  • FIG. 10 shows a top view of a U-shaped flask according to embodiments herein.
  • FIG. 11 shows a side view of a straight neck flask according to embodiments herein.
  • FIG. 12 shows a side view of a canted neck flask according to embodiments herein.
  • FIG. 13 shows a side view of an angled neck flask according to embodiments herein.
  • T flasks and U flasks are available from Corning Life Sciences (Coming Incorporated, Corning, NY).
  • the U flasks comprise redesigned T flasks with reduced material usage per flask.
  • meld lines were observed on the bottom corners of the panel.
  • numerical modeling of U175 and U225 also showed that meld lines are formed on the panel.
  • numerical modeling of the U25 flask showed no such meld line formation.
  • the present disclosure illustrates methods and a related machine learning (ML) based model that can be used to quickly evaluate a flask design for its meld line formation tendency. Further, the methods and ML model can be used by a design team that would allow for the design to be changed at the source (i.e., design team) resulting in significant time savings by avoiding various downstream design iterations between various teams (i.e., design team, modeling team, specialists, etc.).
  • design team i.e., design team
  • the present disclosure describes an inexpensive and quick method to verify if the design of a flask is meld line-free. Meld lines are formed when two polymer flow fronts meet at an angle greater than 135°. In the context of cell culture flasks, meld lines were observed in manufacturing cell culture flasks such as U75, U175, and U225 (Coming Incorporated, Corning, NY). The identification of meld line formation was done at a downstream step, such as the prototyping stage of U75, which led to time-consuming design iterations that involved multiple technical teams to avoid formation of meld lines.
  • the method herein is a simple and effective way to check the meld line formation tendency in a flask. It is simple enough to be used by a design team to verify if a design is meld line-free at the source, thereby avoiding time-consuming downstream design iterations.
  • the proposed method is based on a machine learning (ML) model.
  • the ML model is trained on data obtained by varying geometric parameters of the U225 and U25 cell culture flasks. These two flasks were chosen as they are based on a common design philosophy and yet, U225 displays meld line formation tendency but U25 does not.
  • the panel thickness and panel length were varied in both the flasks, and multiple values of each parameter were tried in all possible combinations.
  • Every design so obtained by varying the geometric parameter was then evaluated for its meld line formation tendency by running it through a numerical model.
  • DOE numerical design of experiments
  • a particular advantage of using this model is that its applicability is not limited to the flask designs that it was trained on. If the U flasks are again redesigned in the future, the ML model can be used by the design team to even evaluate the future redesigns. Thus, the need to setup a numerical model to evaluate any new flask with respect to its meld line formation tendency is done away with.
  • this method is based on a machine learning (ML) model that has been trained on exhaustive values of geometric parameters, its usage is not limited to the flasks on which it was trained on. It can be used to check the meld line formation tendency for any future flask as well. Moreover, unlike numerical modeling, a specialist is not required to use the ML model to verify that the flask panel design is meld line free. It can be used by a design team to quickly verify the design and accordingly change the design, if necessary. Thus, because a design team can use the model to assess the panel design at the source of design, time consuming downstream design revisions with multiple technical teams may be avoided by using methods described herein.
  • ML machine learning
  • FIG. 1 and FIG. 2 illustrate the U225 flask lid and base, and show the terminology or nomenclature used to refer to different regions of the flask 100.
  • FIG. 2 shows a cross-sectional view of Box A of FIG. 1.
  • the flask 100 comprises a bottom 105 and a top or panel 110 disposed opposite to and parallel to the bottom 105.
  • the top or panel 110 and the bottom 105 are flat or substantially flat.
  • a rib 145 is disposed at a perimeter of the top or panel 110 and extends upwards or away from a surface of the panel 110.
  • At least one side wall 125 extends from the top 110 to the bottom 105 and is disposed perpendicular to the top 110 and bottom 105 at a side of the top or bottom.
  • two side walls 125 are disposed parallel to and opposite each other on either side of the flask 100, extending from a first end 141 of the flask 100 to a second end 143 of the flask 100.
  • an end wall is disposed at the first end 141 of the flask 100 and extends from the top 110 to the bottom 105, disposed perpendicular to the top 110 and bottom 105, and arranged perpendicular to side walls 125.
  • the flask comprises a neck region 120.
  • the neck region 120 comprises a canted neck wall 125 with a neck 130 and an aperture 135 allowing access to an internal volume of the flask 100.
  • the neck 130 comprises threading 133 configured for operation with a cap or lid.
  • Panel thickness (Tp), panel length (Lp), panel width (Wp), side wall thickness (Ts), side wall length (Ls), side wall width (Ws), rib thickness (Tr), rib length (Lr), and rib width (Wr) are also designated.
  • FIG. 3 illustrates meld lines 150 observed during a prototyping stage of U75, a U- shaped flask having a 75 cm 2 surface area.
  • the U75 flask panel 110 and side wall 125 were of equal thickness.
  • meld lines form when the polymer flow from the side wall and rib enters the panel. This happens as the flow front in the panel lags behind the flow front in the side wall and rib due to the high flow resistance of the panel.
  • the meld lines may be completely eliminated if the panel thickness is greater than the side wall thickness by a certain critical amount.
  • the learnings obtained through numerical modeling may be applied to obtain a meld line-free flask design.
  • a numerical model in Autodesk Moldflow must first be made that would predict meld line formation. Setting up a numerical model is time-consuming and requires a specialist.
  • ML machine learning
  • the method disclosed herein is simple enough that a design team may use the method to evaluate a design, thereby allowing for a design change at the source. As such, the method disclosed herein may lead to significant time savings, as downstream design iterations between various technical teams may be completely avoided.
  • a simple technique to circumvent this limitation is to train the ML model on ratios of geometric parameters rather than the absolute values of the parameters since the ratios of parameters will lie in a typical range, no matter how small or large a flask is. Further, it is even more advantageous to form ratios of those dimensions that have physical importance. For example, formation of a meld line is dictated by the panel flow resistance and its value in comparison to the side wall and rib flow resistance. Thus, the ratio of these flow resistances is physically important, which in turn depends on the ratio of panel thickness (Tp) to side wall thickness (Ts), panel thickness (Tp) to rib thickness (Tr), and panel length (Lp) to the side wall length (Ls).
  • the ratio of panel width (Wp) to its length (Lp), side wall width (Ws) to its length (Ls), rib width (Wr) to its length (Ls) are also given as inputs to the ML model. This is done as the width of the panel/ side wall/ rib can affect the flow development length in the panel/ side wall/ rib respectively. This will further affect the flow fronts in the panel/ side wall/ rib and hence contribute towards meld line formation.
  • the ML model has 6 inputs, and the nomenclature used to refer to the geometric features comprising the 6 input ratios is illustrated in figure 1. For any given values of these 6 inputs, the model predicts if that flask panel is meld line free or not.
  • FIG. 5 shows a graph of the distribution of all the design cases with the length ratio (Lp/Ls) on the Y axis and the thickness ratio (Tp/Ts) on the X axis, wherein the points are color coded as light grey for presence of a meld line (1) and as dark grey for absence of a meld line (0).
  • Lp/Ls length ratio
  • Tp/Ts thickness ratio
  • FIG. 6 shows a countplot of all the cases with thickness ratio (Tp/Ts) as 1 segregated by the length ratio (Lp/Ls).
  • the bars are color coded as light grey for presence of a meld line (1) and as dark grey for absence of a meld line (0).
  • the plot strongly suggests that for length ratio of 0.8 and below, meld lines are not formed if the thickness ratio is 1. Similar plots are seen when the panel/rib thickness ratio is considered instead of the panel/sidewall thickness ratio, and hence not shown to avoid redundancy.
  • FIG. 7 illustrates the importance of the input parameters in deciding if a flask panel is meld line free or not through their model coefficient values. Basically, the larger the absolute value of the coefficient, the higher its impact is in deciding meld line presence. As expected, both the thickness ratios are the most influential factors followed closely by the length ratio. As for the sign of the coefficients, that just shows the nature of dependence of meld line on them - positive coefficients imply direct relationship and negative coefficients imply inverse relationship.
  • the model is validated on 34 designs of U25 and U225.
  • the model accurately predicts meld line formation for each of the 34 test cases. While making predictions is reasonably simple for cases that have panel/ sidewall or panel/ rib thickness ratio significantly higher or lower than 1, it is quite difficult for cases that have the thickness ratios just around 1. It is even more difficult to predict for the outlier cases i.e., cases with thickness ratio more than one but showing meld line and vice versa.
  • Table 3 illustrates the geometric input ratios of such outlier cases that the machine learning model was able to predict correctly.
  • validating the model on 34 cases is not exhaustive, the range of values covered for each input ratio in the validation cases is almost as wide as the total range of each of the input ratios. This strongly suggests that the model will perform well even on a larger validation set.
  • the model was tested on flasks other than the U-shaped cell culture flasks U25 (25 cm 2 surface area) and U225 (225 cm 2 surface area). Designs of U-shaped cell culture flasks including U75 (75 cm 2 surface area), U150 (150 cm 2 surface area), U175 (175 cm 2 surface area), and traditional T-flask T175 (175 cm 2 surface area) were used to carry out the testing. Table 4 shows the design details of these flasks in terms of the geometric input ratios used by the ML model.
  • the flask may comprise any suitable shape that allows for cell culture within a volume of the flask.
  • the neck of the flask may be any suitable style that allows for cell culture.
  • the flask may further be releasably sealed during cell culture.
  • the flask comprises a rectangular flask (FIG. 8).
  • the rectangular flask may have a ramp from the bottom to a canted neck for easier pouring and pipet access.
  • the canted neck flask may further comprise an anti-tip skirt to enhance stability.
  • the flask comprises an angled neck T flask (FIG. 9).
  • the flask comprises a traditional straight neck flask. Angled neck flasks and traditional straight neck flasks use the entire bottom area for cell growth, the design thereby saving space and reducing medium sloshing into the neck.
  • the flask comprises a U-shaped flask (FIG. 10).
  • U-shaped flasks comprise rounded shoulders in a “U-shape” for an easier grip and better access when removing or tightening the cap.
  • the ergonomic shape reduces the number of corners, improves cell scraping, and allows the use of a larger pipet.
  • the neck may comprise a straight neck (FIG. 11). Straight neck flasks are ideal for larger medium volumes since this design reduces medium sloshing into the cap. [0066] In an embodiment, the neck may comprise a canted neck (FIG. 12). Canted neck flasks may allow for easier pouring and improved access to the flask for pipetting or scraping. [0067] In an embodiment, the neck may comprise an angled neck (FIG. 13). Angled neck flasks may improve pipet access and reduce medium sloshing into the neck.
  • the flask may be releasably sealed by a lid or cap by means of threads.
  • the flask may comprise threads configured to interlock with threads on a lid or cap.
  • Any suitable cap may be used.
  • lids or caps include plug seal caps, phenolic-style caps, and vent caps.
  • Plug seal caps feature one-piece linerless construction and are designed for use in closed systems, providing a liquid- and gas-tight seal. When loosened, this cap can also be used in open systems. Phenolic-style caps are designed (when loosened) for use in open systems requiring gas exchange. With the caps slightly loosened, gas is exchanged between the environments inside and outside of the flask. Vent caps may contain a 0.2 pm pore, hydrophobic membrane sealed to the cap, isolating the container it is placed on from the environment while providing consistent gas exchange. These caps are highly recommended for use in all CO2 incubators, especially for long-term use.
  • a method of determining whether a design of a cell culture flask will be meld line-free comprises: training a machine learning model on cell culture flask design parameter data; inputting parameters of a flask design into a machine learning model; and determining whether the flask design will be meld line-free, based on output from the machine learning model.
  • cell culture flask design parameter data comprises data obtained by varying geometric parameters of cell culture flasks.
  • the cell culture flasks comprise U225 and U25 cell culture flasks.
  • the geometric parameters comprise ratios of geometric parameters.
  • the ratios of geometric parameters comprise: width panel (Wp) to length of panel (Lp); width of sidewall (Ws) to length of sidewall (Ls); thickness of panel (Tp) to thickness of sidewall (Ts); thickness of panel (Tp) to thickness of rib (Tr); width of rib (Wr) to length of rib (Lr); and length of panel (Lp) to length of sidewall (Ls).
  • Wp width panel
  • Ws width of sidewall
  • Ts thickness of sidewall
  • Tr thickness of panel
  • Tr thickness of rib
  • Lr width of rib
  • Lp length of sidewall
  • training further comprises evaluating each design obtained by varying the geometric parameter for its meld line formation tendency by running it through a numerical model.
  • training further comprises conducting a comprehensive numerical design of experiments (DOE) to generate the data on which the machine learning model was trained on.
  • DOE numerical design of experiments
  • the cell culture flask comprises: a panel; a bottom arranged parallel to the panel; a plurality of sidewalls extending between the panel and the bottom, wherein a sidewall disposed at a first end of the flask comprises an endwall, wherein each sidewall has a sidewall length (Ls), sidewall thickness (Ts), and sidewall width (Ws); a neck portion disposed at an opposite second end of the flask; a rib disposed along at an outer perimeter of the panel, the rib extending upwards from an exterior surface of the panel; and an interior chamber defined by interior surfaces of the panel, the bottom, the plurality of sidewalls, and the neck portion.
  • Ls sidewall length
  • Ts sidewall thickness
  • Ws sidewall width
  • the rib surrounds the entire outer perimeter of the panel.
  • the panel comprises a panel length (Lp), a panel thickness (Tp), and a panel width (Wp).
  • each sidewall of the plurality of sidewalls comprises a sidewall length (Ls), sidewall thickness (Ts), and sidewall width (Ws).
  • the rib comprises a rib length (Lr), rib thickness (Tr), and rib width (Wr).
  • the cell culture flask comprises a U-shaped flask.
  • the U-shaped flask comprises a canted neck.
  • the U-shaped flask comprises an angled neck.
  • the cell culture flask comprises a T-shaped flask.
  • the T-shaped flask comprises a canted neck.
  • the T-shaped flask comprises an angled neck.
  • the cell culture flask comprises a rectangular flask.
  • the rectangular flask comprises a canted neck.
  • the rectangular flask comprises an angled neck.
  • the cell culture flask comprises a U-shaped flask, a T-shaped flask, or a rectangular flask.
  • Ranges may be expressed herein as from “about” one particular value, and/or to “about” another particular value. When such a range is expressed, examples include from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another aspect. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint.

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Abstract

L'invention concerne un procédé permettant de déterminer si une conception d'un flacon de culture cellulaire est exempte de ligne de fusion. Le procédé consiste à entraîner un modèle d'apprentissage automatique sur des données de paramètre de conception de flacon de culture cellulaire ; à entrer des paramètres d'une conception de flacon dans un modèle d'apprentissage automatique ; et à déterminer si la conception de flacon sera sans ligne de fusion, sur la base d'une sortie provenant du modèle d'apprentissage automatique.
PCT/US2023/019718 2022-04-29 2023-04-25 Procédés et systèmes de production de flacons sans ligne de fusion WO2023211875A1 (fr)

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US202263336632P 2022-04-29 2022-04-29
US63/336,632 2022-04-29

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JP2017113981A (ja) * 2015-12-24 2017-06-29 東レエンジニアリング株式会社 成形品の設計支援方法、成形品の設計支援装置、コンピュータ・ソフトウェア、記憶媒体

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