WO2019165148A1 - Determining conditions for purification of proteins - Google Patents

Determining conditions for purification of proteins Download PDF

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Publication number
WO2019165148A1
WO2019165148A1 PCT/US2019/019050 US2019019050W WO2019165148A1 WO 2019165148 A1 WO2019165148 A1 WO 2019165148A1 US 2019019050 W US2019019050 W US 2019019050W WO 2019165148 A1 WO2019165148 A1 WO 2019165148A1
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WO
WIPO (PCT)
Prior art keywords
wells
stationary phase
protein
proteins
values
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2019/019050
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English (en)
French (fr)
Inventor
Jeremy Martin SHAVER
Tileli AMIMEUR
Ron GILLESPIE
Randal R. Ketchem
Fernando Garcia
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Just Evotec Biologics Inc
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Just Biotherapeutics Inc
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Publication date
Application filed by Just Biotherapeutics Inc filed Critical Just Biotherapeutics Inc
Priority to CA3091905A priority Critical patent/CA3091905C/en
Priority to EP19710843.4A priority patent/EP3755447B1/en
Priority to EP24161128.4A priority patent/EP4372376B1/en
Priority to US16/969,522 priority patent/US20200408728A1/en
Priority to ES19710843T priority patent/ES2978413T3/es
Priority to JP2020544212A priority patent/JP7332610B2/ja
Publication of WO2019165148A1 publication Critical patent/WO2019165148A1/en
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/86Signal analysis
    • G01N30/8658Optimising operation parameters
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B01PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01DSEPARATION
    • B01D15/00Separating processes involving the treatment of liquids with solid sorbents; Apparatus therefor
    • B01D15/08Selective adsorption, e.g. chromatography
    • B01D15/10Selective adsorption, e.g. chromatography characterised by constructional or operational features
    • B01D15/16Selective adsorption, e.g. chromatography characterised by constructional or operational features relating to the conditioning of the fluid carrier
    • B01D15/166Fluid composition conditioning, e.g. gradient
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/86Signal analysis
    • G01N30/8693Models, e.g. prediction of retention times, method development and validation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/88Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B15/00ICT specially adapted for analysing two-dimensional [2D] or three-dimensional [3D] molecular structures, e.g. structural or functional relations or structure alignment
    • G16B15/20Protein or domain folding
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B5/00ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
    • G16B5/20Probabilistic models
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/88Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • G01N2030/8809Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample
    • G01N2030/8813Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample biological materials
    • G01N2030/8831Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 analysis specially adapted for the sample biological materials involving peptides or proteins
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/88Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • G01N2030/889Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86 monitoring the quality of the stationary phase; column performance

Definitions

  • the material placed into the column that interacts with the molecules moving through the column can be referred to as a stationary phase material.
  • the molecules moving through the column can be included in what can be referred to as a mobile phase or eluent that passes over the stationary phase.
  • Some chromatographic processes can include ion exchange chromatography, affinity chromatography, high pressure liquid chromatography (HPLC), hydrophobic interaction chromatography (HIC), mixed mode chromatography (MMC), reverse phase chromatography, (RPC), size exclusion chromatography, and the like.
  • FIG. 3 illustrates some implementations of techniques to determine models to predict purity and yield of proteins under various purification conditions.
  • a first protein 302 can be associated with first characterization data 304.
  • the first characterization data 304 can include a sequence of the first protein 302, one or more secondary structures of the first protein 302, one or more tertiary structures of the first protein 302, or combinations thereof.
  • the first characterization data 304 can also include values for biophysical properties of the first protein 302.
  • the model generating system 106 can obtain the first characterization data 304 and utilize the first characterization data 304 to generate models to predict yield and purity for various proteins.
  • the model generating system 106 can also obtain data regarding other proteins, up to an N lh protein 306, to generate the models utilized to predict yield and purity.
  • the model generating system 106 can also obtain N th characterization data 308 that includes sequence data for the N lh protein 306, data for one or more secondary structures of the N lh protein, data for one or more tertiary structures of the N lh protein 306, biophysical properties data for the N lh protein 306, or combinations thereof.
  • the computer-readable storage media 508 can be used to store any number of functional components that are executable by the one or more processors 506.
  • these functional components comprise instructions or programs that are executable by the one or more processors 506 and that, when executed, implement operational logic for performing the operations attributed to the protein purification conditions system 502.
  • Functional components of the protein purification conditions system 502 that can be executed on the one or more processors 506 for implementing the various functions and features related to determining conditions for the purification of proteins, as described herein, include protein data collection and storage instructions 512, model generating instructions 514, purification conditions optimization instructions 516, and multi-well plate sampling instructions 518.
  • FIG. 6 is a flow diagram of an example process 600 to determine purification conditions for proteins using one or more chromatographic processes.
  • the process 600 includes providing a plate having a plurality of wells with each well including (i) a stationary phase material of a plurality of stationary phase materials for column chromatography systems, (ii) an amount of a protein, and (iii) an amount of a solution having a pH and a concentration of a salt.
  • Each well of the plurality of wells can have a different combination of the stationary phase material, pH, and concentration of the salt.
  • the process 600 can include determining a measure of performance for each well of the plurality of wells.
  • the measure of performance of an individual well of the plurality of wells can indicate adsorption of the protein with respect to the stationary phase material included in the individual well.
  • the measure of performance can indicate a yield and/or a purity of a chromatographic technique that utilizes the stationary phase material included in the well.
  • a method comprising: generating yield data and purity data for a number of proteins, the yield data and the purity data indicating yield and purity for each of a plurality of proteins over a range of pH values, over a range of salt concentrations, and for a stationary phase material of a column chromatography technique; obtaining sequence data indicating at least a portion of amino acid sequences of individual proteins of the plurality of proteins; obtaining structure data indicating one or more structures exhibited by individual proteins of the plurality of proteins; generating characterization data for the plurality of proteins, the characterization data including values obtained from analytical tests that indicate values of properties of the plurality of proteins; generating a model to predict, at one or more pH values and one or more salt concentration values, yield and purity of an additional protein for the stationary phase material, wherein the model includes a sequence component that indicates a similarity between the amino acid sequences of the plurality of proteins and an additional amino acid sequence of the additional protein and a characterization component that indicates similarities between values of the properties for the plurality of proteins and
  • a system comprising: one or more processors, one or more non- transitory computer-readable storage media storing computer-readable instructions that, when executed by the one or more processor, perform operations comprising: generating yield data and purity data for a number of proteins, the yield data and the purity data indicating yield and purity for each of a plurality of proteins over a range of pH values, over a range of salt concentrations, and for a stationary phase material of a column chromatography technique; obtaining sequence data indicating at least a portion of amino acid sequences of individual proteins of the plurality of proteins; obtaining structure data indicating one or more structures exhibited by individual proteins of the plurality of proteins; generating characterization data for the plurality of proteins, the characterization data including values obtained from analytical tests that indicate values of properties of the plurality of proteins; generating a model to predict, at one or more pH values and one or more salt concentration values, yield and purity of an additional protein for the stationary phase material, wherein the model includes a sequence component that indicates a similarity between
  • Clause 22 The system of clause 21, wherein the yield data and the purity data are determined from running a number of chromatography columns for a number of different proteins using the stationary phase material over the range of pH values and the range of salt concentrations.
  • Clause 23 The system of clause 21 or 22, wherein the yield data and the purity data are determined by analyzing solutions obtained from wells of a multi-well plate, individual wells of the multi-well plate including an amount of a solution including the protein and having a pH level and a salt concentration and including an amount of the stationary phase material.
  • Clause 41 The system of clause 40, wherein the operations further comprise: receiving data indicating selection of a particular selectable option of the plurality of selectable option; and in response to receiving the data, causing the user interface to display at least the chromatography technique, the pH values, the salt concentration value, and an indicator of monetary cost corresponding to the selectable option.
  • Figure 3 highlights the difference in thermal stability by differential scanning fluorimetry (DSF) for an IgGl mAh and a Fc-fusion protein.
  • DFS differential scanning fluorimetry
  • mAh 3 exhibits typical thermal stability for an IgGl along with greater thermal stability as the pH increases.
  • the Fc-fusion protein in addition to an overall lower Tm, exhibits a decrease in thermal stability with an increase in pH and salt strength.
  • the 96-well plate was used to perform batch binding studies to investigate protein- adsorbent interactions over 5 types of chromatographic media across a wide range of pH and salt conditions. This format was used to screen protein A elution conditions; evaluate static resin capacity, gradient elution strength, and selectivity for 2 cation exchange resins; and evaluate selectivity of product and contaminants for three different resins operated in flow-through mode for a single molecule.
  • Figure 4 presents an example of the data obtained in the single plate experiment. These data can be used to estimate Protein A recovery and molecule sensitivity to low-pH viral inactivation; select a CEX resin based on elution strength, recovery and selectivity for contaminants; and, finally, identify the optimal flowthrough resin and conditions for operation.
  • the integrated plate-based method presented herein provides insight into setpoints for individual unit operations as well as sensitivity to operating ranges.
  • mode pairing may be employed to select resins and operating conditions across the entire process (Fig. 5)

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  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Medical Informatics (AREA)
  • Biophysics (AREA)
  • Theoretical Computer Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Biotechnology (AREA)
  • Evolutionary Biology (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Molecular Biology (AREA)
  • Physiology (AREA)
  • Probability & Statistics with Applications (AREA)
  • Crystallography & Structural Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Peptides Or Proteins (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
PCT/US2019/019050 2018-02-21 2019-02-21 Determining conditions for purification of proteins Ceased WO2019165148A1 (en)

Priority Applications (6)

Application Number Priority Date Filing Date Title
CA3091905A CA3091905C (en) 2018-02-21 2019-02-21 Determining conditions for purification of proteins
EP19710843.4A EP3755447B1 (en) 2018-02-21 2019-02-21 Determining conditions for purification of proteins
EP24161128.4A EP4372376B1 (en) 2018-02-21 2019-02-21 Determining conditions for purification of proteins
US16/969,522 US20200408728A1 (en) 2018-02-21 2019-02-21 Determining conditions for purification of proteins
ES19710843T ES2978413T3 (es) 2018-02-21 2019-02-21 Condiciones determinantes para la purificación de proteínas
JP2020544212A JP7332610B2 (ja) 2018-02-21 2019-02-21 タンパク質の精製条件の決定

Applications Claiming Priority (2)

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US201862633584P 2018-02-21 2018-02-21
US62/633,584 2018-02-21

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WO2019165148A1 true WO2019165148A1 (en) 2019-08-29

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US (1) US20200408728A1 (https=)
EP (2) EP3755447B1 (https=)
JP (1) JP7332610B2 (https=)
CA (1) CA3091905C (https=)
ES (1) ES2978413T3 (https=)
WO (1) WO2019165148A1 (https=)

Cited By (2)

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WO2021216635A1 (en) * 2020-04-23 2021-10-28 Amgen Inc. Selecting chromatography parameters for manufacturing therapeutic proteins
WO2022060535A1 (en) * 2020-09-21 2022-03-24 Bayer Healthcare Llc Pathogen clearance system and method

Families Citing this family (3)

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MY204234A (en) 2018-08-27 2024-08-16 Regeneron Pharma Use of raman spectroscopy in downstream purification
WO2025064403A2 (en) * 2023-09-18 2025-03-27 Regeneron Pharmaceuticals, Inc. Methods and systems for developing chromatography protocols
CN121075496B (zh) * 2025-11-05 2026-03-27 鲁东大学 一种基于特征工程与集成学习的蛋白质盐敏感性预测方法

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Cited By (5)

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Publication number Priority date Publication date Assignee Title
WO2021216635A1 (en) * 2020-04-23 2021-10-28 Amgen Inc. Selecting chromatography parameters for manufacturing therapeutic proteins
JP2023522695A (ja) * 2020-04-23 2023-05-31 アムジエン・インコーポレーテツド 治療用タンパク質を製造するためのクロマトグラフィーパラメータの選択
WO2022060535A1 (en) * 2020-09-21 2022-03-24 Bayer Healthcare Llc Pathogen clearance system and method
JP2023544512A (ja) * 2020-09-21 2023-10-24 バイエル・ヘルスケア・エルエルシー 病原体クリアランスシステムおよび方法
JP7756155B2 (ja) 2020-09-21 2025-10-17 バイエル・ヘルスケア・エルエルシー 病原体クリアランスシステムおよび方法

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Publication number Publication date
JP7332610B2 (ja) 2023-08-23
ES2978413T3 (es) 2024-09-12
EP4372376A3 (en) 2024-07-17
CA3091905A1 (en) 2019-08-29
EP3755447B1 (en) 2024-03-06
EP4372376B1 (en) 2026-04-01
EP4372376A2 (en) 2024-05-22
EP3755447A1 (en) 2020-12-30
US20200408728A1 (en) 2020-12-31
CA3091905C (en) 2023-03-21
JP2021521412A (ja) 2021-08-26

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