Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings.

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Title: Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings.
Authors: Hemida, Mohamed1 (AUTHOR) mohdhamdy_84108@hotmail.com, Haidar Ahmad, Imad A.1 (AUTHOR) iahmad.umn@gmail.com, Barrientos, Rodell C.1 (AUTHOR), Regalado, Erik L.1 (AUTHOR)
Source: Analytica Chimica Acta. Mar2024, Vol. 1293, pN.PAG-N.PAG. 1p.
Subjects: Hydrophilic interaction liquid chromatography, Supercritical fluid chromatography, Liquid chromatography, Hydrophobic interactions
Abstract: The (bio)pharmaceutical industry is rapidly moving towards complex drug modalities that require a commensurate level of analytical enabling technologies that can be deployed at a fast pace. Unsystematic method development and unnecessary manual intervention remain a major barrier towards a more efficient deployment of meaningful analytical assay across emerging modalities. Digitalization and automation are key to streamline method development and enable rapid assay deployment. This review discusses the use of computer-assisted multifactorial chromatographic method development strategies for fast-paced downstream characterization and purification of biopharmaceuticals. Various chromatographic techniques such as reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), ion exchange chromatography (IEX), hydrophobic interaction chromatography (HIC), and supercritical fluid chromatography (SFC) are addressed and critically reviewed. The most significant parameters for retention mechanism modelling, as well as mapping the separation landscape for optimal chromatographic selectivity and resolution are also discussed. Furthermore, several computer-assisted approaches for optimization and development of chromatographic methods of therapeutics, including linear, nonlinear, and multifactorial modelling are outlined. Finally, the potential of the chromatographic modelling and computer-assisted optimization strategies are also illustrated, highlighting substantial productivity improvements, and cost savings while accelerating method development, deployment and transfer processes for therapeutic analysis in industrial settings. [Display omitted] • Computer-Assisted multifactorial chromatographic strategies were addressed. • Using proper linear and non-linear models were discussed. • Applications in various chromatographic techniques are critically reviewed. • Important parameters for retention mechanism modelling are demonstrated. • Computer-Assisted optimization strategies are highlighted for generic methods. [ABSTRACT FROM AUTHOR]
Copyright of Analytica Chimica Acta is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
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  Data: Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings.
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  Data: <searchLink fieldCode="AR" term="%22Hemida%2C+Mohamed%22">Hemida, Mohamed</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mohdhamdy_84108@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Haidar+Ahmad%2C+Imad+A%2E%22">Haidar Ahmad, Imad A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> iahmad.umn@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Barrientos%2C+Rodell+C%2E%22">Barrientos, Rodell C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Regalado%2C+Erik+L%2E%22">Regalado, Erik L.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Analytica+Chimica+Acta%22">Analytica Chimica Acta</searchLink>. Mar2024, Vol. 1293, pN.PAG-N.PAG. 1p.
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  Data: <searchLink fieldCode="DE" term="%22Hydrophilic+interaction+liquid+chromatography%22">Hydrophilic interaction liquid chromatography</searchLink><br /><searchLink fieldCode="DE" term="%22Supercritical+fluid+chromatography%22">Supercritical fluid chromatography</searchLink><br /><searchLink fieldCode="DE" term="%22Liquid+chromatography%22">Liquid chromatography</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrophobic+interactions%22">Hydrophobic interactions</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The (bio)pharmaceutical industry is rapidly moving towards complex drug modalities that require a commensurate level of analytical enabling technologies that can be deployed at a fast pace. Unsystematic method development and unnecessary manual intervention remain a major barrier towards a more efficient deployment of meaningful analytical assay across emerging modalities. Digitalization and automation are key to streamline method development and enable rapid assay deployment. This review discusses the use of computer-assisted multifactorial chromatographic method development strategies for fast-paced downstream characterization and purification of biopharmaceuticals. Various chromatographic techniques such as reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), ion exchange chromatography (IEX), hydrophobic interaction chromatography (HIC), and supercritical fluid chromatography (SFC) are addressed and critically reviewed. The most significant parameters for retention mechanism modelling, as well as mapping the separation landscape for optimal chromatographic selectivity and resolution are also discussed. Furthermore, several computer-assisted approaches for optimization and development of chromatographic methods of therapeutics, including linear, nonlinear, and multifactorial modelling are outlined. Finally, the potential of the chromatographic modelling and computer-assisted optimization strategies are also illustrated, highlighting substantial productivity improvements, and cost savings while accelerating method development, deployment and transfer processes for therapeutic analysis in industrial settings. [Display omitted] • Computer-Assisted multifactorial chromatographic strategies were addressed. • Using proper linear and non-linear models were discussed. • Applications in various chromatographic techniques are critically reviewed. • Important parameters for retention mechanism modelling are demonstrated. • Computer-Assisted optimization strategies are highlighted for generic methods. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Analytica Chimica Acta is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1016/j.aca.2023.342178
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      – Code: eng
        Text: English
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      – SubjectFull: Hydrophilic interaction liquid chromatography
        Type: general
      – SubjectFull: Supercritical fluid chromatography
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      – SubjectFull: Liquid chromatography
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      – SubjectFull: Hydrophobic interactions
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      – TitleFull: Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings.
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            NameFull: Hemida, Mohamed
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            NameFull: Barrientos, Rodell C.
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            NameFull: Regalado, Erik L.
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            – D: 08
              M: 03
              Text: Mar2024
              Type: published
              Y: 2024
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