Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

High-Performance Liquid Chromatography: Types of Detectors01:15

High-Performance Liquid Chromatography: Types of Detectors

621
The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte...
621
Gas Chromatography: Overview of Detectors01:13

Gas Chromatography: Overview of Detectors

628
Detectors in gas chromatography (GC) help identify and quantify the components of a mixture by translating chemical properties into measurable signals, which are displayed on a chromatogram. Detectors can be categorized into two main types: destructive and non-destructive.
A non-destructive detector allows a sample to be analyzed without altering or consuming it, meaning the sample can be collected after detection for further analysis. Examples include thermal conductivity detectors and...
628
Gas Chromatography: Types of Detectors-II01:19

Gas Chromatography: Types of Detectors-II

420
In gas chromatography, different detectors are employed to meet specific analytical needs. These detectors are often categorized based on their detection mechanisms and the types of compounds they are best suited to analyze. Thermal Conductivity Detectors (TCD), Flame Ionization Detectors (FID), and Electron Capture Detectors (ECD) represent common categories, each with unique operating principles and applications. However, beyond these, several other detectors are designed for more specialized...
420

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comparative Transcriptomic Profiling Reveals Differences in Initiation of Antiviral Response in Low rAAV Producing HEK293 Suspension Cells.

Biotechnology journal·2026
Same author

Comparative Analysis of rAAV Production from Plasmid-Encoded Versus Chromosomally Integrated rAAV Transgene in HEK293 Cells.

International journal of molecular sciences·2026
Same author

High-Yield Production and Cost-Effective Purification of an Alkali-Resistant Hexameric Protein A Variant for Antibody Affinity Chromatography.

Biotechnology journal·2026
Same author

Engineered Bacterial Ligand From Streptococcus pneumoniae on Macroporous Resins for Selective Affinity Capture of Secretory IgA.

Biotechnology and bioengineering·2026
Same author

Comparative Analysis of HEK293 Genomic Variability.

Biotechnology and bioengineering·2025
Same author

Status and future developments for downstream processing of biological products: Perspectives from the Recovery XIX yield roundtable discussions.

Biotechnology and bioengineering·2024

Related Experiment Video

Updated: Jul 23, 2025

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.4K

Sensors and chemometrics in downstream processing.

Astrid Dürauer1, Alois Jungbauer1,2, Theresa Scharl3

  • 1Institute of Bioprocessing Science and Engineering, University of Natural Resources and Life Sciences, Vienna, Austria.

Biotechnology and Bioengineering
|July 20, 2023
PubMed
Summary
This summary is machine-generated.

Biopharmaceutical manufacturing is transitioning towards automated, autonomous processes. Integrating soft sensors and predictive chemometrics enables real-time monitoring and control for robust biomanufacturing.

Keywords:
continuous integrated biomanufacturingmachine learningprocess controlreal‐time release

More Related Videos

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
11:16

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling

Published on: July 22, 2017

14.1K
Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Published on: March 14, 2013

12.8K

Related Experiment Videos

Last Updated: Jul 23, 2025

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis
08:43

PTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysis

Published on: May 11, 2017

12.4K
A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling
11:16

A Hydroponic Co-cultivation System for Simultaneous and Systematic Analysis of Plant/Microbe Molecular Interactions and Signaling

Published on: July 22, 2017

14.1K
Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS
07:34

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Published on: March 14, 2013

12.8K

Area of Science:

  • Biopharmaceutical Manufacturing
  • Process Control
  • Chemometrics

Background:

  • The biopharmaceutical industry traditionally operates in batch mode due to stringent regulations and reliance on offline quality control.
  • Key product quality attributes include quantity, purity, potency, and absence of adventitious agents and bioburden.
  • Emerging trends like single-use technologies and integrated bioprocessing are shaping the future of biomanufacturing.

Purpose of the Study:

  • To review the steps toward automated and autonomous bioprocessing, focusing on monitoring and control strategies.
  • To explore the integration of soft sensors and predictive chemometrics for modern process control.
  • To demonstrate the application of these concepts in downstream biopharmaceutical processing.

Main Methods:

  • Review of current bioprocessing practices and regulatory initiatives (Process Analytical Technologies, Quality by Design, Continuous Integrated Manufacturing).
  • Concept of gradual integration of real-time monitoring using soft sensors.
  • Application of statistical tools like multivariate statistics and neural networks for model training.

Main Results:

  • Soft sensors offer a viable approach for integrating real-time monitoring into bioprocessing.
  • Predictive chemometrics, combined with soft sensors, can enhance process control.
  • Successful application demonstrated in downstream processing steps like chromatography and membrane filtration.

Conclusions:

  • Automation and autonomous bioprocessing are achievable goals for the biopharmaceutical industry.
  • Soft sensors and predictive chemometrics are key enablers for real-time release and robust biomanufacturing.
  • Gradual implementation of these technologies will lead to highly predictive and efficient biomanufacturing systems.