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ARGEN

ARGEN Digital Booklet

The ARGEN Digital Booklet provides insight into various applications utilizing ARGEN’s patented simultaneous multiple sample light scattering (SMSLS) technology to accelerate and optimize the development of novel biotherapeutics. Biopharmaceutical companies are experiencing greater demand to develop novel biologic therapeutics in less time, and this requires a paradigm shift in the way teams approach formulation development...
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Fluence Analytics to exhibit at ARBRE MOBIEU’s Molecular Biophysics Conference

ARBRE MOBIEU 2019 Conference – Booth 10 The 2019 meeting of ARBRE MOBIEU, the Association of Resources for Biophysical Research in Europe — Molecular Biophysics in Europe, is taking place in Zagreb, Croatia from March 18 – 20. At booth number 10, Fluence Analytics will showcase ARGEN, a static light scattering instrument for analyzing molecular aggregation...
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Reproducibility of Thermally Induced and Contact-stir Induced Protein Aggregation

This peer-reviewed publication by Fluence Analytics’ research partner Tulane PolyRMC addresses the reproducibility of protein aggregation. The publication, which appears in the Journal of Physical Chemistry, specifically discusses reproducibility following temperature-induced and contact-stir induced aggregation of bovine serum albumin and a monoclonal antibody. Using ARGEN, PolyRMC assessed protein aggregation reproducibility for global stressors which affect an...
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Assessing Stirring Stress and Other Impacts of Bioprocessing

The successful development of biotherapeutics requires an in-depth understanding of the impacts associated with mechanical and physical stress. Instability and subsequent aggregation can render them biologically inactive or even induce an immunological response in patients. Stirring stress is one of the most notable factors which disrupts native biopolymer structure and promotes aggregation. However, contact stirring...
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Using 90° Static Light Scattering to Determine Mw

On the limits of 90° static light scattering for determining weight average molar mass Mw   A discussion with Chief Science Officer, Dr. Wayne Reed   This Technical Note assesses the fractional error in Mw that results when θ=90° static light scattering detection is used, instead of a full angular extrapolation via MALS.  
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Benefits of In Situ Aggregation Kinetics with ARGEN

Explore the advantages of In Situ Aggregation Kinetics with ARGEN! Chris Roberts, a Professor at the University of Delaware (UD), explores the benefits of using in situ aggregation kinetics during this webinar which includes data collected on an ARGEN, a static light scattering instrument. The webinar also incorporates the presentation of two case studies where...
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Fluence Analytics Brochure

Fluence Analytics Brochure: realtime data. realtime optimization.
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Fluence Analytics to exhibit at PEGS Boston: The Essential Protein Engineering Summit

  PEGS: The Essential Protein Engineering Summit is one  of the industry’s preeminent events for anyone involved in biotherapeutic drug development. The annual conference is always held in Boston, and this year’s summit will take place at the Seaport World Trade Center from April 30 – May 4. At booth number 438, Fluence Analytics will...
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Intro to Light Scattering by Dr. Wayne Reed

 Interested in learning about the fundamentals of Light Scattering? Want to know more about the differences between DLS and SLS? Watch the free webinar by Fluence Analytics CSO, Dr. Wayne Reed, who provides an introduction to light scattering then discusses how the technique’s use as a characterization tool has evolved with the growing needs of the...
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Rapid Determination of Mw for a Monoclonal Antibody

Colloidal stability is determined by the balance of repulsive and attractive intermolecular interactions between protein molecules, like a monoclonal antibody, to conserve the native folded state. Simply stated, the propensity for aggregation is reduced by less intermolecular interaction. Therefore, determination of the second virial coefficient (B22) is a valuable screening tool to predict aggregation propensity....
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