How to Assess Molecular Weight with GPC

How to Assess Molecular Weight with GPC

Image Credit: Jordi Labs

Molecular weight is a main feature employed when characterizing polymer-based products. The term describes the molar mass distribution of polymer chains which can significantly vary within polymers of identical chemistry.

This can cause issues in regulated markets where products must adhere to a strict degree of consistency, for example the pharmaceutical industry.

Gel permeation chromatography (GPC) is a cutting-edge technique for establishing the molecular weight distribution of a sample in solution. It is among the leading techniques for evaluating the stability and suitability of packaging media and pharmaceutical products.

The dissolved sample is sieved via a column filled with porous materials in this technique, where compartments of different molecular weights elute through the solid phase at various speeds which causes the sample to differentially partition over time. The data produced can be employed to evaluate the batch to batch consistency of polymers.

The importance of novel GPC columns

The GPC technique can be employed to evaluate the quality and stability of packaging materials and excipient materials utilized in pharmaceutical manufacturing.

A range of complex polymer systems are employed for drug delivery systems, tablet coatings, microfluidic vessels, blister packaging, and many other biopharmaceutical elements. Biological polymers such as naturally derived carbohydrates, synthetic polyolefins, and proteins are included.

The most widely used synthetic polymer for pharmaceutical and medical packaging applications are polyolefins. Polyolefins commonly have high polydispersity values and diverse molecular weight distributions. The molecular weight of polyolefins can differ by multiple orders of magnitude according to their purpose and type.

The use of gel permeation chromatography to quantify the molecular weight distribution of polyolefins requires a superior high-temperature GPC system that can differentiate molecular compartments across a broad molecular weight range from 500 to more than 10,000,000.

A customized GPC column has been produced by Jordi Labs that consists of porous divinyl benzene particles of 13 μm in size directly made for the analysis of polyolefins. These highly porous particles have been integrated into mixed bed columns ideal for high-resolution polyolefin characterization for pharmaceutical packaging.

A range of high-resolution Jordi Resolve DVB columns with a 5 μm particle size are included with the 13 μm GPC column. These offer higher resolution for ranges of molecular weight.

Pharmaceutical testing with Jordi Labs

Providing one of the best services for molecular weight determination in the US, Jordi Labs has a range of products enhanced for the performance of GPC in the pharmaceutical field.

Please do not hesitate to contact Jordi Labs for further information about quantifying the molecular weight distribution of polymer-based samples in pharmaceutical manufacturing.

About Jordi Labs

Jordi Labs provides the highest quality contract analytical services and polymer HPLC columns to some of the world’s leading consumer products, polymers, pharmaceutical and medical device manufacturers. Our team of PhD analytical chemists specialize in chemical identification. One of core competencies is Extractables & Leachables testing.

We are also worldwide leaders in;

  • Particulates & residue analysis
  • Good-bad comparisons
  • Method development/validation
  • Polymer analysis
  • Polymer failure

We also help companies from Fortune 500s to innovative startups with method development, preparative HPLC, training seminars, depositions and consulting. As a family company, we take pride in the production of all of our products and analytical service offerings. It is our goal to help our customers overcome their analytical challenges by providing excellent products and personal assistance from our highly-trained staff of PhD chemists


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Last updated: Aug 23, 2024 at 4:58 AM

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