Amgen Inc.

Other

Zhongqi Zhang

Pavel V Bondarenko

Sohye Kang

Chung Huang, Jr

Chung-Jr Huang

Linda Owers Narhi

Hedieh Barkhordarian

Joshua M Tokuda

Nathan Joh

Gerd Richard Kleemann

Marisa K Joubert

Yunlong Zhang

Noel J Rieder

Systems and methods are described for reducing lab-to-lab and/or instrument-to-instrument variability of Multi-Attribute Methods (MAM) analyses via run-time signal intensity calibration. In various aspects, multiple MAM-based instruments each have detectors and different instrument conditions defined by different instrument models or sets of settings. Each MAM-based instrument receives respective samples and a reference standard as a calibrant. Each MAM-based instrument detects, via its detector, sample isoforms of its respective sample and reference standard isoforms of the reference standard. The MAM-based instruments are associated with processor(s) that determine, via respective MAM iterations, correction factors and sample abundance values corresponding to the sample isoforms. The correction factors are based on the reference standard, and the sample abundance values are based on the correction factors. A variance value of the sample abundance values may be reduced based on correction factors of each of the MAM-based instruments.

Systems and methods for reducing lab-to-lab and/or instrument-to-instrument variability of multi-attribute method (MAM) by run-time signal

The present invention relates to a method for manipulating the high mannose glycoform content of recombinant glycoproteins by regulating ornithine metabolism during cell culture.

Increasing ornithine accumulation to increase high mannose glycoform content of recombinant proteins

Decreasing ornithine production to decrease high mannose glycoform content of recombinant proteins

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Thousand Oaks, CA, United States of America

Zhongqi Zhang