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Putting MAM on the Map

Developed at Amgen, Multi-Attribute Method (MAM) harnesses the power of high-resolution accurate mass (HRAM)-MS to support the journey of optimization of bioprocesses all the way to ensuring the safety of final biologic drugs. The ground-breaking approach which was developed from concept to reality mostly in the last decade to be leveraged for biopharma analytical strategy development and implementation in QC, has been endorsed by regulators and is now being adopted by medicine makers worldwide.

In this article series, we trace the journey of MAM from idea to real-world implementation, speaking with some of the scientists who played a key role in developing the approach.

Multi-Attribute Method Articles

Focus on Quality – and the Rest Will Follow

| Sponsored by Thermo Fisher Scientific

Amgen developed the Multi-Attribute Method (MAM) to obtain high-fidelity understanding of the quality of its own biologics. Click to read article

Mapping Out MAM

| Sponsored by Thermo Fisher Scientific

Amgen has brought the Multi-Attribute Method (MAM) into the mainstream, but what’s next for this analytical workflow. Click to read article

What is the Multi-Attribute Method

The MAM Consortium

The MAM Consortium is a non-profit, industry-wide forum for the Multi-Attribute Method (MAM) and other LC/MS applications. These applications are used at pharmaceutical and biotechnology companies for product characterization, in-process control, and GMP release and stability testing. Currently, the MAM Consortium has over 300 members from pharmaceutical companies, regulatory agencies, CDMOs, and instrument/software vendors.

The MAM Consortium

Multi-Attribute Method related articles

Development of a quantitative mass spectrometry multi-attribute method for characterization, quality control testing and disposition of biologics.
Click here to read article

A View on the Importance of “Multi-Attribute Method” for Measuring Purity of Biopharmaceuticals and Improving Overall Control Strategy
Click here to read article

Multi-Attribute Method for Quality Control of Therapeutic Proteins. Rogstad S, Yan H, Wang X, Powers D, Brorson K, Damdinsuren B, Lee S.
Anal Chem. 2019; 91(22): 14170-14177
Click here to read article

Advancing Mass Spectrometry Technology in cGMP Environments. Ren D. Trends Biotechnol. 2020; 38(10): 1051-1053
Click here to read article

Industry events where the Multi-Attribute Method has been advocated

Venue Presenter Year
USP Bob Bailey 2012
Bioprocess International Bob Bailey 2013
ASMS Alain Balland 2013
CASSS MS Alain Balland 2013
CASSS EU Tony Mire-Sluis 2014
ASMS Rich Rogers 2014
ASMS Sabrina Benchaar 2014
CASSS MS Lowell Brady 2014
CASSS MS Rich Rogers 2014
Bioprocessing Summit Catherine Eakin 2014
BIOMAN Jette Wypych 2014
AAPS Sabrina Benchaar 2015
CASSS MS Da Ren 2015
Bioproduction Jette Wypych 2015
CASSS WCBP Rohini Deshpande 2016
CASSS CMC Strategy Europe Jette Wypych 2016
BIOMAN Richard Wu 2016
CASSS CMC Strategy US Tamer Eris 2016
CASSS US Jette Wypych 2017
PDA Mike Abernathy 2017
AAPS Mike Abernathy 2017
CASSS CMC Strategy Japan Mike Abernathy/Jette Wypych 2017
IFPAC Workshop Mike Abernathy/Jette Wypych 2018
CASSS EU AT Workshop Jette Wypych/Patrick Swan 2018
AAPS Nina Cauchon 2018
PEGS Da Ren 2018
CASSS MS Da Ren 2018
BIO Jette Wypych 2019
ESACT Jette Wypych 2019
ASMS Da Ren 2019
CASSS MS Zhongqi Zhang 2019
USP Jette Wypych 2020
WCBP Da Ren 2020
Bioprocess international Ting Song 2020

MAM Scientific Contributors

Learn more about the scientists who contributed to the Multi-Attribute Method project.

Jette Wypych

Jette Wypych is Executive Director in Attribute Sciences in the Process Development organization at Amgen, where she leads a department of more than 80 staff members with responsibilities in pre-clinical, clinical as well as commercial programs.

With more than 30 years of experience in biotechnology, Jette has been responsible for key discoveries in cytokine and hematopoietic research. For the past decade she has dedicated her time to aspects of process and product development. She has contributed to the development of several programs and been responsible for the analytical characterization and formulation development of pipeline molecules leading to the content in the chemistry, manufacturing and control (CMC) sections of numerous regulatory filings. She is currently actively advancing novel analytical technologies for implementation in the quality and manufacturing environment. More recently Jette developed the concept and application of the quality target product profile in process and product development at Amgen, advancing the QbD principles in product development. Her work has resulted in more than 40 publications.

Jette earned her graduate degree in chemical engineering from the Danish Technical University, Copenhagen, Denmark.

Da Ren

Da Ren currently holds the position of Scientific Director in Process Development at Amgen, where he is responsible for the strategy and execution of Multi-Attribute Method (MAM). Da joined Amgen in 2004 and held multiple roles with increasing responsibility from analytical development to cGMP release and stability testing. In 2015, he led the first in industry implementation of MAM in the cGMP environment. He has more than 20 publications and patents applications during his tenure at Amgen.

Da also actively contribute to the analytical community in the biotech industry. He was invited to present in many external conferences and served as session chair. Da is co-leading the industry-wide MAM Consortium and he is a member of the CASSS MS organizing committee.

He received his Ph.D. in Analytical Chemistry from the University of Akron in 2002.

Ting Song

Ting Song is a Senior Scientist at Amgen. Ting grew up in China and moved to the US in 2011 for studies at the University of California, Davis where she received a PhD. Ting joined Amgen in 2016 shortly thereafter. Her career at Amgen started in Research where she supported multiple early drug discovery projects including the pre-clinical study of AMG 510. She then transferred to Quality Control (QC) to work on the implementation of the Multi-Attribute Method (MAM) in Quality Control. This includes the validation of the MAM system to fit into the cGMP environment, the continuous improvement and optimization of MAM to be more QC user-friendly, designing training programs for QC, and supporting release and stability testing using MAM.


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