Biomarkers and Precision Medicine Community (BPMC)

In the most recent monthly meeting of the PK Methodology Working Group, Mark facilitated a constructive conversation regarding the potential application of machine learning in the development of ligand binding assays. Members actively contributed valuable insights in the following areas:

•         Assessing the feasibility of employing machine learning approaches and distinguishing them from traditional automation methods.

•         Identifying challenges associated with data collection and ensuring the completeness of the dataset.

•         Recognizing the importance of industry collaboration in the creation of a practical algorithm to guide the development of ligand binding assay methods.

The monthly gathering of the PK Assay Working Group, focusing on PK Methodologies for Biologics, Cell, and Gene therapies, provides an invaluable platform for industry experts to come together. During these meetings, we collaboratively share best practices, tackle emerging challenges, and exchange valuable experiences. The primary goal is to support each other in refining PK methodologies and facilitating successful filling and submission processes.

Hi Mark,

Thank you for sharing your discussions with the Biomarker community. This is such a great topic and it seems like AI/ML is being incorporated in the industry in many different ways. We have discussed quite a bit in our community on the role of AI and ML in parsing through large data sets for biomarker discovery as well as analytics for high content biomarkers. I am definitely interested to hear about employing ML in a PK setting to guide ligand binding method development. I am eager to hear more from what comes of these discussions. Are you planning an OSD on this topic by chance?

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Amanda Hays Ph.D.
Scientific Officer
BioAgilytix
Olathe KS
[email protected]

Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.

Original Message:
Sent: 09-14-2023 12:57
From: Mark Ma
Subject: Employing ML for Guiding the Ligand-Binding Assay Development

In the most recent monthly meeting of the PK Methodology Working Group, Mark facilitated a constructive conversation regarding the potential application of machine learning in the development of ligand binding assays. Members actively contributed valuable insights in the following areas:

•         Assessing the feasibility of employing machine learning approaches and distinguishing them from traditional automation methods.

•         Identifying challenges associated with data collection and ensuring the completeness of the dataset.

•         Recognizing the importance of industry collaboration in the creation of a practical algorithm to guide the development of ligand binding assay methods.

The monthly gathering of the PK Assay Working Group, focusing on PK Methodologies for Biologics, Cell, and Gene therapies, provides an invaluable platform for industry experts to come together. During these meetings, we collaboratively share best practices, tackle emerging challenges, and exchange valuable experiences. The primary goal is to support each other in refining PK methodologies and facilitating successful filling and submission processes.

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Mark Ma Ph.D.
VP. Head of Translational Clinical Sciences
Rallybio
New Haven CT
[email protected]

Disclaimer: Opinions expressed are solely my own and do not express the views or opinions of my employer.
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