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Preparation of Peripheral Blood Mononuclear Cell Pellets and Plasma from a Single Blood Draw at Clinical Trial Sites for Biomarker Analysis

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An improved model for fragment-based lead generation at AstraZeneca.

Nathan Fuller¹, Loredana Spadola², Scott Cowen¹

¹AstraZeneca, Discovery Sciences, Innovative Medicines and Early Development Biotech Unit, 35 Gatehouse Drive, Waltham, MA 02451, USA.

Drug Discovery Today

|May 16, 2016

Summary

This summary is machine-generated.

AstraZeneca (AZ) improved fragment-based lead generation (FBLG) by optimizing its fragment library and screening methods. This enhanced model successfully delivers lead series for drug discovery projects.

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Area of Science:

Medicinal Chemistry
Drug Discovery
Structural Biology

Background:

Fragment-based lead generation (FBLG) projects at AstraZeneca (AZ) faced challenges with modest success rates.
Operational changes were implemented to enhance FBLG performance.

Purpose of the Study:

To summarize the operational changes implemented at AZ to improve FBLG.
To detail the AZ fragment library construction, screening practices, and working model.

Main Methods:

Construction and composition of the AZ fragment library, including the second-generation fragment library (FL2).
Screening practices, including profiling specific fragment subsets and near-neighbor selection for hit follow-up.
Statistical assessment of fragment hit follow-up capabilities.

Main Results:

The second-generation fragment library (FL2) demonstrated the complementary value of flat and 3D fragments in exploring protein-binding pockets.
Multiple screening techniques successfully delivered fragment hits across various target classes.
The revised working model significantly impacted the delivery of lead series to drug discovery projects.

Conclusions:

The implemented changes and optimized fragment library have substantially improved the success rates of fragment-based lead generation.
The new model enhances the ability to identify and develop novel lead series for drug discovery.