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Updated: Jun 22, 2026

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Efficient and effective compound management to support lead optimization.

Chad W Johnson1, Moneesh Chatterjee, Steve Kubala

  • 1Department of Applied Biotechnology, Bristol-Myers Squibb Company, Hopewell, New Jersey 08534, USA. chad.johnson@bms.com

Journal of Biomolecular Screening
|June 2, 2009
PubMed
Summary
This summary is machine-generated.

Lean Six Sigma methods streamline drug discovery workflows, reducing costs and timelines. This approach enhances compound management for faster decision-making in lead optimization.

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Area of Science:

  • Drug Discovery
  • Process Optimization
  • Bioinformatics

Background:

  • Lean thinking and Six Sigma are increasingly adopted in drug discovery to improve efficiency and manage costs.
  • The compound management department at Bristol-Myers Squibb partnered with researchers to optimize workflows.
  • Cost-disciplined science is a key objective in modern pharmaceutical research.

Purpose of the Study:

  • To evaluate and streamline processes within the compound management department using Lean Six Sigma.
  • To optimize the automation and informatics environment for parallel compound processing.
  • To facilitate rapid and simultaneous data generation from structure-activity and structure-liability assays.

Main Methods:

  • Implementation of Lean Six Sigma methodologies.
  • Optimization of automation and informatics systems for compound management.
  • Development of a platform for parallel processing and data generation.

Main Results:

  • Streamlined workflows in compound management.
  • Optimized automation and informatics environment supporting parallel processing.
  • Facilitated rapid, simultaneous data generation from structure-activity and structure-liability assays.
  • Reduced timelines and improved decision-making in lead optimization.

Conclusions:

  • Lean Six Sigma approaches effectively enhance efficiency and reduce costs in drug discovery.
  • Optimized compound management processes accelerate the lead optimization phase.
  • The implemented platform supports faster scientific decision-making through rapid data generation.