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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Modelling iterative compound optimisation using a self-avoiding walk.

John Delaney1

  • 1Syngenta, Jealott's Hill International Research Centre, Bracknell, Berkshire RG42 6EY, United Kingdom. john.delaney@syngenta.com

Drug Discovery Today
|November 26, 2008
PubMed
Summary
This summary is machine-generated.

Drug development optimization is poorly understood. A new model simulating projects reveals target and process parameters distinctly impact drug discovery success.

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Last Updated: Jun 27, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Area of Science:

  • Drug development
  • Computational chemistry
  • Project management

Background:

  • The optimization phase in drug development is critical but poorly understood.
  • Lack of documentation for failed projects hinders statistical analysis of performance factors.

Purpose of the Study:

  • To develop an underlying theory for drug development project mechanics.
  • To model and simulate drug development projects and portfolios.

Main Methods:

  • A modified random walk model in chemical space was developed.
  • Simulations were used to explore parameters affecting project performance.

Main Results:

  • Project performance parameters were categorized into two groups: target and process.
  • Both target and process parameters were shown to affect overall project performance distinctly.

Conclusions:

  • The developed model provides a theoretical framework for understanding drug development project dynamics.
  • Simulation analysis highlights the differential impact of target and process parameters on project outcomes.