Evolving molecules using multi-objective optimization: applying to ADME/Tox

Ekins, Sean; Honeycutt, J. Dana; Metz, James T.

doi:10.1016/j.drudis.2010.04.003

Cited by 93 publications

(80 citation statements)

References 113 publications

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“…In an engineering discipline, characteristics may commonly be measured to accuracies within parts per million or predicted computationally to within a fraction of a percent. This may be contrasted with drug discovery where measured properties, such as IC 50 or K i values, may have an experimental variability of a factor of two, while predictions may have statistical uncertainties of an order of magnitude. This dramatically increases the challenge because, even if an ideal compound exists among the available options, we cannot expect to identify it with absolute confidence, thus running the risk of missing opportunities for high quality drugs [6].…”

Section: Introductionmentioning

confidence: 96%

“…Ekins et al described a software tool, "Pareto Ligand Designer," that combines molecular transformation with Pareto optimization to evolve initial compounds with sub-optimal properties toward structures that are more likely to achieve a required property profile [50]. The algorithm employs an engine that transforms compounds using a set of rules similar to those implemented in the Drug Guru package [39].…”

Section: Evolving Molecules Using Pareto Optimizationmentioning

confidence: 99%

“…Ideally, the project would like to identify a compound with high potency (pIC 50 ) and good stability in human liver microsomes (% remaining after incubation for 40 minutes). This ideal goal is represented by the top right corner of the plots in Figure 2.…”

Section: Pareto Optimizationmentioning

confidence: 99%

“…The range of efficiency metrics has been further extended to include percent efficiency index (PEI), defined as the percent inhibition (as a fraction between 0 and 1) divided by MW in kDa; binding efficiency index (BEI), defined as pIC 50 divided by MW in kDa; and surface efficiency index (SEI), defined as pIC 50 divided by PSA in 100s of Å. All of these combine a measure of potency related to another property representing the 'druglikeness' of the compound and are reviewed in detail in [23].…”

Section: Calculated Metricsmentioning

confidence: 99%

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Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties

Segall

2012

CPD

148

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A successful, efficacious and safe drug must have a balance of properties, including potency against its intended target, appropriate absorption, distribution, metabolism, and elimination (ADME) properties and an acceptable safety profile. Achieving this balance of, often conflicting, requirements is a major challenge in drug discovery. Approaches to simultaneously optimizing many factors in a design are broadly described under the term 'multi-parameter optimization' (MPO). In this review, we will describe how MPO can be applied to efficiently design and select high quality compounds and describe the range of methods that have been employed in drug discovery, including; simple 'rules of thumb' such as Lipinski's rule; desirability functions; Pareto optimization; and probabilistic approaches that take into consideration the uncertainty in all drug discovery data due to predictive error and experimental variability. We will explore how these methods have been applied to predicted and experimental data to reduce attrition and improve the productivity of the drug discovery process.

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Section: Introductionmentioning

confidence: 96%

Section: Evolving Molecules Using Pareto Optimizationmentioning

confidence: 99%

Section: Pareto Optimizationmentioning

confidence: 99%

Section: Calculated Metricsmentioning

confidence: 99%

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Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties

Segall

2012

CPD

148

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“…Biological processing of xenobiotics via ADME determines the feasibility of medicinal substances to become effective therapeutic agents (Eddershaw et al, 2000;Ekins et al, 2010;Lombardo & Waters, 2011;Ruiz-Garcia et al, 2008). Factors affecting the fate of xenobiotics may exist anywhere along the ADME process and may lead to a change of well designed and documented pharmacokinetic profiles of registered pharmaceuticals (Harris et al, 2003;.…”

Section: The Beauty and Odds Of Xenobiotics In The Biological Systemmentioning

confidence: 99%

System Building For Safe Medication

Wang¹,

Lian²,

Wang³

2011

Risk Management Trends

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Advances in Multiobjective Optimization for Drug Discovery and Development

Honeycutt

Zorn

Clark³

et al. 2021

Burger's Medicinal Chemistry and Drug Discovery

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Drug discovery requires the simultaneous optimization of many properties such as bioactivity, absorption, distribution, metabolism, excretion, toxicity, and the underlying physicochemical properties. The ability to satisfy many requirements at once is termed multiobjective optimization, and we will discuss the importance of research in this area for drug discovery and development. In particular, we provide examples of Pareto and other optimization methods and how they can be used in drug discovery to make trade‐offs between different predicted or real molecular properties, and we describe advances in software that applies these approaches.

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Evolving molecules using multi-objective optimization: applying to ADME/Tox

Cited by 93 publications

References 113 publications

Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties

Multi-Parameter Optimization: Identifying High Quality Compounds with a Balance of Properties

System Building For Safe Medication

Advances in Multiobjective Optimization for Drug Discovery and Development

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