The challenges of making decisions using uncertain data

被引:12
|
作者
Segall, Matthew D. [1 ]
Champness, Edmund J. [1 ]
机构
[1] Optibrium Ltd, Cambridge CB25 9TL, England
关键词
Uncertainty; Probability; Drug discovery; Compound optimisation; Multi-parameter optimisation; Desirability function; DRUG DISCOVERY; PERMEABILITY; BALANCE;
D O I
10.1007/s10822-015-9855-2
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
All of the experimental compound data with which we work have significant uncertainties, due to imperfect correlations between experimental systems and the ultimate in vivo properties of compounds and the inherent variability in experimental conditions. When using these data to make decisions, it is essential that these uncertainties are taken into account to avoid making inappropriate decisions in the selection of compounds, which can lead to wasted effort and missed opportunities. In this paper we will consider approaches to rigorously account for uncertainties when selecting between compounds or assessing compounds against a property criterion; first for an individual measurement of a single property and then for multiple measurements of a property for the same compound. We will then explore how uncertainties in multiple properties can be combined when assessing compounds against a profile of criteria, a process known as multi-parameter optimisation. This guides rigorous decision-making using complex, uncertain data to focus on compounds with the best chance of success, while avoiding missed opportunities by inappropriately rejecting compounds.
引用
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页码:809 / 816
页数:8
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