Towards polypotent natural products: The Derringer desirability approach and nonparametric ranking for multicriteria evaluation of essential oils

Abstract

Chemical complexity of natural products often results in their pharmacological polypotency. However, selecting a natural product with desirable activity profile is not a straightforward task, especially if optimization of one feature results in deterioration of other facets. Recently, in the field of multiobjective optimization, the sum of ranking differences (SRD) has emerged as a simple and statistically sound method for fusion of multiple criteria. However, the data pretreatment seems to strongly influence the ranking outcome, which may lead to ambiguous or even false interpretations. Therefore, in the present study, the data of 55 essential oils originated from different plant species and tested on multiple bacterial and fungal strains as well as 4 antioxidative assays were studied. Essential oils were ranked using the classical Deringer desirability approach, and results were compared with the SRD analysis of primary activity data as well as the previously row‐wise standardized data, normalized data, and the data scaled to fit the preferences. Ultimately, the most promising candidate (polypotent) essential oils, as well as the most resilient and most sensitive bacterial and fungal strains, and antioxidative assays were identified. Data transformation based on the Deringer desirability approach, compared with the data that have not been previously transformed or those that transformed using a row‐wise standardization or normalization to the unit length vector, seemed to be the crucial step providing the sound and meaningful SRD ranking.

Apportionment and districting by Sum of Ranking Differences

“…The Moment Invariant measures obtained some of the best and worst SRD scores, which indicates that the parameter of the function should be chosen carefully. Nagy and Szakál [47] suspect, based on empirical observations, that the most effective interval for the β parameter is [1,3]. Indeed β = −0.5 is second worst among the solutions and just barely falls outside the error limit.…”

“…The aim of this paper is twofold. Firstly, to promote SRD, a novel statistical method which is rapidly gaining popularity in various fields of applied science, such as analytical chemistry [1,2], pharmacology [3], decision making [4], and finance (see case study No. 2 in [5]) and which can be also potentially interesting to the Political Science and Social Choice community.…”

Does Lake Balaton affected by pollution? Assessment through surface water quality monitoring by using different assessment methods

“…This allows the identification of potential factors that influence the aqatic environment systems and represents a valuable tool for a further reliable management of water resources ( Shrestha and Kazama, 2007 ). The benefits of combining different methods are the maximisation of the advantages of these methods and the avoidance of the inherent the differences between methods, by promoting the Sum of ranking differences (hereafter SRD), a novel statistical method that is rapidly becoming popular in various fields of applied science, such as analytical chemistry ( Andrić, 2018 ). The SRD evaluation method was also used to explore the pharmacokinetic properties in pharmacology ( Ristovski et al, 2018 ).…”

Ranking and multicriteria decision making in optimization of raspberry convective drying processes

“…SRD has been successfully used in many different fields for the comparison of prediction models in eye‐tracking, essential oils, binary similarity measures, nutritional composition of edible insects, and beers, just to name a few from the latest publications.…”

“…27 The latest results have provided the possibility to choose proper validation variant of SRD results, in which the effect of way of cross-validation (contiguous and resampling), the number of folds (fivefold, sevenfold, and 10-fold), and the compared methods/models are analyzed in a three-way analysis of variance model. 28 SRD has been successfully used in many different fields for the comparison of prediction models in eye-tracking, 29 essential oils, 30 binary similarity measures, 31 nutritional composition of edible insects, 32 and beers, 33 just to name a few from the latest publications.…”