Use of Design of Experiments and Manuscripts Rejection Rate
Aydin Berenjian and Jason Ryan
DOI : 10.3844/ajbbsp.2015.44.44
American Journal of Biochemistry and Biotechnology
Volume 11, Issue 2
Traditional one-variable-at-a-time method was and stillis for some researchers, the general procedure to determine the optimalconditions for a chemical, biochemical or biological mechanism. According tothis technique, a large number of experiments should be performed to obtain ahigh precision in effect assessment and also the interaction among thevariables cannot be defined. To overcome the limitations of this labor-intensive,time-consuming and expensive technique, the statistical Design of Experiments (DoE)was proposed by.
DoEis recently the preferred method for optimization owing to the use of pivotalprinciples of statistics, randomization and replication. It is a suitablemethod to analyze the alteration of all factors simultaneously according to adesign matrix. Therefore, the effect of each variable and also the combinedeffect of two or more variables can be estimated with a minimum number ofexperiments. With the advent of modern computing this method has become aubiquitous tool in most research labs. While this approach is a versatilemethod for optimisation, its application can sometimes be haphazard orinappropriate under some conditions.
Today, a significant fraction of the submitted manuscripts are influencedby the DoE methodology and the progress in the use of these techniques in thehistory of biotechnology has been nothing but astonishing. Based on the SCOPUSdatabase, over the last 10 years, the number of manuscripts with ‘Design ofexperiment’ as a keyword has tripled across the major life and physical sciencejournals. Whilst a vast majority of these manuscripts are published in medicaljournals and are a standard requirement for drug efficacy testing, within thebiotechnology and biochemistry journals there has been a steady increase in thenumber of manuscripts using DoE methodology.
An ever-increasing number of manuscripts that use DoE as a means to demonstratethe optimisation of the production of microbial compounds are being published,with a vast majority reporting incremental changes to the existing literature.However, some of the most highly cited papers have used DoE approaches. DoEsoftware can produce subsequent number of tables/figures and consequentlyimprove the quantity of the paper. However, this technique is only half of the wholestory. The novelty of the research, its contribution to the field of study anddata collection is the other half.
Rejection of a manuscript in a peer-reviewed journal isa not a pleasant experience for the authors. Scientists plan to submit theirworks to quality journals forgetting the severe acceptance criteria for thejournal. Manuscripts depend as much on DoE software tools without anycontribution to the scientific community are likely to be rejected at theinitial editorial screening. Manuscripts, therefore, should more rely on highquality research that helps in understanding of the role of science and technologyin solving the key scientific and societal difficulties for the benefit ofmankind and environment.
ConclusionIt isstill expected that the use of DoE software will continue to help scientists toproduce accurate information from the data generated and further enhance theexcitement about the original. However, authors must consider what degree of noveltythere is through the application of DoE methodology to an existing knowledge,if the only outcome is optimisation.
© 2015 Aydin Berenjian and Jason Ryan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.