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PubMed2002

Optimization of a multielement sequential extraction method employing an experimental design approach for metal partitioning in soils and sediments.

The optimisation of a simple multielement extraction method employing an experimental design approach is described. The method uses centrifugation to pass one extractant solution at varying pH through a contaminated soil sample. The nature and concentration of the acid, rate of centrifugation and time, number of sequential leachates and the ratio of extractant volume: sample weight have been studied in order to obtain the optimum conditions for extraction. A fractional factorial experimental design was performed, and the results were used to identify significance which was then evaluated by carrying out a central composite experimental approach. Once optimum conditions had been obtained, sequential leaches were analysed by ICP-AES and chemometrics were employed to identify the composition of each component. Comparisons have been made with previous studies and tentative assignments, based on well defined separated fractions and percentage compositions for individual elements, used to identify the different physico-chemical components in the sample.

Chemistry Techniques, Analytical↗
PubMed1985

Single-case experimental designs in family therapy research: limitations and considerations.

Recent authors have encouraged the use of single-case experimental design in family therapy research. However, several issues related to the application of these designs have not been addressed. The present article suggests that the applicability of single-case methods to family therapy research may be limited. The first issue raised is the general lack of adequate dependent measures of family interaction that fulfill the requirements of the single-case experimental designs. Suggestions for development of appropriate measures are given. Second, the necessary reliance on relatively weak single-case designs often allows only relatively weak conclusions. Finally, the strategy of beginning the single-case study of family functioning and family therapy in laboratory settings is suggested.

Communication↗
PubMed1991

Use of experimental design in the pharmaceutical industry.

Statistical modelling and experimental design (SMED) are essential tools for the development and understanding of complicated products and processes. SMED allows efficient experimentation in which all or a large subset of factors are together varied over a set of experiments, in contrast to the traditional approach of varying only one at a time. An overview of the SMED methodology and the generalization of statistical design to multivariate design is presented. The following examples illustrating the use of these methods are discussed: (1) use of factorial designs to improve drug solubility; (2) testing the robustness of an analytical method; and (3) use of multivariate design to select the solvent in analytical method development.

Chemistry Techniques, Analytical↗
PubMed2002

Experimental designs for mixtures of chemicals along fixed ratio rays.

Experimental design is important when studying mixtures/combinations of chemicals. The traditional approach for studying mixtures/combinations of multiple chemicals involves response surface methodology, often supported by factorial designs. Although such an approach permits the investigation of both the effects of individual chemicals and their interactions, the number of design points needed to study the chemical mixtures becomes prohibitive when the number of compounds increases. Fixed ratio ray designs have been developed to reduce the amount of experimental effort when interest can be restricted to a specific ray. We focus on the design and analysis issues involved in studying mixtures/combinations of compounds along fixed ratio rays of the compounds. To obtain the inference regarding the interactions among the compounds, we show that the only data required are those along the fixed ratio ray.

Dose-Response Relationship, Drug↗
PubMed2002

Microbial biodiversity: approaches to experimental design and hypothesis testing in primary scientific literature from 1975 to 1999.

Research interest in microbial biodiversity over the past 25 years has increased markedly as microbiologists have become interested in the significance of biodiversity for ecological processes and as the industrial, medical, and agricultural applications of this diversity have evolved. One major challenge for studies of microbial habitats is how to account for the diversity of extremely large and heterogeneous populations with samples that represent only a very small fraction of these populations. This review presents an analysis of the way in which the field of microbial biodiversity has exploited sampling, experimental design, and the process of hypothesis testing to meet this challenge. This review is based on a systematic analysis of 753 publications randomly sampled from the primary scientific literature from 1975 to 1999 concerning the microbial biodiversity of eight habitats related to water, soil, plants, and food. These publications illustrate a dominant and growing interest in questions concerning the effect of specific environmental factors on microbial biodiversity, the spatial and temporal heterogeneity of this biodiversity, and quantitative measures of population structure for most of the habitats covered here. Nevertheless, our analysis reveals that descriptions of sampling strategies or other information concerning the representativeness of the sample are often missing from publications, that there is very limited use of statistical tests of hypotheses, and that only a very few publications report the results of multiple independent tests of hypotheses. Examples are cited of different approaches and constraints to experimental design and hypothesis testing in studies of microbial biodiversity. To prompt a more rigorous approach to unambiguous evaluation of the impact of microbial biodiversity on ecological processes, we present guidelines for reporting information about experimental design, sampling strategies, and analyses of results in publications concerning microbial biodiversity.

Bacteria↗
PubMed2002

From experimental design to uncertainty estimation for the European Pharmacopoeia HPLC analysis of human insulin.

In this paper the process from experimental design (e.g. ruggedness test) to uncertainty estimation is described. The uncertainty estimate was calculated for the peak area of insulin plus A21 desamido insulin resulting from an HPLC analysis of a sample of an injectable human insulin preparation, Actrapid HM 100 IU ml(-1) (Novo Nordisk A/S). The analytical method used was the European Pharmacopoeia assay. (4) An expanded uncertainty (1) of 1.8% (of the area from the HPLC analysis) at an approximately 95% confidence level was found and confirmed by a validation study. This uncertainty refers to the peak area of the analyte from a single injection of the sample. The input parameters to the uncertainty estimate were found from a factorial experimental design (e.g. ruggedness test) consisting of 9 factors applied to the HPLC analysis. The input parameters were chosen to cover the probable contributors to the variability of the measured area of the HPLC analysis, including the sample preparation, but excluding uncertainty deriving from the reference material(s).

Chromatography, High Pressure Liquid↗
PubMed2000

Suitable experimental design for determination of auxin polar transport in space using a spacecraft.

It is necessary to establish a suitable experimental design for the determination of auxin (indole-3-acetic acid: IAA) polar transport in space using a spacecraft in concerning with the role of gravity. Problems in space experiments are as follows: I) Selection of suitable plant species; II) Preservation of integrity of plant segments for activities of auxin polar transport; III) Stop of auxin polar transport of the segments after the transport experiment in space. Segments of etiolated pea epicotyls and etiolated maize coleoptiles showed relatively high activities of auxin polar transport among dicotyledonous and monocotyledonous plants tested, respectively. The activities decreased dramatically when the segments were pre-stored at 25 degrees C only for 1 day. On the other hand, the storage at low temperature (5 degrees C) in the presence of antioxidants or chelating agents, especially EGTA, maintained relatively high activities of auxin polar transport in pea epicotyl segments. Low temperature (5 degrees C) substantially inhibited the activity of auxin polar transport. Based on the results in this study, a suitable experimental design for the space experiment of auxin polar transport using a spacecraft is also proposed.

Biological Transport↗
PubMed2002

The effect of experimental design on the modeling of a tablet coating formulation using artificial neural networks.

The aim of this study was to investigate the effect of experimental design strategy on the modeling of a film coating formulation by artificial neural networks (ANNs). Box-Behnken, central composite and pseudo-random designs of 102, 90 and 100 simulated records, respectively were used to train a multilayer perceptron (MLP) ANN comprising six input and two output nodes separated by a single hidden layer of five nodes. Network over-training was limited by using a test set of 40 pseudo-randomly distributed records. The models were validated using a set of 60 pseudo-randomly distributed records. Crack velocity was highly curved with respect to pigment particle size and size distribution. Similarly, film opacity was highly curved in response to pigment concentration and film thickness. The Box-Behnken and central composite designs generated models that were unable to predict crack velocity and showed extensive bias in prediction of film opacity. The pseudo-random design was unable to predict crack velocity of the test data set but yielded acceptable predictions for the validation set. Film opacity was well predicted by the pseudo-random design model. The poor predictive ability of the Box-Behnken and central composite models was attributed to poor interpolation of the high curvature of the response surfaces. In contrast, the pseudo-random design mapped the interior of the design space allowing improved interpolation and predictive ability. It is concluded that Box-Behnken and central composite experimental designs are inappropriate for ANN modeling of highly curved responses and that extensive internal mapping of the design space is essential to generate predictive ANN models.

Drug Design↗
PubMed1998

Randomized event-related experimental designs allow for extremely rapid presentation rates using functional MRI.

Previous studies have shown that hemodynamic response overlap severely limits the maximum presentation rate with event-related functional MRI (fMRI) using fixed intertrial experimental designs. Here we demonstrate that the use of randomized experimental designs can largely overcome this limitation, thereby allowing for event-related fMRI experiments with extremely rapid presentation rates. In the first experiment, fMRI time courses were simulated using a fixed intertrial interval design with intervals of 16, 3, and 1 s, and using a randomized design having the same mean intertrial intervals. We found that using fixed intertrial interval designs the transient information decreased with decreasing intertrial intervals, whereas using randomized designs the transient information increased with decreasing mean intertrial intervals. In a second experiment, fMRI data were collected from two subjects using a randomized paradigm with visual hemifield stimuli presented randomly every 500 ms. Robust event-related activation maps and hemodynamic response estimates were obtained. These results demonstrate the feasibility of performing event-related fMRI experiments with rapid, randomized paradigms identical to those used in electrophysiological and behavioral studies, thereby expanding the applicability of event-related fMRI to a whole new range of cognitive neurosciences questions and paradigms.

Cerebrovascular Circulation↗
PubMed2006

Modeling and optimization of biopolymer (polyhydroxyalkanoates) production from ice cream residue by novel statistical experimental design.

Polyhydroxyalkanoates (PHAs) are thermoplastic polyesters synthesized by Ralstonia eutropha and other bacteria as a form of intracellular carbon and energy storage and are accumulated as lipid inclusions in the cytoplasm of these bacteria. The modeling and optimization of PHA production by fermentation from industrial waste (ice cream residue) was studied by employing statistical experimental design methods. A series of iterative experimental designs was used to find optimal factor conditions (medium components and fermentation process time) in the order of fractional factorial design, path of steepest ascent, and full factorial augmented with axial design (rotational central composite design). An optimal range characterized by lipid (15 mg/mL) and % lipid (88%) values was found and further investigated to verify the optimal conditions for PHA production from ice cream (56.68 mL of ice cream or 56.68% ice cream in water [v/v], 5.03 mL of buffer, 1 mL of mineral salts solution, 100 muL of trace element solution, 100 mL of seed culture, and 213.76 h of fermentation time).

Analysis of Variance↗
PubMed2006

Monolithic supports for the characterization of commercial maize products based on their chromatographic profile. Application of experimental design and classification techniques.

Modern analytical techniques based on the use of RP-HPLC with monolithic stationary phases and the application of experimental design and classification tools have been applied to the analysis of maize proteins. Solubilization conditions of maize proteins and separation conditions (temperature, detection wavelength, type and concentration of ion-pairing agent, and gradient) were optimized. The elution gradient was optimized by the application of experimental design techniques. The optimized method consisted of a linear binary gradient of water/acetonitrile/0.1% trifluoroacetic acid in three steps at a flow rate of 3 mL/min with a column temperature of 35 degrees C and UV detection at 280 nm. The developed method enabled the separation of maize proteins in an analysis time close to 8 min. Moreover, this is the first time that commercial maize products have been characterized by the use of multivariate classification techniques.

Chromatography, High Pressure Liquid↗
PubMed2000

Optimisation of alachlor solid-phase microextraction from water samples using experimental design.

We have tested screening and response surface experimental designs to optimise the solid-phase microextraction (SPME) of the widely used herbicide alachlor. Extraction time and sample volume were the only statistically significant factors from those studied. In the final optimised conditions the procedure was applied to the SPME-HPLC analysis of alachlor in spiked water samples with excellent figures of merit.

Acetamides↗
PubMed2004

Statistical experimental design of protein crystallization screening revisited.

A statistical experimental design approach was used to prepare a set of solutions for the screening of protein crystallization conditions. This approach is shown to be amenable to quantitative evaluation and therefore to the rational optimization of the screening results. All solutions contain a cryoprotectant, thus eliminating the need for subsequent optimization of crystal freezing conditions.

Algorithms↗
PubMed2006

Experimental design optimization for the ICP-AES determination of Li, Na, K, Al, Fe, Mn and Zn in human serum.

A chemometric approach based on experimental design and desirability functions was used to develop and validated a method for the determination of some metals of biological concern by a fast sequential ICP-AES. The elements considered are Al, Fe, Mn, Zn, Li, Na and K. The experimental design was used to investigate the effects of three instrumental most crucial parameters, such as sheath gas flow rate, pump speed and auxiliary gas flow rate. In order to improve the multielemental analysis speed, although a sequential instrument allows the use of a separate parameter set for each wavelength, regression models and desirability functions were applied to find the experimental conditions providing the highest global sensitivity. Validation was performed in terms of limits of detection (LOD), limits of quantitation (LOQ), linearity, precision and recovery. By using the 167.02 nm wavelength, aluminium LOD was 0.5 microg L(-1) while the highest LOD was found for K (65 microg L(-1)). A linear range of at least three orders of magnitude was statistically demonstrated for each element. Precision was evaluated by testing two concentration levels, and good results in terms of intra-day repeatability were obtained, with R.S.D. values lower than 4.1% at the lowest concentration level. Lacking a suitable certified reference material, trueness was estimated using the recovery rate on fortified samples. The validated method was then used in the quantification of the elements considered in a serum sample.

Aluminum↗
PubMed2003

How experimental design can improve the validation process. Studies in pharmaceutical analysis.

A critical discussion about the possibility of improving the method validation process by means of experimental design is presented. The reported multivariate strategies concern the evaluation of the performance parameters robustness and intermediate precision, and the optimisation of bias and repeatability. In particular, accuracy and precision improvement constitutes a special subset of experimental design in which the bias and the relative standard deviation of the assay are optimised. D-optimal design was used in order to plan experiments for this aim. The analytical methods considered were capillary electrophoresis, HPLC, adsorptive stripping voltammetry and differential pulse polarography. All methods were applied to real pharmaceutical analysis problems.

Adsorption↗
PubMed1993

Experimental design in alcohol administration research: limitations and alternatives in the manipulation of dosage-set.

This article reviews literature on the utility of different experimental designs in human alcohol administration research, with particular attention to the balanced-placebo design (BPD). Many believe the BPD can orthogonally manipulate alcohol's pharmacological effects and the effects of dosage-set (believing that one has consumed a certain amount of alcohol). However, research has accumulated that suggests these effects cannot be disentangled at moderate to high doses of alcohol. The strengths and weaknesses of a number of experimental designs are discussed with regard to the variables that designs can assess or control. Methodological issues in deception conditions and manipulation checks are reviewed. Topics in need of empirical investigation are highlighted. It is concluded that the appropriate alcohol administration design depends on the particular theoretical and methodological issues of a research program.

Alcohol Drinking↗
PubMed1990

An application of the D-optimal criterion to define the experimental design for a particular class of semi-parametric models.

An updated version of the computer program EXCAD [1] allows the user to optimize experimental design to estimate parameters of particular semi-parametric models. The semi-parametric models take the general form of a function of time (t): Y(t) = NL (c(t,alpha),beta). The function NL(C(t,alpha),beta), is, in general, a non-linear transformation of a function, C(t,alpha), that in turn is the convolution of two others. One of these two functions is expressed in a non-parametric form, and is not of direct interest to the experimenter. The other is of direct interest: it is a parametric function depending on a set of parameters alpha. This semi-parametric model applies to numerous kinds of biological experiments, such as pharmacokinetic/pharmacodynamic, physiological, circulatory flow experiments. This paper presents a new method for determining an optimal experimental design to estimate the parameters alpha and beta. The new approach adopts the D-optimal criterion, and is illustrated using real thiopental data.

Animals↗
PubMed2004

"Statistics" is not a sausage machine: a statistician's viewpoint and some comments on experimental design.

Any experiment involving the use of animals which is not well-planned, meticulously carried out, and scrupulously analysed, is unethical. Planning, or good experimental design, followed by analysis appropriate for the design, will help to ensure the optimal use of animals. Thus, collaboration between biologist and statistician, especially at the planning and analysis stages, is one of the best ways of achieving an ethical and successful experiment. However, genuine communication is necessary for any collaboration, and this requires time and patience, on the part of both biologist and statistician. Although the three fundamental principles of experimental design, replication, randomisation and local control, are straightforward in theory, there is substantial scope for misunderstanding and misinterpretation in practice. Each experiment presents unique and interacting biological and statistical problems, and both the right design and the correct analysis should be decided on a case-by-case basis.

Interdisciplinary Communication↗