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Experimental design deck for clinical research: A new learning resource in aid of scientific thinking.

The Experimental Design Deck for Clinical Research is a simulation of a problem in experimental design in a card deck format. It is intended to stimulate the development of skills in scientific thinking by allowing the student, in a self-directed fashion, to design a clinical trial to test either a given hypothesis (specific deck) or a hypothesis that the player provides (general deck). In addition to its use as an educational tool, the Experimental Design Deck can be used as a guide to the application of scientific thinking in a variety of biomedical activities. It can easily be modified for application to problems in nonmedical research and evaluation.

Clinical Trials as Topic↗

Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry.

Experimental design of (13)C-tracer studies for metabolic flux analysis with mass spectrometric determination of labeling patterns was performed for the central metabolism of Corynebacterium glutamicum comprising various flux scenarios. Ratio measurement of mass isotopomer pools of Corynebacterium products lysine, alanine, and trehalose is sufficient to quantify the flux partitioning ratios (i) between glycolysis and pentose phosphate pathways (Phi(PPP)), (ii) between the split pathways in the lysine biosynthesis (Phi(DH)), (iii) at the pyruvate node (Phi(PC)), and reversibilities of (iv) glucose 6-phosphate isomerase (zeta(PGI)), (v) at the pyruvate node (zeta(PC/PEPCK)), and (vi) of transaldolase and transketolases in the PPP. Weighted sensitivities for flux parameters were derived from partial derivatives to quantitatively evaluate experimental approaches and predict precision for estimated flux parameters. Deviation of intensity ratios from ideal values of 1 was used as weighting function. Weighted flux sensitivities can be used to identify optimal type and degree of tracer labeling or potential intensity ratios to be measured. Experimental design for lysine-producing strain C. glutamicum MH 20-22B (Marx et al., Biotechnol. Bioeng. 49, 111-129, 1996) and various potential mutants with different alterations in the flux pattern showed that specific tracer labelings are optimal to quantify a certain flux parameter uninfluenced by the overall flux situation. Identified substrates of choice are [1-(13)C]glucose for the estimation of Phi(PPP) and zeta(PGI) and a 1 : 1 mixture of [U-(12)C/U-(13)C]glucose for the determination of zeta(PC/PEPCK). Phi(PC) can be quantified by feeding [4-(13)C]glucose or [U-(12)C/U-(13)C]glucose (1 : 1), whereas Phi(DH) is accessible via [4-(13)C]glucose. The sensitivity for the quantification of a certain flux parameter can be influenced by superposition through other flux parameters in the network, but substrate and measured mass isotopomers of choice remain the same. In special cases, reduced labeling degree of the tracer substrate can increase the precision of flux analysis. Enhanced precision and flux information can be achieved via multiply labeled substrates. The presented approach can be applied for effective experimental design of (13)C tracer studies for metabolic flux analysis. Intensity ratios of other products such as glutamate, valine, phenylalanine, and riboflavin also sensitively reflect flux parameters, which underlines the great potential of mass spectrometry for flux analysis.

Computer Simulation↗

Method development and validation for the chiral separation of peptides in the presence of cyclodextrins using capillary electrophoresis and experimental design.

The present study describes the application of statistical experimental design to the optimization of enantioselective separations of peptides in capillary electrophoresis in order to obtain optimal operating conditions for routine work. Hydroxypropyl-beta-cyclodextrin was used as chiral selector and Ala-PheOMe as model peptide. The experiments were performed according to a face centered cube response surface experimental design for obtaining information how the factors such as concentration of the chiral selector, pH, buffer concentration and voltage affected the two response goals, resolution and analysis time. In order to achieve the simultaneous optimization of these two major electrophoretic performance goals for efficient and fast separation, the Derringer desirability functions were tested. While in the predefined experiments the analysis time for baseline separation was 25 min the desirability functions proposed a CE method, which diminished the analysis time and permitted the complete separation of the peptide enantiomers within 9 min.

Cyclodextrins↗

Experimental design and husbandry.

Rodent gerontology experiments should be carefully designed and correctly analyzed so as to provide the maximum amount of information for the minimum amount of work. There are five criteria for a "good" experimental design. These are applicable both to in vivo and in vitro experiments: (1) The experiment should be unbiased so that it is possible to make a true comparison between treatment groups in the knowledge that no one group has a more favorable "environment." (2) The experiment should have high precision so that if there is a true treatment effect there will be a good chance of detecting it. This is obtained by selecting uniform material such as isogenic strains, which are free of pathogenic microorganisms, and by using randomized block experimental designs. It can also be increased by increasing the number of observations. However, increasing the size of the experiment beyond a certain point will only marginally increase precision. (3) The experiment should have a wide range of applicability so it should be designed to explore the sensitivity of the observed experimental treatment effect to other variables such as the strain, sex, diet, husbandry, and age of the animals. With in vitro data, variables such as media composition and incubation times may also be important. The importance of such variables can often be evaluated efficiently using "factorial" experimental designs, without any substantial increase in the overall number of animals. (4) The experiment should be simple so that there is little chance of groups becoming muddled. Generally, formal experimental designs that are planned before the work starts should be used. (5) The experiment should provide the ability to calculate uncertainty. In other words, it should be capable of being statistically analyzed so that the level of confidence in the results can be quantified.

Animal Husbandry↗

[Analysis of paired comparison data based on experimental design: expression using structural equation modeling].

Paired comparison is a useful method for assessing ranks among several objects, and it enables us to obtain more reliable data than assessing objects one by one. But paired comparison principally provides information only about the ranks of the objects. On the other hand, experimental design provides a framework for elucidating causal associations. If we could analyze paired comparison data by the experimental design framework, it would be a very effective method. But experimental design, in its original form, is not readily applicable to paired comparison data. However, if we adopt the perspective of structural equation modeling (SEM), we can deal with paired comparison and experimental design in a unified way, because they are both submodels of SEM. The purpose of this study is to provide a new method to analyze causal connection of paired comparison data by using SEM. Here, two actual numerical examples are shown, one of which is obtained by within-subject design and the other is obtained by between-subject design.

Humans↗

An experimental design strategy for quantitating complex pharmacokinetic models: enterohepatic circulation with time-varying gallbladder emptying as an example.

A four-step strategy is proposed for determining appropriate experimental designs for investigating the pharmacokinetics of drugs characterized by complex compartmental models and this strategy has been applied to the pharmacokinetics of enterohepatic circulation (EHC). The four steps are (1) to establish an appropriate pharmacokinetic model, (2) to complete an identifiability analysis for the model to determine the route(s) of administration and sampling compartment(s) that are theoretically adequate for the quantitation of model parameters, (3) to carry out nonlinear least-squares fitting for the proposed number and timing of simulated error-free data points, and (4) to complete nonlinear least-squares fits of the model to data obtained by adding random error to the simulated data in step 3. The four-compartment model chosen for EHC of unchanged drug contained central, peripheral, gallbladder, and intestinal compartments and an intermittent gallbladder emptying rate constant. Identifiability analysis demonstrated that three alternative experimental designs for route(s) of administration and sampling compartment(s) are adequate for quantitating all model parameters, when the gallbladder emptying rate constant as a function of time is known (using controlled emptying from an engineered gallbladder in an animal model or quantitation in humans or animals using imaging techniques). Parameter estimates from fitting error-free data matched closely with the known values for all three experimental designs, indicating an adequate number and appropriate timing of data points. Results from fitting simulated data containing +/- 10% random error indicated unacceptable coefficients of variation and a nonrandom pattern in residual plots for one of the experimental designs.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

Introducing optimal experimental design in predictive modeling: a motivating example.

Predictive microbiology emerges more and more as a rational quantitative framework for predicting and understanding microbial evolution in food products. During the mathematical modeling of microbial growth and/or inactivation, great, but not always efficient, effort is spent on the determination of the model parameters from experimental data. In order to optimize experimental conditions with respect to parameter estimation, experimental design has been extensively studied since the 1980s in the field of bioreactor engineering. The so-called methodology of optimal experimental design established in this research area enabled the reliable estimation of model parameters from data collected in well-designed fed-batch reactor experiments. In this paper, we introduce the optimal experimental design methodology for parameter estimation in the field of predictive microbiology. This study points out that optimal design of dynamic input signals is necessary to maximize the information content contained within the resulting experimental data. It is shown that from few dynamic experiments, more pertinent information can be extracted than from the classical static experiments. By introducing optimal experimental design into the field of predictive microbiology, a new promising frame for maximization of the information content of experimental data with respect to parameter estimation is provided. As a case study, the design of an optimal temperature profile for estimation of the parameters D(ref) and z of an Arrhenius-type model for the maximum inactivation rate kmax as a function of the temperature, T, was considered. Microbial inactivation by heating is described using the model of Geeraerd et al. (1999). The need for dynamic temperature profiles in experiments aimed at the simultaneous estimation of the model parameters from measurements of the microbial population density is clearly illustrated by analytical elaboration of the mathematical expressions involved on the one hand, and by numerical simulations on the other.

Bacteria↗

Assessing the influence of scanner background noise on auditory processing. I. An fMRI study comparing three experimental designs with varying degrees of scanner noise.

We compared two experimental designs aimed at minimizing the influence of scanner background noise (SBN) on functional MRI (fMRI) of auditory processes with one conventional fMRI design. Ten subjects listened to a series of four one-syllable words and had to decide whether two of the words were identical. This was contrasted with a no-stimulus control condition. All three experimental designs had a duration of approximately 17 min: 1) a behavior interleaved gradients (BIG; Eden et al. [1999] J Magn Reson Imaging 41:13-20) design (repetition time, TR, = 6 s), where stimuli were presented during the SBN-free periods between clustered volume acquisitions (CVA); 2) a sparse temporal sampling technique (STsamp; e.g., Gaab et al., [2003] Neuroimage 19:1417-1426) acquiring only one set of slices following each of the stimulations with a 16-s TR and jittered delay times between stimulus offset and image acquisition; and 3) an event-related design with continuous scanning (ERcont) using the stimulation design of STsamp but with a 2-s TR. The results demonstrated increased signal within Heschl's gyrus for the STsamp and BIG-CVA design in comparison to ERcont as well as differences in the overall functional anatomy among the designs. The possibility to obtain a time course of activation as well as the full recovery of the stimulus- and SBN-induced hemodynamic response function signal and lack of signal suppression from SBN during the STsamp design makes this technique a powerful approach for conducting auditory experiments using fMRI. Practical strengths and limitations of the three auditory acquisition paradigms are discussed.

Acoustic Stimulation↗

Application of experimental design methodology in development and optimization of drug release method.

The aim of our research was to apply experimental design methodology in the development and optimization of drug release methods. Diclofenac sodium (2-[(2,6-dichlorophenyl)amino]benzeneacetic acid monosodium salt) was selected as a model drug and Naklofen retard prolonged release tablets, containing 100 mg of diclofenac sodium, were chosen as a model prolonged release system. On the basis of previous results, a three-level three-factorial Box-Behnken experimental design was used to characterize and optimize three physicochemical parameters, i.e. rotation speeds of the stirring elements, pH, and ionic strengths of the dissolution medium, affecting the release of diclofenac sodium from the tablets. The chosen dependent variables (responses) were a cumulative percentage of dissolved diclofenac sodium in 2, 6, 12 and 24 h. For estimation of coefficients in the approximating polynomial function, the least square regression method was applied. Afterwards, the information about the model reliability was verified by using the analysis of variance (ANOVA). The estimation of model factors' significance was performed by Student's t-test. For investigation of the shape of the predicted response surfaces and for model optimization, the canonical analysis was applied. Our study proved that experimental design methodology could efficiently be applied for characterization and optimization of analytical parameters affecting drug release and that it is an economical way of obtaining the maximum amount of information in a short period of time and with the fewest number of experiments.

Analysis of Variance↗

Nutrient balance studies in the preterm infant: crossover and parallel studies as methods of experimental design.

Crossover and parallel studies were compared as methods of experimental design during nutritional balance studies in the preterm infant. Twelve formula-fed infants (birth weight, 1,362 +/- 125 g, mean SD; gestational age, 32.3 +/- 1.7 weeks) were studied over 2 continuous weeks, "period" being the only obvious difference between the weeks. During each week, growth was determined, and 84-h nutrient balance was performed. Growth was adequate during both weeks. Increased absorption and retention (mg/kg/day and percent) of calcium and copper were noted during the 2nd week. Increased retention (mg/kg/day and percent) of phosphorus and magnesium was noted also, indicating increased nutrient assimilation due to a period effect. However, the variance due to the period effect (crossover) was less than that associated with "patient characteristics" (parallel study). In addition, sample size requirements were less, indicating that crossover studies are more efficient than parallel studies as a method of experimental design.

Analysis of Variance↗

Bile salt/lecithin mixed micelles optimized for the solubilization of a poorly soluble steroid molecule using statistical experimental design.

Bile salts and lecithin combine physiologically to form mixed micelles which aid the solubilization and absorption of dietary fats and drug molecules. In this series of experiments, we have shown how experimental design procedures aid the optimization of a formulation incorporating a bile salt, lecithin, and water with fluticasone propionate (FP) as the model poorly soluble drug. The initial inclusion of a categorical variable ruled out the use of classic response surface designs; therefore the experimental design was constructed using a d-optimal selection from a candidate set of all possible experimental combinations. A separate 2-factor central composite design was used to determine the optimum lecithin and bile salt concentrations over an extended range after the categorical variable had been eliminated. It has been demonstrated that an increase in either lecithin or cholic acid concentration produces an increase in solubility of FP, while sodium taurocholate appears to depress the solubility of FP compared with the other two bile salts. The increase in solubility associated with the increase in bile salt and lecithin is further demonstrated by a linear relationship between FP solubility and the total lipid in the formulation. The influence of molar ratio of lecithin to bile salt in the formulation is also significant. The physical properties of the mixed micellar system (solution turbidity and viscosity ranking) were used to further discriminate between formulations. The optimization showed that the dominant effect was the lecithin, which improves the solubilizing characteristics of the formulation with increasing concentration. The effect of salt concentration is less marked though slightly quadratic in nature. The overall increase in solubility demonstrated was from <1 microg/mL in water to 205 microg/mL in the optimized mixed micellar system.

Bile Acids and Salts↗

Experimental design optimisation: theory and application to estimation of receptor model parameters using dynamic positron emission tomography.

The general framework and various criteria for experimental design optimisation are presented. The methodology is applied to the estimation of receptor-ligand reaction model parameters with dynamic positron emission tomography data. The possibility of improving parameter estimation using a new experimental design combining an injection of the beta+-labelled ligand and an injection of the cold ligand is investigated. Numerical simulations predict a remarkable improvement in the accuracy of the parameter estimates with this new experimental design and particularly the possibility of separate estimations of the association constant (k+1) and of the receptor density (B'max) in a single experiment. Simulation predictions are validated using experimental PET data in which parameter uncertainties are reduced by factors ranging from 17 to 1000.

Computer Simulation↗

EDIBLE: experimental design and information calculations in phylogenetics.

UNLABELLED: Although evolutionary inference from molecular sequences is a statistical problem, little attention has been paid to questions of experimental design. A computer program, EDIBLE, has been developed to perform likelihood calculations based on Markov process models of nucleotide substitution allied with phylogenetic trees, and from these to compute Fisher information measures under different experimental designs. These calculations can be used to answer questions of optimal experimental design in molecular phylogenetics. AVAILABILITY: Source code (ANSI C), executables and documentation for EDIBLE are available from http://ng-dec1.gen.cam. ac.uk/info/index.htmland 'downstream' Web pages. CONTACT: N.Goldman@gen.cam.ac.uk

Likelihood Functions↗

A reconsideration of operations research experimental designs.

Of the three types of experimental designs used in social science research (true experiments, nonexperiments, and quasi-experiments), the most common in family planning OR are two quasi- and two nonexperimental designs. There has been a shift over time in the OR Program from true to quasi- and now, apparently, to nonexperimental designs. The strengths and weaknesses of these designs can be summarized as a tradeoff between greater validity and lower practicality, or greater practicality and lower validity. A number of suggestions have been made for improving the validity of nonexperimental designs or improving the practicality of quasi-experiments, but these suggestions do not significantly reduce the tradeoff. The designer, therefore, has to make a choice when selecting a design. With the current emphasis in the OR Program on providing useful information to managers, it may be time to include the managers in that decision, especially if they are to be the users of the results. It may also be time to look to other methodologies, particularly management science, for appropriate tools and techniques to use in family planning field settings. Nine criteria have been suggested for helping manager-researcher teams select an appropriate design: the time it takes to carry out a design, the cost involved, the expected utility of the results, the risk involved in accepting the results as valid, the audience that will use the results, the complexity of the issue to be studied, the state of existing knowledge about the subject, the difficulty of measuring the indicators selected, and the risk of contamination of control or experimental groups. Using these criteria, a researcher could help the manager decide how much of an investment to make in the study design. Nonexperimental designs could be applied to studies that can be done quickly, that are inexpensive, that involve low risk, that are limited to the manager as the audience, that are not complex, that have high utility, about which a good deal is already known, and for which the desired indicators are easy to measure. The more rigorous designs would be selected for studies that are at the other end of the continuum: that are lengthy, that are expensive, that are high-risk, that have multiple audiences, that are complex, about which little is known, that are difficult to measure, and that have a high chance of contamination. Obviously, no single methodology or study design should be applied to all OR problems. Experiments are important in certain circumstances, but not in all, perhaps not in many.(ABSTRACT TRUNCATED AT 400 WORDS)

Causality↗

An unbalanced experimental design for dose response studies.

Sixty sets of real data for 15 different pesticides from both sexes of Balb/C mice in two different experimental designs were generated at NCTR. The quantal responses for the dose groups in this data ranged from 1% to 90%. It was shown that the data could be represented equally well by a probit or logit transformation. It was further shown that the investment in terms of 7 times as many animals would greatly increase the confidence in estimating the parameters of the model and in predicting the dose at the low end of the dose response. Most important, it was shown that the estimation of a safe dose for a specified risk was greatly influenced by the choice of experimental design and method of extrapolation. It might be worth the investment in better experimental design to both the consumer and to the chemical industry if higher safe doses could be established which would allow the chemical to better accomplish its purpose and yet improve the assurance of the safety of the consumer.

Animals↗

The effect of experimental design on memory for typical and distinctive faces.

The effect of experimental design on memory for typical and distinctive faces was investigated in three experiments. In Experiments 1 and 2, a between-subjects, between-lists (distinctive-only faces, or typical-only faces) manipulation of distinctiveness was compared with a within-subjects mixed-list design. The results demonstrated an interaction between design type and distinctiveness, indicating an increase in the rate of misidentifications and a decrease in the response criterion to distinctive faces in the distinctive-only set relative to distinctive faces in the mixed-list condition. Experiment 3 addressed the locus of this effect by comparing the standard mixed-list within-subjects design with two sets of faces in which the target images were different in type from the distractor images, i.e. a typical target-distinctive distractor set and a distinctive target-typical distractor set. The results of this experiment demonstrated that distinctive distractor faces were more readily rejected as new faces when typical target faces were included in the same set. The relative sensitivity of memory for typical and distinctive faces to manipulations of experimental design are discussed with reference to current models of facial distinctiveness.

Discrimination, Psychological↗

Experimental design constraints on carcinogenic potency estimates.

The multistage model is used by U.S. regulatory agencies to calculate estimates of the carcinogenic potency (beta) of chemicals; the data for these estimates are generally obtained from chronic rodent bioassays. Three quantities characterize each group tested in the chronic bioassay: the dose level, the sample size, and the number responding to the dose. The dose levels tested are fixed by conventional protocols; the typical National Toxicology Program (NTP) experimental design calls for use of the maximum tolerated dose (MTD), one-half and one-fourth MTD, plus a control group. Only rarely are doses even one order of magnitude less than the MTD utilized in chronic bioassays. This experimental design constraint on dose selection limits the possible values of beta that can arise from multistage model analyses of chronic bioassay data. Sample size is also constrained by the experimental design of the chronic bioassay; the typical sample size in NTP studies is 50 animals. Occasionally, fewer animals are used, but only rarely are more. Thus, the multistage model which theoretically has three variable quantities with which to estimate carcinogenic potency, has in practice only one: the incidence of treatment-related response. Even this can vary within only a narrow range determined by sample size, the control incidence, and the level of statistical significance desired. The net result of these design constraints is that carcinogenic potency estimates derived from multistage-model analyses of chronic bioassay data may vary within only a narrow range surrounding the inverse maximum dose tested. We have illustrated this by calculating the largest possible finite potency estimates that could have arisen from the experimental designs used to test 82 mouse carcinogens in chronic bioassays. On average these maximum potency estimates were within one order of magnitude of the inverse maximum dose tested. We thus conclude that the chronic rodent bioassay, in and of itself, is altogether inadequate as a data source for estimating the risk to humans from exposure to carcinogenic chemicals.

Animals↗

The effectiveness of family planning programs evaluated with true experimental designs.

OBJECTIVES: This paper describes the magnitude of effects for family planning programs evaluated with true experimental designs. METHODS: Studies that used true experimental designs to evaluate family planning programs were identified and their results subjected to meta-analysis. RESULTS: For the 14 studies with the information needed to calculate effect size, the Pearson r between program and effect variables ranged from -.08 to .09 and averaged .08. CONCLUSIONS: The programs evaluated in the studies considered have had, on average, smaller effects than many would assume and desire.

Family Planning Services↗