Pharmaceutical Experimental Design

Lewis, Gareth; Mathieu, Didier; Phan‐Tan‐Luu, R.

doi:10.1201/9780203508688

Cited by 216 publications

(246 citation statements)

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“…4. 25) (4) where S(X) is the distance function generalized by the standard deviation SD k of the observed values for each response variable, FD k (X) is the optimum value of each response variable optimized individually over the experimental region and FO k (X) is the estimated value of all the responses given in the same set of causal factors, i.e., X. The simultaneous optimum solution can be estimated by minimizing S(X) under the restriction of the experimental region.…”

Section: Determination Of Response Variablesmentioning

confidence: 99%

“…2) When describing a design space, a design of experiments (DOE) is effectively used for determining the relationship between factors affecting a process and the output of the process. 3,4) Moreover, a response surface method (RSM) is useful for the visual understanding of factors and the facilitation of the clarification of problems to be solved for optimization in a pharmaceutical development study. [5][6][7][8][9][10][11] The design space is represented by the response surface model resolved at the limit of a satisfactory response, and it is determined from the region of successful operating ranges for multiple critical quality attributes.…”

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confidence: 99%

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Reliability Evaluation of the Design Space of the Granulation Process of Mefenamic Acid Tablets Using a Bootstrap Resampling Technique

Arai

Suzuki

Yada

et al. 2011

CHEMICAL & PHARMACEUTICAL BULLETIN

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The design space of the granulation process of mefenamic acid tablets, based on Box and Behnken design datasets, was described by a response surface method incorporating multivariate spline interpolation. The reliability of the optimal solutions and the acceptance ranges were evaluated by a bootstrap (BS) resampling technique. The distribution of the BS optimal solutions was almost symmetrical; however, several solutions, which were quite different from the original solution, were mixed. The reason for this problem was considered to be the mixing of the global and the local optima. Therefore, we applied self-organizing map (SOM) clustering for dividing data into several clusters and identified the cluster containing the global optima. The accuracy and reproducibility of the optimal solution in the cluster containing the optimal solution were quantitatively evaluated. In addition, the response surfaces modeled from all the BS datasets contained in the cluster were plotted into the same coordinates with the original response surface. The plots of BS optimal solutions were distributed around the original solution. Moreover, the average of all the BS response surfaces sufficiently corresponded with the original response surface. The conservative limits of the 95% confidence intervals of the acceptance ranges in three response variables could be calculated using the standard deviations of the BS response surfaces. Consequently, it was considered that a novel evaluation method based on BS resampling and SOM could be used for quantitatively evaluating the precision of the nonlinear response surface model.

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Section: Determination Of Response Variablesmentioning

confidence: 99%

mentioning

confidence: 99%

Reliability Evaluation of the Design Space of the Granulation Process of Mefenamic Acid Tablets Using a Bootstrap Resampling Technique

Arai

Suzuki

Yada

et al. 2011

CHEMICAL & PHARMACEUTICAL BULLETIN

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“…As defined by the ICH (27), robustness of an analytical procedure refers to its capability to remain unaffected by small and deliberate variations in method parameters. In order to study simultaneous variations of the factors on the considered responses, a multivariate approach using a design of experiments is recommended in robustness testing (17,18). Central Composite Circumfacited (CCC) design required 2 k + 2k + n = 17 runs, where k is the number of parameters studied (k = 3) and n is the number of central points included (n = 3).…”

Section: Validationmentioning

confidence: 99%

Use of chemometrics for development and validation of an RP-HPLC method for simultaneous determination of haloperidol and related compounds

Petkovska¹,

Dimitrovska²

2008

Acta Pharmaceutica

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Haloperidol is one of the most widely used antipsychotic drugs in the treatment of schizophrenia, mania and other psychiatric disorders (1). Chemically, haloperidol (Hal) is 4-[4-(4-chlorophenyl)-4-hydroxy-1-piperidinyl]-1-(4-fluorophenyl)-1-butanone. The drug has six known related compounds specified as impurities: 4-(4-chlorophenyl)-4-hydroxy A rapid resolution reversed-phase high performance liquid chromatographic (RR RP-HPLC) method has been developed and validated for simultaneous determination of haloperidol and six related compounds. Investigated matrix was a laboratory mixture of a therapeutic active substance haloperidol and its six related compounds in concentration ratio 300:1. Experimental design was used during method optimization (full factorial 2 3 design) and robustness testing (Central Composite Circumscribed design). Three factors: organic phase variation during gradient elution, flow rate and gradient rise time were independent variables. To estimate the system response during the optimization procedure and robustness testing, resolution (R s ) and a chromatographic response function (CRF) were used. Chromatography was performed with the mobile phase containing phosphate buffer pH 6.5 and acetonitrile as organic modifier. Separation was achieved using gradient elution (organic phase fraction changed linearly from 20 to 72 %) over 7 min. A Zorbax Eclipse XDB C18 Rapid Resolution HT 4.6 mm´50 mm, 1.8 mm particle size, column was used at 25°C at a flow rate of 1.5 mL min -1 . UV detection was performed at 230 nm. The total time for chromatographic separation was 5.5 min with a total analysis time of 7.0 min. The method was validated for its linearity, precision, modal recovery and robustness.

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“…Furthermore, it is widely recognized that standard experimental designs, such as (fractional) factorial designs, orthogonal arrays, or PlackettBurman designs offer large benefits over change-oneparameter-at-a-time experiments. For a clear overview of the use of experimental designs in the pharmaceutical industry, we refer to [2,3]. Frequently, it is shown that experimental designs bear the advantage of requiring less experiments and providing more reliable results, specifically about interactions.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Efficient Process Development Using Optimal Experimental Designs

et al. 2011

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Introduction The aim of this study was to develop and demonstrate a framework assuring efficient process development using fewer experiments than standard experimental designs. Methods A novel optimality criterion for experimental designs (Iw criterion) is defined that leads to more efficient process development because: (a) prior knowledge is used in the experimental design to focus on optimal processing conditions and (b) a lean design is used which can dramatically reduce the number of experiments compared to standard designs. In this way, the criterion serves as a framework to connect a series of screening and optimization designs. Results The philosophy behind the Iw criterion is explained including a detailed step-wise discussion how to apply it in practice. Moreover, its advantages were shown in an industrial process development case using a screening and an optimization design that were not explicitly connected. In this paper, a reduction of 21% of experiments could be obtained compared to the traditional approach using standard experimental designs and no framework. Conclusions The Iw criterion is a valuable tool to increase accuracy and to speed up research that contain sets of experiments and where prior knowledge is already available or will be derived using screening designs.

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Pharmaceutical Experimental Design

Cited by 216 publications

References 0 publications

Reliability Evaluation of the Design Space of the Granulation Process of Mefenamic Acid Tablets Using a Bootstrap Resampling Technique

Reliability Evaluation of the Design Space of the Granulation Process of Mefenamic Acid Tablets Using a Bootstrap Resampling Technique

Use of chemometrics for development and validation of an RP-HPLC method for simultaneous determination of haloperidol and related compounds

A Framework for Efficient Process Development Using Optimal Experimental Designs

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