Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University , Linnaeus väg 10, 901 87 Umeå, Sweden.
Chalmers University of Technology , 412 58 Gothenburg, Sweden.
Anal Chem. 2017 Jun 20;89(12):6491-6497. doi: 10.1021/acs.analchem.7b00506. Epub 2017 May 30.
Design of experiments (DOE) is an established methodology in research, development, manufacturing, and production for screening, optimization, and robustness testing. Two-level fractional factorial designs remain the preferred approach due to high information content while keeping the number of experiments low. These types of designs, however, have never been extended to a generalized multilevel reduced design type that would be capable to include both qualitative and quantitative factors. In this Article we describe a novel generalized fractional factorial design. In addition, it also provides complementary and balanced subdesigns analogous to a fold-over in two-level reduced factorial designs. We demonstrate how this design type can be applied with good results in three different applications in analytical chemistry including (a) multivariate calibration using microwave resonance spectroscopy for the determination of water in tablets, (b) stability study in drug product development, and (c) representative sample selection in clinical studies. This demonstrates the potential of generalized fractional factorial designs to be applied in many other areas of analytical chemistry where representative, balanced, and complementary subsets are required, especially when a combination of quantitative and qualitative factors at multiple levels exists.
实验设计（DOE）是研究、开发、制造和生产领域中用于筛选、优化和稳健性测试的一种成熟方法。由于具有较高的信息量，同时保持实验数量较低，两水平部分因子设计仍然是首选方法。然而，这些类型的设计从未扩展到能够包含定性和定量因素的广义多级简化设计类型。本文描述了一种新颖的广义部分因子设计。此外，它还提供了类似于两水平简化因子设计中的折叠的补充和平衡子设计。我们展示了如何在分析化学的三个不同应用中很好地应用这种设计类型，包括（a）使用微波共振光谱法进行多元校准以测定片剂中的水分，（b）药物产品开发中的稳定性研究，以及（c）临床研究中的代表性样本选择。这表明广义部分因子设计有可能应用于分析化学的许多其他领域，特别是在存在多个水平的定量和定性因素组合时，需要具有代表性、平衡性和互补性的子集。
