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Fisher was a mathematical prodigy at school and university, aided rather than hampered by severe myopia that encouraged mental rather than written work. His first mathematical publication appeared in his graduation year, 1912, but his great passion was for eugenics and this drew him to the study of statistics and genetics. In her superb biography of her father, Joan Fisher Box 1 refers to the next period as the ‘wilderness years’, as he fluctuated between school teaching and farming while continuing to produce important research work. The breakthrough came in 1919, with his appointment to Rothamsted Experimental Station, the major centre for agricultural research in the UK. During the next 15 or so years he revolutionized statistical theory and methodology. Before his time, in what JBS Haldane called the ‘pre-piscatorial era’, the theory of statistics had been extremely fragmentary, with many unsolved problems and a good deal of confusion especially about the role of inverse probability—the assignment of probabilities to hypotheses, or what we should now call ‘Bayesian’ methods. Fisher produced a powerful theory of estimation and hypothesis testing free of such prior assumptions, backed up by penetrating mathematical results on the distributions of test statistics. For the first time it was possible to provide the research worker with a practical kit of tools for the analysis of many standard types of data. Fisher’s own book on statistical methods 2 was a hard nut to crack, but it engendered several other more approachable books during the inter-war period, such as those by Mather, Snedecor, Goulden, and Tippett.

Especially relevant for our present topic was Fisher’s work on experimental design, a topic he could be said to have invented. This was first presented in Fisher’s 1925 book, 2 expanded in a 1926 paper, 3 aimed at agricultural research workers, and developed more fully in his 1935 book The Design of Experiments. 4 One of its key features was the technique of random assignment of treatments or varieties to the field plots, and I shall say more about this later. Two points are worth making at this stage. Fisher always thought of design as going hand-in-hand with analysis. A design should maximize efficiency but must also provide a means of valid inference: randomization was an essential condition for the validity of Fisherian analysis. Secondly, note that the experiments considered by Fisher are the somewhat restricted class of controlled comparisons of treatments or varieties on arbitrarily variable experimental plots. The relevance of Fisher’s work to medical trials is clear, the ‘plots’ in this case being the individual patients.

Bradford Hill was the son of a distinguished physiologist, Sir Leonard Hill, and his intention to follow a medical career was thwarted by the onset of tuberculosis in 1917. He was an invalid for several years, during which he took a degree in economics by correspondence. He received help from the leading medical statistician of the time, Major Greenwood, who had worked in physiology under Hill’s father and also in statistics with Karl Pearson, the dominant figure in British statistics during the first two decades of the century. In 1927 Hill moved with Greenwood to the London School of Hygiene and Tropical Medicine and during the 1930s he researched mainly in occupational epidemiology. His renown in medical statistics started in 1937 with the publication of his textbook 5 based on a series of articles in the Lancet . This was entirely consistent with Fisherian methodology although the style was wholly different from Fisher’s, emphasizing practical snags and difficulties rather than theoretical minutiae. In this book he advocated randomization, although not initially distinguishing it from other apparently reasonable methods of avoiding allocation bias, such as alternation. He emphasized the distinction later and was able to put the method into practice in the trial of streptomycin in pulmonary tuberculosis and in the trial of pertussis vaccines planned earlier but published later.

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Volume 30
Issue 6
June 1992
L.J. Lorenz
Lilly Research Laboratories, Eli Lilly and Company
P.O. Box 685, Lafayette, Indiana 47902
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F.N. Bashore
Lilly Research Laboratories, Eli Lilly and Company
P.O. Box 685, Lafayette, Indiana 47902
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B.A. Olsen
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, Volume 30, Issue 6, 1 June 1992, Pages 211–216, https://doi.org/10.1093/chromsci/30.6.211
Published:
01 June 1992
Article history
Received:
16 December 1991
Received:
24 April 1992
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L.J. Lorenz, F.N. Bashore, B.A. Olsen; Determination of Process-Related Impurities and Degradation Products in Cefaclor by High-Performance Liquid Chromatography, Journal of Chromatographic Science , Volume 30, Issue 6, 1 June 1992, Pages 211–216, https://doi.org/10.1093/chromsci/30.6.211

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Abstract

A method employing gradient elution high-performance liquid chromatography (HPLC) is described for the determination of process-related impurities and degradation products in the cephalosporin antibiotic, cefaclor. The separation is performed on an ODS column (4.6 mm × 250 mm, 5-μm particles) using 50 mM phosphate buffer, pH 4.0, with a two-stage acetonitrile gradient from 2.25 to 45%. Ultraviolet detection at 220 nm is used. The mobile phase pH is an important factor in the separation of amphoteric compounds present in the sample, with pH 4.0 providing good separation and little fluctuation of retention with changes in pH. Applicability of the method for monitoring cefaclor bulk stability and determining the effect of manufacturing or sourcing changes on quality is demonstrated. The potential for extending the method to formulations is also described.

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