If the number of potentially relevant compounds which have to be optimally selected is large, then random balance experimentation provides a useful tool for the development of nutrient media.The object of investigation was a thiostrepton producing Srreptomyces strain from our own collection. The thiostreptone formation was increased although we had insufficient information about the physiological needs or regulation aspects concerning the biosynthesis. The medium development was carried out alongside mutation experiments within a limited temporal interval.Our study shows how a 9-component medium can be improved by a 6-point experimental design. At the end of the paper the basic principles for constructing restricted random balance designs are outlined.One of the most common operations to study the physiology of micro-organisms is the development of a medium, optimal for the parameters in which one is interested, with regard to cell yield, the yield of a metabolic product, or the related enzyme level in the cell, Although our knowledge of the cellular regulation and the mechanisms of biosynthesis is generally good, each special case demands as a rule empirical practice.Since medium-screening is essentially an optimization process, it was considered worthwhile to investigate the use of response surface methodology in this situation.This technique is a collection of mathematical and statistical methods which have been developed and used to aid the solution of particular types of problems, pertinent to scientific and engineering processes. The methods include experimental designs, statistical inference, and mathematical optimization methods, which when combined enable the experimenter to make an efficient empirical investigation of the processes in which he is interested.This approach to exploring the relationship between variables has, to date, found its best application in industry. In fact, its modern development was motivated by problems encountered in the chemical industry (Box and WILSON 1951). Typically, in this area the problem is one of optimizing the yield of a particular process. In such situations, for example, it is known that the yield of the process is related to the levels of the input variables, and it is of interest to determine the level of each of these variables that produces an optimum yield.The essence of a response-surface approach is that a mathematical relationship (model) exists between the levels of treatment and the outcome observed. Thus, one generally works with causal models where the levels of treatment or design variables can be controlled by the researcher.In Fig. 1 a classification of response surface techniques is given. The so-called "systematic approach" is based on the following philosophy: Starting from a base point, corresponding to the best prior estimate of the optimum conditions, the first step is to construct and carry out a small initial group of experiments around this base point, in order to estimate tlie main effects. The best design here is the 2 factorial arrange...