Abstract
The usefulness of the strategically designed sample composition (SSC) methodology for the screening of four anti-inflammatory drugs (ibuprofen, naproxen, tolfenamic acid and diclofenac) in water samples is demonstrated. Assuming that in screening campaigns only a limited number of the samples are contaminated with the analytes, the proposed approach allows the reliable identification of the contaminated specimens and the approximate estimation of their concentrations, with a 50% reduction in the total number of processed samples. To achieve this, a limited number of composite samples are built from the individual specimens. Automatic preparation of composite samples avoids human mistakes during this time-consuming and tedious operation, increasing the reliability of the predictions. In this work, a low-cost automatic device able to mix the individual specimens in the proportions indicated in the composition matrix is used. Moreover, the efficiency of evolutionary algorithms to predict the concentrations of the anti-inflammatory drugs in ultrapure and river water samples, artificially polluted in the laboratory and their robustness against large errors during the analysis of the composite samples, are evaluated.
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