Summary Infections in critically ill patients are associated with persistently poor clinical outcomes. These patients have severely altered and variable antibiotic pharmacokinetics and are infected by less susceptible pathogens. Antibiotic dosing that does not account for these features is likely to result in sub-optimal outcomes. In this paper, we review the patient- and pathogen-related challenges that contribute to inadequate antibiotic dosing and discuss how a process for individualised antibiotic therapy, that increases the accuracy of dosing, can be implemented to further optimise care for the critically ill patient. The process for optimised antibiotic dosing firstly requires determination of the physiological derangements in the patient that can alter antibiotic concentrations including altered fluid status, microvascular failure, serum albumin concentrations as well as altered renal and hepatic function. Secondly, knowledge of the susceptibility of the infecting pathogen should be determined through liaison with the microbiology laboratory. The patient and pathogen challenges can then be solved by combining susceptibility data with measured antibiotic concentration data (where possible) into a clinical dosing software. Such software uses pharmacokinetic-pharmacodynamic (PK/PD) models from critically ill patients to accurately predict the dosing requirements for the individual patient with the aim of optimising antibiotic exposure and maximising effectiveness.

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SIGNIFICANCE STATEMENT (74WORDS)Bivariate flow cytometric analysis of DNA content and FITC-labelled microsatellites enabled all the chromosomes in the U, M, S and C genomes ofAegilopsto be discriminated and purified. Mapping COS markers with known position in the wheat genome to flow-sorted Aegilops chromosomes revealed significant evolutionary rearrangements in the U and C genomes, but not in the M and S genomes. COS markers assigned to Aegilops chromosomes will facilitate alien introgression breeding in wheat.