The cost of drug development has exploded in recent years and risen to a level that soon will no longer be affordable to society. One reason for the high cost of drug development are many unnecessary studies where the results could have been predicted with reasonable certainty. PK/PD modeling is a tool that can be used to collect and integrate all the available information about a drug candidate and its class in order to make rational decisions on studies that will decrease the uncertainty of the compound. It is based on quantitative data on drug exposure and response and particularly well suited to address the question of dose finding and optimization. In the drug development process, it bridges the complete cycle from discovery to clinical use. The advantage of this approach is to define objective go/nogo decision criteria for the development process rather than relying on subjective empirical decisions. There is no way that today all developing questions can be answered by experimental evidence, and modeling and simulation is a powerful alternative approach. This modeling and simulation approach is of particular need in the field of new antiinfective agents where the rise of resistance has become an international threat to society. However, very few drug companies are currently developing new antibiotics due to the poor perspective of return on investment. However, the cost of anti-infective drug development can be dramatically lowered by applying pharmacometric concepts and selection of some key experiments based on pharmacokinetic/pharmacodynamic (PK/PD) concepts. Using microdialysis, it is today possible to measure the local exposure at the infection site in both animals and humans. This PK information is much more useful than traditional serum pharmacokinetics. Furthermore, pharmacodynamic activities can be much better captured by analyzing time-kill curves rather than simple minimum inhibitory concentrations (MICs). The use of the MIC has been a major obstacle for fully using all available data in anti-infective pharmacology. MIC is imprecise as it is measured in tewofold increments. It is monodimensional and only assessed at one time-point. MIC does not disclose any information about the maximum kill rate since it is defined by reaching visible growth, independent of maximum kill rate. This is a fundamental difference to EC50 which is defined as the concentration that produces half-maximum effects. There are many situations where the use of MIC is grossly inadequate but the field has been creative in inventing ‘patches’ (post-antibiotic effect, sub-MIC effect) that are widely accepted without rationale. Kill curve measurement can be shown to provide much more detailed information about the quantitative concentration-effect relationships and is a much more powerful tool to identify optimum dosing regimens both in drug development as well as in patient care. Examples from various classes of antibiotic drugs will be presented where these concepts are applied and illustrated. Application of these concepts will help to develop new anti-infective treatments at low cost to combat resistance development with optimum efficacy and safety. MIC is seen as a threshold value that results from the inability of our brains to integrate multiple simultaneous quantitative relationships. In the old days these situations were often resolved by gut-level decisions. If it gets too complicated we like to draw a line to visualize ‘how much we need’. Fortunately, we do now have computers that can aide us in making better and explicit decisions. Appropriate computer software and apps are currently being developed that will make the applications of these PK-PD concepts user friendly and easy to implement.
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