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Predictive Medicine aims at the detection of changes in patient's disease state prior to the manifestation of deterioration or improvement of the current status. Patient-specific, disease-course predictions with >95% or >99% accuracy during therapy would be highly valuable for everyday medicine. If these predictors were available, disease aggravation or progression, frequently accompanied by irreversible tissue damage or therapeutic side effects, could then potentially be avoided by early preventive therapy. The molecular analysis of heterogeneous cellular systems (Cytomics) by cytometry in conjunction with pattern-oriented bioinformatic analysis of the multiparametric cytometric and other data provides a promising approach to individualized or personalized medical treatment or disease management. Predictive medicine is best implemented by cell oriented measurements e.g. by flow or image cytometry. Cell oriented gene or protein arrays as well as bead arrays for the capture of solute molecules form serum, plasma, urine or liquor are equally of high value. Clinical applications of predictive medicine by Cytomics will include multi organ failure in sepsis or non infectious posttraumatic shock in intensive care, or the pretherapeutic identification of high risk patients in cancer cytostatic. Early individualized therapy may provide better survival chances for individual patient at concomitant cost containment. Predictive medicine guided early reduction or stop of therapy may lower or abrogate potential therapeutic side effects. Further important aspects of predictive medicine concern the preoperative identification of patients with a tendency for postoperative complications or coronary artery disease patients with an increased tendency for restenosis. As a consequence, better patient care and new forms of inductive scientific hypothesis development based on the interpretation of predictive data patterns are at reach.
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