Treatment options and individualized medicine.
Although several drug targets are identified, current strategies in therapy do not take into account that patients vary in their response to drugs, both with respect to efficacy and toxic side effects. Whereas both clinical and histopathologic predictors of prognosis are established in some diseases, a better understanding of the molecular mechanisms that determine treatment response should play an important role in the development of individualized medicine. Treatment optimization will rely on the ability to adjust treatment algorithms for use in the individual patient based on the identification and validation of the factors that critically determine treatment outcomes, including diagnosis, disease phase and characteristics, organ functions, age, and gender. Although the analysis of a single genetic marker (e.g., CYP polymorphisms) may yield significant information that predicts drug response, the prediction obtained from the analysis of several genetic and epigenetic markers is potentially more powerful in selecting patients for effective therapy, whereas sparing those who would not respond or would suffer undesirable side effects. In this chapter, several relevant examples are presented.
Sioud
Mouldy
M
Department of Immunology, Institute for Cancer Research, The Norwegian Radium Hospital, University of Oslo, Oslo, Norway.
Melien
Oyvind
O
D000367:Age Factors; D003937:Diagnosis, Differential; D020869:Gene Expression Profiling / Q000379:methods / Q000639:trends; D005819:Genetic Markers; D015894:Genome, Human; D006801:Humans; D008991:Monitoring, Physiologic / Q000379:methods / Q000639:trends; D010597:Pharmacogenetics / Q000379:methods / Q000639:trends; D011110:Polymorphism, Genetic; D012737:Sex Factors
D005819:Genetic Markers