Abstract

Although personalized medicine has a long history, today it implies low-variability responses to appropriately prescribed drugs. Achieving large reductions in variability requires reductions to be made in each of the many sources of variance in drug response. The four principal sources are: (i) the kinetics of drug release from formulated drug; (ii) the patients' variable adherence to prescribed dosing regimens; (iii) pharmacokinetics; and (iv) pharmacodynamics. Each source contributes nonlinearly to the overall variability in the relationship between the administered dose and the time courses of the drug's actions: the overall variance in drug response is the square root of the sums of the squares of each source's respective variances. This nonlinearity is a system property that arises from statistical principles; thus, large reductions in an individual source of variability will cause only a modest reduction in the overall variability in drug response. To achieve a substantial reduction in overall variability requires substantial reductions in each principal source of variance. Pharmacogenomics underlies the biochemical mechanisms involved in both pharmacokinetics and pharmacodynamics, and advances in this area will most likely lead to reductions in variance arising from these two sources. This alone will not achieve the goal of making major reductions in the variability of responses to drug treatment, however. Rather, to achieve that goal – seen as the capstone of personalized medicine – will require comparable reductions to be made in all four major sources of variance in drug response.

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