Personalized medicine promises to advance and improve health by targeting the right medication to the right person at the right time, thus maximizing the proportion of treated patients who achieve an effective response to therapy. This Comment article makes the complementary argument that equally important benefits will derive from negative prediction, namely by identifying those individuals who are either not actually in need of, or unlikely to respond to, a drug. Reduction of unnecessary prescription could conceivably save health-care systems many billions of dollars with very little detrimental impact on outcomes.
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G.G. is grateful to the Fulbright Program of the Bureau of Educational and Cultural Affairs of the United States Department of State, administered by the Institute of International Education, and to the College of Sciences of Georgia Tech for sabbatical support in Fall 2017, and especially to A. Navarro and J. Bertranpetit (CEXS-UPF in Barcelona) and L. Waller (Emory) for discussions.
The author declares no competing interests.
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Gibson, G. Going to the negative: genomics for optimized medical prescription. Nat Rev Genet 20, 1–2 (2019). https://doi.org/10.1038/s41576-018-0061-7
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