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A robustness-based approach to systems-oriented drug design

Nature Reviews Drug Discovery volume 6, pages 202–210 (2007)Cite this article

Abstract

Many potential drugs that specifically target a particular protein considered to underlie a given disease have been found to be less effective than hoped, or to cause significant side effects. The intrinsic robustness of living systems against various perturbations is a key factor that prevents such compounds from being successful. By studying complex network systems and reformulating control and communication theories that are well established in engineering, a theoretical foundation for a systems-oriented approach to more effectively control the robustness of living systems, particularly at the cellular level, could be developed. Here, I use examples that are based on existing drugs to illustrate the concept of robustness, and then discuss how a greater consideration of the importance of robustness could influence the design of new drugs that will be intended to control complex systems.

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Figure 1: Basic mechanisms for robustness.
Figure 2: A range of options for drug design.

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References

  1. Kubinyi, H. Drug research: myths, hype and reality. Nature Rev. Drug Discov. 2, 665–668 (2003).

    Article  CAS  Google Scholar 

  2. Horrobin, D. F. Modern biomedical research: an internally self-consistent universe with little contact with medical reality? Nature Rev. Drug Discov. 2, 151–154 (2003).

    Article  CAS  Google Scholar 

  3. Butcher, E. C. Can cell systems biology rescue drug discovery? Nature Rev. Drug Discov. 4, 461–467 (2005).

    Article  CAS  Google Scholar 

  4. Butcher, E. C., Berg, E. L. & Kunkel, E. J. Systems biology in drug discovery. Nature Biotech. 22, 1253–1259 (2004).

    Article  CAS  Google Scholar 

  5. Hood, L. & Perlmutter, R. M. The impact of systems approaches on biological problems in drug discovery. Nature Biotech. 22, 1215–1217 (2004).

    Article  CAS  Google Scholar 

  6. van der Greef, J. & McBurney, R. N. Rescuing drug discovery: in vivo systems pathology and systems pharmacology. Nature Rev. Drug Discov. 4, 961–967 (2005).

    Article  CAS  Google Scholar 

  7. Keith, C. T., Borisy, A. A. & Stockwell, B. R. Multicomponent therapeutics for networked systems. Nature Rev. Drug Discov. 4, 71–78 (2005).

    Article  CAS  Google Scholar 

  8. Kaelin, W. G. Jr. The concept of synthetic lethality in the context of anticancer therapy. Nature Rev. Cancer 5, 689–698 (2005).

    Article  CAS  Google Scholar 

  9. Nicholson, J. K., Holmes, E., Lindon, J. C. & Wilson, I. D. The challenges of modeling mammalian biocomplexity. Nature Biotech. 22, 1268–1274 (2004).

    Article  CAS  Google Scholar 

  10. Fernie, A. R., Trethewey, R. N., Krotzky, A. J. & Willmitzer, L. Metabolite profiling: from diagnostics to systems biology. Nature Rev. Mol. Cell Biol. 5, 763–769 (2004).

    Article  CAS  Google Scholar 

  11. Nicholson, J. K. & Wilson, I. D. Understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nature Rev. Drug Discov. 2, 668–676 (2003).

    Article  CAS  Google Scholar 

  12. Kell, D. B. et al. Metabolic footprinting and systems biology: the medium is the message. Nature Rev. Microbiol. 3, 557–565 (2005).

    Article  CAS  Google Scholar 

  13. Kitano, H. Biological robustness. Nature Rev. Genet. 5, 826–837 (2004).

    Article  CAS  PubMed  Google Scholar 

  14. Stelling, J., Sauer, U., Szallasi, Z., Doyle, F. J. 3rd & Doyle, J. Robustness of cellular functions. Cell 118, 675–685 (2004).

    Article  CAS  PubMed  Google Scholar 

  15. Csete, M. E. & Doyle, J. C. Reverse engineering of biological complexity. Science 295, 1664–1669 (2002).

    Article  CAS  PubMed  Google Scholar 

  16. Csete, M. & Doyle, J. Bow ties, metabolism and disease. Trends Biotechnol. 22, 446–450 (2004).

    Article  CAS  PubMed  Google Scholar 

  17. Carlson, J. M. & Doyle, J. Highly optimized tolerance: robustness and design in complex systems. Phys. Rev. Lett. 84, 2529–2532 (2000).

    Article  CAS  PubMed  Google Scholar 

  18. Carlson, J. M. & Doyle, J. Complexity and robustness. Proc. Natl Acad. Sci. USA 99 (Suppl. 1), 2538–2545 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ferrell, J. E. Jr. Self-perpetuating states in signal transduction: positive feedback, double-negative feedback and bistability. Curr. Opin. Cell. Biol. 14, 140–148 (2002).

    Article  CAS  PubMed  Google Scholar 

  20. Bhalla, U. S. & Iyengar, R. Robustness of the bistable behavior of a biological signaling feedback loop. Chaos 11, 221–226 (2001).

    Article  CAS  PubMed  Google Scholar 

  21. Rutherford, S. L. Between genotype and phenotype: protein chaperones and evolvability. Nature Rev. Genet. 4, 263–274 (2003).

    Article  CAS  PubMed  Google Scholar 

  22. Ma, H. W., Zhao, X. M., Yuan, Y. J. & Zeng, A. P. Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph. Bioinformatics 20, 1870–1876 (2004).

    Article  CAS  PubMed  Google Scholar 

  23. Oda, K., Matsuoka, Y., Funahashi, A. & Kitano, H. A comprehensive pathway map of epidermal growth factor receptor signaling. Mol. Syst. Biol. 1, 25 May 2005 (doi:10.1038/msb4100014).

    Article  CAS  Google Scholar 

  24. Kitano, H. & Oda, K. Robustness trade-offs and host-microbial symbiosis in the immune system. Mol. Syst. Biol. 2, 17 Jan 2006 (doi:10.1038/msb4100039).

  25. Oda, K. & Kitano, H. A comprehensive pathway map of toll-like receptor signaling network. Mol. Syst. Biol. 2, 18 April 2006 (doi:10.1038/msb4100057).

  26. Doyle, J. C. et al. The 'robust yet fragile' nature of the internet. Proc. Natl Acad. Sci. USA 102, 14497–14502 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lamport, L., Shostak, R. & Pease, M. The Byzantine Generals problem. ACM Trans. Program. Languages Syst. 27, 382–401 (1982).

    Article  Google Scholar 

  28. Kitano, H. et al. Metabolic syndrome and robustness tradeoffs. Diabetes 53 (Suppl. 3), 6–15 (2004).

    Article  Google Scholar 

  29. Kitano, H. Cancer as a robust system: implications for anticancer therapy. Nature Rev. Cancer 4, 227–235 (2004).

    Article  CAS  Google Scholar 

  30. Kitano, H. Cancer robustness: tumour tactics. Nature 426, 125 (2003).

    Article  CAS  PubMed  Google Scholar 

  31. Waldor, M. K. & Mekalanos, J. J. Lysogenic conversion by a filamentous phage encoding cholera toxin. Science 272, 1910–1914 (1996).

    Article  CAS  PubMed  Google Scholar 

  32. Hung, D. T., Shakhnovich, E. A., Pierson, E. & Mekalanos, J. J. Small-molecule inhibitor of Vibrio cholerae virulence and intestinal colonization. Science 310, 670–674 (2005).

    Article  CAS  PubMed  Google Scholar 

  33. Normark, B. H. & Normark, S. Evolution and spread of antibiotic resistance. J. Intern. Med. 252, 91–106 (2002).

    Article  CAS  PubMed  Google Scholar 

  34. Druker, B. J. et al. Efficacy and safety of a specific inhibitor of the BCR–ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J. Med. 344, 1031–1037 (2001).

    Article  CAS  PubMed  Google Scholar 

  35. Rowley, J. D. A new consistent chromosomal abnormality in chronic myelogenous leukaemia identified by quinacrine fluorescence and Giemsa staining. Nature 243, 290–293 (1973).

    Article  CAS  PubMed  Google Scholar 

  36. Daley, G. Q., Van Etten, R. A. & Baltimore, D. Induction of chronic myelogenous leukemia in mice by the P210bcr/abl gene of the Philadelphia chromosome. Science 247, 824–830 (1990).

    Article  CAS  PubMed  Google Scholar 

  37. Kelliher, M. A., McLaughlin, J., Witte, O. N. & Rosenberg, N. Induction of a chronic myelogenous leukemia-like syndrome in mice with v-abl and BCR/ABL. Proc. Natl Acad. Sci. USA 87, 6649–6653 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Heisterkamp, N. et al. Acute leukaemia in bcr/abl transgenic mice. Nature 344, 251–253 (1990).

    Article  CAS  PubMed  Google Scholar 

  39. Lugo, T. G., Pendergast, A. M., Muller, A. J. & Witte, O. N. Tyrosine kinase activity and transformation potency of bcr–abl oncogene products. Science 247, 1079–1082 (1990).

    Article  CAS  PubMed  Google Scholar 

  40. Daub, H., Specht, K. & Ullrich, A. Strategies to overcome resistance to targeted protein kinase inhibitors. Nature Rev. Drug Discov. 3, 1001–1010 (2004).

    Article  CAS  Google Scholar 

  41. Nelson, H. S. Advair: combination treatment with fluticasone propionate/salmeterol in the treatment of asthma. J. Allergy Clin. Immunol. 107, 398–416 (2001).

    Article  CAS  PubMed  Google Scholar 

  42. Gupta, E. K. & Ito, M. K. Lovastatin and extended-release niacin combination product: the first drug combination for the management of hyperlipidemia. Heart Dis. 4, 124–137 (2002).

    Article  CAS  PubMed  Google Scholar 

  43. Bays, H. E. et al. Comparison of once-daily, niacin extended-release/lovastatin with standard doses of atorvastatin and simvastatin (the advicor versus other cholesterol-modulating agents trial evaluation [ADVOCATE]). Am. J. Cardiol. 91, 667–672 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. Larder, B. A., Kemp, S. D. & Harrigan, P. R. Potential mechanism for sustained antiretroviral efficacy of AZT–3TC combination therapy. Science 269, 696–699 (1995).

    Article  CAS  PubMed  Google Scholar 

  45. Borisy, A. A. et al. Systematic discovery of multicomponent therapeutics. Proc. Natl Acad. Sci. USA 100, 7977–7982 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Csermely, P., Agoston, V. & Pongor, S. The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol. Sci. 26, 178–182 (2005).

    Article  CAS  PubMed  Google Scholar 

  47. Agoston, V., Csermely, P. & Pongor, S. Multiple weak hits confuse complex systems: a transcriptional regulatory network as an example. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71, 051909 (2005).

    Article  PubMed  CAS  Google Scholar 

  48. Yuan, R. & Lin, Y. Traditional Chinese medicine: an approach to scientific proof and clinical validation. Pharmacol. Ther. 86, 191–198 (2000).

    Article  CAS  PubMed  Google Scholar 

  49. Wang, M. et al. Metabolomics in the context of systems biology: bridging traditional Chinese medicine and molecular pharmacology. Phytother. Res. 19, 173–182 (2005).

    Article  CAS  PubMed  Google Scholar 

  50. Tanaka, R. Scale-rich metabolic networks. Phys. Rev. Lett. 94, 168101 (2005).

    Article  PubMed  CAS  Google Scholar 

  51. Khan, J. et al. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Med. 7, 673–679 (2001).

    Article  CAS  PubMed  Google Scholar 

  52. Li, W. & Yang, Y. Zipf's law in importance of genes for cancer classification using microarray data. J. Theor. Biol. 219, 539–551 (2002).

    Article  CAS  PubMed  Google Scholar 

  53. Shah, M. A. & Schwartz, G. K. Cell cycle-mediated drug resistance: an emerging concept in cancer therapy. Clin. Cancer Res. 7, 2168–2181 (2001).

    CAS  PubMed  Google Scholar 

  54. Fujie, Y. et al. Oxaliplatin, a potent inhibitor of survivin, enhances paclitaxel-induced apoptosis and mitotic catastrophe in colon cancer cells. Jpn. J. Clin. Oncol. 35, 453–463 (2005).

    Article  PubMed  Google Scholar 

  55. Motwani, M. et al. Augmentation of apoptosis and tumor regression by flavopiridol in the presence of CPT-11 in Hct116 colon cancer monolayers and xenografts. Clin. Cancer Res. 7, 4209–4219 (2001).

    CAS  PubMed  Google Scholar 

  56. Schwartz, G. K. & Shah, M. A. Targeting the cell cycle: a new approach to cancer therapy. J. Clin. Oncol. 23, 9408–9421 (2005).

    Article  CAS  PubMed  Google Scholar 

  57. Shah, M. A. et al. A Phase I clinical trial of the sequential combination of irinotecan followed by flavopiridol. Clin. Cancer Res. 11, 3836–3845 (2005).

    Article  CAS  PubMed  Google Scholar 

  58. Levi, F. Cancer chronotherapy. J. Pharm. Pharmacol. 51, 891–898 (1999).

    Article  CAS  PubMed  Google Scholar 

  59. Levi, F. Circadian chronotherapy for human cancers. Lancet Oncol. 2, 307–315 (2001).

    Article  CAS  PubMed  Google Scholar 

  60. Chen, S. T. et al. Deregulated expression of the PER1, PER2 and PER3 genes in breast cancers. Carcinogenesis 26, 1241–1246 (2005).

    Article  CAS  PubMed  Google Scholar 

  61. Gery, S. et al. The circadian gene PER1 plays an important role in cell growth and DNA damage control in human cancer cells. Mol. Cell. 22, 375–382 (2006).

    Article  CAS  PubMed  Google Scholar 

  62. Torrieri, D. Principles of Spread Spectrum Communication Systems (Springer, New York, 2004).

    Google Scholar 

  63. Moriya, H., Shimizu-Yoshida, Y. & Kitano, H. In vivo robustness analysis of cell division cycle genes in Saccharomyces cerevisiae. PLoS Genet. 2, e111 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  64. El-Ali, J., Sorger, P. K. & Jensen, K. F. Cells on chips. Nature 442, 403–411 (2006).

    Article  CAS  PubMed  Google Scholar 

  65. Borisuk, M. T. & Tyson, J. J. Bifurcation analysis of a model of mitotic control in frog eggs. J. Theor. Biol. 195, 69–85 (1998).

    Article  CAS  PubMed  Google Scholar 

  66. Wakeling, A. E. et al. ZD1839 (Iressa): an orally active inhibitor of epidermal growth factor signaling with potential for cancer therapy. Cancer Res. 62, 5749–5754 (2002).

    CAS  PubMed  Google Scholar 

  67. Voldborg, B. R., Damstrup, L., Spang-Thomsen, M. & Poulsen, H. S. Epidermal growth factor receptor (EGFR) and EGFR mutations, function and possible role in clinical trials. Ann. Oncol. 8, 1197–1206 (1997).

    Article  CAS  PubMed  Google Scholar 

  68. Salomon, D. S., Brandt, R., Ciardiello, F. & Normanno, N. Epidermal growth factor-related peptides and their receptors in human malignancies. Crit. Rev. Oncol. Hematol. 19, 183–232 (1995).

    Article  CAS  PubMed  Google Scholar 

  69. Kakiuchi, S. et al. Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839). Hum. Mol. Genet. 13, 3029–3043 (2004).

    Article  CAS  PubMed  Google Scholar 

  70. Lynch, T. J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).

    Article  CAS  PubMed  Google Scholar 

  71. Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  CAS  PubMed  Google Scholar 

  72. Cohen, M. H. et al. United States Food and Drug Administration drug approval summary: gefitinib (ZD1839; Iressa) tablets. Clin. Cancer Res. 10, 1212–1218 (2004).

    Article  CAS  PubMed  Google Scholar 

  73. Kassouf, W. et al. Uncoupling between epidermal growth factor receptor and downstream signals defines resistance to the antiproliferative effect of gefitinib in bladder cancer cells. Cancer Res. 65, 10524–10535 (2005).

    Article  CAS  PubMed  Google Scholar 

  74. Kobayashi, S. et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 352, 786–792 (2005).

    Article  CAS  PubMed  Google Scholar 

  75. Carter, P. et al. Humanization of an anti-p185HER2 antibody for human cancer therapy. Proc. Natl Acad. Sci. USA 89, 4285–4289 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Slamon, D. J. et al. Human breast cancer: correlation of relapse and survival with amplification of the HER2/neu oncogene. Science 235, 177–182 (1987).

    Article  CAS  PubMed  Google Scholar 

  77. Cobleigh, M. A. et al. Multinational study of the efficacy and safety of humanized anti-HER2 monoclonal antibody in women who have HER2-overexpressing metastatic breast cancer that has progressed after chemotherapy for metastatic disease. J. Clin. Oncol. 17, 2639–2648 (1999).

    Article  CAS  PubMed  Google Scholar 

  78. Vogel, C. L. et al. Efficacy and safety of trastuzumab as a single agent in first-line treatment of HER2-overexpressing metastatic breast cancer. J. Clin. Oncol. 20, 719–726 (2002).

    Article  CAS  PubMed  Google Scholar 

  79. Lu, Y., Zi, X., Zhao, Y., Mascarenhas, D. & Pollak, M. Insulin-like growth factor-I receptor signaling and resistance to trastuzumab (Herceptin). J. Natl Cancer Inst. 93, 1852–1857 (2001).

    Article  CAS  PubMed  Google Scholar 

  80. Nagata, Y. et al. PTEN activation contributes to tumor inhibition by trastuzumab, and loss of PTEN predicts trastuzumab resistance in patients. Cancer Cell 6, 117–127 (2004).

    Article  CAS  PubMed  Google Scholar 

  81. FitzGerald, G. A. & Patrono, C. The coxibs, selective inhibitors of cyclooxygenase-2. N. Engl. J. Med. 345, 433–442 (2001).

    Article  CAS  PubMed  Google Scholar 

  82. Kargman, S. et al. Characterization of prostaglandin G/H synthase 1 and 2 in rat, dog, monkey, and human gastrointestinal tracts. Gastroenterology 111, 445–454 (1996).

    Article  CAS  PubMed  Google Scholar 

  83. Evett, G. E., Xie, W., Chipman, J. G., Robertson, D. L. & Simmons, D. L. Prostaglandin G/H synthase isoenzyme 2 expression in fibroblasts: regulation by dexamethasone, mitogens, and oncogenes. Arch. Biochem. Biophys. 306, 169–177 (1993).

    Article  CAS  PubMed  Google Scholar 

  84. Flower, R. J. The development of COX2 inhibitors. Nature Rev. Drug Discov. 2, 179–191 (2003).

    Article  CAS  Google Scholar 

  85. Bresalier, R. S. et al. Cardiovascular events associated with rofecoxib in a colorectal adenoma chemoprevention trial. N. Engl. J. Med. 352, 1092–1102 (2005).

    Article  CAS  PubMed  Google Scholar 

  86. Zarraga, I. G. & Schwarz, E. R. Coxibs and heart disease. J. Am. Coll. Cardiol. 49, 1–14 (2007).

    Article  CAS  PubMed  Google Scholar 

  87. Cortes, J. & Kantarjian, H. New targeted approaches in chronic myeloid leukemia. J. Clin. Oncol. 23, 6316–6324 (2005).

    Article  CAS  PubMed  Google Scholar 

  88. Neckers, L. & Ivy, S. P. Heat shock protein 90. Curr. Opin. Oncol. 15, 419–424 (2003).

    Article  CAS  PubMed  Google Scholar 

  89. Nimmanapalli, R., O'Bryan, E. & Bhalla, K. Geldanamycin and its analogue 17-allylamino-17-demethoxygeldanamycin lowers Bcr–Abl levels and induces apoptosis and differentiation of Bcr–Abl-positive human leukemic blasts. Cancer Res. 61, 1799–1804 (2001).

    CAS  PubMed  Google Scholar 

  90. Gorre, M. E., Ellwood-Yen, K., Chiosis, G., Rosen, N. & Sawyers, C. L. BCR–ABL point mutants isolated from patients with imatinib mesylate-resistant chronic myeloid leukemia remain sensitive to inhibitors of the BCR–ABL chaperone heat shock protein 90. Blood 100, 3041–3044 (2002).

    Article  CAS  PubMed  Google Scholar 

  91. Zsebik, B. et al. Hsp90 inhibitor 17-AAG reduces ErbB2 levels and inhibits proliferation of the trastuzumab resistant breast tumor cell line JIMT-1. Immunol. Lett. 104, 146–155 (2005).

    Article  PubMed  CAS  Google Scholar 

  92. Shimamura, T., Lowell, A. M., Engelman, J. A. & Shapiro, G. I. Epidermal growth factor receptors harboring kinase domain mutations associate with the heat shock protein 90 chaperone and are destabilized following exposure to geldanamycins. Cancer Res. 65, 6401–6408 (2005).

    Article  CAS  PubMed  Google Scholar 

  93. Larder, B. A. & Kemp, S. D. Multiple mutations in HIV-1 reverse transcriptase confer high-level resistance to zidovudine (AZT). Science 246, 1155–1158 (1989).

    Article  CAS  PubMed  Google Scholar 

  94. Tisdale, M., Kemp, S. D., Parry, N. R. & Larder, B. A. Rapid in vitro selection of human immunodeficiency virus type 1 resistant to 3′-thiacytidine inhibitors due to a mutation in the YMDD region of reverse transcriptase. Proc. Natl Acad. Sci. USA 90, 5653–5656 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Nakamura, H. et al. Cooperative cell-growth inhibition by combination treatment with ZD1839 (Iressa) and trastuzumab (Herceptin) in non-small-cell lung cancer. Cancer Lett. 230, 33–46 (2005).

    Article  CAS  PubMed  Google Scholar 

  96. Mendel, D. B. et al. In vivo antitumor activity of SU11248, a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor and platelet-derived growth factor receptors: determination of a pharmacokinetic/pharmacodynamic relationship. Clin. Cancer Res. 9, 327–337 (2003).

    CAS  PubMed  Google Scholar 

  97. Hrushesky, W. et al. A recent illustration of some essentials of circadian chronotherapy study design. J. Clin. Oncol. 22, 2971–2972 (2004).

    Article  PubMed  Google Scholar 

  98. Eriguchi, M. et al. Chronotherapy for cancer. Biomed. Pharmacother. 57 (Suppl. 1), 92–95 (2003).

    Article  CAS  Google Scholar 

  99. Mormont, M. C. & Levi, F. Circadian-system alterations during cancer processes: a review. Int. J. Cancer 70, 241–247 (1997).

    Article  CAS  PubMed  Google Scholar 

  100. Levi, F., Zidani, R. & Misset, J. L. Randomised multicentre trial of chronotherapy with oxaliplatin, fluorouracil, and folinic acid in metastatic colorectal cancer. International Organization for Cancer Chronotherapy. Lancet 350, 681–686 (1997).

    Article  CAS  PubMed  Google Scholar 

  101. Rivard, G. E., Infante-Rivard, C., Hoyoux, C. & Champagne, J. Maintenance chemotherapy for childhood acute lymphoblastic leukaemia: better in the evening. Lancet 2, 1264–1266 (1985).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This research was supported in part by the Exploratory Research for Advanced Technology (ERATO) and the Solution-Oriented Research for Science and Technology (SORST) programs (Japan Science and Technology Agency), a New Energy and Industrial Technology Development Organization Grant (NEDO) of the Japanese Ministry of Economy, Trade and Industry (METI), and the Genome Network Project by the Ministry of Education, Culture, Sports, Science, and Technology.

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  1. Japan; and the Department of Cancer Systems Biology, Hiroaki Kitano is at Sony Computer Science Laboratories Inc., 3-14-13 Higashi-Gotanda, Shinagawa, Tokyo 141-0022, Japan; The Systems Biology Institute, Suite 6A M31 6-31-15 Jingumae, Shuibuya, Tokyo 150-0001, The Cancer Institute, 3-10-6 Ariake, Koutou-ku, Tokyo 135-8550, Japan. kitano@sbi.jp,

    Hiroaki Kitano

  2. The Systems Biology Institute, Suite 6A M31 6-31-15 Jingumae, Shuibuya, Tokyo 150-0001, Japan,

    Hiroaki Kitano

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Using multistage drugs to achieve efficacy and selectivity. (PDF 132 kb)

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The spread spectrum control problem and the long-tail control problem (PDF 120 kb)

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Kitano, H. A robustness-based approach to systems-oriented drug design. Nat Rev Drug Discov 6, 202–210 (2007). https://doi.org/10.1038/nrd2195

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