Jones, A. & Clifford, L. Drug discovery alliances. Nat. Rev. Drug Discov. 4, 807–808 (2005).
Barnes, M. R. et al. Lowering industry firewalls: pre-competitive informatics initiatives in drug discovery. Nat. Rev. Drug Discov. 8, 701–708 (2009).
Yildirim, O., Gottwald, M., Schüler, P. & Michel, M. C. Opportunities and challenges for drug development: public-private partnerships, adaptive designs and big data. Front. Pharmacol. 7, 461 (2016).
Schmeck, B., Bertrams, W., Lai, X. & Vera, J. Systems medicine for lung diseases: phenotypes and precision medicine in cancer, infection, and allergy. Methods Mol. Biol. 1386, 119–133 (2016).
Stingone, J. A. et al. Big and disparate data: considerations for pediatric consortia. Curr. Opin. Pediatr. 29, 231–239 (2017).
Morrison, M. “A good collaboration is based on unique contributions from each side”: assessing the dynamics of collaboration in stem cell science. Life Sci. Soc. Policy 13, 7 (2017).
Wilan, K. H. Opening up the ivory tower. Cell 129, 847–850 (2007).
Melese, T., Lin, S. M., Chang, J. L. & Cohen, N. H. Open innovation networks between academia and industry: an imperative for breakthrough therapies. Nat. Med. 15, 502–507 (2009).
Schleidgen, S., Klingler, C., Bertram, T., Rogowski, W. H. & Marckmann, G. What is personalized medicine: sharpening a vague term based on a systematic literature review. BMC Med. Ethics 14, 55 (2013).
Association of the British Pharmaceutical Industry. Stratified medicine in the NHS: an assessment of the current landscape and implementation challenges for non-cancer applications. ABPI http://www.abpi.org.uk/our-work/library/medical-disease/Documents/stratified_med_nhs.pdf (2014).
Association of the British Pharmaceutical Industry. The stratification of disease for personalised medicines. Research driven recommendations to strengthen a unified UK strategy through a stakeholder alliance. ABPI http://www.abpi.org.uk/our-work/library/medical-disease/Documents/strat_med.pdf (2014).
Academy of Medical Sciences. Stratified, personalised or P4 medicine: a new direction for placing the patient at the centre of healthcare and health education. Academy of Medical Science s https://acmedsci.ac.uk/download?f=file&i=32644 (2015).
UK Trade and Investment. Unlock your global business potential. UK stratified medicine. GOV.UK https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/301775/UK_Stratified_Medicine.pdf (2013).
Medical Research Council. The Medical Research Council stratified medicine research initiatives. MRC https://www.mrc.ac.uk/research/initiatives/stratified-medicine/ (2017).
Peltonen, L. & McKusick, V. A. Genomics and medicine. Dissecting human disease in the postgenomic era. Science 291, 1224–1229 (2001).
Loscalzo, J., Kohane, I. & Barabasi, A. L. Human disease classification in the postgenomic era: a complex systems approach to human pathobiology. Mol. Syst. Biol. 3, 124 (2007).
Botstein, D. & Risch, N. Discovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease. Nat. Genet. 33, 228–237 (2003).
Hirschhorn, J. N. & Daly, M. J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6, 95–108 (2005).
Giacomini, K. M. et al. Genome-wide association studies of drug response and toxicity: an opportunity for genome medicine. Nat. Rev. Drug Discov. 16, 70 (2017).
Chatterjee, N., Shi, J. & García-Closas, M. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat. Rev. Genet. 17, 392–406 (2016).
Berger, B., Peng, J. & Singh, M. Computational solutions for omics data. Nat. Rev. Genet. 14, 333–346 (2013).
Hood, L., Balling, R. & Auffray, C. Revolutionizing medicine in the 21st century through systems approaches. Biotechnol. J. 7, 992–1001 (2012).
Institute for Safe Medication Practices. The five rights: a destination without a map. Institute for Safe Medication Practices http://www.ismp.org/newsletters/acutecare/articles/20070125.asp (2007).
McInnes, I. B., Buckley, C. D. & Isaacs, J. D. Cytokines in rheumatoid arthritis — shaping the immunological landscape. Nat. Rev. Rheumatol. 12, 63–68 (2016).
Baretta, Z., Mocellin, S., Goldin, E., Olopade, O. I. & Huo, D. Effect of BRCA germline mutations on breast cancer prognosis: a systematic review and meta-analysis. Medicine (Baltimore) 95, e4975 (2016).
Bunting, S. F. & Nussenzweig, A. End-joining, translocations and cancer. Nat. Rev. Cancer 13, 443–454 (2013).
Lieber, M. R. Mechanisms of human lymphoid chromosomal translocations. Nat. Rev. Cancer 16, 387–398 (2016).
Slamon, D. J. et al. Studies of the HER-2/neu proto-oncogene in human breast and ovarian cancer. Science 244, 707–712 (1989).
Pauletti, G., Godolphin, W., Press, M. F. & Slamon, D. J. Detection and quantitation of HER-2/neu gene amplification in human breast cancer archival material using fluorescence in situ hybridization. Oncogene 13, 63–72 (1996).
Maemondo, M. et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N. Engl. J. Med. 362, 2380–2388 (2010).
Slamon, D. J. et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N. Engl. J. Med. 344, 783–792 (2001).
Khagi, Y., Kurzrock, R. & Patel, S. P. Next generation predictive biomarkers for immune checkpoint inhibition. Cancer Metastasis Rev. 36, 179–190 (2017).
Siniard, R. C. & Harada, S. Immunogenomics: using genomics to personalize cancer immunotherapy. Virchows Arch. 471, 209–219 (2017).
Ramamurthy, C., Godwin, J. L. & Borghaei, H. Immune checkpoint inhibitor therapy: what line of therapy and how to choose? Curr. Treat. Options Oncol. 18, 33 (2017).
Medical Research Council. MRC Strategic Review of Human Immunology. MRC https://www.mrc.ac.uk/publications/browse/strategic-review-of-human-immunology/ (2007).
Gerlag, D. et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis: report from the Study Group for Risk Factors for Rheumatoid Arthritis. Ann. Rheum. Dis. 71, 638–641 (2012).
Innovative Medicines Initiative. The IMI funding model. IMI http://www.imi.europa.eu/about-imi/imi-funding-model (2017).
Johnson, W. E., Rabinovic, A. & Li, C. Adjusting batch effects in microarray expression data using Empirical Bayes methods. Biostatistics 8, 118–127 (2007).
Herzinger, S. et al. SmartR: an open-source platform for interactive visual analytics for translational research data. Bioinformatics 33, 2229–2231 (2017).