@article {612,
	title = {Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.},
	journal = {Nat Commun},
	volume = {10},
	year = {2019},
	month = {2019 06 17},
	pages = {2674},
	abstract = {<p>The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca{\textquoteright}s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60\% of combinations. However, 20\% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.</p>},
	keywords = {ADAM17 Protein, Antineoplastic Combined Chemotherapy Protocols, Benchmarking, Biomarkers, Tumor, Cell Line, Tumor, Computational Biology, Datasets as Topic, Drug Antagonism, Drug Resistance, Neoplasm, Drug Synergism, Genomics, Humans, Molecular Targeted Therapy, mutation, Neoplasms, pharmacogenetics, Phosphatidylinositol 3-Kinases, Phosphoinositide-3 Kinase Inhibitors, Treatment Outcome},
	issn = {2041-1723},
	doi = {10.1038/s41467-019-09799-2},
	author = {Menden, Michael P and Wang, Dennis and Mason, Mike J and Szalai, Bence and Bulusu, Krishna C and Guan, Yuanfang and Yu, Thomas and Kang, Jaewoo and Jeon, Minji and Wolfinger, Russ and Nguyen, Tin and Zaslavskiy, Mikhail and Jang, In Sock and Ghazoui, Zara and Ahsen, Mehmet Eren and Vogel, Robert and Neto, Elias Chaibub and Norman, Thea and Tang, Eric K Y and Garnett, Mathew J and Veroli, Giovanni Y Di and Fawell, Stephen and Stolovitzky, Gustavo and Guinney, Justin and Dry, Jonathan R and Saez-Rodriguez, Julio}
}
@article {1155,
	title = {Prediction of human population responses to toxic compounds by a collaborative competition.},
	journal = {Nature biotechnology},
	year = {2015},
	month = {2015 Aug 10},
	abstract = {The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson{\textquoteright}s r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.},
	issn = {1546-1696},
	doi = {10.1038/nbt.3299},
	url = {http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3299.html},
	author = {Eduati, Federica and Mangravite, Lara M and Wang, Tao and Tang, Hao and Bare, J Christopher and Huang, Ruili and Norman, Thea and Kellen, Mike and Menden, Michael P and Yang, Jichen and Zhan, Xiaowei and Zhong, Rui and Xiao, Guanghua and Xia, Menghang and Abdo, Nour and Kosyk, Oksana}
}
