{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T20:25:44Z","timestamp":1759091144372,"version":"3.41.0"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2017,3,18]],"date-time":"2017-03-18T00:00:00Z","timestamp":1489795200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Math Artif Intell"],"published-print":{"date-parts":[[2017,10]]},"DOI":"10.1007\/s10472-017-9541-2","type":"journal-article","created":{"date-parts":[[2017,3,18]],"date-time":"2017-03-18T17:05:03Z","timestamp":1489856703000},"page":"155-166","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improving machine learning in early drug discovery"],"prefix":"10.1007","volume":"81","author":[{"given":"Claus","family":"Bendtsen","sequence":"first","affiliation":[]},{"given":"Andrea","family":"Degasperi","sequence":"additional","affiliation":[]},{"given":"Ernst","family":"Ahlberg","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9491-4134","authenticated-orcid":false,"given":"Lars","family":"Carlsson","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,3,18]]},"reference":[{"key":"9541_CR1","volume-title":"Categorical Data Analysis","author":"A Agresti","year":"2001","unstructured":"Agresti, A.: Categorical Data Analysis. John Wiley & Sons, Inc., Hooken (2001)"},{"issue":"8","key":"9541_CR2","first-page":"569","volume":"12","author":"J Arrowsmith","year":"2013","unstructured":"Arrowsmith, J., Miller, P.: Trial Watch: Phase II and Phase III attrition rates 2011\u20132012. Nat. Publ. Group 12(8), 569\u2013569 (2013)","journal-title":"Nat. Publ. Group"},{"issue":"3","key":"9541_CR3","doi-asserted-by":"crossref","first-page":"224","DOI":"10.3109\/03602532.2012.691099","volume":"44","author":"P Ballard","year":"2012","unstructured":"Ballard, P., Brassil, P., Bui, K.H., Dolgos, H., Petersson, C., Tunek, A., Webborn, P.J.H.: The right compound in the right assay at the right time: an integrated discovery DMPK strategy. Drug Metab. Rev. 44(3), 224\u2013252 (2012)","journal-title":"Drug Metab. Rev."},{"key":"9541_CR4","doi-asserted-by":"crossref","first-page":"27:1","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27:1\u201327:27 (2011). Software available at http:\/\/www.csie.ntu.edu.tw\/cjlin\/libsvm","journal-title":"ACM Trans. Intell. Syst. Technol."},{"issue":"6","key":"9541_CR5","first-page":"419","volume":"13","author":"D Cook","year":"2014","unstructured":"Cook, D., Brown, D., Alexander, R., March, R., Morgan, P., Satterthwaite, G., Pangalos, M.N.: Lessons learned from the fate of AstraZeneca\u2019s drug pipeline: a five-dimensional framework. Nat. Publ. Group 13(6), 419\u2013431 (2014)","journal-title":"Nat. Publ. Group"},{"key":"9541_CR6","doi-asserted-by":"crossref","unstructured":"Costello, J.C., Heiser, L.M., Georgii, E., Nen, M.G.O., Menden, M.P., Wang, N.J., Bansal, M., Ammadud din, M., Hintsanen, P., Khan, S.A., Mpindi, J.P., Kallioniemi, O., Honkela, A., Aittokallio, T., Wennerberg, K., Collins, J.J., Gallahan, D., Singer, D., Saez-Rodriguez, J., Kaski, S., Gray, J.W., Stolovitzky, G.: A community effort to assess and improve drug sensitivity prediction algorithms. Nat. Biotechnol. 32, 1202\u20131212 (2014)","DOI":"10.1038\/nbt.2877"},{"key":"9541_CR7","unstructured":"DiMasi, J.A.: Cost of Developing a New Drug. Tech. Rep. R&D Cost Study Briefing, Tufts Center for the Study of Drug Development, Boston, MA (2014)"},{"issue":"5-6","key":"9541_CR8","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.drudis.2007.01.011","volume":"12","author":"H Eckert","year":"2007","unstructured":"Eckert, H., Bajorath, J.: Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches. Drug Discov. Today 12(5-6), 225\u2013233 (2007)","journal-title":"Drug Discov. Today"},{"key":"9541_CR9","doi-asserted-by":"publisher","unstructured":"Eklund, M., Norinder, U., Boyer, S., Carlsson, L.: The application of conformal prediction to the drug discovery process. Annals of Mathematics and Artificial Intelligence pp. 1\u201316. doi: 10.1007\/s10472-013-9378-2 (2013)","DOI":"10.1007\/s10472-013-9378-2"},{"issue":"1","key":"9541_CR10","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s10472-013-9378-2","volume":"74","author":"M Eklund","year":"2015","unstructured":"Eklund, M., Norinder, U., Boyer, S., Carlsson, L.: The application of conformal prediction to the drug discovery process. Ann. Math. Artif. Intell. 74(1), 117\u2013132 (2015)","journal-title":"Ann. Math. Artif. Intell."},{"issue":"3","key":"9541_CR11","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1021\/ci020346o","volume":"43","author":"JL Faulon","year":"2003","unstructured":"Faulon, J.L., Churchwell, C.J., Visco, D.P.: The Signature Molecular Descriptor. 2. Enumerating Molecules from Their Extended Valence Sequences. J. Chem. Inf. Comput. Sci. 43(3), 721\u2013734 (2003)","journal-title":"J. Chem. Inf. Comput. Sci."},{"issue":"3","key":"9541_CR12","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1021\/ci020345w","volume":"43","author":"JL Faulon","year":"2003","unstructured":"Faulon, J.L., Visco, D.P., Pophale, R.S.: The Signature Molecular Descriptor. 1. Using Extended Valence Sequences in QSAR and QSPR Studies. J. Chem. Inf. Comput. Sci. 43(3), 707\u2013720 (2003)","journal-title":"J. Chem. Inf. Comput. Sci."},{"issue":"Jul","key":"9541_CR13","first-page":"2211","volume":"12","author":"M G\u00f6nen","year":"2011","unstructured":"G\u00f6nen, M.: Alpayd\u0131n, E.: Multiple kernel learning algorithms. J. Mach. Learn. Res. 12(Jul), 2211\u20132268 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"9541_CR14","doi-asserted-by":"publisher","unstructured":"Helal, K.Y., Maciejewski, M., Gregori-Puigjan\u00e9, E., Glick, M., Wassermann, A.M.: Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem\u2019s Bioassay Repository. Journal of Chemical Information and Modeling p. acs.jcim.5b00498. doi: 10.1021\/acs.jcim.5b00498 (2016)","DOI":"10.1021\/acs.jcim.5b00498"},{"key":"9541_CR15","unstructured":"Herper, M.: The Truly Staggering Cost Of Inventing New Drugs. Forbes (2012)"},{"key":"9541_CR16","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.neunet.2014.02.002","volume":"53","author":"M Lapin","year":"2014","unstructured":"Lapin, M., Hein, M., Schiele, B.: Learning using privileged information: SVM+ and weighted SVM. Neural Netw. 53, 95\u2013108 (2014)","journal-title":"Neural Netw."},{"key":"9541_CR17","doi-asserted-by":"crossref","unstructured":"Li, W., Dai, D., Tan, M., Xu, D., Van Gool, L.: Fast algorithms for linear and kernel SVM+ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2258\u20132266 (2016)","DOI":"10.1109\/CVPR.2016.248"},{"key":"9541_CR18","doi-asserted-by":"crossref","unstructured":"Liang, L., Cherkassky, V.: Connection between svm+ and multi-task learning 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), pp. 2048\u20132054. IEEE (2008)","DOI":"10.1109\/IJCNN.2008.4634079"},{"issue":"8","key":"9541_CR19","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1021\/acs.jcim.5b00255","volume":"55","author":"R Liu","year":"2015","unstructured":"Liu, R., Schyman, P., Wallqvist, A.: Critically assessing the predictive power of qsar models for human liver microsomal stability. J. Chem. Inf. Model. 55(8), 1566\u20131575 (2015)","journal-title":"J. Chem. Inf. Model."},{"key":"9541_CR20","doi-asserted-by":"crossref","first-page":"24","DOI":"10.3389\/fenvs.2015.00080","volume":"3","author":"A Mayr","year":"2016","unstructured":"Mayr, A., Klambauer, G., Unterthiner, T., Hochreiter, S.: DeepTox: Toxicity Prediction using Deep Learning. Front. Environ. Sci. 3, 24\u201315 (2016)","journal-title":"Front. Environ. Sci."},{"key":"9541_CR21","doi-asserted-by":"publisher","unstructured":"Pasupa, K., Hussain, Z., Shawe-Taylor, J., Willett, P.: Drug screening with elastic-net multiple kernel learning 13th IEEE International Conference on BioInformatics and BioEngineering, pp 1\u20135 (2013). doi: 10.1109\/BIBE.2013.6701529","DOI":"10.1109\/BIBE.2013.6701529"},{"key":"9541_CR22","doi-asserted-by":"crossref","unstructured":"Paul, S.M., Mytelka, D.S., Dunwiddie, C.T., Persinger, C.C., Munos, B.H., Lindborg, S.R., Schacht, A.L.: How to improve R&D productivity: the pharmaceutical industry\u2019s grand challenge. Nature Reviews Drug Discovery 1\u201312 (2010)","DOI":"10.1038\/nrd3078"},{"key":"9541_CR23","unstructured":"Pechyony, D., Izmailov, R., Vashist, A., Vapnik, V.: Smo-style algorithms for learning using privileged information DMIN, pp. 235\u2013241 (2010)"},{"key":"9541_CR24","doi-asserted-by":"crossref","unstructured":"Pechyony, D., Vapnik, V.: Fast optimization algorithms for solving svm+. Stat. Learning and Data Science 1 (2011)","DOI":"10.1201\/b11429-5"},{"key":"9541_CR25","doi-asserted-by":"crossref","unstructured":"Peck, R.W., Lendrem, D.W., Grant, I., Lendrem, B.C., Isaacs, J.D.: Why is it hard to terminate failing projects in pharmaceutical R&D?. Nature Publishing Group, 1\u20132 (2015)","DOI":"10.1038\/nrd4725"},{"issue":"8","key":"9541_CR26","doi-asserted-by":"publisher","first-page":"1399","DOI":"10.1021\/cb3001028","volume":"7","author":"PM Petrone","year":"2012","unstructured":"Petrone, P.M., Simms, B., Nigsch, F., Lounkine, E., Kutchukian, P., Cornett, A., Deng, Z., Davies, J.W., Jenkins, J.L., Glick, M.: Rethinking molecular similarity: Comparing compounds on the basis of biological activity. ACS Chem. Biol. 7(8), 1399\u20131409 (2012). doi: 10.1021\/cb3001028","journal-title":"ACS Chem. Biol."},{"issue":"11","key":"9541_CR27","doi-asserted-by":"crossref","first-page":"10,140","DOI":"10.1016\/j.eswa.2012.02.142","volume":"39","author":"B Ribeiro","year":"2012","unstructured":"Ribeiro, B., Silva, C., Chen, N., Vieira, A., das Neves, J.C.: Enhanced default risk models with SVM+. Expert Syst. Appl. 39(11), 10,140\u201310,152 (2012)","journal-title":"Expert Syst. Appl."},{"key":"9541_CR28","doi-asserted-by":"publisher","unstructured":"Riniker, S., Wang, Y., Jenkins, J.L., Landrum, G.A.: Using information from historical high-throughput screens to predict active compounds. doi: 10.1021\/ci500190p (2014)","DOI":"10.1021\/ci500190p"},{"issue":"2","key":"9541_CR29","doi-asserted-by":"crossref","first-page":"e0147,215","DOI":"10.1371\/journal.pone.0147215","volume":"11","author":"JW Scannell","year":"2016","unstructured":"Scannell, J.W., Bosley, J.: When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis. PLoS ONE 11(2), e0147,215\u201321 (2016)","journal-title":"PLoS ONE"},{"key":"9541_CR30","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.patrec.2014.01.013","volume":"42","author":"C Serra-Toro","year":"2014","unstructured":"Serra-Toro, C., Traver, V.J., Pla, F.: Exploring some practical issues of SVM+: Is really privileged information that helps Pattern Recogn. Lett. 42, 40\u201346 (2014)","journal-title":"Pattern Recogn. Lett."},{"issue":"2","key":"9541_CR31","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1021\/ci025584y","volume":"43","author":"C Steinbeck","year":"2003","unstructured":"Steinbeck, C., Han, Y., Kuhn, S., Horlacher, O., Luttmann, E., Willighagen, E.: The chemistry development kit (cdk) an open-source java library for chemo- and bioinformatics. J. Chem. Inf. Comput. Sci. 43(2), 493\u2013500 (2003). doi: 10.1021\/ci025584y PMID: 12653513","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"9541_CR32","doi-asserted-by":"crossref","unstructured":"Vapnik, V.: Learning Using Privileged Information: Similarity Control and Knowledge Transfer (2015)","DOI":"10.1007\/978-3-319-17091-6_1"},{"issue":"5","key":"9541_CR33","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1016\/j.neunet.2009.06.042","volume":"22","author":"V Vapnik","year":"2009","unstructured":"Vapnik, V., Vashist, A.: A new learning paradigm: Learning using privileged information. Neural Netw. 22(5), 544\u2013557 (2009)","journal-title":"Neural Netw."},{"key":"9541_CR34","volume-title":"Algorithmic learning in a random world","author":"V Vovk","year":"2005","unstructured":"Vovk, V., Shafer, G., Gammerman, A.: Algorithmic learning in a random world. Springer, New York (2005)"},{"key":"9541_CR35","doi-asserted-by":"crossref","unstructured":"Wang, Z., Ji, Q.: Classifier learning with hidden information Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 4969\u20134977 (2015)","DOI":"10.1109\/CVPR.2015.7299131"},{"issue":"7","key":"9541_CR36","first-page":"475","volume":"14","author":"MJ Waring","year":"2015","unstructured":"Waring, M.J., Arrowsmith, J., Leach, A.R., Leeson, P.D., Mandrell, S., Owen, R.M., Pairaudeau, G., Pennie, W.D., Pickett, S.D., Wang, J., Wallace, O., Weir, A.: An analysis of the attrition of drug candidates from four major pharmaceutical companies. Nat. Publ. Group 14(7), 475\u2013486 (2015)","journal-title":"Nat. Publ. Group"},{"key":"9541_CR37","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1111\/j.1469-1809.1955.tb01348.x","volume":"19","author":"B Woolf","year":"1955","unstructured":"Woolf, B.: On estimating the relation between blood group and disease. Ann. Human Genet. 19, 251\u2013253 (1955)","journal-title":"Ann. Human Genet."},{"key":"9541_CR38","unstructured":"Xu, X., Zhou, J.T., Tsang, I., Qin, Z., Goh, R.S.M., Liu, Y.: Simple and efficient learning using privileged information BeyondLabeler: Human is More Than a Labeler. Workshop of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York City, USA. arXiv: 1604.01518 (2016)"},{"key":"9541_CR39","doi-asserted-by":"crossref","unstructured":"Yau, E., Petersson, C., Dolgos, H., Peters, S.A.: A comparative evaluation of models to predict human intestinal metabolism from nonclinical data. Biopharmaceutics & Drug Disposition (2017)","DOI":"10.1002\/bdd.2068"}],"container-title":["Annals of Mathematics and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10472-017-9541-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10472-017-9541-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10472-017-9541-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T02:15:59Z","timestamp":1750126559000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10472-017-9541-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,18]]},"references-count":39,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2017,10]]}},"alternative-id":["9541"],"URL":"https:\/\/doi.org\/10.1007\/s10472-017-9541-2","relation":{},"ISSN":["1012-2443","1573-7470"],"issn-type":[{"type":"print","value":"1012-2443"},{"type":"electronic","value":"1573-7470"}],"subject":[],"published":{"date-parts":[[2017,3,18]]}}}