Applications of Genetic Programming in Drug Discovery and Pharmacokinetics

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Vanneschi:2013:NICSO,
  author =       "Leonardo Vanneschi",
  title =        "Applications of Genetic Programming in Drug Discovery
                 and Pharmacokinetics",
  booktitle =    "VI International Workshop on Nature Inspired
                 Cooperative Strategies for Optimization (NICSO 2013)",
  year =         "2013",
  editor =       "German Terrazas and Fernando Esteban Barril Otero and 
                 Antonio D. Masegosa",
  volume =       "512",
  series =       "Studies in Computational Intelligence",
  pages =        "x",
  address =      "Canterbury, United Kingdom",
  month =        sep # " 2-4",
  publisher =    "Springer",
  note =         "Plenary Talk",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-01691-7",
  DOI =          "doi:10.1007/978-3-319-01692-4",
  size =         "0.5 pages",
  abstract =     "The success of a drug treatment is strongly correlated
                 with the ability of a molecule to reach its target in
                 the patient's organism without inducing toxic effects.
                 Moreover the reduction of cost and time associated with
                 drug discovery and development is becoming a crucial
                 requirement for pharmaceutical industry. Therefore
                 computational methods allowing reliable predictions of
                 newly synthesised compounds properties are of utmost
                 relevance. In this talk, I discuss the role of Genetic
                 Programming (GP) in predictive pharmacokinetics,
                 considering the estimation of adsorption, distribution,
                 metabolism, excretion and toxicity processes (ADMET)
                 that a drug undergoes into the patient's organism. In
                 particular, I discuss the ability of GP to predict oral
                 bioavailability (F), median oral lethal dose (LD50) and
                 plasma-protein binding levels (PPB). Since these
                 parameters respectively characterise the percentage of
                 initial drug dose that effectively reaches the systemic
                 blood circulation, the harmful effects and the
                 distribution into the organism of a drug, they are
                 essential for the selection of potentially effective
                 molecules. In the last part of the talk, I show and
                 discuss how recently defined geometric semantic genetic
                 operators can dramatically affect the performances of
                 GP for this kind of application, in particular on
                 out-of-sample test data.",
  notes =        "Only abstract in proceedings. See also
                 \cite{Freitas:2013:NICSO}
                 http://www.nicso2013.org/programme.html

                 http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-319-01691-7",
}

Genetic Programming entries for Leonardo Vanneschi

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