title: Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.
abstract: BACKGROUND
  Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches.
  
  
  METHODS
  Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds.
  
  
  RESULTS
  Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively.
  
  
  CONCLUSIONS
  Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development.
authors.affiliation: Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow, 226028, Uttar Pradesh. India.
authors.forename: Rajnish
authors.initials: R
authors.lastname: Kumar
authors.affiliation: Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow, 226028, Uttar Pradesh. India.
authors.forename: Anju
authors.initials: A
authors.lastname: Sharma
authors.affiliation: Department of Bioengineering, Integral University, Dasauli, P.O. Basha, Kursi Road, Lucknow, Uttar Pradesh. India.
authors.forename: Mohammed Haris
authors.initials: MH
authors.lastname: Siddiqui
authors.affiliation: Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow, 226028, Uttar Pradesh. India.
authors.forename: Rajesh Kumar
authors.initials: RK
authors.lastname: Tiwari
mesh_terms: D001185:Artificial Intelligence; D015195:Drug Design; D006801:Humans; D007408:Intestinal Absorption; D016018:Least-Squares Analysis; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000378:metabolism
chemical_list: D004364:Pharmaceutical Preparations
keywords: Absorption; artificial intelligence; drug; pharmacokinetics; prediction