Prediction of drug intestinal absorption by new linear and non-linear QSPR

Alan Talevi, Mohammad Goodarzi, Erlinda V. Ortiz, Pablo R. Duchowicz, Carolina L. Bellera, Guido Pesce, Eduardo A. Castro, Luis E. Bruno-Blanch

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


In order to minimize the high attrition rate that usually characterizes drug research and development projects, current medicinal chemists aim to characterize both pharmacological and ADME profiles at the beginning of drug R&D initiatives. Thus, the development of ADME High-Throughput Screening in vitro and in silico ADME models has become an important growing research area. Here we present new linear and non-linear predictive QSPR models to predict the human intestinal absorption rate, which are derived from a medium sized, balanced and diverse training set of organic compounds. The structure-property relationships so obtained involve only 4 molecular descriptors, and display an excellent ratio of number of cases to number of descriptors. Their adjustment of the training set data together with the performance achieved during the internal and external validation procedures are comparable to previously reported modeling efforts.

Original languageEnglish (US)
Pages (from-to)218-228
Number of pages11
JournalEuropean Journal of Medicinal Chemistry
Issue number1
StatePublished - Jan 2011


  • ADME properties
  • Drug intestinal absorption
  • Model's applicability domain
  • Molecular descriptors
  • QSPR theory
  • Replacement method

ASJC Scopus subject areas

  • Pharmacology
  • Drug Discovery
  • Organic Chemistry


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