title: Modeling analgesic drug interactions using support vector regression: a new approach to isobolographic analysis.
abstract: BACKGROUND
  Modeling drug interactions is important for illustrating combined drug actions and for predicting the pharmacological and/or toxicological effects that can be obtained using combined drug therapy.
  
  
  OBJECTIVE
  In this study, we propose a new and universal support vector regression (SVR)-based method for the analysis of drug interactions that significantly accelerates the isobolographic analysis.
  
  
  METHODS
  Using SVR, a theoretical model of the dose-effect relationship was built to simulate various dose ratios of two drugs. Using the model could then rapidly determine the combinations of doses that elicited equivalent effects compared with each drug used alone.
  
  
  RESULTS
  The model that was built can be used for any level of drug effect and can generate classical isobolograms to determine the nature of drug interactions (additivity, subadditivity or synergy), which is of particular importance in the case of novel compounds endowed with a high biological activity for which the mechanism of action is unknown. In addition, this method is an interesting alternative allowing for a meaningful reduction in the number of animals used for in vivo studies.
  
  
  CONCLUSIONS
  In a mouse model of toxic peripheral neuropathy induced by a single intraperitoneal dose of oxaliplatin, the usefulness of this SVR method for modeling dose-effect relationships was confirmed. This method may also be applicable during preliminary investigations regarding the mechanism of action of novel compounds.
authors.affiliation: Faculty of Production Engineering, Warsaw University of Life Sciences, Nowoursynowska 164, 02-787 Warsaw, Poland.
authors.forename: Robert
authors.initials: R
authors.lastname: Sałat
authors.affiliation: Department of Pharmacodynamics, Chair of Pharmacodynamics, Jagiellonian University, Medical College, Medyczna 9, 30-688 Cracow, Poland. Electronic address: salat.kinga@gmail.com.
authors.forename: Kinga
authors.initials: K
authors.lastname: Sałat
mesh_terms: D000700:Analgesics / Q000494:pharmacology*; D000818:Animals; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D007274:Injections, Intraperitoneal; D008297:Male; D051379:Mice; D009944:Organoplatinum Compounds / Q000008:administration & dosage / Q000494:pharmacology; D000077150:Oxaliplatin; D010523:Peripheral Nervous System Diseases / Q000139:chemically induced; D060388:Support Vector Machine
chemical_list: D000700:Analgesics; D009944:Organoplatinum Compounds; D000077150:Oxaliplatin
keywords: Combined drug therapy; Dihydrofuran-2-one; Isobolographic analysis; Oxaliplatin (PubChem CID: 5310940); Oxaliplatin-induced neuropathy; Pregabalin; Pregabalin (PubChem CID: 5486971); Support vector regression