title: Pattern Recognition in Pharmacodynamic Data Analysis.
abstract: Pattern recognition is a key element in pharmacodynamic analyses as a first step to identify drug action and selection of a pharmacodynamic model. The essence of this process is going from data to insight through exploratory data analysis. There are few formal strategies that scientists typically use when the experiment has been done and data collected. This report attempts to ameliorate this deficit by identifying the properties of a pharmacodynamic model via dissection of the pattern revealed in response-time data. Pattern recognition in pharmacodynamic analyses contrasts with pharmacokinetic analyses with respect to time course. Thus, the time course of drug in plasma usually differs markedly from the time course of the biomarker response, as a consequence of a myriad of interactions (transport to biophase, binding to target, activation of target and downstream mediators, physiological response, cascade and amplification of biosignals, homeostatic feedback) between the events of exposure to test compound and the occurrence of the biomarker response. Homing in on this important-but less often addressed-element, 20 datasets of varying complexity were analyzed, and from this, we summarize a set of points to consider, specifically addressing baseline behavior, number of phases in the response-time course, time delays between concentration- and response-time courses, peak shifts in response with increasing doses, saturation, and other potential nonlinearities. These strategies will hopefully give a better understanding of the complete pharmacodynamic response-time profile.
authors.affiliation: Division of Pharmacology and Toxicology, Department of Biomedical Sciences and Veterinary Public Health, SLU, Box 7028, SE-750 07, Uppsala, Sweden. Johan.Gabrielsson@slu.se.
authors.forename: Johan
authors.identifier: http://orcid.org/0000-0001-7270-2106
authors.initials: J
authors.lastname: Gabrielsson
authors.affiliation: Department of Molecular and Clinical Medicine, Institute of Medicine, The Sahlgrenska Academy at Gothenburg University, SE-413 45, Gothenburg, Sweden.|PharmaLot Consulting AB, V. Bäckvägen 21B, SE-434 92, Vallda, Sweden.
authors.forename: Stephan
authors.initials: S
authors.lastname: Hjorth
mesh_terms: D000818:Animals; D015415:Biomarkers; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D006801:Humans; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D010599:Pharmacokinetics; D012107:Research Design
chemical_list: D015415:Biomarkers
keywords: duration of response; exploratory data analysis; intensity of response; mixture dynamics; modeling; onset of action; oscillatory response; physiological limit; response half-life; response-time courses; saturation; transduction; turnover