title: Dose-response analysis in the joint action of two effectors. A new approach to simulation, identification and modelling of some basic interactions.
abstract: In systems with several effectors, the results of dose-response (DR) experiments are usually assessed by checking them against two hypotheses: independent action (IA) and concentration addition (CA). Both are useful simplifications, but do not represent the only possible responses, and avoid to a large extent the analysis of the interactions that are possible in the system. In addition, these are often applied in such a way that they produce insufficient descriptions of the problem that raises them, frequent inconclusive cases and doubtful decisions. In this work a generative approach is attempted, starting from some simple mechanisms necessarily underlying the response of an elementary biological entity to an effector agent. A set of simulations is formulated next through an equally simple system of logical rules, and several families of virtual responses are thus generated. These families include typical responses of IA and CA modes of action, other ones not less probable from a physiological point of view, and even other derived from common and expectable forms of interactions. The analysis of these responses enabled, firstly, to relate some phenomenological regularities with some general mechanistic principles, and to detect several causes by which the IA-CA dualism is necessarily ambiguous. Secondly, it allowed identifying different forms of synergy and antagonism that contribute to explain some controversial aspects of these notions. Finally, it led to propose two sets of explicit algebraic equations that describe accurately a wide diversity of possible and realistic responses.
authors: Instituto de Investigacións Mariñas (IIM-CSIC), Galicia, Spain.
authors: Miguel Anxo
authors: MA
authors: Murado García
authors: Miguel Ángel
authors: MÁ
authors: Prieto Lage
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D008954:Models, Biological
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