Inferring biochemical reaction pathways: the case of the gemcitabine pharmacokinetics

The method of network inference presented in this paper is inspired by the theory of time-lagged correlation inference with regard to the deduction of the interaction network, and on a maximum likelihood approach with regard to the estimation of the kinetic parameters of the network. Both network inference and parameter estimation have been designed specifically to identify systems of biotransformations, at the biochemical level, from noisy time-resolved experimental data. We use our inference method to deduce the metabolic pathway of the gemcitabine. The inputs to our inference algorithm are the experimental time series of the concentration of gemcitabine and its metabolites. The output is the set of reactions of the metabolic network of the gemcitabine.Time-lagged correlation based inference pairs up to a probabilistic model of parameter inference from metabolites time series allows the identification of the microscopic pharmacokinetics and pharmacodynamics of a drug with a minimal a priori knowledge. In fact, the inference model presented in this paper is completely unsupervised. It takes as input the time series of the concetrations of the parent drug and its metabolites. The method, applied to the case study of the gemcitabine pharmacokinetics, shows good accuracy and sensitivity.Drug metabolism is a process by which pharmaceutical substances undergo biochemical modification in living organisms. Such modifications may lead to the generation of an active drug from an inactive precursor or in other cases lead to the generation of an inactive compound from an active substance, aiding in detoxication. This process is performed by a network of biochemical reactions that modify the pharmaceutical substances. The mechanisms of action of a drug refer to the specific biochemical, chemical, or physical interactions through which a drug substance exerts its pharmacological effect. The biochemical transformations of a drug form part of the pharmacokinetic pathway, whereas