In this paper an adjoint-based algorithm for parameter identification problems in systems of ordinary differential equations (ODEs) is presented. This is done by solving a minimization problem in which the cost function is defined in order to quantify the mismatch between the observed data and the numerical solution of the ODEs. Most of existing local minimizers need the derivatives of both the cost function and the constraints that are usually calculated by finite-difference formulas. In this paper we show how they can be computed much more efficiently and accurately by the so-called adjoint method. We apply this method to the problem of estimating a set of unknown parameters appearing in chemical reaction models. Numerical results showing the efficiency of the adjoint method are included. (C) 2017 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.