Interior point methods have recently become an interesting alternative in a number of numerical applications. In particular, their performance in the solution of problems involving complementarity equations has been the subject of extensive research and their efficacy is well documented. In this paper, following a brief description of the fundamentals of interior point methods and the globally convergent framework proposed by Wang et al. (Mathematical Programming 74 (1996) 159), we show how we can apply such an algorithm for solving the complementarity representation of a conditional model (Industrial Engineering and Chemical Research 38 (1999) 519), where such models involve sums of complementary products being zero. Furthermore, we modified Wang's algorithm in order to apply a high order strategy designed to improve convergence (SIAM Journal of Optimization 2 (1992) 575). We then use the proposed approach to solve some conditional models encountered in the field of chemical engineering. This technique has been incorporated into the ASCEND modeling environment with the implementation of the solver IPSLV.