Intermodal journey planning (IJP) provides travel itineraries for personal journeys combining several modes of transportation such as public transport (bus, train, boat, airplane) and private transport (car, bicycle, walking). Each mode permits travels within a defined transportation network and a journey may traverse several networks at transition points. Travel time, travel cost, and number of transits are important criteria. In a real-world setting a transportation network is frequently subject to real-time events that affect which journey is optimal at a given time. We propose a system for optimized IJP able to handle large transportation networks while immediately taking real-time information into consideration. The requirement for fast response while handling real-time events makes it hard to utilize popular speed-up techniques relying on pre-processing of the networks. We present the main challenges relating to this approach, how they are modelled, algorithms applicable for the model, and preliminary computational results.