Cycling is crucial for sustainable urban transportation. Promoting cycling critically relies on sufficiently developed infrastructure; however, designing efficient bike path networks constitutes a complex problem that requires balancing multiple constraints. Here we propose a framework for generating efficient bike path networks, explicitly taking into account cyclists’ demand distribution and route choices based on safety preferences. By reversing the network formation, we iteratively remove bike paths from an initially complete bike path network and continually update cyclists’ route choices to create a sequence of networks adapted to the cycling demand. We illustrate the applicability of this demand-driven approach for two cities. A comparison of the resulting bike path networks with those created for homogenized demand enables us to quantify the importance of the demand distribution for network planning. The proposed framework may thus enable quantitative evaluation of the structure of current and planned cycling networks, and support the demand-driven design of efficient infrastructures.