In recent years, quantum computing has emerged as a promising platform for simulating strongly correlated systems in chemistry, for which the standard quantum chemistry methods are either qualitatively inaccurate or too expensive. However, due to the hardware limitations of the available noisy near-term quantum devices, their application is currently limited only to small chemical systems. One way for extending the range of applicability can be achieved by means of hybrid classical-quantum embedding approaches, multiple of which have been put forward all with different tradeoffs. In this talk, I will present a projection-based embedding method for combining the variational quantum eigensolver (VQE) algorithm, although not limited to, with density functional theory (DFT). The developed VQE-in-DFT method was recently implemented in Qiskit and used to compute the triple bond breaking process in butyronitrile on an IBM quantum device. Our results show that the developed method is a promising approach for simulating systems with a strongly correlated fragment on a quantum computer. This development as well as its future extensions will benefit many different chemical areas including the computer aided drug design as well as the study of metalloenzymes with strongly correlated components.