Software transplantation generates new piece of software by reusing existing parts from a given piece of software (i.e., host) to enhance other parts of a same software or different software (i.e., donor). To date, its use has been proved beneficial for traditional software systems. In this paper, we argue that software transplantation can be used for automatically producing video game procedural content. We assessed the feasibility of our idea by realising the first search-based algorithm for procedural content transplantation and empirically evaluating it in an industrial case study in collaboration with the developers of the commercial video game Kromaia. Specifically, our proposed approach, dubbed IMHOTEP, enables developers to choose what video-game content to transplant and where, and automatically searches for an appropriate solution to integrate the organ into the host. Such a search is performed by using an evolutionary algorithm guided by a simulation-based fitness function, which is novel w.r.t previous transplantation work generally guided by test-suite compliance. We empirically evaluate the effectiveness of IMHOTEP to transplant procedural content, specifically non-playable characters, for the commercial video game Kromaia and benchmarked it against a state-of-the-art approach in search-based procedural content generation, as well as a variant of IMHOTEP itself guided by a test-suite-based fitness function. We found that using IMHOTEP, Kromaia developers were able to transplant 129 distinct organs taken from the game’s scenarios into five different hosts, thus generating a total of 645 new transplanted non-playable characters for this game. Moreover, we found that the game content generated by using IMHOTEP was 1.5 times superior than the one obtained by using its test-suite-based variant, and 2.5 times superior than the one generated by the state-of-the-art benchmark. Furthermore, the transplants generated by IMHOTEP have also unveiled organ interactions that had not been previously identified in the literature. Finally, a focus group with game developers indicated their satisfaction with the content generated by IMHOTEP and willingness to use it in their game development activity. The positive results obtained by IMHOTEP, prove the viability of Procedural Content Transplantation and open up new research avenues for automated video-game content generation as well as for software transplantation.