For embedded systems as well as for biological cell systems, design is a feature that defines their identity. The assembly of different components in designs of both systems can vary widely. Given the similarities between computers and cellular systems, methods and models of computation from the domain of computer systems engineering might be applied to modeling cellular systems. Our aim is to construct a framework that focuses on understanding the design options and consequences within a cell, taking an in silico (forward-) engineering approach rather than a reverse engineering approach that is used in this domain as a default now. We take our ideas from the domain of embedded computer systems. The most important features of our approach, as taken from this domain, are a variable abstraction level of components that allows for addition of components when detailed information is lacking, and a separation of concerns between function and performance by components in the design. This allows for efficient and flexible modeling. Also, there is a strict separation between computation within- and communication between components, reducing complexity. As a proof of principle, we show that we can make a statement regarding the design of the gene expression machinery of the cell to produce a protein, using such a method