Non Bio problems/solutions applied to bio problems/solutions also has a long history, though seldom acknowledged.

The focal range a lens is limited to a narrow range, but users need to modify the focal range to the distance from some target (the non bio problem) the lenses were ground to change their curvature ( the non bio solution). Poor human eyesight from a poor focal length (the bio problem) is corrected by surgical lasers changing the eye lens curvature to a target distance (the bio solution).

A more recent example is in programming computers. Run time errors in constantly running systems that could not be stopped for maintenance, (the non bio problem) a programming patch was run to replace a block of code at a specified location in computer memory, correcting the errors with the next tick of the system clock (non bio solution).

Genetic errors in living systems (the bio problem) are corrected by an engineered virus that overlays the DNA code at a specific location, eliminating the genetic errors with the next reproduction cycle (the bio solution).

What is the value of this approach? It allows a more structured analysis of the metaphors that link the problem/solution pairs and that rigorous analysis will lead to other novel solutions that would not otherwise be immediately apparent.

Here is an example.  Until recently, automated manufacturing controllers of cutting heads were processed data stored on mylar tape.  The mechanical reader of the tape detected the holes punched in the tape, reading the operation type, set up the operation and executed the corresponding instruction to move the cutter up/down, start the cutter, move to a point, change the speed, add lubricant …  The mylar tapes were limited in length, so when when the end of tape was signaled by end of record code, the tape reading operation was paused and waited for a new tape to be loaded.  Errors in reading or execution of an instruction were first handled by a robust automated error handling/recovery because the cost of invoking external human intervention was very costly however the cost of damaging a partially completed part was also high because it represented not only the cost of the raw materials, but the time and energy used by the manufacturing system up to the point at which the error occurred.  The number of error correction actions the controller could in response to the flagging of an error were limited by the controller.  The controllers were adaptive, adjusting instructions to avoid damage to the machines/parts.  This was sometimes referred to as artificial intelligence, but the controllers did not have insights to other controllers or the error rates on other parts.  The range of errors that could be handled and the variety of corrective actions were greatly extended when the controllers were networked to a larger and more robust computing system that could coordinate the data from many controllers for improved decision making.  This allowed defective machines/parts to be identified earlier lowering cost and reducing unproductive time.  The addition of an large and more robust external computing system that allowed better and more timely correction to errors.

DNA/RNA functions in the fabrication of proteins are driven by reading the genetic instructions to assemble the proteins and what signals to raise in response to errors.  If the signals could be detected by a computer system a more targeted and immediate response could be inserted.  This might provide a novel intervention to tumor growth.   This is analogous to allowing networking to a larger computing system to reduce costs..