Welcome to the community. I do not understand your situation, but here are my thoughts/questions:
Are you interested in understanding causal structure our are you trying to "pick a winner"?
I'm a bit confused, are the 2 Molecule Category factors independent? Are both going to be part of the final product, or are you choosing between A & B? Do you care about a possible interaction between A & B? Or are these part of a mixture (in which case you might want to use a mixture design)?
What model are you investigating?
One interpretation: You have 3 factors, X1 is Molecule Category with 2 levels, A&B (Am I correct in assuming factor 1 is a categorical factor?). X2 is Candidate (can't tell if this is categorical or continuous), this may be nested? X3 is Concentration whose levels depend on levels of X1 and is continuous (this is definitely nested). With nesting, you can determine the effects of each factor, but not interaction effects.
Y = X1 + X2[X1] + X3[X1, X2]
Another interpretation: You have 2 factors, X1 is molecule category and it has 4 levels. X2 is continuous and X2 levels depend on X1 so it is nested.
Y = X1 + X2[X1]
Another, If molecule category is independent:
Y = X1 + X2 + X1X2 + X3 [X1, X3]
"All models are wrong, some are useful" G.E.P. Box