How to add proper nouns as vocab to Spacy models?
I'm not sure exactly what you want to do... but below are solutions for a few possibilities.

You have a complete list of the medicines/drugs of interest...
i. and you want a special rule for tokenisation of these strings: Would not recommend this approach but in principle you could add special cases to the Tokenizer.
ii. and you simply want to find them: Then you should use a Matcher to find them efficiently after you've created the Doc. Then you can do what you want with the spans that you find. Make them pronouns if you want.
You don't have a complete list of the medicines/drugs of interest...
i. but you want to generally identify them: Then you'll need to train an NER model to recognize them. To generate the training data you could take a whole bunch of papers and use a Matcher looking for known medicines/drugs to grab a whole bunch of example sentences. Then you train...

Later edit: To be clear, the Vocab only stores strings and assigns them a unique ID for working with under the hood. It's the Tagger which decides whether it's a PRON or not.
I am using Spacy 1.8.0 with Python and I would like to use Spacy to do analysis on Medical Documents. There is a way off adding new entity types to spacy's named entity recognizer. However, is it possible to add the names of medicines/drugs as proper nouns to spcay's vocab? Or do they need to be added by training the spacy NER? 
Thanks