I fear this entire thread is going to veer dangerously close to opinionation. But regardless of how one feels about the Perl language and its various libraries and communities, I think we can objectively say that the era of Perl's dominance in the bioinformatics community has passed. A lot of tools and libraries implemented in Perl are still widely used, and there is a tremendous amount of legacy Perl code around. The ability to read and write Perl remains a valuable skill.
But in 2019, few people (with a choice) are learning Perl or implementing new tools and frameworks in Perl. Python fits snuggly into the niche once occupied by Perl, and its native OO support is (I dare to say) objectively superior to any post hoc OO support Perl 3rd-party libraries provide.
The broader web/tech community moved on from Perl to Python (and Ruby and others) even before the bioinformatics community did, and this broader community's offerings (IPython, Jupyter, scipy, numpy, pytest, etc.) make Python an even more attractive alternative to Perl for bioinformatics work.
In the meantime, the "hadleyverse" ecosystem of R packages for data manipulation make R much more capable of the types of data pre-processing tasks for which an R programmer might have previously used a language like Perl or Python.
In short, Perl is waning in popularity (if not relevance), and I would not expect much enthusiasm from the bioinformatics community for a new framework built around a relatively obscure Perl extension.