I disagree there - peer review as a system isn't designed to catch fraud at all, it's designed to ensure that studies that get published meet a minimum standard for competence. Reviewers aren't asked to look for fake data, and in most cases aren't trained to spot it either.
Whether we need to create a new system that is designed to catch fraud prior to publication is a whole different question.
Whether we need to create a new system that is designed to catch fraud prior to publication is a whole different question
That system already exists. It's what replication studies are for. Whether we desperately need to massively bolster the amount of replication studies done is the question, and the answer is 'yes'.
We could award a certain percentage of grants and grad students should be able to get degrees doing replication studies. Unfortunately everyone is chasing total paper count and impact factor rankings and shit.
Yeah, reviewing is about making sure the methods are sound and the conclusions are supported by the data. Whether or not the data are correct is largely something that the reviewer cannot determine.
If a machine spits out a reading of 5.3, but the paper says 6.2, the reviewer can't catch that. If numbers are too perfect, you might be suspicious of it, but it's really not your job to go all forensic accountant on the data.
You're conflating peer review and studies that verify results. The problem is that verifying someone else's results isn't sexy, doesn't get you grant money, and doesn't further your career. Redoing the work and verifying the results of other "pioneers" is important, but thankless work. Until we insensitivise doing the boring science by funding all fundamental science research more, this kind of problem will only get worse.