There are indeed many good arguments for unrestricted and easy access to full RCT data. Yet, simply uploading all trial data on a website would entail its own problems.
First among those is the issue of personal data protection or patient
confidentiality, a concept that is very different from commercial
confidentiality. There is a small risk that personal data could inadvertently be publicized. There is also a small risk that an individual patient could be identified from an anonymized dataset, for example, from trials in ultra-rare diseases. Achieving an adequate standard of personal data protection is not an insurmountable obstacle, though, and proposals for best practice for publishing raw data are available 
. However, implementation is not straightforward, standards will need to be agreed upon up front, and data redaction may in a few cases be resource intensive.
Our second caveat is likely more contentious. We do not dispute that financial conflicts of interests (CoIs) may render analyses and conclusions “vulnerable to distortion” 
. However, surrounding the ongoing debate over sponsor-independent analyses is an implicit assumption that “analysis by independent groups” is somehow free from CoIs. We beg to differ. Personal advancement in academia, confirmation of previously defended positions, or simply raising one's own visibility within the scientific community may be powerful motivators. In a publish-or-perish environment, would the finding of an important adverse or favorable drug effect at the p
<0.05-level be more helpful to a researcher than not
finding any new effects? Will society always be guaranteed that a finding that is reported as “confirmatory” was not the result of multiple exploratory re-runs of a dataset? We submit that analyses by sponsor-independent scientists are not generated in a CoI-free zone and, more often than not, ego trumps money. Independent analyses may therefore also be “vulnerable to distortion”. We are concerned that unrestricted availability of full datasets may in some cases facilitate the publication of papers containing misleading results, which in turn lead to urgent calls for regulatory action. In a worst case, this would give rise to unfounded health scares with negative public health consequences such as patients refusing vaccinations or discontinuing drug treatment 
Aside from CoIs, independent analysis per se is no guarantee of high quality. The regulatory community has been confronted with meta-analyses that were later contradicted by additional evidence 
or found to be flawed 
. We argue that independent analyses warrant a similar level of scrutiny as sponsor-conducted analyses do.
Finally, re-analysis of trial data could be misused for competitive purposes.