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Abstract

This article addresses the problem of restricted access to industry-sponsored clinical trial data. In particular, it analyzes the intersection of the competing claims that mandatory disclosure of pharmaceutical test data impedes drug sponsors' innovation incentives and that access facilitates new drug development. These claims are characterized in terms of public-good and common-resource dilemmas. The analysis finds confidentiality protection ofprimary research data plays an ambiguous role. While secrecy, as such, does not solve the public-good problem in pharmaceutical innovation (in the presence of regulatory instruments that protect the originator drug against generic competition), it is likely to exacerbate the common- resource problem, in view ofdata as a source ofscientific knowledge. It is argued that the claim by the research-based industry that disclosure of clinical data impedes innovation incentives is misplaced and should not be leveraged against pro-access policies. While much attention has been paid to the problem ofappropriability ofdrug R&D investment, this analysis highlights another consequence resulting from the private provision of clinical trials, i.e., factual confidentiality and possession of data by drug sponsors. The associated social costs are qualified in terms of internalized knowledge externalities. Since, in a competitive environment, companies are unlikely to change the strategy of non-sharing of primary data, the resulting economic inefficiencies at the sector level call for regulatory intervention. To reconcile the competing policy objectives, it is proposed that the rules ofaccess should be designed in such a way that third-party use of primary data does not interfere with protection against generic competition. At the same time, the long-term collective benefit can be maximized when the "cooperative choice" (i.e., when everyone shares data) becomes the "dominant strategy." This can be achieved only when access is not subject to the authorization of the initial trial sponsors, and when primary data is aggregated, refined, and managed on the collective basis.