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Leru asks October’s UN biodiversity meeting not to throw obstacles in front of researchers
Ahead of a major UN meeting on biodiversity, a group of European research universities has repeated its call for genetic data to be shared openly through a globally agreed system, rather than be subject to a plethora of national restrictions.
Countries will discuss access to genetics data at the meeting in Kunming, China, from 11-15 October. The League of European Research Universities, which represents 23 institutions, said on 27 September that governments at the meeting must agree a simplified, universal system for sharing genetic data.
Leru said national leaders should not decide that genetic data fall under the scope of the existing legal frameworks of the Nagoya Protocol, a supplementary agreement to the UN Convention on Biological Diversity that is intended to ensure fair and equitable sharing of the benefits arising from the use of genetic resources.
Under the protocol, signatory governments are able to set different requirements for the ways in which the genetic resources of their country are used. But Leru said the protocol is “impractical”, and that most of the concerns it expressed in 2018 about accessing genetic data under the protocol remain valid today.
“One of the key problems that universities face complying with the Nagoya Protocol is the complexity of dealing with differing national legislations, and the enormous amount of time and the transaction costs required to carry out bilateral negotiations,” the group said in its new statement.
Among the issues that Leru says need fixing is the fuzzy definition of which data fall under the scope of so-called digital sequence information that could be governed by the protocol. It wants a “globally accepted, legally binding definition” of DSI and open access to such data.
The group added that conditions around access to genetic data should be reserved for commercial uses, and warned that too much red tape could prevent poorer countries from building their capacity to work with pooled data.