Two years after countries agreed that companies using genetic data from plants, animals and microorganisms should help fund nature conservation, contributions to the United Nations-backed Potash Fund have reached only US$10,588. Just five companies have donated so far, despite earlier estimates that the mechanism could raise about $1 billion a year.
The fund was established in 2024 after years of negotiations over how to share the benefits of “digital sequence information” used to develop medicines, cosmetics, genetically modified crops and other products. The debate intensified because low-resource countries with rich biodiversity but relatively few biotechnology companies argued that wealthy nations and companies were committing “biopiracy” by using publicly available genetic data collected from wildlife without providing compensation.
“No one expected the amount actually raised to be so small,” says Amber Scholz, a microbiologist at the Leibniz Institute DSMZ in Braunschweig, Germany, who was involved in negotiations over the fund. “Too bad. There’s no way to bring this to the surface.”
The Potash Fund is intended to distribute corporate contributions to global conservation projects. Its creation was hailed as a breakthrough in efforts to ensure that countries providing genetic resources share in the benefits generated from them. For example, a gene from one plant might be inserted into another to make it more drought tolerant.
Limited corporate participation
“In other fields, if you use a resource, you are expected to pay for it,” says James Finnigan, technical director at Prozomix, a small biotechnology company in Haltwhistle, UK. Prozomix has pledged to donate 0.1% of its future profits to the fund and has made a $5,000 deposit—the largest contribution from a company so far.
“It’s part of putting something back into the biodiversity that we all use,” Finnigan says.
Prozomix is one of only five companies to have contributed to the fund. The lack of participation was discussed at COP17, the latest UN biodiversity summit, which concluded last week in Yerevan, Armenia. During the two-week meeting, countries reviewed progress towards stopping biodiversity loss driven by climate change and humanity’s expanding environmental footprint. They remain far from the goal of mobilizing $200 billion a year for biodiversity conservation by 2030.
In theory, the fund could become a significant source of new conservation finance. More than 20,000 companies worldwide that use publicly available genetic information are considered large enough to contribute, according to a June report by Agata Makowska-Curran, an economist at the London School of Economics and Political Science.1 Companies with annual revenues of at least $50 million, for example, are considered sufficiently large.
Makowska-Curran’s analysis found that the fund could raise as much as $3.6 billion annually if all eligible companies contributed 0.1% of their revenue or 1% of their profits, as the United Nations encourages. Because contributions are discretionary, however, she suggested that a more realistic estimate would be about $1 billion a year.
Genetic data and artificial intelligence
Biodiversity advocates are urging companies to contribute in proportion to their use of genetic resources. COP17 also examined the growing use of such data to train artificial-intelligence models for biological research.
The New York-based advocacy group Common Initiatives highlighted the rapid growth of AI biology companies such as London’s Isomorphic Labs in a position paper posted online. In May, Isomorphic raised more than $2 billion in an investment round to develop drugs using AlphaFold, a protein-folding model trained with public genetic resources.
“Public facilities are subsidizing a private gold rush,” the paper said. Isomorphic did not respond to queries from Nature about why it had not donated to the fund.
London-based Basecamp Research is another company frequently mentioned by fund supporters. The company raised $140 million in an investment round in September and is building its own database by collecting genetic information from organisms living in extreme environments around the world. It uses the data to train AI biology models and develop treatments.2
Source: www.nature.com