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We will explore the adaptation of classical licensing practices to the many novel issues and challenges presented by the licensing of human data, especially biomedical data. Data is an emerging asset class that does not fit neatly into traditional categories of intellectual property, yet data sets have become increasingly attractive assets for monetization. Hence, the need to address challenges of data licensing is becoming ever more acute. Human biomedical data presents unique complexities for the prospects of licensing, including data governance, data privacy, the rights of data subjects, and rapidly evolving complexities in national and international laws addressing data accessibility, use and cybersecurity. Concerns are especially acute in situations where biomedical data is used to develop or train an artificial intelligence (AI) model, or where such data is ingested by an AI and used to generate results germane to human clinical research, diagnosis, treatment or prognosis.
We will explore how these issues map onto and challenge existing license agreement frameworks, raising the need for new and expanded definitions and creative grants of licenses, restrictions on use, the impact of data-specific risks on representations and warranties, liabilities and indemnities. One of the most pressing questions is valuation and structure of financial terms, given the sparsity of publicly available data licenses to provide examples...
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