While the traditional process of discovering a new drug is long and expensive, artificial intelligence drug development platforms can help reduce time and money by efficiently analyzing vast data sets within the drug discovery process. Researchers can use such AI platforms for identifying new biological targets associated with a particular disease, screening known compounds for new applications and designing new therapeutic compounds, among other applications.
In this article, originally published in Law360, we explain the top 10 considerations for AI transactions involving use in drug discovery, which are:
- Consider the nature of the services being provided.
- Be mindful of IP ownership.
- Consider quality and privacy issues for training data.
- Consider exclusivity.
- Account for infringement risk.
- Be reasonable with royalties.
- Evaluate confidentiality and competitive use.
- Plan for uncertainty.
- Scrutinize contractual risk allocation.
- Beware of an evolving regulatory landscape.
For more detail on each of the considerations, read the full article.