Intellectual Property Strategies in the age of AI
To biopharmaceutical firms, AI is both an opportunity and a threat. The opportunity comes from the advent of better tools and processes that reduce costs and increase the likelihood of success. The threat comes from not only the uncertainty of AI predictions, but the reality that AI, not biopharma, is now the darling of investors. After all, the market capitalization of Nvidia alone – over $4 trillion at the time of writing – is higher than the $3.70 trillion combined market cap of the top 20 biopharmaceutical firms. For small and mid-sized biopharma firms to succeed today in making productive use of AI, they must revisit their business strategies and build a more balanced IP portfolio, with less reliance on patents, and more accepting of data sharing.
AI challenges biopharma’s traditional, closed IP model. Adapting to AI means sharing data, including negative results. That is because AI only works where it has data – lots of it and in well-curated forms – to both train and validate predictive models. A firm seeking to benefit from AI must prioritize data sharing or risk being left behind. Waiting for others to contribute data means losing influence over AI’s design and trajectory, and being forced to adapt later to where competitors already play. This reality shapes how small and medium (SME) biopharma firms must develop their IP strategies.
SMEs have been sold the idea that without patents they cannot survive, even when those patents get in the way of their goals. What’s often overlooked is that patents are just one form of IP, and not always the most advantageous. In fields such as cell therapies, synthetic biology, or AI-assisted drug discovery, for example, patents may provide only weak protection that is easy to circumvent. Further, US courts strike down between 43 and 46% of patents, making reliance on them uncertain. The truth is, other forms of exclusivity are often broader, more legally reliable, and less expensive than patents.
Fortunately, firms can openly share without losing exclusivity as long as they are smart. Being smart means developing an IP strategy that serves business purposes rather than developing business strategies based on patents. In many instances, sharing is becoming a business necessity, one that drives research and development efficiency. Rather than focusing on maximizing protection through patents – and creating silos that undermine AI development – firms now need to redefine their critical goals and re-establish how they can deploy IP in support of these goals. The path forward is a strategy that combines territories of exclusivity with areas of sharing.
Rather than rely solely on patents, biopharma firms hoping to benefit from AI and data sharing need to focus on developing a broader set of exclusivities, including but not limited to regulatory exclusivities (e.g. for new chemical entities or orphan drugs), reputation backed by a trademark, relationships with customers and other stakeholders, being first to market, and overall “know-how”, including developing the technical know-how to safely make sensitive data available and benefit from such sharing. Building such a portfolio of exclusivities – both formal IP and adjacent rights – provides more security because even if one right is held invalid, the remainder stay in place. Significantly, most exclusive rights are more compatible with sharing than patents. While a firm in theory could patent and share, in practice most avoid sharing for fear of jeopardizing future patents on improvements or dosage forms.
To create a flexible IP strategy that meets today’s business needs, firms need guidance. They need consultants or lawyers who have experience beyond patenting and who understand the necessity of sharing. Luckily, a growing number of experts bring real experience in open sharing and IP. One example is Conscience’s Open Science Advisory Services (OSAS) program, which provides funding for organizations to engage third-party advisors, such as consultants, legal and regulatory specialists, business strategists, and Contract Research Organizations, to help advance open science initiatives. In order to capitalize on AI and its potential while supporting unique business needs, firms need to expand their networks, find experts in open sharing, and adapt their advice to advance their own business goals.
E. Richard Gold and Peng Fu
Richard Gold is Chief Policy and Partnerships Officer and Peng Fu is CEO at Conscience, a non-profit focused on enabling drug discovery and development in areas where open sharing and collaboration are key to advancement towards accessible treatments. Both are members of the Law Society of Ontario and Gold is also a Distinguished James McGill Professor at McGill University.
