Academic-industry collaboration: Intertwined for drug discovery

This is a guest editorial by Hakim Djaballah, president and CEO of Keren Therapeutics. It is adapted from the article “Academic-Industry Collaboration: Intertwined for Drug Discovery” published on CAS’s blog (www.cas.org/blog) on Jan. 11, 2019.

The business models for drug discovery have evolved in many ways over the past decade. One of the most impactful changes has been an increase in collaboration between researchers in academia and the pharmaceutical industry. Recently approved drugs resulting from such partnerships include Spinraza and Kymriah.

For academia, the benefits of collaboration are obvious. Financial backing from pharma provides steady funding and increased opportunity for academics to do impactful work. For pharma, there are benefits as well. Collaboration may begin as funding for academic research with right of first refusal to license any promising candidates that emerge. This helps pharmaceutical companies fill gaps in their portfolio at lower cost and risk. Although this model is the most common, examples of other types of innovative academic-industry collaborations include Takeda Pharmaceutical’s partnership with Kyoto University.

Despite successes from these types of partnerships, academic and industry institutions have evolved starkly different cultures that challenge productive collaboration. Here, I highlight three challenges to the success of academic-industry collaboration and offer ideas to overcome them.

Talent silos. Historically, scientists have chosen either academic or industry career paths, and they rarely switch tracks. This often leads to insular perspectives on both sides and constrains communication and mutual understanding in collaborative agreements. To overcome these challenges, drug companies may hire leaders from academia into research leadership positions or vice versa.

One of the best-known examples is Merck & Co.’s hiring of professor Peter S. Kim from the Massachusetts Institute of Technology in 2001. A bold and risky move at the time, it paved the way for other established academics to make similar moves to lead larger research operations.

However, career mobility between academic and industry research environments remains limited. Programs that intentionally provide increased opportunities to cross-recruit talent between the two environments, or even provide short-term visiting researcher opportunities, would help build shared understanding that would likely fuel collaborative success.

Prickly intellectual property problems.Pharma companies manage the IP of research outcomes as an asset and ensure confidentiality until a patent has been filed. Academia focuses on publishing and sharing results to encourage further research and has had little use for, or awareness of, patents.

Although academic institutions have been shifting toward greater focus on IP, the long-standing cultural difference often challenges collaboration. To grow overall understanding of basic patent law within academia, IP education should be incorporated into the fundamental science and technology curriculum for students. While academic researchers will continue to share their discoveries, they must consider their disclosures from an IP perspective to avoid conflict with planned patent filings by an industry partner.

Insufficient platforms for open innovation. Open innovation is a model that allows multiple parties to share common data and other information that each can use to advance its science. Such data sharing is critical for academic-industry collaboration. But it is most efficient when enabled by a technology platform that manages data hosting, structuring and security, and user authentication. Building and maintaining that infrastructure can be expensive and time consuming, making it a difficult investment for many industry or academic institutions alone to justify. Large-scale platforms managed by neutral third parties should be developed to relieve these barriers. If members of a collaboration could simply pay a fair portion of the cost on the basis of their use and not get bogged down in the administrative and management aspects of the platform, the model would likely work better. This would enable research teams to use common data repositories.

Views expressed on this page are those of the author and not necessarily those of ACS or C&EN.