Anirudha Lakshminarasimhan, Director R&D Genetic Engineering, Laurus Bio, Bengaluru
The goals of industry and academia may seem different. Industries aim to come up with products or processes with an end application, translating to profitability. On the other hand, academia focuses on scientific contributions in the form of publications in high-impact factor journals or patents, translating to research funding. The level of innovation may vary across different sectors of individual industries and academia. A novel idea published in a high-impact journal may not be commercially viable for various reasons. On the other hand, a simple extrapolation of an existing idea can be of high market value.
Academic research can be categorised into fundamental and translational or applied research. A lab working on translational research needs to collaborate with other institutes, industries, clinicians, or non-profit organisations to bring a product into the market or establish a process. Else, it can result in an isolated study leading to a publication or patent with a low technology readiness level, as it may lack a complete understanding of the current scenario. Further, it can lose focus of the goal and use up resources to generate data for publications or patents, without working on the actual steps needed to reach the endpoint. Therefore, it will be ideal if one can consider all the stakeholders even while proposing the first phase of the project, which is typically executed in the lab. With this integrated approach, early collaborations with multiple stakeholders will not only help keep ‘the end in mind’ but also prevent multiple iterative cycles of optimization, saving valuable time and resources. This also considers the freedom to operate as most of the reagents used in academic labs are not meant for commercial use along with minimising the cost of the product or process. To collaborate early, one needs to have an innovative and convincing idea, or the proof of principle needs to be demonstrated in the lab. If early collaboration is not possible, the project should undergo a reality check and have definitive endpoints with a high predictive technology readiness level. Taking decisions based on market trends, and terminating a project that no longer is commercially viable (but still has an academic interest) may not be easy but can be deemed necessary. Academic labs also need to fine-tune themselves with the timelines expected for translational research, which are extremely competitive, and on par with industrial standards.
Industries by collaborations with domain experts gain access to a wealth of information, not readily available in the public domain. In addition to this, they also have access to cutting-edge technologies, which are high on investment. Typically, industries work on projects whose objectives and the steps associated with them are streamlined. In this process, they forego efforts wherein the process or product can be further improved. As industries work on focused projects with tangible endpoints, they may lack the bandwidth to do exploratory work, involving optimization studies to improve the product. In such cases, it will be worthwhile for them to collaborate with labs with expertise in the same area, funding the project, the results of which can add value to their pipeline of products or processes. More avenues for funding have opened with the availability of government-aided funding for academia- industry collaborative projects.
Startup companies, while establishing their facility can collaborate with academic labs, thereby employing trained personnel and optimised processes to their benefit. Once the proof of principle is established in the lab, the technology can be transferred to the new startup facility. Again, this can save time and resources for the startup which can be of great value, considering their limited availability of funding and facilities at the initial phase of establishment.
Collaborations will require a lucid memorandum of understanding listing all possible clauses with utmost clarity along with the expectations from both parties to agree upon. As industry and academia with their strengths and weaknesses complement each other, a win–win strategy can foster several Industry-academia partnerships, wherever possible.