LCGC Blog: How Industry–Academia Collaboration Shapes the Future of Separation Science

Collaboration between academia and industry has profoundly shaped my professional journey and, more broadly, the evolution of separation science as a discipline. From my early days as a postdoctoral researcher to my current role as a faculty, working closely with industrial partners has consistently influenced how I think about research, personnel training, and impact.

My first exposure to academia–industry collaboration began during my postdoctoral work at the University of Waterloo, where I was involved in projects driven simultaneously by fundamental scientific questions and practical industrial needs. Looking back, it is clear to me that many of the most impactful advances in separation chemistry, and their downstream societal benefits, have emerged precisely because of strong, sustained partnerships between academia and industry.

One example that is particularly close to me is the development and widespread adoption of solid-phase microextraction (SPME). The close collaboration between the academic inventor of SPME, Janusz Pawliszyn, and industrial partners created a uniquely effective pathway in which fundamental innovation and commercialization advanced hand in hand. That partnership ensured not only scientific rigor but also robustness, accessibility, and broad adoption, ultimately enabling what many consider a green revolution in sample preparation. I wonder if SPME would have achieved the same reach or impact without that level of cooperation on both sides.

Beyond technological advances, one of the aspects I value most about industry–academia collaboration is how it keeps science grounded in reality, particularly from a student-training perspective. As a trainee and now as an advisor, I have consistently observed that projects involving industrial collaborators come with clearly defined objectives, firm timelines, and tangible expectations. This introduces productive pressure that pushes teams to troubleshoot efficiently, communicate clearly, and deliver meaningful outcomes. It also forces researchers to articulate the value of their work beyond academic language. As a colleague of mine often says, research has its greatest impact when it can save time, save money, or ideally do both. Industry collaborations make that reality unavoidable and help prepare students to step outside the “academic bubble” and into diverse professional environments.

To complement my academic perspective, I reached out to several industrial collaborators to gather their perspective on the value of these partnerships. Despite differences in organization size, business model, and application focus, their responses converged on several themes.

From an industrial standpoint, collaborations with academia are a powerful engine for innovation because they unite academic creativity with industrial pragmatism. One collaborator captured this succinctly: “This combination of academic creativity and industrial realism tends to unlock solutions we would not reach on our own.” Academic partners contribute deep mechanistic understanding, methodological innovation, and freedom to explore emerging ideas, while industry brings access to real samples, real constraints, and real performance requirements related to robustness, throughput, cost, and regulatory compliance. Together, these elements allow promising concepts to be tested under realistic conditions early, accelerating their translation into practical analytical solutions.

Several collaborators emphasized that the most effective partnerships are those anchored to clearly defined, real-world problems, while still preserving academic freedom to explore fundamentals in depth. One noted that successful translation depends on “joint method development projects, where both sides co-design experiments and share data early and often,” highlighting transparent communication as a critical success factor. Others stressed the importance of academic partners being willing to engage with practical challenges such as matrix effects, sample preparation constraints, instrument robustness, and method transferability, which are factors that often determine whether a technique can move from proof of concept to routine use.

Another recurring theme was the challenge of bridging the gap between fundamental discovery and proof of concept. One collaborator pointed out that “many fundamental ideas sit in a gap between theory and proof of concept,” often due to limited resources, risk tolerance, or visibility. Others noted that incubator programs, dedicated industrial research teams, and even emerging artificial intelligence (AI)-driven tools may help connect ideas across disciplines and industries, increasing the likelihood that promising concepts find a path to application.

The strongest consensus across all collaborators, however, centered on workforce development and the marketability of students and postdoctoral researchers involved in industrial collaborations. One industrial partner stated: “Students and postdocs who work on industrially motivated separation problems gain exposure to real-world constraints such as turnaround times, regulatory compliance, and cost of goods.” Another emphasized the hiring advantage this creates, noting that these trainees are “technically strong, comfortable with advanced instrumentation, and already familiar with how their work connects to product development and manufacturing.”

From the perspective of hiring managers, these experiences translate directly into career readiness. As one collaborator explained, “Hiring newly minted students who have worked on these collaborations allows them to hit the ground running and contribute more significantly earlier in their careers, which translates into faster career growth.” Another added that access to sophisticated tools and real industrial decision-making makes students “more marketable and in demand when transitioning to either academia or industry.” In this sense, industry–academia collaboration is not only advancing separation science, it is also actively shaping the next generation of separation scientists.

While the scientific, technological, and training benefits of these partnerships are clear, it is equally important to acknowledge what truly enables them to happen. Meaningful collaboration does not occur by chance, and it does not happen without resources. In today’s academic environment, research activities, including graduate student training, require substantial financial support. Contrary to a common misconception, funding does not simply “exist” within academic institutions. Graduate student stipends, tuition, benefits, and research costs are often supported almost entirely through externally funded research, including industry-sponsored projects. Sustaining the human capital that drives academic research is not optional for the success of these collaborations.

For this reason, academic institutions must play an active and flexible role in enabling industry partnerships. A sustainable research ecosystem depends on a balanced funding portfolio that values both conventional sources, such as federal grants, and alternative pathways, including industrial collaboration. Industry-funded research should be recognized as complementary rather than competing with traditional funding mechanisms, and institutional policies must reflect the different timelines, deliverables, and success metrics associated with these collaborations. Greater flexibility in areas such as overhead structures, intellectual property negotiations, publication timelines, and student appointment mechanisms would significantly reduce barriers without compromising academic integrity.

At the same time, it is essential to recognize the substantial effort required from faculty to establish and sustain successful industry partnerships. These collaborations are built on trust, scientific reputation, long-term productivity, and consistent delivery, often developed over years. Institutions should acknowledge this work as a meaningful component of scholarly activity, particularly when it results in high-quality student training, technology translation, and measurable societal impact.

Taken together, these perspectives strongly reinforce my own experience: collaboration between academia and industry is not merely beneficial, it is essential. By bridging curiosity with application, and training with real-world relevance, these partnerships ensure that separation science remains scientifically rigorous, societally impactful, and capable of preparing a highly skilled and market-ready workforce. If academia and industry can communicate more openly and act more flexibly, collaboration will not be the exception, but a defining feature of the future of separation science.