The future of microplastics analysis, according to Dr. Win Cowger

Introducing Voices in Microplastics Science, a new interview series on The Microplastic Blog exploring the challenges and developments shaping the field through conversations with the researchers behind them. For our first interview, we spoke with Dr. Win Cowger (Moore Institute / Open Specy), a pioneer in microplastic standardization and characterization, about why major spectrometer manufacturers are adopting open-source software and what the next decade holds.

Here are the insights straight from the source. Let’s dive in!

1. Microplastic Solution (MPS) : From your perspective, what is currently the biggest scientific barrier to obtaining reliable and comparable data on microplastics between laboratories?

Dr. Win Cowger: Reference spectra are critical for creating accurate and comparable identifications, and you need a lot of variability in your reference spectra for all labs to be able to accurately identify all materials. We have been spending a lot of time curating additional spectra to be added to the Open Specy library and the newest release will have around 80k spectra in it but I know there are still likely more things that need to be added. To identify those gaps in reference libraries you need to have people who are both trained in spectroscopy and microparticle identification at a very high level. This is why we have focused a lot of our effort on trainings and workshops. 

Validation of the database produced using Open Specy’s out-of-the-box settings to identify the material type. The X-axis is the spectral collection mode employed in collecting the database. The Y-axis is the accuracy in percent of correct identifications of Open Specy in identifying spectra from the spectral collection mode group. The total number of spectra tested for each spectral collection mode is listed above the bars. The height of the bars is the accuracy (%). Spectra counts were not identical across the techniques because not all particles were measured in all modes, and some particles were measured more times than others (Cowger et al. 2024)

2. Microplastic Solution (MPS) : Open Specy was originally developed, in part, as a response to the limitations of proprietary spectral libraries. Do you see it becoming the global standard in 5-10 years; potentially being integrated into existing spectroscopy software?

Dr. Win Cowger: Yes absolutely, commercial manufacturers are also seeing it. In the last few weeks, 3 of the largest spectroscopy companies separately requested meetings with me to discuss exactly this. They want to figure out how to integrate Open Specy more easily into their pipeline. It is a win-win for them: if the software and reference libraries aren't their problem, they can focus on developing and selling the hardware, and their customers will know that their system is compatible with the best spectroscopy software available. I can definitely see a "Send to Open Specy" analysis button in commercial software offerings comming in the next 5-10 years. 

3. Microplastic Solution (MPS) : Open Specy 1.0 introduced automated processing, hyperspectral analysis, and machine learning classifiers. What do you consider to be the greatest scientific opportunity and the greatest risk of increasing automation in microplastic identification?

Dr. Win Cowger: The biggest opportunity is high throughput, accurate, and reproducible analysis. For example, when our lab opened, we had to charge >2k$ per sample due to the extensive analytical burden of microplastic analysis. Thanks to the most recent developments in Open Specy we are getting that cost < 500$ per sample. This will directly translate into more people being aware of microplastic exposure and taking management and policy actions. Simultaneously, automation makes things so easy the field risks falling into complacency, blindly trusting Open Specy's outputs and ignoring issues if they do arise. We aren't there yet, there are still issues in automated analysis that have not been automated away and will result in incorrect conclusions if not mitigated. 

4. Microplastic Solution (MPS) : Spectral libraries reflect the materials and conditions under which their spectra were collected. Should we ensure that machine learning models and spectral databases remain discriminated between degraded, aged, additive-containing,plastics found in real-world samples, or could this over-complicate identification? Where do we stop?

Dr. Win Cowger: This is a really tricky question to answer. There isn't a clear definition that I am aware of that defines when we call a plastic "aged" or "degraded" so those would be challenging to add as classes. A 2.0 version of Open Specy I have in the works is solving this issue by allowing measurement of carbonyl index and similar degradation metrics so you can quantify aging along with knowing the polymer it is. However at some point, the polymer is so weathered that it may even by depolymerized and this has been a tricky thing to deal with as that material may have the same signal as natural materials. Additives have a variety of signals, some are very weak and would not be easily characterized in an environmental sample while others are very strong and could overwhelm the plastic signal. In general with both aging and additives we try to solve this issue by having many examples of these types of plastics in the reference library so that we can still accurately identify it as plastic. 

5. Microplastic Solution (MPS) : Microplastics analysis is increasingly moving towards automated, high-throughput workflows. Do you think the industry is approaching a point where routine microplastics monitoring can now be standardized sufficiently for regulatory purposes?

Dr. Win Cowger: Definitely, I run an accredited lab Moore Institute for Plastic Pollution Research, that uses state-standardized methods for microplastic analysis. 

6. Microplastic Solution (MPS) : Looking ahead to the next 5-10 years, what technological advance would you consider most transformative for microplastics research?

Dr. Win Cowger: In situ analysis through advanced novel sensors would be a game changer. There are several technologies proposed, from flow through Raman tweezers to impedance spectroscopy. I am honestly not sure which one will win, but I can guarantee you that whoever decides to focus on high-throughput, accurate, reproducible, and transparent workflows will have a much easier path to adoption than those shrouded in proprietary. This has been my philosophy with Open Specy and why it has seen exponential adoption over the last few years. 

Microplastic Solution extends its sincere gratitude to Dr. Win Cowger for sharing his profound insights. As an organization dedicated to delivering actionable microplastic detection and consulting, we share the conviction that transparent, clever and economically accessible spectral matching software is needed.

By Emilio José Orovengua López 

Biochemist | Scientific Communicator & Blog Manager