As the worst flu season in a decade marches on, public health experts and private companies are re-evaluating the way we fight flu. The idea of a universal vaccine is being bandied about yet again, Bloomberg reported recently, and others are trying to speed up the time it takes to manufacture vaccines.

Boulder-based InDevR is in the thick of things, tackling the problem on multiple fronts. Its newest product, FluChip-8G, is taking aim at the limited effectiveness of vaccines. In a typical year, flu vaccines are 40 to 60 percent effective; this year, it was just 25 percent effective.

InDevR in 2014 won a $14.7 million contract from the federal government to develop FluChip-8G, in the hopes of preventing a global flu pandemic. As the product nears commercialization, we sat down with InDevR Chief Technical Officer Erica Dawson to learn more:

This interview has been edited for length and clarity.

1.) Why is the flu so bad this year, and how could InDevR's FluChip-8G help with that?

This year, the vaccine was poorly matched to the H3N2 strain that is currently circulating. As a result of that, we're having a really, really severe flu season. Vaccines have to be made well in advance — the World Health Organization just last week chose strains for the 2018-2019 flu season that are likely to be the dominant flu strains, and companies have a six-month period before they have to have the vaccines on the shelf.


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What InDevR's flu products aim to do is improve influenza surveillance and speed up the process of manufacturing flu vaccines. FluChip-8G is based on a DNA microarray: We take a swab from a patient, process it and put that it onto a specially designed piece of glass that has little bits of DNA that match the influenza genome on it.

Amplifying flu from a patient sample to detect it is not new — what's new is the fact that we use a sophisticated pattern recognition algorithm to interpret the large amount of data. You can think of it somewhat like facial recognition software: Facebook suggests who may be in your photos by using an algorithm able to identify features: this person's eyes and nose are here, and their face is shaped like this, and therefore that's likely your sister-in-law.

What we really want to do is apply big data, machine learning to a diagnostic assay so you get the benefit of high-information content combined with the ease of simple data interpretation. We want the user to run the assay and have the software say, 'This is the result.'

We're hoping this technology can be put in surveillance facilities across the globe, because if we can be in the field validating this, finding those red flag viruses that need further investigation to try and head off a potential pandemic, that would be fantastic.

2.) Pandemic is a word that gets thrown around every few years. It sounds scary, but is it an actual threat?

It's a tricky thing to predict, and people are trying. The mission of the government funding agency that gave us the money, Biomedical Advanced Research and Development Authority (BARDA), is pandemic preparedness.

I don't want to be gloom and doom about it, but as a person who does influenza research for a living, I certainly worry about the next pandemic.

This year is the 100th anniversary of the Spanish Flu (which killed 3 percent to 5 percent of the world's population). Certainly things have improved since then; public health agencies are doing an excellent job of surveillance, but everyone admits we could be doing a much, much better job.

3.) Aside from a potential pandemic, is influenza that big a deal? I mean, haven't we all had it and survived?

You hear everybody say, 'I have the flu.' When they say they have the flu, they just mean they feel bad. Influenza is a specific virus; it's a much different disease. I had diagnosed influenza a few years ago. I was out of work for a week; I had a fever of over 103 for four days in a row; I had to use a nebulizer. I felt like I got hit by a truck.

I think the disconnect is the flu is this colloquial term and probably very few of those cases are actual flu. But influenza is very dangerous, especially in children and the elderly.

4.) Is this something that will show up in doctor's offices, too?

It is better suited for public health trends and surveillance. That's not to say it couldn't be used clinically, but I think it would be used in a slightly more niche application. We're not looking to capture that entire clinical diagnostics market. What we really want to do is make an impact where more information can feed into making better vaccines.

5.) What's your timeline for commercialization?

We are at that phase where we are preparing for regulatory submission; however, we really want to get this out for research use. In the July/August timeframe, we hope to be installing units overseas and training people so that we can do a bunch of field validation of this research.

We are still pursuing FDA clearance. We plan to submit our application sometime in mid-2018.

One of the things we're really proud of as a company is that every single technology we've launched was launched with government funding before that funding came to a close. Often you hear this thing called the valley of death, where you have funding to develop the technology 90 percent of the way, and you can never quite get through the valley of death to actually make it commercialized.

We've taken government funding and translated it into products on the market without needing bridge funding. We've never taken any dilutive capital, so never any private equity or angel investment.

Shay Castle: 303-473-1626, castles@dailycamera.com or twitter.com/shayshinecastle