What has been the most significant development in your field over the past 10 years?
Fast tissue imaging using infrared and Raman spectroscopy has added a lot of scientific value. Now, we can analyze tissue samples for disease, such as cancers, with extreme accuracy and cost effectiveness. Hospitals and clinics can now look at biopsies and diagnose disease within 24-hours without the time-consuming staining and counterstaining steps. This simply wasn’t possible 10 years ago. Our technology in particular is easy-to-use, and people with minimal scientific training can run some of these tests.
What made this possible?
The incorporation of very fast translating devices, and new types of spectroscopic sources has made fast tissue imaging possible. In our system, we use an array of quantum cascade lasers to rapidly image important areas of tissue. The number of spectra is hundreds of millions, and this can be done in 15 minutes because the new source is so bright that the signalto- noise ratio eliminates the need for co-averaging of multiple scans – one scan is sufficient.
How would you say your company has made a difference over the past 10 years?
We’ve solidified ourselves as the leader in scientific instrumentation and imaging in the life-science world, with specialists visiting from stateof- the-art hospitals around the world interested in implementing our tools – some already are. For example, St. Jude Children’s Research Hospital, USA, recently began using one of our imaging systems for cancer detection in children. This work, using infrared, Raman, and MALDI imaging to analyze tissue samples and diagnose disease, has had a real impact.
Thinking about the future of life sciences... What excites you most?
Disease detection will continue to forge ahead, as will state-of-the art, tailored treatments for cancer. We have the tools to make a difference in these areas. And given the significant proportion of our revenue we spend on R&D, I’m excited to see where we can innovate over the next decade.
Are there any other trends that excite you?
We have also seen the emergence of machine-based AI in the past few years, which is allowing the scientific community to manage images that are many gigabytes in size. Instead of taking weeks to analyze data sets, it can be done in mere minutes by just using more careful, adaptive algorithms. We have formed a team to employ machine learning AI-based algorithms to handle large datasets, for example. But the field as a whole is still in its infancy – so I’m excited to see what this will allow us to do in another 10 years.
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