We welcome you all for this week’s interview with scientist series.
This week we had a pleasure of speaking to Dr. Tom Leung. Dr. Leung completed his MSc in Virology and PhD in Epigenetics at the University of Toronto. For his PhD thesis, he investigated the molecular mechanism of repressive genetic bookmarking during cellular division and the potential application of reversing these bookmarks as alternative cancer therapeutic approaches. As a molecular biology research scientist, he experienced first hand the inefficient organization of biomedical publications.
Dr. Leung is very passionate about the development of a solution to better organize the vast amount of data in scientific literature in order to bring the most relevant information to scientists to facilitate the next big biomedical breakthrough.
Thank you Dr. Leung for taking time to speak to us.
Can you tell us something about yourself.
My name is Tom and I am the founder and chief scientist at BenchSci, an AI driven platform that helps scientists find antibodies for their experiments (https://www.benchsci.com). I did my MSc in Virology and my PhD in Epigenetics, both at the University of Toronto.
What’s your area of research?
My PhD thesis investigated the inheritance of repressive epigenetic histone markers, in particular the H3K27me3 facilitated by the Polycomb Repressive Complexes, during cell cycling and DNA replication.
What do you think about the current publication trend, and is publish or perish a valid statement for young scientists?
The notion “publish or perish” has been a recurring theme for quite some time, these three words succinctly capture the reality that funding is allocated to labs/institutes that are most productive in publishing.Although the Canadian government just recently dedicated more funding for basic sciences, calling it “a historic investment in research”, raw publication count still largely determine if a PI will receive some of that funding. This constant push to publish more papers has two negative consequences: 1) researchers forgoing longer term, more ambitious projects favoring shorter, simpler studies and 2) labs shying away from novel research areas, focusing on “popular and trendy” topics to increase likelihood of acceptance by major journals. To break this current predicament, the system with which productivity and contribution is calculated in research needs to be reinvented.
What do you think of preprint servers? Do you think they are useful?
Two things came to mind: preprints on one hand will offer the advantage of versatility and freedom to publish your discoveries faster prior to lengthy reviews by editors, but on the other hand this brings the obvious disadvantage of the potential “scooping” that ensues when competing labs take your data and rush to publication themselves. Despite issues of quality control and reproducibility of un-critiqued work, I believe this is a promising solution to the current “publish or perish” predicament. Using the preprint system, we can leverage the entire scientific community, not just the selected few journal editors, to review the published work as a whole and determine its contribution. This can then be used as a measurement or guideline for funding agencies to allocate subsequent rounds of funding. Researchers can plan more ambitious projects and publish their progress and findings regularly to secure further funding to continue their work, as oppose to “hiding” that data and “saving” them up for one big paper. I believe the current trend is slowly migrating towards this direction, however, this will not be impactful until more scientists adopt this new initiative. The more researchers participate, the lesser the fear of being scooped, and this will in turn encourage more researchers to join the movement.
Do you think science is communicated well to non-scientists? What are some ways to improve science communication?
With the advent of multiple social media outlets, I believe that science is being communicated to non-scientists faster than ever. I have seen many graduate students take it upon themselves to share their passion for science and research with non-scientists and younger generations. However, the opposite is also true, false information is also disseminated to non-scientists very rapidly. This is especially impactful when celebrities are involved. As a case in point, a certain singer artist in Hong Kong recently denounced the use of influenza vaccine on social media. I think this is a very serious concern and we as trained scientists should be mindful of fake information being circulated online and make sure only legitimate information is conveyed to the general population.
As we know, there are more PhD’s graduating every year as compared to available tenure track positions. Do you think there is way to improve this?
There is no easy solution for this dilemma, the fact remains that PIs need many students to do research, far more than there are opportunities in academia. PhD graduates who are passionate to continue their research as post doctorate fellows are not transitioning into more permanent research positions in their institutes or universities. There are simply not enough positions being generated to go around.
What are alternative career options for young scientists apart from applying for tenure track positions?
I think that soon-to-be graduates must start looking “outside the box” for career options. Research scientist positions in the pharmaceutical industry are highly sought after by PhD graduates, however, in Toronto these positions are few and far between. I think careers in the start-up industry offer a very realistic alternative option. There are many great biotech start-ups here in Toronto that are developing some cool technologies. I think PhD graduates should seize new opportunities in this up-and-coming industry and try it out for themselves. Life in a start-up is quite similar to research, a lot of problem solving and critical thinking is involved when you are building something new, I think it will automatically resonate with all PhD graduates.
Apart from science, what do you enjoy doing the most?
Reading, or should I say listening, to audiobooks is something that I have picked up recently. I always knew that I need to read more books but fail to find the time to do so until recently some colleagues of mine introduced me to the wonderful world of listening to books. Now I can “read” when I am commuting or going out for a walk. Filling up these so called “edge time” has been very productive and rewarding.
What do you think is a recent scientific invention which has changed the way we do science now?
I think the recent advent of Big Data and Machine Learning technologies that can summarize and analyze large amounts of information from scientific literature has transformed the way scientists learn new knowledge. A rough estimate in 2016 showed that there are over 2.5 million scientific papers published each year, which translates to around 7000 papers each day, it is humanly impossible to keep up with new papers published in your field. Using AI to read and extract relevant information from new papers for respective scientists will not only allow scientists to keep up-to-date with new discoveries but also devote more time to ground breaking research.
Thank you Dr. Leung for talking to us today. It was a pleasure.