Columns Journey of a YI

To be or not to be at the bench

Amit Lahiri

Amit Lahiri is a Senior Scientist at CSIR-Central Drug Research Institute, Lucknow. He is one of the Young Investigators (YIs) selected to attend YIM 2020. In this invited article, he writes about the need for a researcher who has recently set up his/​her lab to balance benchwork with other necessary activities such as writing grants, teaching, and administrative work. 

Amit Lahiri
Amit Lahiri 

It is surprising that we spend decades working at the bench aspiring for a time when we don’t have to do it anymore. On average, a young faculty must have spent around 8 – 12 years doing their doctoral (PhD) and Postdoctoral research training. During these years, the major goal was to be productive at the workbench and effectively translate the lab results into publications in peer-reviewed journals. 

As a young graduate student or postdoc, one is expected to do their quintessential reading and writing in their spare time (“beyond the core working hours when you are not busy doing experiments”). After all those years spent working at the bench, a young PI, upon securing a position and finally gaining a laboratory of his/​her own with grad students and project trainees, can now finally read, write, and execute his research goals at peace in his/​her little cubicle (called his/​her office).

On a personal note, I keep wondering to what extent a new PI should/​can contribute to working at the bench after landing the coveted assistant professorship. How can one juggle time between writing grants to procure funds essential for running the new laboratory, the mandatory teaching assignments, and, of course, the administrative responsibility? 

I feel the answer largely depends on your PhD students, the start-up funding that you have received, and your passion for bench work. In academia, a Principal Investigator (PI) is definitely expected to have teaching responsibilities to a certain extent (courses and extensiveness varying between Institutes) and that decides one’s schedule. 

Let us discuss this with some examples.

Early students and start-up funding:

It has been said by many that the early/​initial students build your career. If there is someone with you who is not a novice to handling a pipette, has a good technical grasp (perhaps owing to any short-term research training they might have undergone during their undergrad years), and has a good scientific acumen, it is certainly an advantage. For example, if you could afford to hire a postdoc early in your career, it’s definitely a boon as you can spend more time writing grants, while you can trust the postdoc to oversee/​teach your first-year graduate students. 

On the other hand, if the institute provides a healthy start-up grant, you can start slow on writing grants, without worrying too much about the resources to run the laboratory. In such a case, you can directly start working on the projects which might help you to get your first paper out soon. 

Teaching and administrative work 

Research institutes differ in their course curriculum and thus the teaching responsibilities vary widely across institutes world over. Certainly, this factor decides how much time you can dedicate as a new PI to carry out experiments in the laboratory. You are also expected to handle multiple administrative responsibilities, which in turn dictate your spare time. Getting human and animal approvals for the experiments you intend to do, visiting hospitals to establish effective collaborations to procure patient samples, etc. also take up a lot of time and play a role in determining how one can segregate their free time between bench work and writing.

Love for bench-work and trust issues 

Now some of us really love doing our own experiments. There are many of us who do not want to forego the joy of doing experiments, generating results, and see their research hypothesis working. These PIs can serve as an experienced extra working hand, especially early in their career. There is a high probability of mistakes (calculation errors etc.) while working with inexperienced students which would drastically change the course of expected results. This is when the PI has to dedicate time to guiding and patiently teaching his leading warriors – the first few students! These factors can also modulate your working habit in the laboratory as you need to put in extra hours doing experiments in such cases. 

Generating preliminary data and standardizing everything 

One of the major hurdles an early career investigator faces is to generate preliminary data for grant applications. To generate the preliminary data, a young PI needs to work in the laboratory as you cannot really expect first-year students to get publication-quality data in a new lab. One needs to standardize everything and that too with very limited resources. Letting the novice student do those early and deciding experiments completely on their own is a great risk for a new PI, as in the end, one might just end up losing precious reagents without anything getting accomplished. Further, it will be easier for an experienced person like a young PI to perform the first set of experiments and standardize the experimental procedures so that students can reproduce the data. 

Balancing work, writing, and training students

Once the preliminary data is generated and the first grant is secured, it becomes very crucial to balance work and writing. One needs to carefully plan all the endeavours. One should start training the students by carefully planning the experiments. Next job is to make sure the students are able to understand what is expected from them and they are getting better both at the bench and reading. In the meantime, a new PI needs to start thinking about the next grant submission and hopefully, by then the students are adept at generating the next set of data that could be used as preliminary data. Given that a PhD is a training program, one cannot expect too much from a first-year student. It is the responsibility of the PI to train them appropriately and then base their expectations on the quality of such training.

Life is not easy, but it’s your data

Let me share my experience with you here. I joined CSIR-Central Drug Research Institute, Lucknow as a Senior Scientist just about a year ago. I initially took two summer trainees. They were instrumental in setting up the laboratory and procuring reagents to perform the early experiments. The first few months, I worked with them religiously and generated some basic data, though of rather poor quality. After almost 9 months of slow but steady work, we started getting some results. 

When two PhD students came on board, things started to look a little better. To get the preliminary data for our first grant, I worked constantly in the laboratory with the students and the trainees. Each step of every experiment was performed together, we discussed all problems that arose, and performed troubleshooting on a daily basis. Finally, I could submit our first funding proposal. 

Now with the first grant being sanctioned, I am momentarily free of my funding woes. I have started spending more time on writing other funding applications and with three PhD students, it appears that they might quickly become accustomed to independently doing experiments. We talk every day, discuss what they plan to do, and if all the resources to perform the task are available. We discuss the results once weekly. I am hopeful that in a year or so, the students might become adept at working and thinking independently and be able to take the project forward on their own without my constant presence in the lab. 

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