Susanna Basappa is a M.D./Ph.D. student in Mayo Clinic College of Medicine and Science. She completed her undergraduate degree at the University of San Francisco and came to Mayo Clinic to begin her studies in medicine and in cancer prevention research.
My name is Susanna Basappa, and I am an MD/PhD student who chose to join the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery for my PhD thesis work, under Lila Rutten, Ph.D., in the Population Health Science Program. I have been told that this is an unusual choice, but my reasons for joining this department are simple. Or perhaps not?
Why I want to study the people side of things
When people think of biomedical research, the first thing that comes to mind is often mixing chemicals, and pipetting substances onto flasks and petri dishes. This is what is commonly referred to as wet lab work, and is where I began my career in research. Correspondingly, when I was an undergraduate, I spent the majority of my lab experience working with cell cultures and mice.
I enjoyed my work, but felt that studies identifying and clarifying specific biological mechanistic pathways, while interesting, were largely clarifying scientific minutia over long periods of time, and had little practical application. Additionally, as often as not, cells might overgrow their plates, or might become infected and die despite the number of precautions taken to keep everything sterile. Chemical reagents run out or expire without notice, experimental protocols can be a nightmare to modify and perfect, and generally there is a large amount of downtime between required time points. There are so many external factors beyond human errors in wet lab work, such that even if the research questions were interesting, non-automated pipetting was never sufficiently engaging to me to keep my interest for large amounts of time. We choose to go into research because we love it, not because we tolerate spending a certain (large) percentage of our day to get to the results we want. Or at least that's how I feel about it – give me chart review over cell maintenance any day!
Furthermore is the issue of replicability in research – the ability to take a protocol and follow it to receive exactly the same outcome. Due to minor variances in everyday life, and due to major deviations over time in terms of culturing and environment, replicability in cell culture studies is extremely low. This is especially true when working with cancer cell lines, which may accumulate additional mutations and may evolve into a subtype entirely different from what a scientist might think they are assessing. Within the same lab on different days results for the same experiment might be different, which is bad enough; worse yet is the notoriously low levels of agreement between labs. I did not want to deal with poor replicability for the rest of my life and career - it seemed better to me, therefore, to work in a dry lab setting; a dry lab being a pipette free zone, which commonly involves being surrounded by computers. Tongue-in-cheek humor aside, working in silico is not for everyone, but I think it’s the sort of work that I like best.
If you run the same line of computer code for the same dataset, you always get the same answer, and if you don’t, you look at the line of code, fix the human errors and try again. If you do a literature review and compile a library of papers to interpret, any of your colleagues can go through the same papers to identify the same outcomes and produce the same statistics. Human error is always an issue in research, but using data and computer code is cleaner (both physically and in terms of straightforwardness) and replicable in the way that wet lab work inherently cannot be. While basic biological science research attracts many people, I knew from early on that it wasn’t going to be where I was happiest – rather; I believe that there may be a potentially bigger issue at hand that I can help address.
That issue, of course, is big data. So much data has been accumulated at the bench, transition, and clinical levels – and so much has not yet been interpreted or mined for significant outcome data. To maximize efficiency, I think there is significant value in contributing towards the efforts to use our ever-growing database – and more importantly, aggregating this data for generalizability to the larger population (or populations). Which brings me to one of my final points in my (apparently not so simple) reasoning as to why I chose to work with Dr. Rutten and the Mayo Clinic Kern Center for the Science of Health Care Delivery.
Because it’s all about the people
While I enjoy my in silico work, part of the reason I wanted to move away from basic science is that I wanted to work in more applicable settings, and I wanted to work directly with the people whom my research will serve. That is why I am interested in going into primary care, and in prevention-based medicine. There is that old saying, “an ounce of prevention is worth a pound of cure,” but it really is true. For example, my grandma is diabetic. She never exercised, always ate desserts with massive amounts of sugar, and always had her Pepsi in hand. She’s now facing renal failure, has had a leg amputated, and had sufficient retinopathy, that for several months she was unable to drive, effectively isolating herself at home. I love her dearly, but if she had been engaged in efforts to prevent progression of her disease, if her physicians had been able to help her change her behavior, it is far more likely that she would not have to manage this level of severity of her disease.
Instead, her physicians seemed to treat everything that happened as if it were inevitable, told her what to do, and gave her medications. Needless to say, she did the minimum necessary to keep herself out of the hospital. I don’t want for my patients to have to deal with situations like my grandma. My research interest is in studying breast cancer screening in women with dense breasts, for whom there are no recommendations, rather than diabetes, but my mindset is the same – there is no reason why a woman should have to find that she has metastatic breast cancer because there were no guidelines for early diagnosis attempts and considerations in her care.
As a Clinical and Translational Science MD and PhD candidate, I know that my choice of research focus is relatively unconventional (many of us seem to gravitate toward basic science labs despite the broad nature of our track), but I have hopes that other MD/PhD and PhD candidates will choose to follow my path. I have been fortunate to be supported by the Mayo Clinic Medical Scientist Training Program (MD/PhD) despite my unusual research approach. However, I have been asked by others if Mayo supports me enough times that it seems some of my peers may believe the old adage that “the nail that sticks out gets hammered down,” in terms of my choice versus their choices at Mayo. This is somewhat alarming to me. As graduate students, aren’t we supposed to push limits, and find our niches? I’ve heard of MD/PhD students who pursue their PhDs in humanities in other schools – so why not in the science of health care delivery, and in dissemination and implementation of optimized practice in health care – fields that could not be any more tied to the choices and well-being of our patients? We can make the best innovation for health care in the world, but if our patients don’t know about it, or choose not to use it, what value does such an innovation have? I think that is where I would like to be, and that’s where clinician scientists can come in to effect change on individual, and potentially systematic levels.
So far, I have greatly enjoyed my time with the center – I have settled in and found everyone I meet to be engaging and supportive of my ideas and research focus. I really feel that I am among my people. Moreover, I have learned several new skills and ways of approaching problems, and have developed my networking ability in the mere few months that I have been here more than I had in my four years of undergrad or two years of medical school. My mentor, Dr. Rutten, and everyone else I’ve worked with so far have been incredibly welcoming and wonderfully helpful. I am absolutely sure that there are others in the center who would be just as excellent mentors to PhD or MD/PhD students. I hope that more of the faculty will offer to mentor graduate students – I like to think there is value for the mentors as well as the students in these relationships. I also believe, in the age of big data, that we need more students interested in this type of work. Interest in research, however, cannot stand without supportive mentorship.
My path is constantly evolving, but with the support of my mentor and the Mayo Clinic Kern Center for the Science of Health Care Delivery, I believe I will achieve my career goals. But in the end, what it’s all really about is meeting the needs of our patients, unmet as they often are, and in doing so, I hope to join my colleagues in improving health care in a sustainable and viable way.