How is Data Science Applicable to Modern Healthcare?
An Interview With Amrita Mohan — Director, Clinical Bioinformatics at CHDI Management, Inc.
Over the past few decades, improvements in medicine and molecular biology in conjunction with reducing costs of data generation platforms such as genomics, proteomics, imaging, electronic health systems have given led to an exponential rise in data related to disease phenotypes and pathology. Bioinformatics in particular, and Healthcare Informatics in general are two leading specialized areas that involve intensive data science capabilities to analyze this deluge of data before transforming it into testable hypotheses and novel medical insights aimed to improve patient care.
In our conversation with Amrita, we picked her brain to inquire more about the field and her research. Amrita has a background in Information Technology with focus in Molecular and Cell Developmental Biology. Her training over the years has enabled her to develop a portfolio of pre-clinical and clinical research modeling methods applicable in oncological and neurodegenerative diseases.
1.
How is data science applicable to modern healthcare? How did you enter this space?
“Data Science in my opinion is a very multidisciplinary cross functional space.”
A data scientist can come with a life science, a financial engineering or economics background. An individual’s domain expertise can serve as the foundation for a more specialized career as a data scientist (e.g. in healthcare, financial technologies or public policy).
Bioinformatics (my area of specialization) is a specialized Data Science area and strongly relies on a combination of Life Sciences, Statistical Sciences and Information Technology. Using sophisticated computational techniques one can explore a variety of questions in large genomics, clinical etc dataset in support of healthcare. However, given the inherent biases and complexities present within such datasets it’s important to be cautious and know how to distinguish true biological phenomena from experimental artifacts (i.e. noise).
I transitioned to the area of BioInformatics when there weren’t many mature oppurtunities in india. At the time, as a technology major in early 2000s, it was difficult to easily pivot to a life science/medical R&D space. Therefore to continue building expertise in the area, while pursuing a four year degree in Information Technology I undertook many independent projects in the biology space (experimental as well as computational). Subsequent to my undergraduate degree, I also obtained a Masters and Doctorate to further hone my training and skills in the field of Bioinformatics.
2.
What are your current projects?
After spending four years in oncology, I moved to my current organization and had the opportunity to shift gears and focus on a rare human genetics disorder — Huntington’s Disease (HD).
HD is a familial, neurological genetic disorder caused by a mutation in the huntingtin (Htt) gene. A child has a 50–50 chance of acquiring a mutant HTT gene if either of his/her parent is also carrier of this gene. Currently there are no known cures but many researchers and institutions across the globe are working towards identifying ways to ameliorate the symptoms and progression of this disease. The team I currently work with aims to understand clinical manifestation of HD as well as to improve clinical opportunities for HD patients by enabling new therapies.
More specifically, in my current role I maintain a portfolio of clinical computational projects that leverage HD clinical data to understand disease progression and identify refined disease stages. Data largely is drawn from HD clinical trials that accumulate behavioral, neurological, imaging and other types of data from multiple participants. Among other things, such large datasets are typically mined to understand HD clinical phenotypes, identify new opportunities to medically intervene in HD or even decode why some patients did (or did not) respond to a drug.
3.
What are possible career routes one can take as a Bioinformatics Data Scientist and how can one get there?
Currently there are certainly a lot of opportunities for young folks training in technical areas such as Computer Science, Informatics, Statistics etc to transition to Bioinformatics. Besides sound technical skills, however they will also need to build subject matter expertise in a basic science field such biology or medicine. If the goal is to join academia or a biotechnology/pharmaceutical company in an R&D function, then a doctorate would be advisable. Alternatively a masters in Bioinformatics (or Medical Informatics, Statistical Genetics etc) would also offer excellent career trajectories in product/platform development focused enterprise.
As for which universities to look out for to pursue graduate studies — my general recommendation is to identify an area of interest and pursue graduate studies with leading academicians/clinicians in that space. This approach is somewhat different from deciding where to pursue an MBA or Medicine. Since Bioinformatics is still a research oriented area it is advisable to seek opportunities to collaborate and publish impactful research findings with pioneering scientists. Having said that, Stanford University, Indiana University (my alma mater), Carnegie Mellon, Georgia Tech all offer various degree programs for those interested in specializing in Bioinformatics (and related areas).
4.
What is your advice to young generation interested in pursuing a career in Bioinformatics?
I think remaining open minded and a preserving deep love for robust data analytics are very important for succeeding this area. If I had to give advice to my 20 year old self it would definitely be to not be afraid to try new ideas and to quickly learn to develop creative ways to address new, unexplored problems.
Connectedreams.com is an online data-driven, cultural context-aware networking platform, bridging the role model & mentorship gap.
- Request an Invitation and Follow us on Facebook and Medium to get weekly updates on useful professional resources to advance your career.
