(7il) Dynamic Systems Spanning Engineering to Medicine

Anwesha Chaudhury, PhD

John Higgins’ group (February 2015-present)

Center for Systems Biology, Massachusetts General Hospital; Pathology, Massachusetts General Hospital; Systems Biology, Harvard Medical School

Email: achaudhury@mgh.harvard.edu, anwesha_chaudhury@hms.harvard.edu

Education

Doctor of Philosophy

December 2014
Department of Chemical and Biochemical Engineering

Rutgers-The State University of New Jersey, NJ, USA

Masters of Technology

August 2010

Department of Chemical Engineering

Indian Institute of Technology, Kharagpur, India

Bachelors of Technology

June 2008

Department of Chemical Engineering

West Bengal University of Technology, India

Research Interests:

The overarching theme of my research is to define and delineate complex dynamic systems -- both biological and synthetic -- in terms of tractable yet accurate mathematical models. My diverse training in engineering and medicine puts me in a strong position to make significant progress toward these goals. I firmly believe that we are at an inflection point in our ability to minutely quantify enough aspects of complex systems and to computationally use vast troves of such data to make increasingly accurate predictions about even systems that are not completely understood. The ongoing advancements in clinical measurements and rapid growth in the availability of computational resources presents a unique opportunity to develop inexpensive tools that circumvent inefficient manufacturing process operations and streamline the diagnosis and treatment of diseases in patients. My current research is working toward such a clinical tool that takes advantage of fine-grained but readily available blood cell measurements, and predicts risk for a set of specific diseases for individual patients. In the short-term, I aim to continue developing data-driven population dynamics models for blood cells to predict onset and risk of several important diseases. Using this approach, I also intend to develop hypotheses for the underlying molecular and cellular mechanisms of disease conditions, which can thereafter be investigated using experiments. I plan to integrate these models for the various lineages of white blood cells in order to investigate the crosstalk in the immune system - a subject with vast potential applications.

From a process systems perspective, I intend to continue developing mathematical models for particulate systems, which can then be utilized for process control and optimization. I have significant experience with developing numerical techniques to solve complex partial differential equations, which I would like to continue incorporating into my research. One of my primary goals is to develop realistic models, which can actually be used for practical applications. With this intent in mind, I plan to continue collaborating closely with experimentalists in order to use systems engineering with a practical application.

Research experience:

I am a Chemical Engineer by training, and have worked on a wide variety of research projects within the field, and in several other realms of basic science and engineering. The common denominator across all my research experiences is mathematical modeling and systems engineering. From working on non-linear system dynamics pertaining to reaction engineering, to developing mechanistic mathematical models for improving processes operation in pharmaceutical drug manufacturing, and now working with clinical data to understand human pathophysiology, I have been interested in different fields where I feel I may be able to make a significant contribution using the core skill sets of systems modeling. While working as a theoretician during my PhD tenure, I collaborated closely with my experimental colleagues in order to develop realistic mathematical models and better understand the underlying assumptions required for the models. Towards the end of my PhD, I was drawn into the enigma of systems biology, which led me to switch fields and broaden the applications of my mathematical modeling skills. In my current position, I am working in an extremely multi-disciplinary environment where I am leveraging my engineering training and expertise to develop models that can improve disease prognosis and alleviate the shortcomings of a delayed therapeutic intervention while also testing hypotheses and revealing details about molecular and cellular disease mechanisms. A specific disease condition -- sickle-cell disease -- has physical and chemical mechanisms with deep relevance to my chemical engineering training, and I am studying the biorheological properties of blood precipitating a clinical sickle cell vaso-occlusive crisis. Our work motivates a collaboration with single-cell assay experts to develop a novel method to identify biomarkers for sickle cell disease. During my PhD and postdoctoral career, I have received several awards and grants, demonstrating an ability to secure external funding and interest in my research.

Teaching Interests:

In addition to research, I have a keen interest in mentoring students and teaching core as well as advanced engineering topics. During the tenure of my PhD I was a teaching assistant (TA) for several courses including: Transport phenomenon-I, Junior design and economics, and Process control. As a postdoctoral research fellow, I have co-instructed a Health Science and Technology course (Matlab for Medicine) for medical students, which is a required core course for the Harvard-MIT MD curriculum. I have derived immense pleasure from teaching and helping undergraduate students learn the chemical engineering curriculum. During my PhD tenure, I have mentored more than five undergraduate and masters students, who have successfully performed research and have co-authored publications in leading peer-reviewed journals. During my postdoctoral training, I have helped supervise two graduate rotation students and an undergraduate summer intern, as well. I have always encouraged undergraduate students to pursue research in addition to their coursework. I am very comfortable with teaching the core chemical engineering subjects, and I would be very excited to design additional courses that combine the knowledge of chemical engineering, mathematics and statistics.

Awards and Honors:

• October 2016, Life Science Research Foundation (LSRF) postdoctoral fellowship, Good Ventures fellow.
• May 2015, Awarded the prestigious Outstanding Graduate Student Award by the School of Engineering, Rutgers University in recognition of the achievements as a graduate student.
• June 2014, Awarded the Baden-Wuerttemberg Scholarship to pursue research at
• University of Konstanz, Germany.
• July 2012, Awarded the Marshall Plan Fellowship to pursue research at TU Graz, Austria.
• May 2012, Awarded the best poster prize at the New Jersey Pharmaceutical Association for Science and Technology graduate student poster competition.
• September 2010, School of Engineering Fellowship, Rutgers University, USA.

Selected publications: (total 22 published, 9 first author publications)

• A. Chaudhury, L. Noiret, J. M. Higgins, White Blood Cell Population Dynamics for Risk Stratification Of Acute Coronary Syndrome, Under Review.
• A. Chaudhury, A. Tamrakar, M. SchÓ§ngut, D. Smrčka, F. Å těpánek, R. Ramachandran, Multidimensional population balance model development and validation of a reactive granulation process, Industrial Engineering & Chemistry Research, 2015, 54(3).
• A. Chaudhury, A. Armenante, R. Ramachandran, Compartment based population balance modeling of a high shear wet granulation process using data analytics, Chemical Engineering Research and Design, 2015, 95.
• A. Chaudhury, H. Wu, M. Khan, R. Ramachandran. A mechanistic population balance model for granulation processes: Effect of process and formulation parameters. Chemical Engineering Science, 2014, 107.
• A. Chaudhury, I. Oseledets, R. Ramachandran. A computationally efficient technique for the solution of multi-dimensional PBMs of granulation via tensor decomposition. Computers and Chemical Engineering 2014, 61.
• M. Sen, A. Chaudhury, R. Singh, J. John, R. Ramachandran, Multi-scale flowsheet simulation of an integrated continuous purification-downstream pharmaceutical manufacturing process, International Journal of Pharmaceutics, 2013, 445(1-2).
• A. Chaudhury, A. Niziolek, R. Ramachandran. Multidimensional Mechanistic Modeling of Fluid Bed Granulation Process: An Integrated Approach. Advanced Powder Technology, 2012, 24.
• A. Chaudhury, S. Chakraborty, Dynamics of Mixing-Limited Pattern Formation in Non-Isothermal Homogeneous Autocatalytic Reactors: a Low-Dimensional Computational Analysis, Industrial Engineering and Chemistry Research, 2011, 50 (8).

Book chapters:

• A. Chaudhury, D. Barrasso, Daniel A. Pohlman, James D. Litster, R. Ramachandran, Mechanistic modeling of high shear and twin screw mixer granulation processes, Modeling of pharmaceutical unit operations in solid dosage forms, Elsevier, 2016, In Press.
• A. Chaudhury, M. Sen, D. Barrasso, R. Ramachandran, Population balance models for pharmaceutical processes, Handbook in Process Simulation and Data Modeling in Solid Oral Drug Development and Manufacture, Humana Press, 2016, 43-83.

Teaching and research mentoring experience:

September 2011-June 2012; September 2014-December 2014, Teaching assistant, Department of Chemical and Biochemical engineering, Rutgers University

(Courses taught: Transport phenomenon I, Junior design, Process control).

August 2016; August 2017, Teaching assistant, Health Science and Technology, Harvard Medical School (Course: Matlab for Medicine).