ATOM Tech Team Spotlight: Dr. Neha Murad

July 3, 2019

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Neha Murad, Ph.D., is a Biomathematician and a Postdoctoral Researcher at ATOM. Neha has a keen interest in the biomedical applications of mathematics and enjoys spreading awareness about this field with diverse audiences. She actively participates in science outreach activities and has volunteered with programs like Skype a Scientist. Neha has also recently been an invited speaker at an undergraduate level mathematics course at Haverford College, Pennsylvania.

Neha was first exposed to the scope of mathematical applications in biology during her M.S. studies in Applied Mathematics at Jadavpur University. Prior to that she had earned a B.S. in Mathematics with honors, graduating with a First Class distinction from St. Xavier’s College. Neha earned a second M.S. in Mathematics from the University of Iowa where she explored various applications of mathematics before transferring to the Biomathematics Ph.D. program at North Carolina State University to further explore the research areas of ecology, epidemiology and personalized medicine.

Neha joined GSK and the ATOM Pharmacokinetics (PK) team in July 2018. Her expertise in biomathematics is a key asset in ATOM’s computational modeling efforts, specifically physiologically-based pharmacokinetics modeling.

Understanding PK properties such as absorption, distribution, metabolism and excretion (ADME) is crucial to determining optimal drug dosage in patients, thus PK is an important optimization criterion in the process of drug discovery. As a member of the PK Modeling team, Neha has built a PK pipeline that combines traditional mathematical models and machine learning models to build physiologically-based PK models that provide valuable insight into ADME properties of drugs. ATOM combines this predictive PK capability with safety, efficacy models to generate novel drug candidates in silico.

ATOM’s current PK pipeline can predict PK properties and plasma concertation time profiles directly from the molecular structure of a drug. The PK pipeline has been validated using experimental data and is in the process of further validation along with the addition of prediction uncertainty quantification features. The pipeline will ultimately be made openly available to the broader research community.

Neha has played a pivotal role in ATOM’s predictive PK efforts and will be presenting her work at the Drug Metabolism Gordon Research Conference in Holderness, New Hampshire from July 07 - July 12, 2019.