Eshita Khera is the Journal of Pharmacology and Experimental Therapeutics Highlighted Trainee Author for October 2023. Dr. Khera earned her PhD in Chemical Engineering from the University of Michigan under the mentorship of Dr. Greg Thurber. The JPET article that earned her the honor of being selected as Highlighted Trainee Author is titled: “Mechanistically Weighted Metric to Predict In Vivo Antibody-Receptor Occupancy: An Analytical Approach” and is available at: https://doi.org/10.1124/jpet.122.001540.
Dr. Khera’s research is focused primarily on using in silico, in vitro, and in vivo tools to understand the intratumoral distribution of antibody-drug conjugates (ADCs), from both the perspective of the antibody and released payload, and reverse translate the learnings to develop guidelines for designing optimal ADCs. The highlighted work is a serendipitous product from the innovative integration of niche academic knowledge and industry practices – finding its humble beginnings as Dr. Khera’s graduate summer internship project at Novartis and eventually growing to become a part of her doctoral dissertation at the University of Michigan.
Currently, Dr. Khera is a Principal Scientist in Pharmacokinetic Sciences (PKS) Modeling & Simulation at Novartis Institutes for BioMedical Research, where she provides translational modeling support for ADCs and immuno-oncology therapies. In the discovery space, she uses Quantitative Systems Pharmacology (QSP) modeling to help guide the design and optimization of preclinical drug candidates, while in the development space, she uses QSP and population PK/PD to translate preclinical data to a recommended First-in-Human trial dose range.
The anticipated impact of Dr. Khera’s work can bear a significant impact on the clinical development of oncology drugs. With the launch of Project Optimus by the FDA, oncology drug development is undergoing a paradigm shift with increasing emphasis on optimizing clinical dosing strategy. Modeling plays a critical role in achieving this goal, particularly in the case of complex drugs such as ADCs and immuno-oncology agents where the drug relies on several interdependent kinetics before exerting its therapeutic action. By developing mechanistic QSP models that are physiologically relevant, Dr. Khera’s work holds the promise of not only aiding in dose optimization in the development space but also guiding rational drug design in the discovery space, which would ultimately cascade to efficient development of highly optimized oncology therapeutics.
In Eshita’s spare time, she enjoys sailing, nature hikes, and reading. She also enjoys experimental baking (using friends and coworkers as taste testers).