Dr. Adithya Polasa is a seasoned computational chemist with over seven years of experience in protein research and biotherapeutics development. He currently serves as a Computational Protein Engineering Scientist in Insilco Antibody Development at Boehringer Ingelheim, where he leads initiatives to design and optimize antibodies using cutting-edge computational methods.

Dr. Polasa's expertise spans a wide range of technical skills, including molecular modeling, docking, molecular dynamics simulations, and machine learning. He is proficient in using various software tools like Autodock, MOE, Maestro, NAMD, VMD, PyMol, BioLuminate, TensorFlow, PyTorch, scikit-learn, Keras, Biopython, and more.

As a Computational Scientist at Schrödinger, I specialize in bridging the gap between cutting-edge machine learning and biotherapeutic discovery. With a Ph.D. in Biochemistry and extensive experience in computational protein engineering, I focus on developing advanced in silico strategies to accelerate drug development.

My expertise lies in leveraging generative AI and deep learning models—including RFdiffusion and ProteinMPNN—to predict antibody structures, optimize binding affinities, and streamline high-throughput screening. My background is deeply rooted in molecular dynamics, protein characterization, and physics-informed modeling, allowing me to approach complex biological challenges with a rigorous, data-driven perspective.

Prior to Schrödinger, I drove in silico antibody development projects at Boehringer Ingelheim, where I implemented machine learning algorithms to enhance predictive modeling and optimize antibody design. My earlier research journey includes developing a physics-based binding free energy estimator at the University of Arkansas and leading the development of drug design software applications at BINDINSILICO LLC. My entrepreneurial and research efforts have been recognized through renowned journal publications and the NSF I-Corps award.

I am deeply passionate about advancing human health through innovative computational chemistry and fostering collaborative research that pushes the boundaries of in silico drug discovery. I thrive at the intersection of structural biology and artificial intelligence, dedicated to transforming how we design the next generation of life-changing therapeutics.