Narbe Mardirossian
About Narbe Mardirossian
Narbe Mardirossian Chief Technology Officer
Narbe Mardirossian serves as the Chief Technology Officer at Terray Therapeutics. In this role, he leads the company's technical strategy, focusing on the integration of chemical experimentation and computation to drive drug discovery and development. As part of the leadership team, he works to ensure that Terray Therapeutics leverages advanced technological methodologies to innovate within the therapeutic domain.
Narbe Mardirossian's Academic Qualifications
Narbe Mardirossian holds a Ph.D., underscoring his advanced expertise in technology and scientific research. His rigorous academic background provides a solid foundation for his work in integrating computational techniques with chemical experimentation. This educational foundation supports his innovative approach to drug discovery at Terray Therapeutics.
Narbe Mardirossian's Background in Technology and Scientific Research
Narbe Mardirossian has a background rooted deeply in technology and scientific research. His experience spans various facets of scientific inquiry and technological application, enabling him to bridge the gap between experimental chemistry and computational models. This dual expertise is pivotal in his role at Terray Therapeutics, where he focuses on enhancing the drug discovery process.
Narbe Mardirossian at Terray Therapeutics
Narbe Mardirossian is an influential member of the leadership team at Terray Therapeutics. His work combines chemical experimentation with computational techniques to advance the field of drug discovery. By integrating these two approaches, he aims to expedite the development of new therapeutics and improve the overall efficiency of discovery pipelines.
Integration of Chemical Experimentation and Computation
Narbe Mardirossian is involved in the innovative integration of chemical experimentation and computation to drive drug discovery at Terray Therapeutics. This cutting-edge approach allows for more precise and efficient identification of potential drug candidates. By leveraging both chemical and computational methods, the process becomes more streamlined and effective.