MoU Signing between ICGEB ND & Neoh Tech Pvt Ltd
Strategic MoU to accelerate the development of next-generation molecular tools through the integration of Artificial Intelligence and Synthetic Biology
New Delhi, India, 10 Sep 2026: ICGEB New Delhi and Neoh Technologies Private Limited have joined hands through a strategic Memorandum of Understanding (MoU) to advance next-generation biotechnology by integrating Artificial Intelligence (AI), machine learning and synthetic biology. The MoU was signed by Dr. Ramesh V. Sonti, Director, ICGEB New Delhi and Dr. Venkatachalapathy Pacha Dharma Naidu, Director, Neoh Technologies Private Limited at ICGEB New Delhi campus on 09 Sep 2026.
The collaboration will focus on the AI-guided engineering of thermostable enzymes for high-temperature DNA amplification. Enzymes used in DNA amplification are central to a wide range of molecular biology and sequencing applications. While current high-performance enzymes enable high-fidelity DNA synthesis, their thermal limitations can pose challenges for emerging workflows that require elevated operating temperatures and greater stringency. The project aims to address the thermal limitations of existing enzymes and develop robust molecular tools capable of maintaining high processivity and performance at elevated temperatures.
The ICGEB research teams from the Microbial Engineering Group and Translational Bioinformatics Group will deploy an automated Design-Build-Test-Learn (DBTL) platform combining AI-driven protein design, machine learning-guided redesign, rapid protein expression and high-throughput biochemical screening. Through iterative design and experimental validation, the partnership seeks to accelerate the development of improved enzymes for emerging DNA amplification and sequencing applications.
The collaboration represents a convergence of advanced computational methods and experimental biotechnology. By integrating AI and machine learning with high-throughput laboratory platforms, the partnership seeks to accelerate the traditionally time-intensive process of enzyme engineering and enable the systematic exploration of novel protein variants.
