From data to decisions: AI's emerging role in oligonucleotide development and manufacturing

Tuesday 08:00 PDT / 11:00 EDT / 16:00 BST / 17:00 CEST

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From data to decisions: AI's emerging role in oligonucleotide development and manufacturing

AI and machine learning (ML) are discussed with growing frequency in nucleic acid manufacturing, yet most concrete activity still sits in discovery rather than production. Separating genuine application from aspiration has become difficult, and manufacturing teams have had few opportunities to assess where these tools realistically contribute today.

This is a spinoff from the April 2026 Special Interest Group "Enhancing the Efficiency and Sustainability of Oligonucleotide Manufacturing," extending that discussion into where AI/ML earn a place in production. Nucleic Acid Insights has convened manufacturing, analytical, and supply chain experts to examine where these tools add value across oligonucleotide production, and where the field is not yet ready.

It will also examine the obstacles to building reliable predictive models for therapeutic design, and assess how realistic digital twins and agentic AI are for oligonucleotide manufacturing specifically.

Attend for insights into:

Where AI and ML add genuine value across oligonucleotide manufacturing today, and where the promise still runs ahead of the reality
What it takes for ML to support synthesis optimization, real-time impurity characterization during chromatographic purification, and supply chain decision-making
How realistic digital twins and agentic AI are for oligonucleotide production, and what would need to mature before they earn a place on the manufacturing floor

Bao Zhong Cai, PhD

Vice President of Oligonucleotide CMC at Gondola Bio

Bao Zhong Cai, PhD, is Vice President of Oligonucleotide CMC at Gondola Bio, with nearly three decades of experience in oligonucleotide drug development, CMC strategy, process development, and GMP manufacturing. Previously, Dr Cai spent nearly 28 years at Sarepta Therapeutics, formerly AVI BioPharma, where he held senior CMC and process development leadership roles and contributed to multiple IND and NDA submissions, including the first PMO NDA and the commercialization of three Duchenne muscular dystrophy therapies.

Srdan Masirevic, PhD

Computational Biologist and Machine Learning Scientist at A*STAR's Genome Institute of Singapore

Srdan Masirevic is a computational biologist and machine learning scientist at A*STAR's Genome Institute of Singapore, working under Dr Mile Sikic on generative AI and machine learning models for RNA structure prediction, RNA–small molecule binding, and tRNA-based therapeutic discovery. He earned his PhD in Biological Sciences from the National University of Singapore, focusing on structure-based drug discovery and molecular modeling of protein-ligand interactions. He previously worked with Procter & Gamble on antimicrobial and antiviral discovery. Starting in October 2026, he will join Singapore's National Initiative for RNA Biology and its Applications (NIRBA), focusing on predictive models for mRNA endosomal escape. He has published in journals including Cell Reports Physical Science, iScience, Frontiers in Microbiology, and Scientific Reports, and serves as a peer reviewer for the Journal of Computational Biophysics and Chemistry, Biophysical Journal, and Physical Chemistry Chemical Physics, as well as for conference submissions to AAAI.