Shanghai, China | August 27–28, 2026 — As artificial intelligence continues to reshape biotechnology R&D and industrialization, the convergence of AI, enzyme engineering, and synthetic biology is opening new possibilities for biomanufacturing.

Hzymes Biotech is pleased to announce that Dr. Guangyu Yang, Founder and Chairman of Hzymes Biotech and Researcher at Shanghai Jiao Tong University, has been invited to speak at the 2026 Ecom Healthcare Biomanufacturing Conference & Exhibition (Summer), taking place on August 27–28 in Shanghai.

Dr. Yang will deliver a keynote presentation at the session “Applications of Artificial Intelligence in Biomanufacturing R&D and Industrialization”, sharing Hzymes’ perspectives on how AI can accelerate enzyme discovery, engineering, optimization, and industrial implementation.

AI Applications in Biomanufacturing R&D & Industrialization

Keynote Presentation: AI + Specialty Enzyme Engineering and Industrialization in the Era of Synthetic Biology

Featured Interview: AI Applications in Biomanufacturing R&D & Industrialization

Date: August 27, 2026
Location: Minhang District, Shanghai, China
Speaker: Dr. Guangyu Yang, Founder & Chairman, Hzymes Biotech; Researcher, Shanghai Jiao Tong University

From AI Algorithms to Industrial Enzyme Solutions

The development of synthetic biology is increasingly moving beyond individual biological components toward engineering complex biological systems with predictable and scalable performance. Enzymes, as core biocatalysts in many biomanufacturing processes, are at the center of this transformation.

Traditional enzyme engineering often depends on iterative cycles of sequence design, experimental screening, characterization, and optimization. While effective, this approach can become increasingly time- and resource-intensive as the sequence space expands.

AI is introducing a new paradigm.

By combining large-scale enzyme sequence data, structural information, computational modeling, machine learning, and experimental validation, researchers can explore enzyme sequence space more efficiently and identify promising candidates with greater precision.

For industrial applications, however, prediction alone is not enough.

The real challenge is to connect AI-based prediction with experimental enzyme engineering and scalable manufacturing, translating computational insights into enzymes that deliver reliable activity, stability, specificity, and manufacturability.

This is where Hzymes is focusing its efforts.

Building an AI-Enabled Enzyme Engineering Platform

Hzymes Biotech has been developing an integrated technology platform covering enzyme gene resource discovery, directed evolution, and AI-assisted enzyme design.

The goal is to connect different stages of enzyme development into a more efficient workflow:

Enzyme Resource Discovery → AI-Assisted Design → Experimental Validation → Directed Evolution → Process Optimization → Industrial Manufacturing

Rather than treating AI as an isolated computational tool, this approach aims to integrate AI with experimental capabilities and industrial production technologies.

This integration is particularly important for specialty enzymes, where performance requirements can vary significantly depending on the application, substrate, reaction conditions, and downstream manufacturing process.

Through the combination of computational prediction and wet-lab validation, AI can help narrow down candidate space, guide mutation design, and accelerate the identification of enzymes with desired properties.

Infographic 1：AI + Enzyme Engineering Workflow

AI + Enzyme Engineering: From Local Optimization to Global Navigation

The potential of AI in enzyme engineering extends beyond simply predicting whether a mutation may improve enzyme performance.

One emerging direction is to use AI models to navigate the broader sequence landscape, helping researchers identify promising regions of enzyme sequence space that may be difficult to reach through conventional screening alone.

This concept has also been explored through emerging AI-driven approaches such as CATNIP, which demonstrates how machine learning can support a more global navigation strategy for enzyme prediction and engineering.

Instead of relying solely on incremental optimization around a known sequence, AI-enabled approaches have the potential to help researchers explore a much broader solution space.

For enzyme engineering, this could mean moving toward a development paradigm characterized by:

• Faster candidate discovery
• More rational mutation design
• Reduced experimental screening burden
• Broader exploration of enzyme sequence space
• Improved integration between computational design and experimental validation

However, successful industrialization still requires more than computational performance. Enzymes ultimately need to work under real process conditions and meet practical requirements for activity, stability, specificity, yield, scalability, and cost.

Infographic 2：AI × Enzyme Engineering

From Scientific Innovation to Industrialization

The transition from laboratory discovery to industrial application remains one of the most important challenges in biomanufacturing.

For AI-designed enzymes, this means establishing a complete development loop in which computational models and experimental data continuously inform each other.

A potential workflow can be illustrated as:

AI Prediction → Candidate Selection → Enzyme Expression → Activity & Stability Testing → Directed Evolution → Process Validation → Scale-Up

Each experimental cycle can generate new data, which in turn can improve subsequent computational predictions.

This creates a design–build–test–learn (DBTL) cycle that can continuously improve enzyme engineering efficiency.

For Hzymes, the combination of AI-driven enzyme design, directed evolution, enzyme expression, and industrial-scale manufacturing represents an important direction for building the next generation of biocatalytic solutions.

Connecting AI, Synthetic Biology, and Biomanufacturing

The upcoming Ecom Healthcare Biomanufacturing Conference brings together researchers, biotechnology companies, manufacturers, investors, and other stakeholders across the biomanufacturing ecosystem.

With more than 2,000 attendees, 100+ speakers, and 20+ exhibitors, the 2026 conference will focus on scientific breakthroughs and cross-disciplinary industrial applications across areas including:

• Biopharmaceuticals and healthcare
• Biomaterials and green chemicals
• Food biotechnology
• Agricultural biotechnology
• AI-enabled biomanufacturing

For Hzymes, this provides an opportunity to exchange ideas with researchers and industry partners on how AI and enzyme engineering can contribute to the industrialization of synthetic biology.

The company will also participate in a dedicated thematic interview following Dr. Yang’s presentation, offering further perspectives on the opportunities and challenges of AI-enabled enzyme engineering.

Hzymes Biotech: Enabling the Next Generation of Biocatalysis

Hzymes Biotech focuses on the R&D, manufacturing, application, and technical services of enzymes and other core biological raw materials for biopharmaceutical and in vitro diagnostic applications.

By integrating enzyme resource discovery, directed evolution, AI-assisted design, and industrial manufacturing capabilities, Hzymes is working to shorten the path from enzyme innovation to real-world application.

As synthetic biology continues to evolve, the next competitive frontier may not simply be discovering new enzymes, but developing the ability to design, optimize, manufacture, and apply enzymes faster and more intelligently.

At the 2026 Ecom Healthcare Biomanufacturing Conference, Hzymes looks forward to sharing its perspective on this transformation and exploring new opportunities for collaboration across the AI, enzyme engineering, and biomanufacturing ecosystem.

Meet Hzymes Biotech in Shanghai on August 27–28, 2026, and join the conversation on the future of AI-powered enzyme engineering and biomanufacturing.

Explore AI-Enabled Enzyme Engineering with Hzymes

Interested in AI-assisted enzyme design, enzyme engineering, or customized biocatalytic solutions?

Talk to our technical team to explore potential collaboration opportunities.

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