During the recently concluded 2026 APEC Business Advisory Council China Forum,华熙生物董事长赵燕One sentence sparked widespread attention: "Traditionally, cultivating strains took one to two years. With AI-driven simulation, we can now achieve results in just a few months—and as quickly as a few days."

从“一到两年”到“短短几天”，这不是实验室里的个案突破，而是一项已经广泛应用于研发全流程与整条供应链的成熟技术。AI is rapidly reshaping the fundamental logic of biomanufacturing.

[从“试错”到“推演”] .

Traditional strain cultivation relies heavily on experience and trial-and-error. Screening for a high-yield strain requires researchers to test fermentation performance one by one from a vast pool of candidates, with each round of experiments taking months.It took BLOOM Biotech two full years to screen its first microbial strain.。

合成生物技术For the first time, efficiency has been significantly improved—enabling new bacterial strains to be developed in just two to three months through gene editing, genetic testing, and big data. AndAIits addition has propelled this process to a new level.

For over two decades, Bloomage Biotech has focused on synthetic biology, accumulating a vast repository of primary experimental data. This data serves as the fuel for training AI private models, enabling predictive insights into strain development and compressing lengthy trial-and-error cycles into intelligent simulations.

This "data + algorithm" approach, replacing "trial-and-error + waiting," is transforming the core R&D process in biomanufacturing.

[AI Race Among Industry Leaders]

Bloomage Biotechnology is not the only biomanufacturing leader with an AI strategy.

Cathay BiotechBy investing in Molecular Heart and building a high-throughput R&D platform, the company is actively advancing its "AI + Biomanufacturing" strategy. As one of the few global biomanufacturers with an end-to-end footprint spanning from strain fermentation to commercialization, it holds a leading global market share in its core product, adipic acid (long-chain dicarboxylic acid). Its bio-based polyamides are now deployed in battery materials and automotive lightweighting applications. Expansion projects in Wusu, Taiyuan, and other locations are progressing steadily, underscoring the company's strong confidence in the long-term growth of the biomanufacturing sector.

智源深澜This pushes AI to the forefront—its development of the world's first industrial-grade, programmable continuous protein evolution platform enables an AI-driven, self-iterating biological data factory. The 3.0 era of AI for Science has moved from concept to reality, transforming enzyme evolution from "manual screening" to "AI-led autonomous iteration."

Academia is also validating the efficiency advantages of AI.Tsinghua University Professor Zhang Chong will appear at the exhibition, share the report. His team proposed a high-throughput parallel DBTL strategy to enable low-cost testing and data learning for thousands of genotypes; they invented microfluidic-based technologies and equipment for high-throughput testing of strain cultivation process data, significantly improving the efficiency of acquiring industrial phenotypic data for strains.中国科学院天津工业生物技术研究所研究员夏建业博士将亮相展会现场Share Report. Over four years, our team developed a high-throughput micro-parallel reactor through three generations of iteration, overcoming key challenges in miniaturization and parallel control. The latest third-generation unit is just one-fifth the size of traditional benchtop reactors, supports 12 parallel channels, and can be operated by a single user—delivering several-fold efficiency gains. Future upgrades will expand capacity to 24 channels.

AI's role in strain R&D is to transform experience-driven processes into data-driven ones. Fermentation data, strain information, and metabolic pathway data accumulated by industry leaders are becoming core assets.

This is an irreversible trend. From Bloomage Biotech to Tsinghua Tsinow, from BGI Shenzhen to the Tianjin Institute of Industrial Biology, leading companies and research institutions are all betting on the same direction—Whoever first closes the loop from data to model, strain to product will gain a competitive edge in the next phase of bio-manufacturing.

论坛部分日程

AI-Driven High-Throughput Biological Manufacturing & Automated Equipment

11:00-11:20 Report: AI + Automation Lab (Lab 4.0): Building a Closed-Loop R&D System for Biomanufacturing and Industrialization Practices

Guest: Xia Jianye, Researcher and Director of the Center for Intelligent Biomanufacturing at the Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences; Deputy Chair of the Committee on Biochemical Engineering Modeling and Control, Chinese Society for Microbiology

11:20-11:40 Report: High-Performance Strain Development Driven by High-Throughput Genotype–Phenotype Association (HT-GPA): From Microfluidics to Whole-Genome Data Learning

Guest: Zhang Chong, Tsinghua University. Tenured Professor; Vice Dean of Tanwei College; Executive Deputy Director of the Beijing Key Laboratory of Recombinant Protein Synthesis and Biomanufacturing; Secretary-General of the Microbial Breeding Branch of the China Bio-fermentation Industry Association.

11:40-12:00 Report: AI-Assisted Intelligent Analysis of Experimental Data: Multi-Omics Data Mining and Target Discovery

12:00-12:20 Report: From Automation to Intelligence – How AI is Reshaping R&D and Production Capacity in Biomanufacturing

2026 (2nd) EMBC Bio-Manufacturing Industry Conference & Exhibition (Summer)

2026 (2nd) EMBC Bio-Manufacturing Industry Conference & Exhibition (Summer)will be8 27-28Held in Shanghai, the exhibition will invite2000+ Attendees,100+Speaker,20+Premium exhibitors, featuring "Exhibitions - Conferences - Meetings - EventsFour core modules focused on "breakthroughs in fundamental research + cross-domain industrial implementation."

Exhibition FocusMedical Aesthetics, Bio-based Materials & Green Chemicals, Food, Agriculture, and AI EmpowermentExhibitor recruitment is now open. Contact us for details on participating in the exhibition.