Analytical Science & Technology (Bioprocess Data Integration)

Digitalising Biomanufacturing for Better Bioprocesses

The Bioprocess Data Integration group creates computational and data-driven methods and frameworks to digitalise the process development for biomanufacturing processes. By developing and applying a variety of modelling approaches, we aim to better understand biological mechanisms across a wide spectrum of scales. Hence, our work accelerates decision-making and translation, enabling the faster, smarter, and cost-effective development of innovative biotherapeutics.

Focus Areas

  • Computational metabolic modelling
  • Natural Language Processing (NLP)
  • Scientific software development
  • Immune cell manufacturing modelling
  • Process Modelling and Techno-Economic Analysis (TEA)

Our Capabilities

Computational Metabolic Modelling for Culture Media Design

  • Genome-scale metabolic modelling integrated with experimental metabolomics to design and/or refine culture media formulations
  • Accelerates development process using simulation; enables rapid scenario screening and Design of Experiments (DoE) guided iterations

NLP for Biological Relationship Extraction

  • Mapping cellular signalling networks by building interactive knowledge graphs for Critical Quality Attributes (CQAs), biomarkers, and pathway insights
  • Fine-tuning to extract more nuanced biochemical relations (phosphorylation, ubiquitylation, ligand–receptor)

Immune Cell Modelling for NK Cell Manufacturing

  • Immune cell-specific genome-scale metabolic modelling linking Critical Process Parameters (CPPs) to cell growth, metabolism, and functional potency
  • Predictive in silico scale-up models to reduce reliance on costly trial-and-error experimentation and enable rational bioprocess design, and reduce the high cost and variability in large-scale production
  • Generating Integrated multi-modal datasets combining growth kinetics, transcriptomics, immunophenotyping, and functional readouts
  • Building a modelling framework that captures yield-function trade-offs, supporting more robust, scalable, and reproducible NK cell manufacturing processes

Process Modelling and TEA of Biomanufacturing Processes

  • Process modelling and TEA at the conceptual design stage to evaluate the feasibility of variations of process designs, calculate CAPEX and OPEX, and identify bottlenecks
  • Performing sensitivity analyses and multi-objective optimisation to understand the effect of different parameters on the process design and guide cost/sustainability trade-offs

 

Our Technologies

Metabolic Modelling Software Suite

  • An interactive desktop application that performs metabolic and enzyme-constrained simulations to predict flux distributions and growth behavior
  • Uses a base metabolic model combined with experimental growth and nutrient data to generate accurate, data-driven predictions
  • Enables the user to perform in-silico DoE parameter testing, thus significantly shortening the time to optimise media formulations
  • Results are displayed using images, charts, and tables for rates/flux, protein balance, heatmap & Z-score, DoE, and carbon analysis

NLP-Driven Cell Signalling Knowledge Graphs

  • An interactive graph-based web application to explore that includes the pipeline to parse PubTator-annotated corpora, extract entity–relation triples, and render cell signalling networks as knowledge graphs
  • Entities are represented as nodes and relations as edges in the graph

 

The Team

Zach Pang (resized)

Dr Zach Pang

Senior Scientist II
Group Leader

zach_pang@a-star.edu.sg

Sun Zhendong (resized)

Dr Sun Zhendong

Scientist

sun_zhendong@a-star.edu.sg

Toh Jia Ying (resized)

Dr Toh Jia Ying

Scientist

tohjy@a-star.edu.sg

Our Track Record

Significant Milestones

  • Industry Translation, Media Design Spinoff & Licensing: Creation of an A*STAR Spinoff company, AuctuCel Pte Ltd

Featured Publications

  • Sammueal Jun Kai Ong, Matthew Myint, Sean Chia, Chee Fan Tan, Yi Fan Hong, Meiyappan Lakshmanan, Ying Swan Ho, Thomas T. Wheeler, Xuezhi Bi, Ian Walsh and Kuin Tian Pang (2025) Health benefits of polysaccharides in red algae: a comprehensive review. Food Frontiers 1-26
  • Ian Walsh †, Thimo Ruethers †, Sim Lyn Chiin, Gavin Teo, Shi Jie Tay, Corrine Wan, Kuin Tian Pang, Sean Chia, Andreas L. Lopata and Beiying Qiu (2025) Differentiation of Fish Species Based on O-Acetylated N-Glycan Fragments Using LC-IM-MS to Combat Seafood Adulteration. Applied Food Research 5(2): 101428
  • Sammueal Ong Jun Kai, Matthew Myint, Chee Fan Tan, Yi Fan Hong, Meiyappan Lakshmanan, Ying Swan Ho, Thomas T. Wheeler, Xuezhi Bi, Ian Walsh, Sean Chia and Kuin Tian Pang (2025) Is green algae polysaccharide a 'green path' to health? Algal Research 91: 104268
  • Hanzhang Zhou, Larry Sai Weng Loo, Francesca Yi Teng Ong, Xuanming Lou, Jiahao Wang, Matthew Khine Myint, Aaron Thong, Deborah Chwee San Seow, Mario Wibowo, Shengyong Ng, Yunbo Lv, Leng Gek Kwang, Rachel Z Bennie, Kuin Tian Pang, Renwick C J Dobson, Laura J Domigan, Yoganathan Kanagasundaram and Hanry Yu (2025) Cost-effective production of meaty aroma from porcine cells for hybrid cultivated meat. Food Chemistry 473: 142946
  • Hoi Kong Meng, Kuin Tian Pang, Corrine Wan, Zi Ying Zheng, Qiu Beiying, Yuansheng Yang, Wei Zhang, Ying Swan Ho, Ian Walsh and Sean Chia (2024) Thermal and pH stress dictate distinct mechanisms of monoclonal antibody aggregation. International Journal of Biological Macromolecules 282: 136601
  • Kuin Tian Pang, Yi Fan Hong, Fumi Shozui, Shunpei Furomitsu, Matthew Myint, Ying Swan Ho, Yaron R Silberberg, Ian Walsh and Meiyappan Lakshmanan (2024) Genome-scale modeling of CHO cells unravel the critical role of asparagine in cell culture feed media. Biotechnology Journal 19(11): e202400072

† Authors contributed equally to this work.

 

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