BIOTEC × KMUTT · BANG KHUN THIAN
One research environment. Two connected laboratories.
The collaboration connects upstream biological understanding with the engineering needed to translate it: biosciences and systems biology identify, model and design; biopharmaceutical engineering develops, scales, purifies and prepares production under demanding quality conditions.
Use genomics, proteomics, systems biology and bioinformatics to find mechanisms and candidates.
Connect cell or microbial design with fermentation, monitoring, downstream processing and scale-up.
Move from analysis and laboratory evidence toward pilot production, training and responsible technology transfer.
ONE TEAM NETWORK · TWO LABORATORY CAPABILITIES
From biological discovery to production-ready process thinking.
The two pages are presented separately because their infrastructure, research questions and outputs differ. They remain connected by the BIOTEC–KMUTT collaboration and the Biochemical Engineering and Pilot Plant Research and Development Unit (BEC).
Biosciences and Systems Biology Research Laboratory
Bioprocess development, fermentation and pilot-scale expansion meet systems biology, metabolic engineering, peptide informatics, algal biotechnology and high-sensitivity sensing.
Explore laboratory → BIOPHARMACEUTICALS · BSL2 · 500 L · PILOT PLANTBiopharmaceutical Engineering Research Laboratory
The National Biopharmaceutical Facility supports clinical-grade manufacturing development with microbial and cell-culture fermentation, harvesting, purification, and aseptic fill-and-finish capabilities.
Explore laboratory →Organizational and facility descriptions are summarized from the official BIOTEC research-team page; this page explains the collaboration context and does not claim ownership of BIOTEC facilities. BIOTEC ↗
RESEARCH COLLABORATOR · COMPUTATIONAL BIOLOGY
Supatcha Lertampaiporn
A research journey that begins with biological sequences—not with a preferred algorithm.
Supatcha’s work connects RNA identification, protein localization and therapeutic-peptide prediction through biological feature design, heterogeneous ensemble learning and evaluation that keeps downstream experiments in view.