As biology moves towards automation and industrial applications, modelling starts taking an essential role in guiding experiments. AdvanceSyn is a startup from Singapore aiming to save experimental resources via in silico strain optimization. I had the chance to interview the company’s founders Dr Chueh Loo Poh and Dr Maurice Ling and ask them about their journey so far.
Kostas Vavitsas: Could you tell us how AdvanceSyn started and what is the market that you are aiming to cover?
Chueh Loo Poh: We see that bioeconomy is rapidly growing in many countries and sustainability concerns are driving the demand of bio-derived products. Engineering Biology is instrumental to the development of bioenconomy.
Maurice Ling: Companies are actively engineering microbes to produce the products across different markets, including energy, healthcare, and food. These engineered microbes cover a range of applications, from production to conversion to degradation of various compounds.
Chueh Loo: However, we recognise that the current approach to derive engineered biological systems is still highly inefficient and costly, requiring many iterations of resource intensive and time-consuming experiments. A particularly pain point that companies is facing is the scaling up process. Cells developed in lab scale might not work optimally in the scaled-up conditions, as different culture conditions would be encountered in the final process.
Consequently, both engineered cells and the bioprocesses need optimization, and it is difficult. There are many factors to tune. One common approach is the use of combinatorial, high throughput screening, which requires high infrastructure and running cost. The “best” clones that were finally selected may not always reflect the optimal yield in the eventual scale-up process.
We started to think that there must be a better solution to the current approach. As an engineer by training, we have witnessed how design and modelling tools have transformed other fields of engineering. However, in engineering biology, the use of modelling is still not common.
Within my own research, we have been using modelling to aid in our development of living biosensors, one that is designed to sense and kill Vibrio Cholerae in our gut. We are convinced that modelling can help to make the process more rational and predictive.
Maurice: At the same time, we also learned that it is important to model the circuit in the context of the cells and its environment and we could model the cells at a level of abstractions. However, building predictive model is complex and requires lots of experimental data to train the model.
We need tools that allow automated building of models, design tools that interface with modelling tools, and tools that allow systematic capturing of experimental data and training of models throughout the scaling up process. However, there’s a lack of such tools in the market.
Hence, we started developing AdvanceSyn platform and toolkits. We strive to provide solutions for rational and predictable biological engineering through the use of data and model-driven platform, achieving desired product faster with reduced resources.
Kostas: What kind of input can your system use? And for which organisms is it applicable?
Chueh Loo: At the moment, we focus on microbes, mainly E. coli which is a workhorse in the industry. We focus on the engineering of microbes for bioproduction.
Maurice: Our AdvanceSyn studio enables the creation of complex dynamic model, based on ordinary differential equation, combining different aspects of a cell, including metabolism, gene circuits and biochemical pathway. The input to the system includes the pathway involve in the production, enzymatic kinetics and experimental data for training.
Chueh Loo: Our platform comprises comprises databases to store experimental data, a library of different types of models including models of cells, genetic circuits and bioreactors. At the same time, we have the corresponding biological parts and system. The databases are interfaced with our software, AdvanceSyn Studio, to support the modelling and design process.
Kostas: What was the biggest technological challenge when developing the platform?
Maurice: We recognised that it is important to model the gene circuits pathways in the context of the cells and model the cells in the its environment context. We faced several technological challenges and one of the biggest is to figure out the key components in the cells that would enable more predictable modelling while still having the model being able to be modelled in a bioreactor model. To address this challenge, we utilised different types of models, including genome scale models to coarse-grained kinetic models. We had to spend significant amount of effort to validate and refine the approach using experimental data.
Chueh Loo: Another challenge is to interface the different modules together to achieve seamless and automated building, training and analysis of the models. This includes getting experimental data into the system and generating useful analysis report.
Kostas: Given the advances in automation and modelling, do you think synthetic biology will be happening “in a cloud” in a few years?
Maurice: We are starting to see more users and companies storing and managing data on the “cloud”. There are a few design tools that are already cloud based. I could that there will be more activities happening in the “cloud”, mainly for design, modelling and data management.
Chueh Loo: However, we still need physical infrastructure to do the actual engineering biology. I would imagine that we will see many more biofoundries being established. These are advanced setup utilising automation, ICT, modelling, and high throughput analytical tools.
Kostas: How is the synbio landscape in Singapore? Is it easy to bring a good idea to the market?
Chueh Loo: We see that the Synbio and Bioeconomy in Singapore are emerging. Singapore has invested in Synbio, through National Research Foundation, over the past few years. Singapore is very supportive in startups and has been pushing for entrepreneurship. There are quite a few government-supported initiatives to support startups and we see that the startup ecosystem is growing rapidly.
Maurice: We now have a Singapore consortium for Synthetic Biology, SINERGY to foster the translation of research in synthetic biology for industry applications. AdvanceSyn is a founding industry member of Sinergy and that has helped AdvanceSyn to engage researchers in co-development and potential customers.
Dr. Chueh Loo Poh is an Associate Professor with the Department of Biomedical Engineering at National University of Singapore (NUS), Singapore. He is also a Principal Investigator at NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI) and leads the NUS Biofoundry. He is co-founder and non-executive director of a Singapore startup company, AdvanceSyn Pte Ltd, which specializes on providing model assisted design tools and services for Synthetic Biology. He obtained his PhD in Bioengineering from Imperial College London, UK and B.Eng. in Electrical and Electronic Engineering from Nanyang Technological University (NTU), Singapore. His research group has been reprogramming microbes for medical and industrial applications. His current research interests include microbial biosensors, optogenetics, synthetic gene circuits design and automation, modelling of biological systems for design, and computer aided design (CAD) tools for SynBio. He has received a number of awards including Tan Chin Tuan Fellowship in 2012 and NTU Excellence in Teaching award in 2010. He is currently the co-Editor-in-Chief of IET Engineering Biology journal.
Dr. Maurice HT Ling is co-founder and director of a Singapore startup company, AdvanceSyn Pte Ltd, which specializes on providing model assisted design tools and services for Synthetic Biology. He is also a Research Assistant Professor with the School of Data Science at Perdana University, Malaysia. He obtained his PhD in Bioinformatics and B.Sc(Hons) in Molecular and Cell Biology from The University of Melbourne, Australia; as well as B.Sc in Computing from University of Portsmouth, UK. His current research interests include modelling of biological systems, evolutionary computing, computer aided design (CAD) tools for SynBio,as well as the professional and social aspects of science and education. He has received the Outstanding Mentor Award from Ministry of Education, Singapore, in 2010.