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Demystifying Synthetic Biology III: The 21st Century Technologies Advancing Synthetic Biology

Just joining us? Check out Part I and Part II of the series.

Synthetic biology is often touted as a software-driven and automation-empowered approach to biological research. Buzzwords like artificial intelligence and robotics are commonly used alongside the phrase synthetic biology, leading many to assume synthetic biologists spend their time coding and automating huge experiments. This is not quite the case. While technologies like automation and machine/deep learning play an increasing role in our field, it has not become dominated by them yet.

These 21st Century technologies have helped rapidly excel modern R&D by improving the quality and quantity of data. Machine/deep learning algorithms were originally built to simulate human learning, detect patterns, and play complex games. When combined with high-throughput liquid handlers, artificial intelligence has proven useful in advancing molecular biology techniques by complementing the engineering strategies that lie at the core of our field. The perceived value of these technologies within the industry has become so great that graduate programs are now training the next generation of synbio researchers in both biology and coding skills. As part of our continuing blog series on demystifying synthetic biology, we look at how automation and software have advanced synthetic biology R&D, what the current limitations are, and where they make the most impact today.

Data science as a cornerstone

Synthetic biology is built around the Design-Build-Test-Learn (DBTL) cycle. Connecting Design and Learn in the R&D process is arguably the most important part of synthetic biology, as this is where we learn from the data to generate an improved design. It’s no surprise that software to capture and wrangle data, mine databases, and design experiments plays a major role at the junction between the Design and Learn phases.

Computational tools have become essential for today’s biological research, from identifying new protein targets to comparing gene variations. Vast databases of -omics data – collectively containing an organism’s known genes (genome), mRNA (transcriptome), and proteins (proteome) – exist for thousands of organisms and microorganisms. By mining these databases, synbio researchers can start to make predictions. Common prediction targets include the function of an enzyme or group of enzymes in a pathway, the conserved areas of genes likely necessary for their product’s functionality, and regions more amenable to mutation and engineering.

Comparing these sequences alone is not enough to draw insightful conclusions; the genotype data must be related to a meaningful phenotype, that is the physical effect genetic variations have on the organism and its behavior. Knowing which mutations are associated with increased production of a compound means we can rationally design a pathway for the organism relatively quickly using related datasets. But this approach is limited by the quality of the data. Robust, high-quality data are essential for drawing insightful conclusions and making biology a little more predictable. Data science underpins synthetic biology, helping iterate organism design through the DBTL cycle.

Automating research with robotics

Automation enables high-throughput research while reducing human error, dramatically scaling the amount of high-quality data that can be produced. Robotics in modern laboratories looks similar to the automation components used in car factories but on a smaller scale. For example, chemical reagents, DNA, buffers, and even cell cultures are often stored as liquids. Specialized liquid handling robots are adept at consistently and accurately preparing hundreds of samples simultaneously, compared to just dozens of samples by manual preparation.

Many of the molecular biology techniques used in the Build phase are amenable to automation. The most common involve performing molecular cloning techniques like PCR, assembling DNA sequencing libraries, and transforming target organisms like E. coli or yeast. Automation also plays a role in the Test phase, when small-scale fermentation and cell culture can be performed and monitored, helping to screen up to hundreds of engineered strains coming from a high-throughput Build step. The increased throughput and consistency afforded by automation help synthetic biologists standardize their research and boost the statistical power of data to help draw meaningful conclusions.

However, automation is not a magic bullet for enabling R&D. Every experiment must be tested and optimized and one machine cannot do every single step, nor can everything be automated. Programming and optimizing new experimental steps across several devices requires a lot of time and specific skill sets uncommon among biologists. Bottlenecks in the R&D process may occur where certain steps simply cannot be automated.

While automation is not essential for synthetic biology, its benefits of consistency and accuracy have led to widespread adoption across the field. In addition, automated platforms can also capture valuable metadata such as ambient temperature and precise timings of each step, creating a robust data set for each experiment and helping identify deviations.

Artificial intelligence in synthetic biology

Data is more available than ever. Thanks to automation, we have mountains of internally generated biological data, as well as publicly available research and -omics databases. How can we sort through it all to derive meaningful insights? Often, there is so much information that we cannot know exactly where to look, or we are trying to make a prediction based on obvious conclusions. So, how do we investigate the non-obvious and get the most from data? This is where artificial intelligence software like machine learning (ML) and deep learning (DL) tools come into play for synthetic biologists, capitalizing on the sheer amount of data now available in the field.

ML and DL algorithms can play a role in the Design phase, for example, by suggesting iterations on previous experimental conditions or proposing beneficial genetic modifications that may improve product yield. These algorithms can point out non-obvious correlations in the data to identify connections between genotype and phenotype that would otherwise escape our notice.

To spot these trends and patterns within datasets, the data must be statistically powerful enough to have meaning – after all, you don’t want to chase a perceived pattern in what turns out to be random noise. High-throughput and high-quality data capture provide statistically powerful data for modeling, making predictions, and further analysis with ML and DL algorithms. Good quality data are therefore essential for feeding into these algorithms and obtaining meaningful outputs. As the old computer science axiom goes: garbage in equals garbage out.

Artificial intelligence is surging in popularity across all fields, synthetic biology included. Though its value and potential impact are clear, artificial intelligence remains a relatively inaccessible technology for many biologists – most biologists are not software engineers and most software engineers don’t understand the intricacies of biological systems. Biology is incredibly complex and these tools are only as good as the data fed into them, which must be validated to further train and improve their capability. Synthetic biologists must become fluent in both disciplines and work in a cross-disciplinary environment to maximize the impact of this very new, highly valuable, and rapidly evolving technology.

Faster solutions to world problems

Data is the Alpha and Omega of synthetic biology, driving forward novel and sustainable bio-based solutions to global challenges. High-quality datasets inform everything from our experimental design to the tools we use to capture new data. Automation tools help standardize molecular biology and allow a higher throughput of data gathering, while artificial intelligence software can help us make sense of more data than ever before.

The synthetic biology industry is increasingly adopting cross-discipline teams to make the most of these technologies, bringing together biologists, software engineers, data specialists, and more. Future synthetic biologists will be better equipped with the skills to use these technologies, as budding biologists are now encouraged to learn to code and gain a deeper understanding of data and statistical knowledge. These technologies allow researchers to test more hypotheses accurately in less time, leading to more cost-effective and robust innovation of bio-based solutions to global challenges.

Next Time …

In the next edition of our Demystifying Synthetic Biology series, we’ll dig into fermentation and the many variables synthetic biologists encounter at this stage of the process. We’ll discuss the history of fermentation and how a centuries-old technology once used exclusively for brewing beer and fermenting foods has been reimagined and reapplied to solve some of the most pressing challenges of our lifetime.

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Richard Sherwin

Head of Commercialization

Richard is an industry veteran with more than 30 years of experience in the KSM, API, and intermediate markets. He is responsible for leading the commercialization and revenue generation for Antheia’s robust pipeline of products. Richard brings an exceptional track record of leading international sales teams, driving revenue growth, building strategic partnerships, and delivering innovative products to market, including ANDA and NDA developments. Richard led commercial efforts at some of the leading global pharmaceutical companies and most recently, built his own consultancy business advising a range of clients, including $1B divisions of major multinationals.

Appropriate regulatory submissions will be prepared and submitted to support Antheia’s customers who need to reference and access necessary process-related information.

Yihui Zhu, PhD

Head of Fermentation

Yihui leads the fermentation team at Antheia. With over 25 years of hands-on experience in the field, he brings in-depth knowledge and expertise in microbial metabolism and fermentation process development. He is also skilled in developing comprehensive fermentation data collection, analysis, and visualization systems. Prior to joining Antheia, he served as a fermentation lead at Intrexon and Codexis where he successfully built fermentation labs and teams and led multiple biofuel and biochemical projects to reach stretch milestones and tech transfer. Yihui is passionate about the potential of fermentation and is dedicated to advancing the field through innovative research and development.

Yen-Hsiang Wang, PhD

Head of Strategy, Partnerships, and Finance

Yen-Hsiang leads strategy, partnerships and finance at Antheia. He completed his M.S. and Ph.D. in Bioengineering at Stanford, with extensive research experience in synthetic biology, metabolic engineering and computational modeling. Before joining Antheia, he worked at McKinsey and Tencent with a strong focus in corporate strategy and big data/advanced analytics. At Tencent, he served as Director of Strategy and Business Development for the AI Lab, leading corporate initiatives in healthcare AI/ML applications and commercialization. He also served in AI4H (Artificial Intelligence for Health), a collaboration between WHO and ITU, to establish global standards for AI in healthcare.

Audrey Wang

Head of Financial Planning and Analysis

Audrey leads financial planning and analysis at Antheia. With an MBA from Washington University in St. Louis, Audrey is passionate about leveraging financial analysis, digital technology, and data analytics to guide companies in making optimal investments and strategic business decisions. Audrey has a decade of experience in helping companies solve unique problems and creating long-term impact with unconventional approaches. Before joining Antheia, she was at Vir Biotechnology and Merck where she led various FP&A workstreams, including investment valuation, asset prioritization, and manufacturing sites operation finance support. Audrey completed CFA Level II and passed the U.S. CPA exam in 2011.

Antonij Tjahjadi, CPA

Head of Accounting

Antonij Tjahjadi leads accounting at Antheia and holds active CPA license. He joined Antheia with more than 20 years of experience in corporate accounting, bringing deep expertise in ramping up accounting operations for start-up companies, SEC reporting/technical accounting, and SOX implementation efforts. Before joining Antheia, he held various leading roles in both public and private company settings, including directing accounting functions at Ambys Medicines, where he successfully implemented Netsuite with Point Purchasing integration and set up various accounting policies and processes, and played a key role in the initial public offering of Nutanix, Inc.

Ken Takeoka

Head of Biology

Ken leads the Biology team at Antheia, which incorporates both strain and protein engineering functions. He has more than 16 years of experience in the synthetic biology field, working with leading companies, including Amyris and Novartis. One of his passions is molecular biology tool development and he previously worked to build the foundation for the automated strain engineering pipeline at Amyris. At Novartis, he modernized the molecular biology techniques and established a platform to model mechanisms of antibiotic resistance in a range of organisms.

Suzanne Sato

Head of Downstream Processing

Suzy leads downstream chemistry processes at Antheia. She has 19 years of experience in process development, including route development through synthetic chemistry and scale-up of small molecule APIs for GPCR targets under cGMP for Phase I-III trials. Before joining Antheia, Suzy led a full DSP team at Amyris where she successfully pivoted developments from biofuels hydrocarbon products to pharmaceutical intermediate, flavor, fragrance and nutraceutical products. She led a team that scaled 11 products and took five products to commercial manufacturing.

Farrah Pulce, PMP

Head of Project Management

Farrah leads program and project management at Antheia. She has over 20 years of experience leading program and project management, operations, and engineering for companies across the CPG, aerospace, and automotive industries. Prior to joining Antheia, Farrah implemented and led the sustaining program management team at Impossible Foods. She also led product operations, project management, and cost optimization at Blue Bottle Coffee and Tyson Foods to develop and commercialize new products. As a certified project management professional (PMP), Farrah has a proven record of successful project delivery, improving project management practices, and building collaborative teams.

Jordyn Lee

Head of Communications

Jordyn leads communications and external affairs at Antheia. She brings a decade of multidisciplinary communications experience in helping companies make complex science and technology accessible to broad audiences, all while maintaining technical accuracy and integrity. She has a passion for visionary storytelling and translating impact across the entire communications ecosystem – her work has spanned from public relations to corporate communications to marketing. Jordyn has served as an advisor to a number of different life sciences companies and most recently led corporate communications at Amyris.

Ben Kotopka, PhD

Head of Data Science

As Head of Data Science at Antheia, Ben manages in-house software development and external partnerships for storing and interpreting research data, executing bioinformatics analyses, and streamlining business processes. Prior to Antheia, Ben worked as an academic researcher at the intersection of machine learning, bioinformatics, and synthetic biology. Following this, as an entrepreneur and consultant, he developed and deployed data science solutions for biotechnology applications ranging from metabolomics-driven compound discovery to MRI segmentation.

Guerin Kob

Head of Supply Chain

Guerin is responsible for leading the design, development, management and improvement of Antheia’s end-to-end global supply chain. He has over 15 years of experience leading high-performing supply chain and procurement teams at leading biotechnology and specialty chemical companies, with extensive experience in process development and end-to-end supply chain optimization. Prior to joining Antheia, Guerin served as Senior Director of Global Supply Chain for Sumitomo Chemical’s biotechnology division with Valent Biosciences, where he led the end-to end supply chain including procurement, logistics and distribution, integrated business planning, materials management, customer service, and supply planning functions globally.

Pavel Aronov, PhD

Head of Bioanalytics

Pavel leads the Bioanalytics team at Antheia. He has 20 years of experience in analytical and clinical chemistry, mass spectrometry, chromatography, and metabolomics. Pavel built and led the original Chemistry and Analytics team at Impossible Foods enabling strain development, fermentation, DSP, regulatory, QC, and scale-up of leghemoglobin biomanufacturing. During his academic career at UC Davis and Stanford University Pavel developed a vitamin D assay used by all major clinical diagnostics laboratories and pioneered metabolomics studies to investigate kidney disease and microbiome.

Jesse Ahrendt

Head of Quality Assurance and Regulatory Affairs

Jesse has more than 25 years of experience in regulatory affairs, quality systems, manufacturing quality, and regulated industries, ranging from early- to late-stage pharmaceuticals, biomanufacturing, consumer care, and medical devices. He has supported global product launches and the underlying quality supply chain components in industries that require strict adherence to internationally accepted quality standards. Before Antheia, he led quality efforts at Zymergen and Sandoz, and supported many global pharmaceutical companies during his time in Biotech Consulting at NSF International, all to bring quality to the forefront in manufacturing, standardize global processes, and support customer regulatory requirements.

Heidi Pucel

Chief People Officer

Heidi is a results-driven human resources executive and HR business partner who leverages decades of experience in empowering, motivating, and inspiring to drive transformation within high-performing and rapidly-growing workforces. A certified executive coach and passionate advocate for people-oriented solutions, Pucel serves as a partner to executive teams to design programs that support employee development, engagement, and recruitment and retention. Pucel most recently served as Chief People Officer for Countsy, where she worked as an interim HR executive for clients in the biotechnology and software industries, such as Ceribell and Tune Therapeutics.

Zack McGahey

Chief Operating Officer

Zack is a leading executive in operations management, specializing in bioprocess engineering and manufacturing management. He has over 20 years of experience leading manufacturing functions for companies across the pharmaceutical, synthetic biology, diagnostics, and automotive industries. Before joining Antheia, Zack was VP of manufacturing and capex project management at Zymergen. He also gained experience managing commercial scale facilities operations for Tesla, where he was responsible for managing 10 million square feet of factory, lab and warehouse space during the Model 3 ramp.

Kristy Hawkins, PhD

Co-Founder & CSO

Kristy has over 20 years of experience in the field of synthetic biology, focusing on yeast metabolic engineering for the production of small molecules. She did the founding work on the benzylisoquinoline alkaloid pathway during her graduate studies and gained valuable industry experience at Amyris and Lygos. Kristy is an expert in tool development, high-throughput screening, and host strain and heterologous pathway engineering.

Christina Smolke, PhD

Co-Founder & CEO

Christina is a pioneer in synthetic biology and metabolic engineering, where she has over 20 years of experience. As Professor of Bioengineering and Chemical Engineering at Stanford University, her laboratory led the breakthrough research to engineer baker’s yeast to produce some of the most complex and valuable medicines known. Under her leadership, Antheia’s synthetic biology platform enables new possibilities for drug discovery and efficient, sustainable, transparent, and on-demand drug manufacturing at scale. Her vision and accomplishments have garnered numerous awards, including the Chan-Zuckerberg Biohub Investigator, NIH Director’s Pioneer Award, Nature’s 10, Novozymes Award for Excellence in Biochemical Engineering, and TR35 Award.

Antheia Announces Continued Partnership with Olon

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