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LABORATORY INFORMATICS


the complexity of biology can only be properly addressed with advanced software and automation. This investment in Synthace is a significant step in turning that recognition into reality.’ The white paper asserts that CAB


is a conceptual framework, around which there is an emerging ecosystem of tools that collectively transform how we approach biological research, development and manufacturing. Only by connecting tools and software


into a single ecosystem, both physical and digital, and enabling an integrated loop, will scientists be able to address the challenges of biology in the 21st century. ‘We’re pleased to offer these insights and approach,’ said Fell. ‘In this white paper, we highlight how the emerging computer- aided biology ecosystem is evolving, and how companies from the technology and life science domains are coming together to make biology a true engineering discipline.’ The white paper highlights the


importance of CAB processes and also lays out the problems that have led to delays in lab-based industries adopting digital technologies. It states: ‘Despite the rapid advances in the complexity and power of research methodologies, the majority of biological laboratory research is still conducted in


www.scientific-computing.com | @scwmagazine


”Digital-to-physical workflows have transformed the semiconductor, aerospace, automobile and many other industries”


a similar manner as it always has been: manually, and in a reductionist ‘one factor at a time’ way. As such, despite huge advances, biological research still translates poorly from controlled environments into complex dynamic environments. For example, the translation of results


from in-vitro assays to in-man clinical trials is expensive to conduct and often fails due to unforeseen circumstances.’ This is contrasted with semiconductor and automotive industries, which have more readily embraced digital technologies that enable reproducible, scalable processes from digital blueprints. ‘By observing how these industries


reduce cost, while increasing product complexity, we gain new insights into how to conduct more resource-efficient biological research,’ the white paper reports.


The document highlights how the


digital-to-physical workflow is akin to other transformations that have occurred in other industries, such as electronic design automation. ‘In isolation, these tools create value,


but value creation is significantly enhanced by connecting all aspects of the ecosystem together, digital and physical, to create an integrated and iterative loop of design, simulation, experimentation, and analysis.’ One of the key tools for this


transformation is design of experiments. Enabling users to easily modify the parameters to understand the dynamics and properties of biological processes, enables agility and flexibility in an organisation.


This is much different to the traditional


view of molecular biology, which treats each variable individually. The future of biology will rely on new


approaches that use computing and technical software to more quickly and accurately interrogate biological materials to accelerate the time to research and release new products. ‘While our theoretical frameworks now often treat biology as a system, our experimental methods have lagged, necessitating this new CAB [approach],’ the white paper states.


April/May 2019 Scientific Computing World 15


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