Synthetic Biology
Biosynthesis Digital experimeand and DOE

Biosynthesis Digital experimeand and DOE

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Biosynthesis Digital experimeand and DOE

Fig 1. Digital Experimentation and DOE.

In recent years, the integration of digital experimentation (DE) and design of experiments (DOE) services has revolutionized the design phase of the DBTL cycle, enhancing efficiency and accelerating innovation. CD Biosynsis is dedicated to providing professional digital experimentation and DOE services to help researchers around the world advance their cutting-edge research.

Introduction to Digital Experimentation and DOE

Digital experimentation involves the utilization of computational tools and simulations to model and forecast the dynamics of biological systems prior to their physically built and tested in the laboratory. This empowers researchers to probe into design possibilities, predict outcomes, and enhance designs before allocating resources to physical implementation. The prime benefits of digital experimentation encompass:

  • Rapid iteration and testing of design ideas.
  • Cost and time savings by reducing the number of physical prototypes.
  • Insight into system behavior and identification of potential issues.

DOE denotes a methodical strategy for planning, conducting, and analyzing experiments with the objective of comprehending the impact of various factors (variables) on the performance of a system. Within the domain of synthetic biology, DOE aids researchers in optimizing the parameters of their biological systems to achieve intended results in a resource-efficient manner. Instead of modifying one variable sequentially, DOE involves changing multiple variables simultaneously under controlled conditions to reveal interactions and optimal settings. The pivotal advantages of DOE encompass:

  • Efficient exploration of parameter space.
  • Identification of critical factors and interactions.
  • Reduction of experimental resources and time.

Fig 2. Application of experimental design to solving water engineering problems.Fig 1. Application of experimental design to solving water engineering problems. (Lee B C Y, et al., 2022)

Service Offering

During the design phase, researchers use digital experimentation tools to construct and simulate potential systems virtually. Concurrently, the principles of DOE facilitate the selection and manipulation of variables for optimal performance. This integrated methodology enables researchers to identify promising designs and parameter configurations prior to entering the physical Build and Test phases.

Virtual Prototyping and Design Validation

Creating accurate simulations of biological systems and corroborating their accuracy prior to the physical construction of a synthetic biology design enables an intuitive comprehension of the interplay between diverse components. This approach also predicts the behavior of the system under diverse conditions.

Rapid Iteration and Design Refinement

Explore a variety of design variants to support clients  in swiftly iterating their designs. Clients can test different assumptions, adjust parameters, and evaluate the impact of alterations on system performance.

Optimization of Parameters

Enhance parameter configurations to optimize the performance of biological systems. Experiments are designed to methodically alter multiple variables, thereby determining the optimal combination of desirable outcomes.

Our Advantages

Fig 3. Risk Mitigation and Cost Savings.Risk Mitigation and Cost Savings

Fig 4. Data-Driven Insights.Data-Driven Insights

Fig 5. Interactive Design Collaboration.Interactive Design Collaboration

Fig 6. Customized Solutions.Customized Solutions

CD Biosynsis provides our clients with a powerful approach to enhance the DBTL cycle by integrating digital experimentation and DOE into our synthetic biology platform.

Reference

  1. Lee, B C Y.; et al. A comprehensive review of Design of experiment (DOE) for water and wastewater treatment application-Key concepts, methodology and contextualized application. Journal of Water Process Engineering, 2022, 47: 102673.
Please note that all services are for research use only. Not intended for any clinical use.

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