Synthace

What is Synthace?

Synthace is a pioneering platform designed to empower biologists and life science researchers by simplifying the automation of complex experiments. It offers a no-code, drag-and-drop workflow builder that abstracts experiment design into modular building blocks, enabling flexible planning and seamless translation into automation instructions for lab equipment. Synthace integrates multiple devices, simulates experiments in silico to optimize protocols before lab execution, and automatically structures and analyzes data, facilitating collaboration and accelerating biological discovery.

Key Features

• No-Code Experiment Design

  Drag-and-drop interface allows users to build and modify complex experimental workflows without programming knowledge.

• Automated Lab Automation Instructions

  Instant generation of click-to-run scripts that control liquid handlers and other lab devices, eliminating manual scripting.

• In Silico Experiment Simulation

  Pre-run digital simulation of experiments to preview and optimize every step, reducing costly trial-and-error in the lab.

• Integrated Data Management

  Automatic collection, structuring, visualization, and analysis of experimental data and metadata in a unified platform.

• Flexible Protocol Reuse and Scaling

  Protocols can be reused and adapted easily for different experiments and equipment, supporting scalable workflows.

• Multi-Device Integration

  Supports coordination of various lab instruments for seamless execution of complex workflows.

Use Cases

• Assay Development and Automation : Design and automate assays such as ELISA with flexible protocols and automated data handling to improve throughput and reproducibility.
• DNA Assembly and Molecular Biology : Automate combinatorial DNA assembly workflows by importing design files and generating precise liquid handling instructions.
• Design of Experiments (DOE) : Plan, simulate, and execute DOE workflows with automated data structuring and built-in response analysis to optimize biological processes.
• Collaborative Research : Centralize experiment design, execution data, and analysis to enhance teamwork and knowledge sharing across research groups.

FAQs