Synthace Just Got a Whole Lot Better: 4 Improvements Biologists Need to Hear About

Most of our team members have been working from home during the COVID-19 pandemic. However, true to our “in silico” nature, this has not meant a decrease in productivity. Last month we released our biggest update of Antha so far, including:

  • Faster workflow calculations

  • New pinned workflows

  • Improved file management

  • A new Cherry Picker feature that allows scientists to import work lists straight into Antha

Faster Workflow Calculations

Lab automation has a steep learning curve and a high barrier to entry for most biologists. At Synthace, we believe that lab scientists should not need to know the details of the automated liquid handling process or worry about experimental logistics to benefit from automation.

Our software platform, Antha, allows scientists to describe their experiments and communicate with liquid handling robots using common scientific terminology like "sample concentration” or “source liquid volume”. Individual experimental steps are defined by elements, reusable and customisable building blocks that can be connected into a workflow (Figure 1).

Antha then translates the workflow (the what) as defined by scientists into a set of liquid handling instructions for their selected robot (the how).

Figure 1. A workflow for automated Golden Gate Assembly built in Antha. Experimental steps are defined by individual elements (white rectangles) that are connected in a user-defined order to form a workflow. Both the elements and the workflow can be easily modified to suit specific use cases. Antha interprets the workflow and translates it into liquid handling instructions for selected liquid handling robots.

Synthace’s Lab and Customer Success teams help our customers utilise Antha’s predefined protocols, for example, qPCR, synthetic DNA construct assembly, or miniaturised purification. The associated elements and workflows can be easily modified for specific use cases, offering levels of flexibility unmatched by most automation platforms.

When scientists finalise their workflow in Antha, they can simulate it in silico and get an interactive preview of what is going to happen in the lab, i.e., on the deck of their selected liquid handler. They can preview the deck layout (experimental setup) as well as the progression of the experiment with every single liquid transfer (Figure 2).

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The preview shows all the individual steps that will be undertaken by the device in the lab. This makes Antha protocols completely traceable, standardising them and improving data reproducibility between devices, scientists, and teams. In addition, in silico simulation allows users to identify any potential errors in the workflow and optimise it before execution, ensuring experimental success.

Antha is device-agnostic and supports different liquid handlers, like the Hamilton Microlab® STAR™ and Tecan Freedom EVO®.  It will fully plan the experiment on the selected liquid handler, informing the user on:

  • How long the experiment will take

  • How much of each liquid and how many tips are required

  • Where to place each plate on the deck

  • And more…

We have previously demonstrated the device-agnostic capabilities of Antha for qPCR and construct assembly applications.

Antha will also speed up the experiment thanks to its smart use of multi-channeling.

However, computing the plan for the experiment takes time. The exact duration of the computation depends on the given experiment. In our latest release of Antha, this became dramatically faster: for most workflows, computation now finishes within five seconds (Figure 3).

We achieved this by pre-computing and storing common inputs in Antha as well as simplifying the backend infrastructure that runs the computations. What this means for our users is instant feedback on their workflows and confidence in running their experiments.

Figure 3. Computation speed-up in the latest release of Antha. Each bar represents a distribution of how long it took for computations to finish in a given week. The dark bar represents P25-P50, the border between the bars is P50 (the median), the light bar represents P50-P75. In the latest release (marked with the arrow), computation for most workflows finishes within five seconds.

New Pinned Workflows

Antha users can easily share the workflows with their colleagues by “pinning” them in Antha’s cloud-based store. Pinned Workflows are very easy to use: all of the important workflow parameters (the experimental conditions that you might want to change) are shown in a list, with the most commonly used parameters at the top. Scientists can change any of these parameters to suit their use case and then fully plan the experiment in one click (Figure 4).

Pinned Workflows are one of the most popular features among Antha users. In the latest release, we rebuilt this feature from the ground up to make it even easier to use. Users can now drag the most important parameters to the top of the screen to emphasise their importance.

Figure 4. Pinned Workflow for Golden Gate Assembly. Antha users can “pin” their workflows and store them in Antha’s cloud environment for the ease of sharing with the wider team. Workflow parameters can be easily modified by other users if needed, and the workflow can be executed in one click.

Improved File Management

Scientists can also attach a design file to their workflow (i.e. a spreadsheet that describes the experimental conditions, sometimes exported from third-party software like JMP). Antha then interprets the file, propagates that information through the workflow, and programs the liquid handler for physical execution.

In the latest release, it became easier to attach files to workflows. Users can either upload them from their computers or choose one of the files that they have previously uploaded into Antha. They can also easily locate and choose files that were produced by one of the analytic devices in the lab (Figure 5).

Figure 5. Design files from different sources can be attached to Antha’s workflows. Users can upload files that describe the experimental conditions or use files generated previously by any of the lab devices.

New Feature: Cherry Picker

Workflows are a powerful way to define sophisticated experiments. However, sometimes all we want to do is to simply move some liquid from one plate to another. For example, in Golden Gate Assembly assays, scientists might want to select samples with synthetic constructs that yielded many colonies.

This is why we introduced the Cherry Picker feature, an easy-to-operate user interface (UI) that allows scientists to specify individual liquid transfers. They can now specify the source and destination wells as well as define liquid names and policies associated with the transfers (Figure 6).

The policies describe how the transfer should happen: whether there should be a number of mix cycles, whether the robot should dispense above the well or at the bottom, or how fast or slow it should aspirate.

Figure 6. The new Cherry Picker feature in Antha. Users can now specify individual liquid transfers between selected source and destination wells, together with liquid names, policies, and volumes. Here, 12 wells were selected from a 96-well source plate to transfer 75 uL to the first row of the destination plate.

The second reason why we introduced the Cherry Picker is because a lot of scientists have existing R, Python, or Excel scripts for creating a list of liquid transfers for robots. Such lists are typically referred to as "pick lists" or "work lists". We thought it would be great if Antha had the same functionality.

Now scientists can use their existing custom scripts to generate pick lists, while Antha takes care of placing the required labware on deck, links the plate name of your choosing to an actual physical plate type, determines multi-channeling where possible, and converts this to specific instructions for any liquid handler it supports (Figure 7).

Figure 7. New Antha’s capability of interpreting pick lists. (A) An example pick list we created in Python where we scanned an image, converted it to halftone image (i.e. simulating continuous-tone imagery through the use of dots) using Python, and generated a pick list from one deep reservoir to be executed on a Formulatrix® MANTIS® dispenser. (B) The resulting image as printed in the lab by MANTIS® . If you squint, you may actually recognise the jolly fellow pulled by two reindeer.

How Can Antha Help You Revolutionise Your Science?

Developed by both software engineers and lab scientists, Antha offers an intuitive, user-friendly interface that empowers biologists to realise the full potential of lab automation and helps them achieve high-throughput high-quality results in less time. In the latest update, our biggest release to date, Antha was reimagined to provide you with an even better user experience that will help you drive your R&D forwards and revolutionise science altogether.

To learn how our customers and partners utilised Antha for their applications, check out our case studies and webinars. To chat with us directly and find out how Antha can help you and your team, please book a custom demo here or email us at