Digitalization has become an aim of many scientific labs. One way to do so is by transforming written information or even information retained in one’s memory into a digital format. Although scientific data produced by instrumentation or informatics analysis is usually automatically digitally recorded, how an experiment is planned and optimized is one of many areas where the use of digitalization has largely been missing, according to Markus Gershater, PhD. Co-Founder & Chief Scientific Officer of Synthace.
Synthace’s digital experiment model solution is changing this. “Our software builds a very detailed digital experiment model.…All the details of how an experiment might be run. Then it can dynamically turn those into automation instructions,” explained Dr. Gershater. “It allows a scientist to say, in terms which a scientist would use, ‘I want to do these steps in a process,’ and then the planner automatically works out what that actually translates into every last liquid handling step.” He added, “When we think about the experiment of the future, we believe it needs a digital model lying underneath.”
“When we think about the experiment of the future, we believe it needs a digital model lying underneath.”
The Synthace platform allows scientists to drag and drop experiment steps to create and configure their experiments, enabling planning, modification, optimization and automation as well as structured data gathering. Experiment features that can be worked with include workflow relations, simulations and execution.
As with most digital solutions, Synthace’s platform is designed to increase productivity and efficiency. This is done by saving time and labor for the scientist and increasing the accuracy and reproducibility of the experiment’s design, among other advantages. Synthace’s solution automates not only planning but also the format of the data produced. “We’re using our knowledge of the experiment as it was run to auto-structure the data.” This saves labor as well as ensuring more accurate recording of data and metadata.
Traditional experiment planning can often be a process of trial and error, with experiment design only improved upon after actually running an experiment, and it may rely on information that only a single scientist knows. “In today’s lab, if a scientist wants to record exactly how their data was produced, they have to do all that record keeping themselves. They have to sit down and plug it into whatever ELN [electronic lab notebook] system or database they have by hand,” explained Dr. Gershater. This contrasts with other approaches to digitalizing information; as he put it, “How can we digitize the experiment itself? Not just a write-up.”
“The biological expert can be the one who designs the experiments in the first place, and that can then be sent to the lab where someone else can run it.”
Advantages of the solution include collection of metadata and contextual data, automation and no need to code. One of the biggest advantages, according to Dr. Gershater, is that the platform is cloud based. “I would say that the heart of the software is our cloud,” he emphasized. For example, he said, “The biological expert can be the one who designs the experiments in the first place, and that can then be sent to the lab where someone else can run it.” This is another efficiency gain.
Synthace’s platform can also save scientists’ time by streamlining the experiment planning process in other ways, according to Dr. Gershater. “You parameterize with all of those details, and then that’s enough information; it’s asking for all of the essential information, but no more.” He noted, for example, “There’s all sorts of details like, how should you program the automation? Or how exactly should you lay out the plates? If the scientist chooses not to, they don’t have to worry about any of that. If they want a particular plate layout they can define it, but they don’t have to—our planner can do all of that for them if they choose.”
The Synthace platform can also enhance data gathering, said Dr. Gershater. The platform creates a digital documentation of the experiment itself and its context. “Because we have that model of everything that’s happened, we understand where every single data point has come from,” he emphasized. “We’ll put it into analytics at the end of the experiment and get our data. Now, if it was just a raw CSV [file] it would be worthless without the context of how it was all made. But because of the experiment model, we have all the metadata baked in. We have that context.”
The Synthace platform can also enhance a scientist’s overall work process. “We need to free biologists to think at these higher levels, not to be right down in the details,” explained Dr. Gershater. “When we talk to automation engineer …there’s a whole world of science that they have a hard time helping with, because it will take them two to three weeks at least to get a new automation process up and running. With Synthace, it can be as quick as two to three minutes for simple processes, and sometimes that makes all the difference.”
One example in drug discovery is planning an experiment for assay development. “They might use [the Synthace platform] to make 1,500 different assay conditions, some of them so where every single well has a different combination of eight different factors, for example. Then they can build highly complex models after the fact and understand their system much more rapidly,” explained Dr. Gershater. “So instead of three months to build and optimize an assay, you’re now talking three weeks.” Questions asked could include, “Do I want to do a direct dilution? Do I want to do multiple serial dilutions? What’s the volume of each of those dilutions? How much am I diluting by each time?”
Essentially, said Dr. Gershater, this makes digital connections between things that only a scientist knows right now. “The only place where [the experiment] model exists is in the scientist’s head. Right? That’s just what every scientist is used to. You don’t necessarily realize [it], maybe until you’re shown that it doesn’t have to be that way.“ he noted.
“How do you think about the experiment holistically and how do you improve that?”
In addition, recording this knowledge and question externally also can enable easier collaboration with other scientists or new types of collaborations. “How do you think about the experiment holistically and how do you improve that? If it’s stuck inside the mind of a scientist, how do they have to have different conversations with people between different disciplines?” asked Dr. Gershater. “It’s difficult if that’s all stuck inside someone’s head. If you can put it into a digital format that makes it a lot easier to collaborate to understand [and] really work on.”