The Future of Biotech is Data Liquidity: Notes from Bio-IT World 2022

On May 5th 2022, at the Bio-IT World conference in Boston, Benchling laid out three tools and mindsets for enhancing data liquidity throughout the R&D lifecycle: machine learning, collaboration as a competitive advantage, and modern cloud security.

All of these concepts ladder up to our fundamental belief that connecting your R&D workflows will reduce friction, accelerate timelines, improve scientific outcomes, and, ultimately, unlock the full power of biotech. Here's the recap of our three presentations on the subject and how Benchling might be able to help future-ready your R&D:

Machine learning for R&D: From hot topic to practical application

Machine learning is one of the hottest topics in science and technology, but what does it look like when you need to apply it to real-world problems?

For most scientists who work in a fragmented ecosystem of point solutions like email, spreadsheets, and antiquated software, the answer is: it doesn’t look good. They face three major problems:

1. Siloed Data. There’s too much data, and it’s stuck in silos without any consistency in how it gets captured. That means either the most helpful information is never uncovered and shared, or if it is, the process of sharing is time-consuming and error-prone.

2. Limited Collaboration. As teams discover how essential collaboration is to get a product out the door, they also learn that the legacy systems they use are not built to enable real-time, cross-team engagement.

3. Bottlenecked Insights. Everyone from bench scientists to R&D leaders requires access to insights that help them make better decisions—from understanding the results of an experiment to mapping overall program performance and pinpointing bottlenecks.

Benchling’s R&D Cloud is built to solve each of these issues. Let’s break them down:

Data: Benchling is built on a consistent underlying data layer. This means our customers can centralize, standardize, and govern R&D data of any scale. Scientists can focus on what they do best—creating new therapies—while the software and our data management experts take care of the rest.

Collaboration: We enable teams across R&D to get work done and collaborate in one place with a unified application suite that makes it possible for scientists to “live” in Benchling for all their work needs. That means no more time wasted sending emails around the company or shuffling files between team members; instead, all your information is organized in one place where everyone can access it quickly and easily.

Insights: Better data in, better insights out. Data in Benchling helps scientists and operators ask and answer questions—with dashboards, reports, and advanced analytics available through intuitive point-and-click tools.

Collaboration as a competitive advantage

At Benchling, we believe that collaboration is the key to making breakthroughs in the lab. Currently, however, collaboration is not the norm. Scientists are still recording too many experiments in siloed systems like spreadsheets. They might compare data across their own experiments, but they often struggle to see the impact they have on other teams or departments.

This is a problem because often, other teams and leaders need access to the insights from these experiments. The current system creates bottlenecks and slows down the process of passing on crucial information. Whereas the goal is data liquidity, with all teams having easy access to the insights they need, capturing data in separate spreadsheets leads to data illiquidity—difficult to access, and hard to activate.

With Benchling’s Registry, we’re creating a centralized place where everyone can access the data they need. Upstream and downstream components and variables can be linked. Our data model combines a fundamental understanding of biology with a high degree of configurability.

Because R&D teams are able to work with shared, real-time information, they can streamline experiment and assay execution. By taking advantage of end-to-end tracking, teams can iterate on next steps quickly and without redundancy.

Modern cloud security: Dispelling common myths about cloud computing

The cloud has been with us for two decades now, and it's time for us to face the fact that many of our ideas about cloud security aren't living up to the realities of today's world.

Over the last two decades, cloud computing has matured, approaches to security have advanced considerably, and data liquidity has become the expectation. But many commonly held beliefs about cloud computing have prevented some industries and organizations from adopting a strategy of digital transformation. Many of these are myths that don't hold up to scrutiny.

For example, many companies are justifiably concerned about ransomware, but they lack the awareness that ransomware is primarily an on-premise problem. If data is stored in the cloud, it can more easily be recovered—reducing the risks associated with ransomware. Companies can recover from a ransomware attack within hours if their data is stored in the cloud, vs weeks if they stored their data on-premise.

The bottom line is that companies that are slow to adopt cloud computing will fall behind in terms of security. A digital transformation is not possible today without cloud computing.

In summary

The world has changed. With new technologies like machine learning and cloud computing, we are seeing more and more innovation in every industry. 

So how can companies make sure they're getting the most out of these technologies? How can they make sure they're staying ahead of the curve?

At Benchling, we are working hard to provide companies with tools for collaboration and communication, so you can achieve higher-quality outputs with more speed—and security—than ever before. We provide tools to make scientific data more accessible, insightful, and collaborative, all while keeping it safe and secure.

It was an honor to present and attend Bio-IT World 2022 and we hope everyone took away some newfound knowledge on data liquidity, security, and management.