Automation in Drug Discovery Is Accelerating Workflows

Automation in drug discovery is helping to address some of the sector’s most persistent bottlenecks: sample preparation variability, manual labor costs and data acquisition speed.

In its recent Advances in Drug Discovery & Development 2024 symposium, Technology Networks hosted two experts from Agilent Technologies – Stephen Murphy, manager of Workflows and Applications, and Kevin McCann, product manager for RapidFire – who discussed how the AssayMAP Bravo^TM and RapidFire^TM systems are helping to transform early-stage drug research.

Overcoming challenges with automated sample prep

Sample preparation has long been a key source of error and inefficiency in the drug discovery pipeline.

“One of the most common barriers is issues with data quality,” said Murphy.

“Sample prep is particularly challenging because it introduces variability, can involve manual errors and is often costly in terms of labor.”

Murphy introduced Agilent’s AssayMAP Bravo platform, which uses a high-precision liquid handling system combined with chromatography-based cartridges to deliver automated sample prep.

“You have high precision syringe pumps connected to packed columns, so there’s no air gap,” he explained. “Whether you're running 1 or 96 samples, you get chromatographic behavior with highly reproducible results.”

Designed to be flexible and easy to use, the AssayMAP Bravo platform supports a wide range of workflows by offering cartridges with different surface chemistries. Its user-friendly software includes pre-configured applications, which, according to Murphy, makes training fast and accessible: “One of our customers said they were able to get an intern up and running on the system in just an hour.”

Murphy also emphasized that AssayMAP Bravo is built to accompany drug candidates from early discovery through to development.

“You can use the same platform across multiple stages, and when compliance requirements come in, you just turn on features like audit trails and e-signatures, without having to change protocols,” he said.

Furthermore, integrated reporting features simplify documentation and troubleshooting.

Automation in drug discovery: Accelerating data acquisition with RapidFire

While automated sample prep helps ensure reproducibility in drug discovery, accelerating a lab’s mass spectrometry workflows remains equally critical. McCann highlighted how the RapidFire system enables drug discovery teams to acquire data much faster than traditional liquid chromatography-mass spectrometry (LC-MS) workflows allow.

"RapidFire is really made to address the issue of collecting more data, handling more samples in less time," McCann said. "With traditional LC-MS, you're talking minutes per sample. With RapidFire, we're down to 8–15 seconds per injection, and in some cases, as low as 2 seconds."

RapidFire achieves this speed by using online solid-phase extraction instead of chromatographic separation, enabling high-throughput analysis without compromising data quality.

"The cartridges are reusable for hundreds to thousands of injections, and they come in a wide range of chemistries," McCann explained. "If you're familiar with LC-MS, the transition to RapidFire is straightforward."

An additional advantage of RapidFire is its label-free analysis capability, making it ideal for applications like high-throughput screening (HTS) and absorption, distribution, metabolism and excretion (ADME) studies. "You can do MS analysis on native substrates, without the need for a fluorescence tag or other label," said McCann.

To reinforce confidence in the system's reliability, McCann presented multiple correlation studies comparing RapidFire to traditional LC-MS methods.

"You can be confident that increasing throughput isn’t compromising data quality," he said. Whether connected to a triple quadrupole or a time-of-flight mass spectrometer, RapidFire consistently delivered reproducible, high-quality results.

Automation in drug discovery: Supporting the entire process

Both Murphy and McCann underscored that their platforms are designed not just for isolated tasks, but to support the entire drug discovery continuum.

Murphy pointed out that AssayMAP Bravo’s adaptability makes it ideal for multiple sample preparation workflows, from proteomics and biomarker discovery to critical quality attribute (CQA) monitoring in biologics development. "You can develop assays early, transfer them electronically, and use the same platform later with compliance features turned on. It’s a real investment in workflow continuity," he said.

Similarly, McCann highlighted RapidFire’s compatibility across Agilent’s full line of mass spectrometers, making it a flexible solution for different experimental needs and lab setups. "If you're space-constrained, the Ultivo Triple Quad fits right inside the RapidFire footprint," he noted, emphasizing how laboratories can optimize both performance and space.

In real-world case studies, RapidFire has helped cut full study timelines dramatically. "In one ADME workflow, moving from LC to RapidFire reduced data acquisition time from 24 hours down to 2 hours," McCann shared. "When paired with a time-of-flight instrument, the full study timeline dropped from 38.5 hours to just 10 hours."

Looking ahead: Enabling better science faster

The integration of solutions like AssayMAP Bravo and RapidFire represents more than just faster or easier laboratory operations – it marks a broader shift toward automation in drug discovery, allowing scientists to focus on innovation.

"Automation isn't about replacing scientists," Murphy reflected. "It's about freeing them up to do more valuable work by removing tedious and error-prone manual steps."

McCann echoed a similar sentiment: "At the end of the day, it's about moving promising candidates forward faster, making better decisions earlier, and ultimately improving the probability of success in clinical trials."

As the pace of drug discovery continues to accelerate, technologies that simplify complexity, minimize variability and deliver high-quality data faster will be key to turning today's research into tomorrow's therapies.

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