The accuracy of high precision techniques such as GC-MS and LC-MS depends heavily on the quality of the sample preparation preceding them. However, many preparation workflows are complex and time-consuming, involving numerous steps such as homogenization, centrifugation, mixing, filtration, shaking, and dilution. Such labor intensive tasks are often performed manually, requiring highly skilled personnel to ensure accurate and reproducible results. This approach is not only tedious for laboratory staff but also creates a bottleneck – delaying analysis while samples await preparation. Manual workflows create challenges in various fields, such as PFAS and SVOC testing for environmental work and medicinal cannabis screening in pharmaceutical settings, each adding unique complexities to sample preparation.
Three Telling Examples
PFAS in soil
Commonly used methods for per- and polyfluoroalkyl substances (PFAS) analysis, such as EPA 1633, require detection in the low parts-per-trillion range, pushing laboratories to the limits of sensitivity. Complicating matters further, PFAS compounds are found in many common laboratory plastics, increasing the risk of inadvertent contamination during preparation. The soil matrices themselves add another layer of difficulty, as their heterogeneous composition makes consistent extraction and dilution hard to achieve manually.
SVOCs in water
Semi-volatile organic compounds (SVOCs) in water frequently require liquid-liquid extraction: a workflow that is time-consuming, operator dependent, and reliant on hazardous solvents such as dichloromethane. Achieving reproducible phase separation and efficient extraction can be difficult, particularly when working with variable real-world matrices such as surface water or wastewater. This can make it challenging to meet strict regulatory limits defined in recommended methods such as EPA 8270 or 3511.
Medicinal cannabis testing
The processes involved in regulatory testing of cannabis-based medicinal products require accurate quantification of cannabinoids and terpenes alongside screening for contaminants such as pesticides, heavy metals, residual solvents, and microorganisms. Because these products come in a wide range of formulations, preparing reliable extracts for GC- or LC-MS often involves numerous manual steps, each of which can introduce variability. As a result, many laboratories now face preparation-driven backlogs, with samples spending more time waiting to be processed than waiting to be analyzed.
Although these “Three Telling Examples” span very different applications in environmental, pharmaceutical, and consumer safety testing, they all illustrate the same point: manual sample preparation is slow, difficult to standardize, and vulnerable to human variation.
Automation can help address these issues by simplifying critical steps and reducing the risk of human error. However, laboratories must ensure that any automated solution they adopt can support the wide range of workflows required across modern analytical science.
Laboratories have long used various forms of automation to ease the burden of sample handling: traditional liquid-handling robots can streamline routine pipetting and dilution steps, and automated solid-phase extraction systems can help to standardize cartridge-based cleanup procedures. Newer tools – including digital workflow tracking, integrated sensors, and AI-assisted optimization – also contribute to greater consistency. However, these approaches typically address only isolated parts of the workflow and are often limited when matrices are complex or require multiple sequential operations. As workflows become more demanding, partial automation may no longer be enough to support integrated extraction, cleanup, and dilution steps (1,2).
Building on these foundations, recent developments in laboratory automation have introduced more comprehensive platforms capable of handling complex sample preparation workflows with far greater consistency than manual methods. Modern systems can automate essential operations such as extraction, mixing, filtration, and dilution, while controlling volumes and transfer conditions to maintain accuracy at trace levels. Many platforms also support multiple sample formats and can prepare extracts suitable for direct introduction into chromatographic instruments. Importantly, next generation automated approaches are increasingly aligned with sustainability goals, allowing reduced solvent consumption and more efficient use of reagents (2). Standardizing critical stages of preparation in this manner helps to reduce variability and streamline high-throughput workflows.
As laboratories move toward more comprehensive automation, many are already seeing tangible benefits in day-to-day workflows. In our experience working with high-throughput testing facilities, shifting from fully manual extraction, mixing, filtration, and dilution to more structured, sequentially controlled preparation can substantially reduce hands-on time. Workflows that once required several hours of technician input are often completed in far less time simply because repetitive steps are standardized and volumes, mixing conditions, and filtration parameters all applied consistently.
These efficiencies are particularly important when quantifying cannabinoids and terpenes at trace levels, where even small variations can affect accuracy. Facilities adopting more coordinated preparation protocols also report improved reproducibility across operators, leading to fewer repeat analyses and steadier throughput. Similar patterns are emerging across other high-volume testing sectors, illustrating how multi-step automation – rather than isolated robotic tasks – helps laboratories keep pace with rising sample loads and increasingly stringent regulatory expectations.
In conclusion, automation of sample preparation offers a practical solution to current bottlenecks in analytical chemistry workflows – streamlining complex protocols and reducing manual variability to provide more accurate and reliable results. These improvements are especially valuable in applications that require confident identification of trace level compounds across food, environmental, and pharmaceutical testing. Experiences from laboratories that have adopted automated preparation show clear benefits in throughput, reproducibility, and staff workload. As analytical demands continue to rise, and regulatory expectations become more stringent, flexible automated solutions will play a key role in maintaining efficiency and ensuring high quality results.
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References
- DAV Medina et al., “Modern automated sample preparation for the determination of organic compounds: A review on robotic and on-flow systems,” Trends in Analytical Chemistry, 166, 117171 (2023).
- WA Khan et al., “Automation and high throughput sample analysis with various platforms in microextraction techniques: A need for ecofriendly, green, and cost-effective sample preparation approaches – A review,” Trends in Analytical Chemistry, 189, 118247 (2025).
