Laboratory sampling is a critical step in the research and development process, yet it remains a source of significant challenges for many labs. From inconsistent sampling intervals and operator variability to inefficiencies in manual processes, these hurdles can affect data quality, increase costs, and delay timelines.

Automation is increasingly emerging as the solution to these challenges, revolutionizing how labs collect, store, and analyze samples. The Eppendorf Bioprocess Autosampler is one such innovation designed to streamline workflows, enhance data reliability, and reduce operator workloads.

In this Ask the Expert session with Dr. Sarah Wirth, Innovation Manager (Automatization & Software), Bioprocess Lab Solutions at Eppendorf, we explore common sampling issues, the benefits of automation, and how automated systems like the Eppendorf Autosampler can transform laboratory practices. Through insights from Dr. Wirth, you’ll gain a deeper understanding of the challenges faced in traditional sampling methods and how automation addresses these pain points effectively.

1. What are the biggest problems labs face with sampling?

Manual sampling poses several significant challenges. One of the biggest issues is operator availability. Experiments that last several days or weeks often require frequent sampling, but it’s impossible to predict the exact critical time points. As a result, operators may need to take as many samples as possible, which becomes impractical during nights or weekends when no one is available. This creates inconsistent sampling intervals and gaps in process understanding.

Even when operators work extended hours to fill these gaps, it increases stress, costs, and the risk of errors like mislabeling or dilution mistakes. The more hours an operator works, the greater the chance of mistakes due to fatigue.

Additionally, managing multiple tasks simultaneously can make it difficult to take samples exactly on schedule. Even minor deviations can compromise data comparability. Complex experiments involving several bioreactors further complicate this, as sample mix-ups can occur, leading to misleading data.

Another challenge is the variability in operator techniques. Even with standardized protocols, slight differences in how operators handle samples can affect the quality and reliability of the data.

Finally, sampling can be monotonous, especially for experiments requiring frequent collection. Operators may prefer to work on more engaging tasks, which can impact their focus and the accuracy of their sampling.

2. What are the key differences between manual and automated sampling?

Automated sampling solves many challenges associated with manual methods. For example, it enables 24/7 operation, ensuring that critical time points are never missed and maintaining consistent intervals. Automation also eliminates operator variability, ensuring every sample is handled uniformly, which improves data reliability.

Additionally, automation supports intelligent sampling, which can trigger sample collection based on process parameters, like changes in pH or dissolved oxygen, instead of fixed intervals. This captures critical moments without requiring constant operator monitoring.

Automated systems also reduce errors by pre-programming exact sample volumes and automatically storing samples at controlled temperatures. They offer seamless traceability, as all sampling activities are tracked in software, eliminating the need for manual documentation.

Lastly, automation allows for tighter sampling schedules without disrupting other tasks. Operators can focus on more valuable activities while the system handles the sampling process.

3. What kind of data quality gains can you achieve with an autosampler?

Automated sampling significantly enhances data quality by ensuring consistency in sample collection and reducing variability. Without human intervention, operator-related differences are eliminated, improving reproducibility.

Consistent intervals and intelligent sampling ensure no critical data points are missed, resulting in better data harmony. Additionally, the ability to trigger sampling based on process parameters elevates process understanding and performance.

Traceability is another key advantage. Automated systems record all details, including sample volumes, times, and storage locations, making it easier to analyze samples and avoid errors associated with manual record-keeping.

4. Can you talk about the Eppendorf Bioprocess Autosampler and its design inspiration?

The Eppendorf Bioprocess Autosampler was developed to address the industry’s growing need for automation. Our goal was to create a system that simplifies sampling, reduces labor costs, and maximizes resource efficiency.

We prioritized a modular design, allowing customers to upgrade the system as their needs evolve. Early adopters can benefit from future developments by adding hardware or software features.

To ensure ease of use, the autosampler integrates with existing Eppendorf control software, eliminating the need for users to learn a new system. We also designed the system with a compact footprint, enabling it to fit directly above bioreactors to save lab space.

The system supports diverse applications, from microbial to cell culture processes, and is compatible with a wide range of bioreactor sizes. It offers flexibility for both frequent and infrequent sampling needs, making it suitable for various lab setups.

5. What kind of training is required to use the autosampler?

Training for the autosampler is straightforward and typically part of the installation process. Customers are guided through their first experiments to familiarize themselves with the system and its routine procedures.

The training covers basic maintenance tasks, like changing needles or syringes, which require minimal technical expertise.

On the software side, the autosampler operates within the same control software already used for bioreactor management. This makes the learning curve minimal, as users only need to understand how to set up sampling schedules within the existing framework. Most users adapt quickly and can start reaping the system’s benefits immediately.

6. How do you implement the autosampler into current workflows?

Implementing the autosampler involves two key steps: preparing the experiment and configuring the software.

Preparing the experiment is similar to manual methods, with minor adjustments. The bioreactor is connected to the autosampler using tubing, and washing liquids are prepared to ensure the syringe is cleaned between samples to prevent contamination.

In the software, users set up their sampling schedule, specifying intervals, volumes, and any bolus additions. Intelligent planning features ensure sampling schemes are feasible, and schedules can be adjusted during the experiment if needed.

Once configured, the system operates independently, storing samples in designated racks and maintaining complete traceability.

7. In your experience, what surprises labs most after switching to automated sampling?

The ease of use is often the biggest surprise. Many labs expect a complicated transition but find the process seamless. Automated sampling provides more data with less effort and allows technicians to focus on higher-value tasks.

One standout benefit is the ability to start experiments on a Friday and analyze samples by Monday. This accelerates process development and enhances efficiency.

Most labs quickly adapt to the system and find it invaluable, often wondering how they managed without it.

8. What advice would you give to companies considering switching to automated sampling?

My advice is to start by understanding your lab’s specific needs and long-term goals. Think about what you want to achieve—whether it’s reducing operator workload, increasing data points, or improving consistency.

Engage with suppliers to discuss your challenges and expectations. For example, if you have limited lab space, choose a compact system. If you plan to scale up, opt for a modular design that can grow with your needs.

Finally, prioritize training during installation to ensure your team feels confident using the system. Automation is not one-size-fits-all, but with the right approach, it can transform workflows, enhance efficiency, and improve data quality.

For more information, please see Bioprocess Autosampler.