An incubator is a device used to provide the ideal environment for microbiological cultures and cells. Therefore, incubators are no mystery to the life science industry—research design and lab manufacturing often rely on the ability to grow and maintain these valuable scientific assets. They require the perfect synergy between conditions such as temperature, humidity, and CO2/O2 concentrations, each of which can greatly affect the cells if not monitored carefully. Therefore, a crucial element of an incubator’s stability is being able to accurately measure the relevant conditions inside in real-time. One potential issue is relying on the built in sensors for data outputs, as the internal sensors are often built-to-cost and may not be accurate. Just like many pieces of lab equipment, incubators come in a few different forms that change the way in which data is received, making it difficult to monitor. Whether it be dry contact, digital integration, or 3rd-party sensors, it is crucial that your organization has access to reliable data and that lab staff can respond to deviations in real-time. Understanding the level of data and visibility that your organization’s incubator provides is crucial to improving lab operations.
It is essential that incubators in the life science industry are able to provide and maintain the conditions required for the cell cultures at hand. A key facet of these conditions is the physiological pH of the environment; one that is usually slightly acidic, with a pH between 7.2 and 7.4. Unfortunately, pH is a very difficult condition to control. In incubator monitoring, some of the conditions being monitored are simply indicators of a stable pH, specifically carbon dioxide and oxygen gas. CO2, for example, is not a metabolic requirement for cell cultures, but must remain at levels of 5-10% concentration. This concentration is necessary to a chemical reaction that takes place within the incubator and controls the pH of the system. This process lowers the oxygen levels, therefore requiring that this condition be monitored closely as well. Other conditions, such as temperature and humidity, are controlled in the incubator for other biological purposes; however, they do have an impact on the pH of the environment and must be monitored and understood as such.
This poses a unique challenge to laboratories that use incubator technology because—while many companies have claimed to do so—research has shown that it is extremely difficult to accurately and continuously measure pH with a sensor. Therefore, in the case of using carbon dioxide to influence pH, for example, the introduction and maintenance of approximately 5% carbon dioxide into the incubator is actually a microbiological technique used to satisfy the need for a pH sensor. Furthermore, the pH sensors that exist in the market are expensive and difficult, if not impossible, to calibrate reliably. This intensifies the need for sensors that can accurately report conditions such as temperature, humidity, carbon dioxide, and oxygen gas concentrations. Once these sensors are in place, users can be certain that their incubator is functioning properly and maintaining the proper physiological pH for their valuable samples.
Given the complexity and importance of incubator monitoring, a handful of methods are used throughout the industry, each of which provides different levels of data and visibility. Below we will review the 3 types of incubator monitoring techniques as well as the pros and cons of each.
A common application is a dry contact alarm, which provides the simplest form of monitoring. Dry contacts are limited to only two capabilities: detecting if a condition has gone out of parameters and triggering an alarm in response. The dry contact communicates solely with the incubator’s built-in sensor, which is typically not advanced or properly calibrated. Furthermore, this type of monitoring does not provide the specific conditions within the incubator, just that the incubator is currently in an alarm status. Therefore, the relationship between the dry contact monitor and the incubator’s built-in sensor is very simple because it relies on a singular communication between the two. Nonetheless, dry contact alarms can provide stability and safety to important life science samples in stages such as R&D. In lab environments where trained staff are readily available and well-equipped to handle deviations as they occur, monitoring with a dry contact alarm is often sufficient.
An incubator that uses monitoring with digital integration capabilities provides an extra level of information to the user because it includes data points that can be graphed and displayed visually. This display feature enables the user to gain more insight on what is going on inside their incubator, which is particularly important for labs that are dealing with sensitive samples. Unlike dry contact monitoring, digital integration monitoring enables root cause analysis to be conducted. If an alarm is triggered, it will be clear to scientists which parameter has been breached, by how much, and for how long. Therefore, they can troubleshoot and determine if the problem is reversible or if all of the samples must be neglected. There are a number of reasons why an alarm might be triggered, from a detected device malfunction to an out-of-specification environmental condition. A digital output monitor relieves the technician of having to uncover the issue on their own, which can save an invaluable amount of time.
Nonetheless, engagement in root cause analysis can be troublesome if the quality of the sensor is compromised. Digital monitoring is often connected to the incubator’s built-in sensors, which are often built-to-cost, low quality sensors. These sensors experience frequent drift and in some cases require frequent calibration in order to be effective. Another roadblock to monitoring incubators through digital integrations is that each incubator requires different connectors, and this makes it difficult to homogenize data into a single dashboard if you have different types of incubators in your lab. Even the most advanced monitoring system cannot provide accurate information if the relevant sensors are not advanced enough, so it is critical that industrial grade sensors are implemented with the monitoring system. Because of this roadblock, digital integration monitoring creates a complicated relationship of certainty and uncertainty regarding the quality of the data: the device’s outputs will likely be consistent, but not necessarily accurate.
Laboratory monitoring sensors can vary quite widely in price, which suggests that they can vary significantly in quality as well. A high quality sensor is one that has a long lifespan and will have minimal drift after it has been calibrated. Because this is difficult to obtain, companies tend to specialize in developing and producing a specific sensor, such as temperature, humidity, or CO2. If these sensors are produced at an industrial grade level, they can guarantee accuracy and longevity to the customer. Despite this, some providers offer products for incubators that claim to measure temperature, humidity, light levels, air pressure, and carbon dioxide in a single device. Users should be wary of this not only because the quality of each sensor is compromised in this situation, but because it requires replacing the entire device if a single sensor breaks. Additionally, high quality sensors are typically large devices due to the methods required to measure these conditions. For instance, a dual beam laser used to detect CO2 gas concentration can only be so small considering the device’s necessary components. If a device claims to measure several conditions at once, users should be aware that either the quality will be compromised or the device will take up valuable space in the incubator.
It is understandable that labs continue to equip their incubators with these devices, however, because high quality sensors are niche and often have different manufacturers, outputs, and software. Attempting to understand and analyze these outputs creates a headache for the user and often pushes labs to settle for lower quality devices. Fortunately, systems that can homogenize all of the data into a single dashboard are available. These “sensor agnostic” systems allow for the accurate comparison of different variables from a number of different sensors, giving users the most accurate and valuable information to improve lab operations.
Additionally, these agnostic systems should have the ability to do more than simply display a reading. Systems should provide the user with the ability to view and analyze the data, resulting in better overall lab procedures. As displayed in the graph below, an incubator with a 30-second door opening can take over 30 minutes to recover. A 30-second door opening may seem relatively harmless; however, a few small door openings can lead to varied, possibly harmful outcomes. Reliable 3rd-party data in conjunction with a smart software provides organizations with meaningful data. This meaningful data ensures that experiments can be properly reproduced and that scientific outcomes are accurate.
3rd party, calibrated sensors can be used to temperature map box type incubators and measure recovery times, as shown in the graph above. This data is helpful to improve lab SOPs and understand overall equipment health, like stability.
Door contacts are useful for performing root cause analysis and understanding incubator health. This graph exemplifies the recovery time of an incubator after a door opening.
When a CO2 tank runs out, the concentration inside the incubators will drop rapidly and put every sample inside at risk. In this situation, every second counts to prevent a catastrophic loss and save the samples or product inside.
3rd-party data on the performance of your incubator provides you with the real picture of what’s going on inside the incubator to help prevent you from relying on the sweet spot you always go to.
When evaluating your incubator monitoring system, there are many variables that need to be taken into consideration. Incubator type, regulatory compliance needs, budget, and research discipline will all influence your decision. No matter how these variables play a role in your lab, however, you can be certain that there is a solution for you.