Pharmaceutical companies go to great lengths to ensure the stability of their products. They test for it, they plan for it, they design around it. Why? Because stability is essential to the therapeutic success of a product. Without it, maintaining efficacy and safety would be impossible. Proteins are particularly susceptible to aggregation, and this can lead to immunological effects that are detrimental to the patient.

As a result, regulatory agencies expect drug developers to characterize protein aggregates and control their presence in injectable formulations – which shows just how important it is to have effective tools that can monitor particle levels.1

Traditional Analytical Techniques:  What You’re Not Seeing Can Hurt You

 There are a number of analytical techniques currently used to measure the size, shape, and distribution of particles in a sample. However, with current subvisible analysis techniques, companies are only able to measure a tiny fraction of the aggregates present in formulations, leaving them in the dark about potential risks.

  • Microscopy: As the most fundamental analysis technique for the characterization of particles, microscopy provides detailed information on size and morphology. While it is a low-throughput method, it offers the advantage of being a direct counting method that allows for the analysis of each sample in its entirety.1 Still, microscopy is labor intensive and requires trained analysts.
  • Light Obscuration (LO): Light obscuration is an optical technique that measures the loss of light intensity that occurs as particles flow through a beam of light. 1 However, LO methods are unable to accurate count particles in high viscosity formulations and cannot assess particle morphological information. This method also does not provide the same level of detail as microscopy, as particles that are transparent and non-spherical often do not effectively obscure light and thus undercounted in LO.
  • Micro-flow Imaging (MFI): A commonly used method is micro-flow imaging, also referred to as imaging microscopy (FIM) or dynamic imaging analysis (DIA). This method captures dynamic images of particles as they flow through a cell and then uses images to calculate size, shape, and count based on a pixel-by-pixel analysis.1 While this technique provides valuable information, there are drawbacks. For example, the images can be difficult to interpret and the process is time consuming. And because this method is fluidics-based, it requires higher sample volume and user expertise. Pairing that requirement with the risk of clogging, leaking or instrument failure is a big fear. 

Get the Whole Picture with BMI: High Contrast Particle Imaging for Visible and Subvisible Analysis

To help overcome some of these challenges with today’s current methods, Halo Labs has developed a new particle analysis technique called Background Membrane Imaging (BMI). BMI uses a light microscope to image the surface of a membrane, and then applies advanced image processing algorithms to detect and quantify the particles.

BMI reinvents membrane imaging with modern robotics, image processing and novel optics in a 96 well filter plate format that works just like a plate reader. This technique has several advantages over traditional methods, including greater sensitivity and the ability to image large areas of the membrane at once. In addition, BMI does not require the use of expensive equipment or specialized training.

BMI uses sophisticated image-processing techniques to analyze images and acquire particle data.  The key is to first take a background image of the membrane.  After samples are filtered through and particles are captured, the same membrane is re-imaged, this time with particles on the surface. The background image is precisely aligned with the sample image and then subtracted on a pixel-by-pixel basis so that the background texture is eliminated and particles are revealed. Contrast is 10x greater than measurements done in liquid, sizes are calibrated with an electron microscope, and analysis is fully automated.

Recent Studies Demonstrate Effectiveness of BMI

In a recent study, Halo Lab’s Aura® platform (formerly known as HORIZON) was optimized and compared to LO, the MFI™ 5200 Series by ProteinSimple, and the FlowCam® 8000 Series by Fluid Imaging Technologies. The study compared precision, linearity, subvisible particle (SVP) concentration and morphological output of BMI compared to the other three techniques. BMI was shown to be useful tool in measuring protein aggregates in a high-throughput manner. The authors showed that it is a simple, fast method and can produce similar or better precision and sensitivity to current dynamic flow imaging techniques, eliminating the need for large sample volumes and long analysis time.1

In a second study, the goal was to evaluate BMI for its use in the analysis of SVPs and to compare it to DIA methods for pharmaceutically relevant drugs. The authors wrote, “The team demonstrated BMI to be a suitable orthogonal method for the characterization of subvisible particulate matter in biopharmaceutical products. Especially, simplicity of sample processing, high achievable throughput, use of disposable consumables, and low required sample volume can make BMI an attractive alternative or complement to particle analysis by DIA. In particular, BMI might be a highly valuable tool for high-throughput screenings, for example, in formulation development, where various formulations with different excipients and thus disparate properties (e.g., refractive index) need to be compared.”2

Based on their findings the authors concluded: “We suggest an adaptation of the Aura hardware to enable imaging of complete wells therefore enabling accurate particle counting.” 2

The results of these studies demonstrate that BMI can be successfully applied to characterize subvisible particulate matter in biopharmaceutical products. This technology offers a simple and efficient approach for the characterization of these particles, which is valuable for ensuring product quality and safety.

With Halo Lab’s Aura PTx, which utilizes BMI as its primary analytical technique, there’s a better way to perform particle analysis. Aura PTx makes it easy to quickly identify and count aggregates that form due to degraded polysorbate in your formulation. And with two-channel fluorescence, you can determine if aggregation in your protein therapy is caused by proteins or polysorbates in your sample – at the same time.

To learn more about background membrane imaging and how Aura PTx can get you to your best formulation faster, visit:



There is a well-known saying that says, “behind every great man, there is a great woman.”

This quote has never been more relevant than it is today in the biotech industry. Despite making up half of the population, women are severely underrepresented in leadership positions throughout the biotech sector.

However, as we continue to battle against diseases and strive for innovation, it is becoming increasingly clear that women need to be at the forefront of this movement. In order to make real progress in biotech, we must break down barriers and empower women leaders to drive change. Only then can we achieve our ultimate goal: saving lives.

Read more

Did you know that subvisible particles (SVPs) are the leading cause of drug product recalls? Despite being tiny, these particles have a big impact on biologic, cell, and gene therapies – not only limiting a product’s shelf life, but also comprising patient safety. For this reason, injectable drugs face strict requirements to be virtually free of SVPs. Read more

CHO cell line development (CLD) has revolutionized modern therapeutic antibody production due to their scalability benefits, ability to produce proteins with the necessary mammalian posttranslational modifications, and large yield protein titers.1

To meet the exponentially growing demand, CHO cell line developers have focused their attention on maximizing titer. However, newer and more complex biologic modalities such as bispecifics and other types of antibodies that display low expression yield, dramatically higher concentration requirements of injectables, and significant market demands have pushed CHO cell lines to their limit.1

While progress has been made, little has been done to characterize the physical stability of secreted antibodies from their inception during CHO cell line development. Scientists have been pushed to stabilize biologics that were not designed with aggregation in mind from the ground up, often with limited success.

Faster, More Accurate Antibody Stability Pre-Screening 

Halo Labs’ Aura™ immunoassays with particle characterization bridge the gap between cell line development and developability to enable pre-screening for antibody stability once mAbs are secreted from CHO cells. Analyzing biologically complex cellular and protein samples present in CLD to characterize secreted protein stability is now faster and more accurate. Our Aura systems provide an easier way for protein therapeutic developers to rank and select CHO cell line winners.

To demonstrate their effectiveness, we conducted a study in which we used an established antibody labeling protocol (Figure 1) that required only a 40 µL sample to characterize protein titer and rank cell lines according to the physical stability of the secreted antibody.

Figure 1: Schematic of the workflow using the Aura immunoassay to assess CHO stability during cell line development.

Figure 1: Schematic of the workflow using the Aura immunoassay to assess CHO stability during cell line development.

We imaged and analyzed various antibody secreting CHO cell lines using Aura PTx. Images were acquired in brightfield, FL1 Thioflavin T (ThT, red), and FL2 human IgG (HIgG, green) channels. These images allowed us to quickly grasp the secreted antibody stability. As seen in Figure 2, Cell Line K was the most stable with almost zero antibody aggregation, Cell Line M was moderately stable, and Cell Line D was the least stable with several orders of aggregates above control observed. The results demonstrate how Aura PTx can quickly visualize and easily differentiate between high-, mid-, and low-levels of antibody aggregation using the Aura immunoassay, and quickly distinguish if the particles measured are CHO cells or subvisible antibody aggregates.

Figure 2. Stability analysis for antibody secreting CHO cell lines

Figure 2. Stability analysis for antibody secreting CHO cell lines

Cell Line Rankings Based on mAb Stability

Aura PTx with Particle Vue software performs high throughput characterization and identification of subvisible aggregates across an entire experiment, enabling the ranking of samples based on stability. The 15 cell line candidates were ranked for commercialization according to antibody stability based on the total area of particle fluorescence observed in the FL2 HIgG antibody channel (green). The immunoassay results display drastic differences between various CHO cell lines depending on the stability of the secreted antibodies.

With Aura immunoassays, stability testing has never been easier. You can now screen for stability of antibodies in CHO cells quickly and efficiently with only 40 μL per well. This low-volume method provides positive results within 2 minutes or less, resulting in painless analytical measurements that don’t require entire flasks of cells. Our Particle Vue software automatically characterizes and quantifies subvisible antibody aggregates visually, giving you a high-level ranking on each sample. Stored images deliver granular insights into the types of physical instabilities found in biologics for deeper understanding.

And it’s not just about our immunoassay method. Aura systems enable quick characterization of unfiltered cell lines samples through low-volume, high-throughput imaging, counting, sizing and identification. Analyzing biologically complex cellular and protein samples present in CLD to characterize secreted protein stability has never been faster or more accurate.

To learn more about how you can leverage the power of immunoassays during cell line development, download our app note: App Note 18: Identify Stable Biologic Candidates During Cell Line Development