Machine learning drives smarter SPR analysis

Surface plasmon resonance (SPR) is a powerful analytical technique, offering high sensitivity biomolecular interaction analysis for biophysical research across various scientific disciplines. Its ability to provide label-free, real-time monitoring of molecular interaction makes it an invaluable tool for understanding complex biological processes.

However, there are persisting challenges for researchers looking to adopt this approach. As an information-rich technique, SPR generates increasingly large datasets, making analysis a significant bottleneck. This often requires experience and substantial manual oversight, limiting efficiency and accessibility for evaluation of large data sets.

In addition, the industry is facing increasing challenges posed by complex new modalities that require detailed characterization. As a result, there is an increasing need to accelerate R&D productivity with faster results and higher throughput. The diverse technologies used in therapeutic research often hinder a holistic view of a molecule’s properties and critical quality attributes (CQAs), delaying decision-making.

These challenges have driven the adoption of automated solutions, AI-assisted technologies, and machine learning-driven analysis tools that enhance data interpretation and support faster, data-driven insights. This means SPR is now more accessible, efficient, and reliable than ever, no matter the application.

Intelligent SPR analysis

Biacore SPR systems from Cytiva are designed with modern SPR challenges in mind. These systems feature precise temperature control and microfluidics, enabling the measurement of diverse interactions, from rapid fragment binding to slow-dissociating antibodies. With high sensitivity, low baseline noise, and robust reproducibility, Biacore SPR systems promise exceptional data quality. Additionally, this flexible portfolio offers scalable options, accommodating diverse research needs and budgets while optimizing reagent and time usage.

“During more than 30 years on the market, pioneering the use of SPR-based optical biosensors in life sciences, we constantly focused on our users’ needs to deliver innovative, robust and high-quality SPR systems. ,” says Julian Plaga, Global Product Manager of Biacore Software & Digital at Cytiva. “Our system portfolio ranges from the entry level Biacore X100 to the high-throughput Biacore 8 series and features our latest Biacore 1 Series which offers cutting-edge injection tools and field upgrade options.”

Designed for ease of use, Biacore Insight Software is integrated into these systems to streamline interaction analysis. Built-in methods and templates reduce assay development time and allowing scientists to start quickly, regardless of their SPR expertise.

Efficient and reliable analysis of SPR data is crucial, but the growing need for seamless data integration has become equally important as researchers increasingly rely on multiple technologies and readouts to make well-informed decisions. The Biacore Insight Data Integration Extension addresses this challenge by enabling fully automated integration of Biacore SPR data into laboratory information management system (LIMS), scientific data management system (SDMS), and electronic notebooks (ELNs). Leveraging the Biacore Insight Application Programming Interface, users can maximize the value of their SPR data, ensuring streamlined correlation, aggregation, and reporting across diverse platforms.

“We are well aware that our customers are using a variety of technologies to support their research and discovery efforts and ensuring consistency and standardization in data analysis across different scientists and labs can be challenging,” adds Plaga. “To support scientists in this endeavor we recently published the paper Standards for Reporting Optical Biosensor Experiments (STROBE).” The STROBE methodology is technology agnostic and aims to improve the standard of reported biosensor experiments and encourage transparency and reproducibility in scientific research¹. Learn more about how STROBE aims to improve standards in optical biosensor-based data reporting here.

How to maximize your SPR potential

To get the most out of your analysis, there are a range of optional software extensions available. These are designed to enable advanced capabilities to suit your individual application needs, including enhanced data collection and analysis speed, advanced hit selection for drug discovery, and improved accuracy in lead optimization studies.

Biacore Intelligent Analysis^™ is a machine learning software extension designed to take your SPR data analysis to the next level. Compatible with Biacore T200, Biacore S200, Biacore 8 series, and Biacore 1 series SPR systems, the software automates binding level and affinity screening analysis to save over 80% of the time typically spent on data evaluation. Pretrained prediction models offer ready-to-use functionality, while users can refine or create custom models tailored to their needs.

“This software encapsulates over 30 years of development and the vast experience of our scientists,” explains Plaga. “We made it a point to create transparency for the analysts and scientists utilizing this way of automating data analysis – with our recent launch of Biacore Insight Software 6.0 we improved all aspects of Biacore Intelligent Analysis, from performance, to custom classifications and additional automated steps.”

With these capabilities, Biacore Intelligent Analysis software empowers researchers to streamline workflows,and drive faster decisions in therapeutic development:

• Save time by automating tasks like sample classification, outlier removal, and steady-state affinity analysis.
• Improve flexibility by reclassifying samples, retraining models, or developing custom models to align with specific workflows.
• Ensure reproducibility via uniform analysis across multi-user environments.
• Support lab training through use as a learning tool, helping new researchers quickly gain proficiency in data interpretation.

SPR innovations in drug discovery

In the field, Biacore SPR systems have demonstrated remarkable utility, as evidenced by their presence in over 60,000 peer-reviewed publications. By delivering critical kinetic and binding data through robust SPR methodologies, these systems play a pivotal role in accelerating the development of advanced therapeutic modalities.

Proteolysis targeting chimera (PROTAC): PROTACs are novel therapeutic molecules that can degrade target proteins by hijacking a cell’s ubiquitin–proteasome system. Critical to the efficacy of PROTACs is the formation of ternary complex, and the detailed characterization of this formation is essential for facilitating PROTAC development. Studies using Biacore SPR systems have revealed how specific PROTAC designs exhibit target-specific degradation by forming highly cooperative and stable ternary complexes².

Antibody-drug conjugates (ADCs): Label-free, real-time monitoring facilitates the selection of antibody variants with optimal binding properties, which is crucial for designing ADCs with improved therapeutic potential³. By providing precise measurements of binding affinities and kinetics, Biacore SPR systems assist researchers in identifying candidates that exhibit strong and specific interactions with target antigens. Additionally, the ability to perform epitope mapping enables the identification of distinct binding sites on antigens. This ensures that selected antibodies bind to appropriate epitopes, reducing the likelihood of off-target effects and enhancing the safety profile of ADCs.

Multi-specific antibodies: The ability to comprehensively assess antibody-antigen interactions is crucial for designing antibodies with desired specificities, functionalities, and achieve optimal therapeutic performance. Biacore SPR systems have been instrumental in characterizing the binding properties of engineered antibodies, specifically in the development of fragment antigen-binding region (Fab)-based bispecific antibodies⁴. These systems enabled researchers to simultaneously measure multiple binding affinities, kinetics, and specificities, as well as optimize antibody formats using the provided insights on stability and efficacy.

Automation and AI fuels future of SPR

As the demands on biophysical research grow, automation and smart tools have become essential for unlocking the full potential of SPR. By integrating advanced technologies – such as machine learning – modern platforms like Biacore are well positioned to transform how researchers tackle challenges associated with SPR. These innovations not only streamline workflows and accelerate decision-making but also ensure reproducibility, reliability, and scalability in therapeutic development. Embracing these cutting-edge solutions empowers scientists to focus on discovery while advancing the boundaries of SPR’s applications across diverse fields.

Explore the full Biacore portfolio and learn more about SPR interaction analysis here.

References

1. SLAS Discovery (2024) Standards for reporting optical biosensor experiments (STROBE): Improving standards in the reporting of optical biosensor-based data in the literature. [online] Available at: https://www.sciencedirect.com/science/article/pii/S2472555224000546

2. Nature Communications (2023) Affinity and cooperativity modulate ternary complex formation to drive targeted protein degradation. Available at: https://www.nature.com/articles/s41467-023-39904-5

3. PLOS One (2019) Binding and functional profiling of antibody mutants guides selection of optimal candidates as antibody drug conjugates. [online] Available at: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.022659

4. mAbs (2015) Fab-based bispecific antibody formats with robust biophysical properties and biological activity. [online] Available at: https://www.tandfonline.com/doi/full/10.1080/19420862.2015.1022694