🔬 Free & Browser-Based

Free Online SPR Data Analysis

Upload your surface plasmon resonance data, fit binding kinetics with publication-quality models, and export results — all in your browser. No installation, no license fees.

Start Analyzing →Try with Example Data

What Is SPR Data Analysis?

Surface plasmon resonance (SPR) is a label-free biophysical technique used to measure real-time biomolecular interactions. An SPR experiment produces sensorgrams — curves that show how analyte molecules bind to and dissociate from immobilized ligands on a sensor chip surface. These curves encode the kinetic and thermodynamic properties of the interaction.

SPR data analysis is the process of extracting meaningful kinetic parameters from these sensorgrams. This includes determining the association rate constant (ka), dissociation rate constant (kd), and equilibrium dissociation constant (KD) by fitting mathematical models to the experimental curves. Proper SPR data analysis also involves data cleanup steps such as reference subtraction, baseline correction, and outlier removal to ensure accurate and reproducible results.

Traditionally, SPR data analysis has required vendor-specific desktop software — applications like BIAevaluation or Biacore Insight for Cytiva instruments, or FortéBio Data Analysis for Octet systems. These tools are often expensive, restricted to specific operating systems, and locked to a single instrument vendor. KinetiHub provides a modern, vendor-neutral alternative that runs entirely in your browser.

Whether you are characterizing antibody-antigen interactions, screening small molecule drug candidates, or studying protein-protein binding kinetics, robust SPR data analysis is essential for producing reliable, publication-quality results. Learn more about the fundamentals in our Academy — SPR Basics course.

KinetiHub's SPR Analysis Features

Everything you need for rigorous binding kinetics analysis, built for scientists who value accuracy and efficiency.

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AI-Powered Smart Upload

Drag and drop your raw data files. KinetiHub's AI engine automatically detects the instrument format, parses sensorgram data, and organizes your curves by concentration — no manual configuration needed.

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Multi-Vendor Support

Native parsing for Octet BLI, Biacore (all exports except BIDRUN), Gator Bio, and Malvern Creoptics Wave. Carterra LSA is in beta. Upload your data and we'll get it working.

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Interactive Curve Viewer

Explore your sensorgrams with a responsive, zoomable curve viewer. Select individual curves, toggle between raw and processed data, and visually inspect your binding kinetics before fitting.

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5 Kinetic Fitting Models

Choose from five validated fitting models: 1:1 Langmuir, Mass Transport Limited, Heterogeneous Ligand, Two-State Conformational Change, and Steady-State Affinity. Each model reports ka, kd, KD, and goodness-of-fit statistics.

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Data Cleanup Pipeline

Apply reference subtraction, baseline correction, and alignment in a configurable pipeline. Remove artifacts and systematic errors to ensure your kinetic parameters are accurate and your analysis is publication-ready.

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Export to CSV & PowerPoint

Export your fitted parameters, processed curves, and summary tables as CSV files for further analysis or as PowerPoint slides ready for presentations and journal submissions. No screenshots needed.

💻100% browser-based — works on Windows, macOS, and Linux. No downloads, no Java, no license dongles.

How It Works

From raw data to publication-ready results in three steps.

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STEP 1

Upload Your Data

Drag and drop your Biacore, Octet, Carterra, or CSV files. The AI engine identifies the format and extracts your sensorgrams automatically.

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STEP 2

Analyze & Fit

Clean up your data with the processing pipeline, select a kinetic model, and fit your curves. Review residuals, chi² values, and fitted parameters interactively.

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STEP 3

Export Results

Download your kinetic parameters and fitted curves as CSV or PowerPoint. Ready for your next paper, report, or team presentation.

Try It Now — Free →

Supported Instruments

We're building support for every major biosensor platform. Here's where things stand.

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Octet

RED96, RED96e, R8, R2, HTX. FortéBio/Sartorius BLI data files.

✓ Fully supported
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Biacore

T200, 8K, 8K+, S200, X100, T100. All exports supported except BIDRUN files.

✓ Fully supported
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Gator Bio

Gator and GatorPlus BLI platforms. Native data files.

✓ Fully supported
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Creoptics Wave

Malvern Panalytical Creoptics Wave system data.

✓ Fully supported
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Carterra

LSA and LSAXT. High-throughput SPR array data.

Beta — basic support
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CSV / Generic

Any instrument. Export as CSV with time and response columns.

Upload & we'll parse it

Don't see your format? Upload anyway — we review new formats manually and typically add support within 24 hours. Your upload helps us expand coverage. Learn more about experiment design best practices.

Kinetic Fitting Models

KinetiHub offers five validated kinetic models for SPR data analysis. Choosing the right model is critical for obtaining accurate binding kinetics parameters. Read our in-depth guide to fitting models for detailed theory.

1

1:1 Langmuir Binding

The simplest and most commonly used model for SPR data analysis. Assumes a single analyte binds reversibly to a single ligand site with a 1:1 stoichiometry. Reports ka, kd, and KD directly.

Use when: Your interaction is simple, monovalent, and shows clean exponential association and dissociation phases. This is the default starting point for most SPR experiments.

2

Mass Transport Limited

Extends the 1:1 model by accounting for mass transport limitations — situations where analyte diffusion to the sensor surface is slower than the binding reaction itself. Adds a transport coefficient (kt) to the standard kinetic parameters.

Use when: You observe linear (rather than exponential) initial association phases, or when high ligand densities and fast-binding analytes suggest diffusion-limited kinetics.

3

Heterogeneous Ligand

Models a scenario where the analyte binds to two independent populations of ligand on the surface, each with distinct kinetic parameters. Returns two sets of ka and kd values along with their relative contributions.

Use when: The 1:1 model gives poor fits with systematic residuals, and you suspect heterogeneous immobilization or multiple binding orientations of the ligand on the chip surface.

4

Two-State Conformational Change

Describes an interaction where initial binding is followed by a conformational change in the complex, leading to a more stable bound state. The model includes two sequential steps: binding (ka1/kd1) and conformational change (ka2/kd2).

Use when: Dissociation curves show a biphasic pattern that cannot be explained by heterogeneous ligand, or when the biology suggests induced-fit or conformational selection mechanisms.

5

Steady-State Affinity

Rather than fitting the kinetic curves, this model determines the equilibrium dissociation constant (KD) by plotting the steady-state response level as a function of analyte concentration. Fits the resulting isotherm to a Langmuir binding equation.

Use when: Kinetics are too fast to resolve (rapid on/off), the interaction reaches equilibrium during each injection, or you only need an affinity constant rather than individual rate constants.

KinetiHub vs. Traditional SPR Software

See how KinetiHub compares to the desktop applications you may already be using for Biacore data analysis and SPR curve fitting.

FeatureKinetiHubBiacore InsightTraceDrawerBIAevaluation
PriceFree tier availableIncluded with instrument~€2,000+ licenseLegacy / discontinued
InstallationNone — browser-basedWindows installerWindows installerWindows installer
Operating SystemAny (browser)Windows onlyWindows onlyWindows only
Multi-Vendor Support✓ Biacore, Octet, Carterra, CSVBiacore onlyMultiple vendorsBiacore only
AI-Powered Upload✓✗✗✗
Fitting Models5 modelsMultipleMultipleMultiple
Export FormatsCSV, PPTXProprietary, CSVCSV, PDFBIA, CSV
UpdatesAutomaticManual installManual installDiscontinued

Frequently Asked Questions

Common questions about using KinetiHub for SPR data analysis.

Is KinetiHub free?+
Yes. KinetiHub offers a free tier that includes full SPR data analysis capabilities — upload, curve fitting, data cleanup, and export. No credit card required. Advanced features like batch processing and team collaboration are available in paid plans. Check our pricing page for details.
What file formats are supported?+
KinetiHub supports native file formats from Biacore (T200, 8K, S200), Octet (RED96, R8), and Carterra (LSA) instruments. You can also upload standard CSV files from any biosensor platform. The AI-powered smart upload automatically detects your file format and parses it correctly — just drag and drop.
Can I use KinetiHub for publication?+
Absolutely. KinetiHub generates publication-quality kinetic parameters (ka, kd, KD) with statistical measures including chi² values and residual plots. You can export your fitted curves and data as CSV or PowerPoint files suitable for journal submissions. Many researchers already use KinetiHub for their published SPR and BLI data analysis.
How does KinetiHub compare to BIAevaluation?+
KinetiHub is a modern, browser-based alternative to BIAevaluation. Unlike BIAevaluation — which is Windows-only, Biacore-specific, and no longer actively developed — KinetiHub requires no installation, works on any operating system, supports files from multiple instrument vendors, and includes AI-powered features for automatic file detection and data cleanup. It also offers a more intuitive interface with interactive curve visualization.
Do I need to install anything?+
No. KinetiHub runs entirely in your web browser. There is nothing to download, install, or update. It works on Windows, macOS, Linux, and even tablets. Just open the website and start analyzing your SPR data immediately.

Ready to Analyze Your SPR Data?

Join researchers worldwide who use KinetiHub for fast, accurate binding kinetics analysis. Upload your first dataset in under a minute.

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