Explore More Parameter Space. With Fewer Experiments

YMC ChromaCon builds a calibrated mechanistic model of your separation from gradient batch runs with fraction analysis. The model describes the physical and chemical interactions governing your chromatographic system and, once validated, can predict separation behavior under conditions you haven’t yet tested experimentally.

Modeling scope:

• Construction of a mechanistic chromatographic model from your experimental data
• Model calibration using gradient batch runs and fraction composition data
• Model validation against independent experimental data (e.g. a different gradient slope or loading condition)
• Simulation of the effect of operating parameters (gradient slope, load, column dimensions, mobile phase composition, flow rate) on separation performance
• Parameter screening and optimization to identify improved batch operating points
• Scale-up simulations for column dimension and flow rate changes

You receive:

• Calibrated and validated mechanistic model
• Simulation results showing predicted separation under varied conditions
• Recommended optimized batch operating point(s)
• Scale-up parameters and scenarios
• Comprehensive report with all simulation results

Who this is for: Teams working with single-column batch chromatography who want to optimize their process computationally, explore scale-up options, build process understanding for regulatory submissions, or reduce experimental screening effort. No interest in continuous chromatography is required — the batch model is a valuable tool in its own right.

Building on a calibrated batch model (which is created as part of this service), ChromaCon simulates MCSGP continuous polishing performance and evaluates its potential relative to your existing batch process. The MCSGP modeling service is available in two stages.

Stage 1 — Model-Based MCSGP Feasibility Study

Starting from linear gradient batch runs with fraction analysis that you provide, we calibrate and validate the mechanistic model, then simulate MCSGP processes to predict performance.

Scope: MCSGP operating point simulation, batch vs. MCSGP comparison, prediction of yield/purity/productivity, simulation of AutoPeak® dynamic process control impact, and generation of MCSGP scale-up parameters. We support you in transferring the simulated operating point to the Contichrom® CUBE for experimental validation.

Stage 2 — Model-Based MCSGP Optimization

Building on Stage 1, we systematically optimize MCSGP operating parameters and map the process design space through iterative simulation.

Scope: Simulation of parameter variations (column bed height, eluent modifier content, feed purity, flow rate, load), optimization of MCSGP-specific parameters (gradient slope, in-line adjustment ratios, elution/recycling phase borders), design space determination with and without AutoPeak® control, and robustness analysis.

You receive (Stage 2): Optimized and robust MCSGP setpoint, optimized AutoPeak® parameters, full design space evaluation with Pareto plots and robustness maps.

Stage 1 can be commissioned independently. Stage 2 builds on Stage 1 results.

Typical applications: Peptide purification (RP), oligonucleotide purification (AEX).

YMC ChromaCon models your CaptureSMB® continuous capture process using breakthrough curve data and mechanistic modeling. The approach is analogous to the MCSGP modeling service and follows the same two-stage structure.

Stage 1 — Model-Based CaptureSMB® Feasibility Study

We calibrate a mechanistic model using breakthrough curve data and batch binding experiments that you provide. The model is used to simulate CaptureSMB® performance, predict productivity gains and resin utilization improvements relative to batch capture, and evaluate the impact of AutomAb® dynamic loading control.

You receive: Simulated CaptureSMB® performance, batch vs. continuous comparison, AutomAb® impact analysis, and scale-up parameters.

Stage 2 — Model-Based CaptureSMB® Optimization

Building on Stage 1, we optimize the CaptureSMB® operating parameters — loading conditions, phase timing, flow rates — and evaluate robustness through simulated parameter variations. Design space mapping shows how performance responds to variability in feed concentration, flow rate, and column conditions, with and without AutomAb® control.

You receive: Optimized CaptureSMB® setpoint, optimized AutomAb® parameters, robustness analysis, and design space evaluation.

Stage 1 can be commissioned independently. Stage 2 builds on Stage 1 results.

Typical applications: mAb capture (Protein A), recombinant protein capture, bind-elute affinity chromatography.

For batch modeling and MCSGP modeling:

• Linear gradient batch chromatography runs at two or more gradient slopes, with UV chromatograms
• Fraction collection across the elution window for each run
• Analytical characterization of each fraction (purity/composition, e.g. by HPLC, CE, or equivalent)
• Column dimensions, resin type, mobile phase composition, flow rate, and loading conditions
• Feed composition and concentration

For CaptureSMB® modeling (in addition to or instead of the above):

• Breakthrough curve data at one or more flow rates and/or loading conditions
• Static or dynamic binding capacity measurements
• Column dimensions, resin type, and buffer system details
• Feed concentration and composition

For Stage 2 optimization (MCSGP or CaptureSMB):

• Any continuous experimental data generated since Stage 1 (optional but valuable for model refinement)
• Updated feed composition or process constraints, if changed
• Specific optimization objectives or constraints (e.g. minimum yield, target purity, maximum column dimensions for scale-up)

Important: The experimental data does not need to come from a Contichrom® system. We build the model from chromatographic data regardless of the hardware — the modeling is system-agnostic.

We specify the exact data requirements during project scoping. In most cases, the data aligns with experiments you would already perform during routine process development.

We use mechanistic chromatographic models that describe the physical and chemical interactions governing your separation. These models are calibrated using your experimental data and validated against independent experiments before being used for prediction. Our modeling tools are specialized and validated for MCSGP, CaptureSMB®, and their respective dynamic control systems (AutoPeak® and AutomAb®).

Batch and MCSGP modeling are applicable to any gradient or isocratic chromatographic separation. CaptureSMB® modeling is available for affinity and bind-elute capture processes (mAbs, recombinant proteins, etc.).

Yes. The batch modeling service is fully standalone. You receive a calibrated model, optimized batch parameters, and scale-up scenarios — with no requirement to proceed to MCSGP or CaptureSMB® modeling.

They serve complementary purposes. An experimental feasibility study (learn more →) runs your molecule on a Contichrom® system and produces real chromatographic data. A modeling study simulates process performance computationally, allowing you to explore a much wider parameter space in less time. Many customers combine both: modeling to narrow the parameter space, then experiments to validate the predicted optimum.

Batch modeling typically takes 2–4 weeks after receipt of your data. Continuous process modeling (Stage 1) typically takes 3–5 weeks. Stage 2 optimization typically takes 2–4 weeks after Stage 1 completion. Timelines depend on the complexity of the separation.

No. The modeling is system-agnostic. You can provide data from any HPLC or FPLC system.

This depends on the complexity of your separation, but typically 4-6 well-designed batch runs with fraction analysis are sufficient for batch and MCSGP modeling. For CaptureSMB®, breakthrough curves at 2–3 conditions are typically needed. We specify the exact requirements during project scoping.

That’s often the best starting point. Send us what you have and we’ll assess whether it’s sufficient for model calibration or whether additional runs are needed.

We accept chromatographic data in common formats (CSV, Excel, or exported from your chromatography software). Fraction analysis results can be provided in any tabular format.

You do — on your own system, or through a YMC ChromaCon experimental feasibility study. The modeling service provides the simulated operating point; experimental validation confirms it. We support you through the transfer.

Yes. The batch model forms the foundation for MCSGP modeling. If you commission batch modeling first and later decide to explore MCSGP, we build on the existing model — you don’t repeat the calibration work.

Yes. Stage 1 is a standalone service for both MCSGP and CaptureSMB®. Stage 2 is optional.

Yes — and this is a particularly effective approach. The modeling study narrows the parameter space computationally, and the experimental study validates the predicted optimum. Contact us to discuss a combined scope.

Yes. If your team wants to understand the modeling methodology, or if you need hands-on support for experimental validation, we can scope a combined engagement. Learn more about training →

In most cases, all project-specific results (simulation data, reports, optimized parameters) belong to you. The modeling tools and methodology remain YMC ChromaCon’s intellectual property.

YMC ChromaCon’s in-house process modeling services are available to customers Worldwide. The service is data-driven — you provide experimental data, we deliver simulation results. No material shipment is required.