Skip to contents

Quantify Protein Aggregates and Fragments in SEC

Source: R/step_sec_aggregates.R
step_sec_aggregates.Rd

step_sec_aggregates() creates a specification of a recipe step that quantifies high molecular weight species (HMWS/aggregates), monomers, and low molecular weight species (LMWS/fragments) from protein SEC chromatograms.

Usage

step_sec_aggregates(
  recipe,
  measures = NULL,
  monomer_start = NULL,
  monomer_end = NULL,
  method = c("tallest", "manual"),
  hmws_threshold = 0.001,
  include_main_peak = TRUE,
  output_prefix = "purity_",
  role = NA,
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("sec_aggregates")
)

Arguments

recipe

A recipe object.

measures

Character vector of measure columns to analyze. If NULL, analyzes all measure columns.

monomer_start

Start of the monomer peak region (in location units, typically minutes). If NULL, automatically determined.

monomer_end

End of the monomer peak region. If NULL, automatically determined.

method

Method for peak boundary detection when monomer_start or monomer_end is NULL:

  • "tallest" (default): Uses the tallest peak as monomer

  • "manual": Requires explicit boundaries

hmws_threshold

Minimum fraction of monomer height to consider as HMWS signal. Default is 0.001 (0.1%). Below this, signal is considered baseline.

include_main_peak

Logical. Include the main peak boundaries in output? Default is TRUE.

output_prefix

Prefix for output columns. Default is "purity_". Creates columns: {prefix}hmws, {prefix}monomer, {prefix}lmws.

role

Role for generated columns.

trained

Logical indicating if the step has been trained.

skip

Logical. Should the step be skipped when baking?

id

Unique step identifier.

Value

An updated recipe with new columns containing aggregate percentages:

purity_hmws

Percent high molecular weight species (aggregates)

purity_monomer

Percent monomer (main peak)

purity_lmws

Percent low molecular weight species (fragments)

purity_main_start

Start of main peak region (if include_main_peak)

purity_main_end

End of main peak region (if include_main_peak)

Details

Aggregate analysis is critical for biopharmaceutical characterization:

  • HMWS (High Molecular Weight Species): Elute before the monomer peak. Includes dimers, trimers, and higher-order aggregates.

  • Monomer: The main therapeutic protein peak.

  • LMWS (Low Molecular Weight Species): Elute after the monomer peak. Includes fragments, clips, and degradation products.

Calculation Method: $$\% HMWS = \frac{A_{HMWS}}{A_{total}} \times 100$$ $$\% Monomer = \frac{A_{monomer}}{A_{total}} \times 100$$ $$\% LMWS = \frac{A_{LMWS}}{A_{total}} \times 100$$

where A represents integrated peak areas.

Regulatory Importance:

  • ICH Q6B requires aggregate content specification

  • USP <129> provides guidance on aggregate testing

  • Typical acceptance: HMWS < 5%, Monomer > 95%

Note

For accurate results:

  • Baseline correct the chromatogram first

  • Ensure proper column resolution (especially for dimer separation)

  • Use UV detection at 280 nm (or 214 nm for higher sensitivity)

See also

Other sec-protein: step_sec_oligomer(), step_sec_protein()

Examples

if (FALSE) { # \dontrun{
library(recipes)
library(measure)

# Analyze mAb aggregate content
rec <- recipe(~., data = mab_data) |>
  step_measure_input_long(uv280, location = vars(elution_time), col_name = "uv") |>
  step_sec_baseline() |>
  step_sec_aggregates(
    monomer_start = 8.5,
    monomer_end = 10.5
  ) |>
  prep()

# Automatic peak detection
rec <- recipe(~., data = mab_data) |>
  step_measure_input_long(uv280, location = vars(elution_time), col_name = "uv") |>
  step_sec_baseline() |>
  step_sec_aggregates(method = "tallest") |>
  prep()
} # }