If you have been reading about precision and want a single page that covers the useful parts, this is it: definitions, context, how it is studied, and the questions that come up repeatedly.
Last reviewed on 2026-07-20. Where a claim depends on a specific study, the study is described rather than over-claimed.
Routine quality control uses system suitability, blank injections, check standards, and control samples to detect drift or contamination. System suitability criteria may specify minimum resolution, maximum tailing factor, and a permitted range for repeated injections. Blank injections reveal carryover or solvent contamination, while check standards confirm calibration accuracy over a batch. Control samples with known analyte levels can show whether results remain within statistical limits. When a control result falls outside limits, the analyst investigates the cause and may invalidate affected results before repeating the batch.
Documentation and traceability are central to regulated HPLC testing. Records typically include instrument logs, column history, mobile-phase preparation, sample preparation, injection sequences, raw chromatograms, and audit trails. Electronic systems may require user access controls, time-stamped changes, and backup procedures. Training records show that analysts are qualified for assigned methods. Audits and inspections check whether written procedures match actual practice and whether deviations are documented. These controls support reproducibility and allow results to be reconstructed if questions arise later.
Method validation establishes that an HPLC procedure is suitable for its intended purpose. Typical parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, robustness, and solution stability. Accuracy reflects closeness to a reference value, while precision reflects agreement among repeated measurements. Specificity shows whether the method can measure the analyte without interference from matrix components. Validation is documented through protocols and reports, and the required extent depends on the method's use and regulatory context.
Quality control for HPLC testing combines scheduled checks, documented procedures, and review of results. Before sample analysis, system suitability testing confirms that the instrument, column, and method meet predefined criteria. Common criteria include resolution between critical peaks, retention time precision, peak tailing, and theoretical plate count. Failure triggers investigation before results are reported. Records link raw data, calculations, instrument logs, and analyst identity to each batch, supporting audits and repeat analysis.
Method validation evaluates accuracy, precision, specificity, linearity, range, detection limit, quantitation limit, and robustness. Regulatory guidance for pharmaceuticals, foods, and environmental testing defines expected documentation and acceptance criteria. Verification confirms that a validated method works in a specific laboratory with its own instruments and reagents. Calibration curves use reference standards with known purity and traceability, while measurement uncertainty is estimated from validation data, control charts, and collaborative studies. The scope of validation depends on the method's intended use.
Routine quality control monitors retention time shifts, baseline noise, system pressure, and peak shape. Trends can reveal column aging, mobile phase preparation errors, detector drift, or sample degradation. Corrective actions may include replacing the column, preparing fresh mobile phase, or recalibrating the detector. Stability testing often uses HPLC to measure parent compound loss and degradation product formation. Open questions remain about how accelerated stability results extrapolate to long-term storage under varied conditions.
| Property | Value | Notes |
|---|---|---|
| Accuracy | Recovery near 100% | Depends on acceptance criteria and matrix |
| Precision | Relative standard deviation | Often at or below 2% for replicate injections |
| Limit of detection | Signal-to-noise ratio 3:1 | Approximate and method-specific |
| Limit of quantitation | Signal-to-noise ratio 10:1 | Confirmed by precision and accuracy |
| Resolution | 1.5 or greater | Typical system suitability target |
Method validation demonstrates that an HPLC procedure is suitable for its intended purpose. Common validation parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantification, and robustness. Accuracy reflects agreement with a reference value, while precision describes repeatability under defined conditions. Specificity shows whether the method can measure the analyte in the presence of impurities or matrix components. Validation documents are reviewed before a method is used for routine testing or regulatory submissions.
System suitability testing is performed before and during analytical runs to confirm that the instrument and method are working as expected. Typical checks include retention time, peak area precision, resolution between critical pairs, tailing factor, and theoretical plate count. Acceptance criteria are set in the method or pharmacopeial monograph. If a suitability check fails, the run may be rejected and the instrument or sample preparation may need investigation. This practice helps prevent release of data from a system that has drifted out of control.
Quality control samples are inserted at intervals to monitor accuracy and precision throughout a batch. Blank samples detect contamination, while spiked samples assess recovery from the sample matrix. Calibration standards establish the relationship between detector response and concentration, and control samples are prepared independently from them whenever possible. Laboratories also participate in proficiency testing and maintain audit trails, instrument logs, and reagent records. Ongoing review of control charts can reveal trends before they cause out-of-specification results.
Validation establishes that a method is suitable for its intended purpose. Typical parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantification, robustness, and stability of standards and samples. Acceptance criteria are defined in advance, and results are documented in a validation report. Regulatory guidance for pharmaceuticals, foods, and environmental testing differs, so the applicable framework must be identified. Ongoing verification uses control samples and trend charts after validation. Method transfer to another laboratory may require partial revalidation.
Routine quality control includes blanks, duplicates, spiked samples, and certified reference materials. Calibration curves are prepared with standards at several concentrations, and the detector response is checked for linearity. Carryover, column aging, mobile phase evaporation, and temperature drift can shift retention times or peak areas. Maintenance such as replacing seals, filters, and columns helps prevent failures. Records of injections, integration, and deviations support traceability. Audits may request raw data and instrument logs for each batch.
Routine HPLC testing depends on controlled reagents, calibrated instruments, and documented procedures. Columns degrade over time, so retention times and peak shapes are monitored for drift. Mobile phases are filtered and degassed to prevent pump damage and detector noise. Reference standards must be traceable and stored under suitable conditions. Data handling systems record injections, calculations, and audit trails. Quality control samples interspersed with unknowns help detect errors during a run.
Developing an HPLC method begins with defining the purpose, such as quantifying a main component, measuring impurities, or confirming identity. Analysts select separation mode, column, mobile phase, detection, and sample preparation based on analyte properties and matrix. Experiments vary solvent strength, pH, buffer type, and temperature to achieve resolution between critical peaks. The goal is a robust method that produces reliable results across instruments and operators. Method development often involves trial runs and statistical optimization.
Validation demonstrates that a method is suitable for its intended use. Typical performance characteristics include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Regulators and standards organizations provide frameworks, but specific requirements depend on the application and jurisdiction. System suitability tests are run before sample analysis to confirm resolution, peak symmetry, retention time repeatability, and sensitivity. A validated method is not permanently fixed; changes may require partial or full revalidation.
The ABCA subfamily is composed of 12 full transporters split into two subgroups. The first subgroup consists of seven genes that map to six different chromosomes. These are ABCA1, ABCA2, ABCA3, and ABCA4, ABCA7, ABCA12, and ABCA13. The other subgroup consists of ABCA5 and ABCA6 and ABCA8, ABCA9 and ABCA10. A8-10. All of subgroup 2 is organized into a head to tail cluster of chromosomes on chromosome 17q24. Genes in this second subgroup are distinguished from ABCA1-like genes by having 37-38 exons as opposed to the 50 exons in ABCA1. The ABCA1 subgroup is implicated in the development of genetic diseases. In the recessive Tangier's disease, the ABCA1 protein is mutated. Also, the ABCA4 maps to a region of chromosome 1p21 that contains the gene for Stargardt's disease. This gene is found to be highly expressed in rod photoreceptors and is mutated in Stargardt's disease, recessive retinitis pigmentism, and the majority of recessive cone-rod dystrophy.
When multiple copies of a polypeptide encoded by a gene form an aggregate, this protein structure is referred to as a multimer. When a multimer is formed from polypeptides produced by two different mutant alleles of a particular gene, the mixed multimer may exhibit greater functional activity than the unmixed multimers formed by each of the mutants alone. In such a case, the phenomenon is referred to as intragenic complementation. E. coli alkaline phosphatase, a dimer enzyme, exhibits intragenic complementation. By changing the amino acids of the wild-type alkaline phosphatase enzyme produced by Escherichia coli, a mutant alkaline phosphatase is created which not only has a 36-fold increase in enzyme activity, but also retains thermal stability. Typical uses in the lab for alkaline phosphatases include removing phosphate monoesters to prevent self-ligation, which is undesirable during plasmid DNA cloning. Common alkaline phosphatases used in research include:
Ash is the solid remnants of fires. Specifically, ash refers to all non-aqueous, non-gaseous residues that remain after something burns. In analytical chemistry, to analyse the mineral and metal content of chemical samples, ash is the non-gaseous, non-liquid residue after complete combustion. Ashes as the end product of incomplete combustion are mostly mineral, but usually still contain an amount of combustible organic or other oxidizable residues. The best-known type of ash is wood ash, as a product of wood combustion in campfires, fireplaces, etc. The darker the wood ashes, the higher the content of remaining charcoal from incomplete combustion. The ashes are of different types. Some ashes contain natural compounds that make soil fertile. Others have chemical compounds that can be toxic but may break down in soil from chemical changes and microorganism activity. Like soap, ash is also a disinfecting agent (alkaline). The World Health Organization recommends ash or sand as alternative for handwashing when soap is not available. Before industrialization, ash soaked in water was the primary means of obtaining potash.
Sources: en.wikipedia.org
The Shrake–Rupley algorithm is a numerical method that draws a mesh of points equidistant from each atom of the molecule and uses the number of these points that are solvent accessible to determine the surface area. The points are drawn at a water molecule's estimated radius beyond the van der Waals radius, which is effectively similar to 'rolling a ball' along the surface. All points are checked against the surface of neighboring atoms to determine whether they are buried or accessible. The number of points accessible is multiplied by the portion of surface area each point represents to calculate the ASA. The choice of the 'probe radius' does have an effect on the observed surface area, as using a smaller probe radius detects more surface details and therefore reports a larger surface. A typical value is 1.4Å, which approximates the radius of a water molecule. Another factor that affects the results is the definition of the VDW radii of the atoms in the molecule under study. For example, the molecule may often lack hydrogen atoms, which are implicit in the structure. The hydrogen atoms may be implicitly included in the atomic radii of the 'heavy' atoms, with a measure called the 'group radii'. In addition, the number of points created on the van der Waals surface of each atom determines another aspect of discretization, where more points provide an increased level of detail.
An aldehyde tag is a short peptide tag that can be further modified to add fluorophores, glycans, PEG (polyethylene glycol) chains, or reactive groups for further synthesis. A short, genetically-encoded peptide with a consensus sequence LCxPxR is introduced into fusion proteins, and by subsequent treatment with the formylglycine-generating enzyme (FGE), the cysteine of the tag is converted to a reactive aldehyde group. This electrophilic group can be targeted by an array of aldehyde-specific reagents, such as aminooxy- or hydrazide-functionalized compounds.
Affinity chromatography is a method of separating a biomolecule from a mixture, based on a highly specific macromolecular binding interaction between the biomolecule and another substance. The specific type of binding interaction depends on the biomolecule of interest; antigen and antibody, enzyme and substrate, receptor and ligand, or protein and nucleic acid binding interactions are frequently exploited for isolation of various biomolecules. Affinity chromatography is useful for its high selectivity and resolution of separation, compared to other chromatographic methods.
Sources: en.wikipedia.org
Validation establishes suitability for a new method, while verification confirms that a method works in a specific laboratory. Verification is often used when a validated method is adopted with existing equipment and staff. Both rely on documented acceptance criteria.
Quantification usually compares detector response to a standard curve made from reference standards. The curve may be external, internal, or based on standard addition depending on matrix effects. Results are reported with units and, when required, uncertainty.
Carryover occurs when analyte from a previous injection remains in the system and appears in a later chromatogram. It can come from the injector, column, or tubing. Blank injections and needle washes help detect and reduce it.
System suitability is typically performed before each batch or according to the validated method and laboratory procedure. Some long runs include periodic checks during analysis. The required frequency depends on regulatory expectations and method performance.