A practical reference on quality control: what it is, how it behaves, what the literature reports, and where the honest uncertainties sit.
This page was last updated on 2026-08-01 and is reviewed periodically as new material appears.
System suitability testing is performed before and during analytical runs to confirm that the instrument and method are working as expected. Common checks include retention time, peak area, resolution between critical pairs, tailing factor, and theoretical plate count. Results are compared with predefined limits, and a failed check requires investigation before sample results are reported. Quality control samples at low, middle, and high concentrations are injected at intervals to monitor accuracy and precision. Blank injections detect carryover and contamination, while control charts track performance over time.
Data handling and documentation are central to HPLC quality control. Electronic systems should have audit trails that record changes to methods, sequences, and results. Integration parameters, such as peak baseline and threshold, can affect reported areas and must be defined in advance. Out-of-specification results trigger a structured investigation that may include reanalysis, instrument checks, and review of sample preparation. Regulatory inspections often examine raw data, audit trails, and training records to verify that reported results are traceable and reliable.
Method validation establishes that an HPLC procedure is suitable for its intended use. Key parameters include accuracy, precision, specificity, linearity, range, limit of detection, limit of quantitation, and robustness. Accuracy measures agreement with a true or accepted value, while precision describes repeatability and intermediate precision. Specificity confirms that the method measures the analyte without interference from impurities, degradants, or excipients. Validation is documented in a protocol and report, and acceptance criteria are set before experiments begin. Regulatory guidance varies by region, but the general principles are widely harmonized.
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.
| Property | Value | Notes |
|---|---|---|
| Validation parameter | Accuracy | Measured value compared with true or accepted value |
| Precision type | Repeatability | Same analyst, instrument, and short time interval |
| Linearity range | 50–150% of target concentration | Common for assay methods; method-dependent |
| Limit of quantitation | Signal-to-noise ratio of 10:1 | Lowest concentration with acceptable precision |
| Common synonyms | Method validation, analytical validation | Documented confirmation that a method is suitable |
High-performance liquid chromatography is an analytical technique that separates components in a liquid sample. A pump moves a liquid mobile phase through a column packed with a solid stationary phase. Compounds interact differently with both phases and travel at different rates, leaving the column at distinct retention times. A detector records these arrivals as peaks on a chromatogram. The resulting pattern supports identification and quantification of substances in mixtures. Modern instruments use high pressure to force solvent through small particles, which improves speed and resolution compared with older low-pressure liquid chromatography methods.
Separation in HPLC depends on the chemistry of the stationary phase, the composition of the mobile phase, and the physical properties of the column. Reverse-phase separations use a nonpolar stationary phase and a polar mobile phase, and they are common for many organic compounds. Ion-exchange, size-exclusion, and normal-phase modes serve other classes of analytes. Gradient elution changes solvent strength over time, while isocratic elution holds it constant. Flow rate, temperature, particle size, and column length all influence peak shape and resolution. Detection may use ultraviolet absorbance, fluorescence, refractive index, or mass spectrometry, depending on the analyte and the required sensitivity.
Routine HPLC testing compares a sample result with a calibration curve prepared from known reference standards. Peak area or peak height is plotted against concentration, and the curve is used to estimate unknown amounts. Retention time supports tentative identification when compared with a standard, though mass spectrometry or another confirmatory method may be needed for definitive identification. Pre-run checks verify repeatability, resolution, and peak symmetry before sample analysis. Limits of detection and quantification describe the smallest amounts that can be reliably observed or measured. Sample preparation, filtration, and degassing help prevent column damage and inconsistent results.
Several separation modes exist, including reversed-phase, normal-phase, ion-exchange, size-exclusion, and hydrophilic interaction liquid chromatography. Reversed-phase uses a nonpolar stationary phase with a polar mobile phase and is widely applied to small organic molecules. Gradient elution changes mobile phase composition during the run, while isocratic elution keeps it constant. Column chemistry, particle size, temperature, flow rate, and mobile phase pH all influence retention and resolution. Method development selects conditions that separate analytes from matrix components and from each other.
Detection commonly uses ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. Ultraviolet detection depends on molecular chromophores that absorb light at specific wavelengths. Mass spectrometry provides mass information and sensitive quantification, often after electrospray ionization. Before sample batches, performance checks examine resolution, elution time repeatability, peak symmetry, and plate count. Matrix effects and co-elution remain recognized uncertainties; formal validation studies and orthogonal detection help address them. Detector choice depends on analyte properties and required sensitivity.
In quality control laboratories, HPLC testing supports batch release, raw material checks, stability studies, and impurity profiling. A validated method defines sample preparation, instrument settings, calibration, and acceptance criteria. Analysts compare results with specifications and investigate out-of-specification outcomes before a batch is approved. Documentation includes chromatograms, integration records, audit trails, and reagent details. Because results influence product decisions, laboratories follow formal quality systems and data integrity rules. The exact tests and limits depend on the material, its intended use, and the applicable regulatory framework.
Method validation examines whether an HPLC procedure is suitable for its intended purpose. Common parameters include accuracy, precision, specificity, linearity, range, detection limit, quantification limit, and robustness. Accuracy describes closeness to a true or accepted value, while precision describes agreement among repeated measurements. Specificity shows whether the method can measure the analyte without interference from related substances. Robustness tests small deliberate changes in flow, temperature, or solvent composition. Validation is not a one-time event; methods may need partial revalidation after changes to instruments, columns, sample handling, or specification limits. Regulatory guidance provides frameworks, but some details remain method-specific.
Regulatory and pharmacopeial texts shape how HPLC testing is performed and documented. The International Council for Harmonisation provides validation guidance, while pharmacopeias publish general chromatography chapters and monographs for specific materials. Accreditation standards such as ISO/IEC 17025 address laboratory competence and traceability. Inspectors may review instrument qualification, analyst training, reference material control, and electronic records. Open questions include how best to validate methods for new complex products and how to handle automated data processing. Laboratories generally resolve these issues through risk assessment, method lifecycle management, and documented scientific justification.
Antibody mimetics are organic compounds, like antibodies, that can specifically bind antigens. They consist of artificial peptides or proteins, or aptamer-based nucleic acid molecules with a molar mass of about 3 to 20 kDa. Antibody fragments, such as Fab and nanobodies are not considered as antibody mimetics. Common advantages over antibodies are better solubility, tissue penetration, stability towards heat and enzymes, and comparatively low production costs. Antibody mimetics have been developed and commercialized as research, diagnostic and therapeutic agents. BAU (binding antibody unit, often as BAU/mL) is a measurement unit defined by the WHO for the comparison of assays detecting the same class of immunoglobulins with the same specificity.
Automated synthesis systems find new applications with a development of new robotic platforms. Possible applications include: uncontrolled synthesis, time-dependent synthesis, radiosynthesis, synthesis in demanding conditions (low temperatures, presence of specific atmosphere like CO, H2, N2, high pressure or under vacuum) or whenever the same or similar workflow needs to be applied multiple times with the aim to: optimize reactions, synthesize many derivatives in small scale, perform reactions of iterative homologations or radiosynthesis. Automated synthesis workflows are needed both in academic research and a wide array of industrial R&D settings (pharmaceuticals, agrochemicals, fine & specialty chemicals, renewables & energy research, catalysts, polymers, ceramics & abrasives, porous materials, nanomaterials, biomaterials, lubricants, paints & coatings, home care, personal care, nutrition, forensics).
Mycofactocin (MFT) is a family of small molecules derived from a peptide of the type known as RiPP (ribosomally synthesized and post-translationally modified peptides), naturally occurring in many types of Mycobacterium. It was discovered in a bioinformatics study in 2011. All mycofactocins share a precursor in the form of premycofactocin (PMFT); they differ by the cellulose tail added. Being redox active, both PMFT and MFT have an oxidized dione (mycofactocinone) form and a reduced diol (mycofactocinol) form, respectively termed PMFTH2 and MFTH2. The name "mycofactocin" is derived from three words, the genus name "Mycobacterium" (across which it is nearly universal), "cofactor" because its presence in a genome predicts the co-occurrence of certain families of enzymes as if it is a cofactor they require, and "bacteriocin" because a radical SAM enzyme critical to its biosynthesis, MftC, is closely related to the key enzyme for the biosynthesis of subtilosin A, a bacteriocin, from its precursor peptide.
Sources: en.wikipedia.org
The Department was founded in 1934 in Kazan Teachers’ Institute to educate future teachers of chemistry. In November, 2011 the Department of Chemical Education became a structural unit of A. M. Butlerov Institute of Chemistry of Kazan (Volga Region) Federal University. Educational research was combined with fundamental and applied research in chemistry. International, All-Russian and regional research-to-practice conferences on chemical education organized by the Department are of the utmost interest. The Department has received letters of gratitude from school principals for instructing students in research and methodology in their preparation for teaching practice. Today 3 Doctors of Science and 5 Doctors of Philosophy are involved in the educational and bringing-up process at the Department. Since 2010 teachers have been retrained in the field of “Teacher of Chemistry”.The head of the Department is Suria I. Gilmanshina, Doctor of Philosophy in Chemistry, Doctor of Science in Education. The Department conducts research in the following fields:
The H-type pseudoknot core of mini-NAD⁺-II aptamers is structurally analogous to that of the preQ1-I riboswitch class, one of the smallest known natural riboswitch aptamers. Both classes represent the shortest known natural RNA aptamers, yet achieve high ligand-binding specificity. This structural similarity suggests that simple H-type pseudoknots may function as versatile scaffolds for constructing ligand-binding aptamers, either naturally or synthetically. Biochemical analysis using in-line probing confirmed that mini-NAD⁺-II RNAs bind both NAD⁺ and NMN, with strong preference for NMN. Biochemical analysis using in-line probing confirmed that mini-NAD⁺-II RNAs bind both NAD⁺ and NMN, with strong preference for NMN. Mini-NAD⁺-II aptamers discriminate more strongly between NMN and NAD⁺ than the larger P1a containing aptamers, likely because they lack the conserved adenosines flanking P1a that make non-specific contacts with the adenosine moiety of NAD⁺. Gene Regulation NAD⁺-II and mini-NAD⁺-II riboswitches are predicted to function as translational "OFF" switches: when NAD⁺ or NMN concentrations are sufficiently high, the riboswitch ligand-bound conformation sequesters the Shine-Dalgarno sequence within a pseudoknot, preventing ribosome binding and repressing translation of the downstream gene. The downstream genes regulated by NAD⁺-II and mini-NAD⁺-II riboswitches include:
6-carboxytetrahydropterin synthase (EC 4.1.2.50, CPH4 synthase, queD (gene), ToyB, ykvK (gene)) is an enzyme with systematic name 7,8-dihydroneopterin 3'-triphosphate acetaldehyde-lyase (6-carboxy-5,6,7,8-tetrahydropterin and triphosphate-forming). This enzyme catalyses the following reversible chemical reaction. 7,8-dihydroneopterin 3′-triphosphate + H2O ⇌ 6-carboxy-5,6,7,8-tetrahydropterin + acetaldehyde + triphosphate This enzyme binds Zn2+. It is isolated from the bacteria Bacillus subtilis and Escherichia coli. The stimulation is part of the biosynthesis pathway of queuosine. The enzyme from Escherichia coli can also convert 6-pyruvoyl-5,6,7,8-tetrahydropterin and sepiapterin to 6-carboxy-5,6,7,8-tetrahydropterin. Media related to 6-carboxytetrahydropterin synthase at Wikimedia Commons 6-carboxytetrahydropterin+synthase at the U.S. National Library of Medicine Medical Subject Headings (MeSH)
Sources: en.wikipedia.org
System suitability is a set of checks that confirm the instrument and method perform within limits before sample analysis. It typically includes resolution, tailing factor, retention time, and peak area reproducibility. If a check fails, the run is invalidated until the cause is resolved.
QC samples are usually injected at the beginning, at intervals during the run, and at the end. The exact frequency depends on the method, sample count, and regulatory requirements. Results outside acceptance limits can require rejection of the affected samples and investigation.
Method validation demonstrates that an HPLC procedure produces reliable results for its intended purpose. It provides documented evidence for accuracy, precision, specificity, and other performance characteristics. Regulators and quality systems require validation before a method is used for release or stability testing.
Method validation is the documented process of showing that an HPLC procedure produces reliable results for a defined purpose. It examines parameters such as accuracy, precision, specificity, linearity, and robustness. Regulators and quality systems often require validation before routine use.