This is a working overview of method validation, written for readers who want more than a one-paragraph summary but less than a textbook.
Reviewed 2025-02-21. Anything still debated is marked as such rather than presented as settled.
Laboratories apply HPLC testing across pharmaceutical, food, environmental, and industrial chemistry. The method can measure active ingredients, impurities, additives, preservatives, and degradation products. Sample preparation often includes dilution, filtration, and sometimes extraction or derivatization. The choice of column, mobile phase, pH, temperature, and detector depends on the analytes and matrix. Results are compared with reference standards to assign identity and concentration. Method suitability is judged by resolution, precision, and accuracy.
HPLC testing is not a single fixed procedure; it is a family of separation modes. Reversed-phase, normal-phase, ion-exchange, size-exclusion, and affinity chromatography each suit different analyte properties. Reversed-phase methods dominate because they handle many neutral and moderately polar compounds. Detection can be optical, electrochemical, or mass spectrometric, and the detector dictates what information is available. Coupling with mass spectrometry increases selectivity and enables identification when standards are unavailable. The technique cannot separate every mixture without adjustment.
HPLC testing is an analytical technique used to separate, identify, and quantify components in a liquid sample. It relies on a pressurized mobile phase that carries the sample through a column packed with stationary phase. Different compounds travel at different rates because of interactions with the stationary and mobile phases. The resulting signal versus time is a chromatogram. Peak position indicates identity under specified conditions, while peak area or height relates to amount.
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.
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.
| Property | Value | Notes |
|---|---|---|
| Abbreviation | HPLC | Also called high-performance liquid chromatography |
| Separation mechanism | Differential partitioning | Compounds distribute between mobile and stationary phases |
| Typical column chemistry | C18 (octadecylsilane) | Used in reversed-phase separations |
| Typical detector | UV-Vis or photodiode array | Mass spectrometry is common for trace and confirmatory work |
| Typical particle size | 1.8–5 µm | Smaller particles require higher pressure and can improve speed |
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 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.
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.
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.
The origins of alemtuzumab date back to Campath-1 which was derived from the rat antibodies raised against human lymphocyte proteins by Herman Waldmann and colleagues in 1983. The name Campath derives from the pathology department of Cambridge University. Initially, Campath-1 was not ideal for therapy because patients could, in theory, react against the foreign rat protein determinants of the antibody. To circumvent this problem, Greg Winter and his colleagues humanised Campath-1, by extracting the hypervariable loops that had specificity for CD52 and grafting them onto a human antibody framework. This became known as Campath-1H and serves as the basis for alemtuzumab. While alemtuzumab started life as a laboratory tool for understanding the immune system, within a short time it was clinically investigated for use to improve the success of bone marrow transplants and as a treatment for leukaemia, lymphoma, vasculitis, organ transplants, rheumatoid arthritis and multiple sclerosis.
There has been a tremendous advance in speed and cost reduction since the completion of the Human Genome Project, with some labs able to sequence over 100,000 billion bases each year, and a full genome can be sequenced for $1,000 or less. Computers became essential in molecular biology when protein sequences became available after Frederick Sanger determined the sequence of insulin in the early 1950s. Comparing multiple sequences manually turned out to be impractical. Margaret Oakley Dayhoff, a pioneer in the field, compiled one of the first protein sequence databases, initially published as books as well as methods of sequence alignment and molecular evolution. Another early contributor to bioinformatics was Elvin A. Kabat, who pioneered biological sequence analysis in 1970 with his comprehensive volumes of antibody sequences released online with Tai Te Wu between 1980 and 1991. In the 1970s, new techniques for sequencing DNA were applied to bacteriophage MS2 and øX174, and the extended nucleotide sequences were then parsed with informational and statistical algorithms. These studies showed that well-known features, such as coding segments and the triplet code, could be revealed in straightforward statistical analyses and were proof of the concept that bioinformatics would be insightful.
An antibody–drug conjugate consists of three components: Antibody - targets the cancer cell surface and may also elicit a therapeutic response. Payload - elicits the desired therapeutic response. Linker - attaches the payload to the antibody and should be stable in circulation only releasing the payload at the desired target. Multiple approaches to conjugation have been developed for attachment to the antibody and reviewed. DAR is the drug to antibody ratio and indicates the level of loading of the payload on the ADC.
Databases are essential for bioinformatics research and applications. Databases exist for many different information types, including DNA and protein sequences, molecular structures, phenotypes and biodiversity. Databases can contain both empirical data (obtained directly from experiments) and predicted data (obtained from analysis of existing data). They may be specific to a particular organism, pathway or molecule of interest. Alternatively, they can incorporate data compiled from multiple other databases. Databases can have different formats, access mechanisms, and be public or private. Some of the most commonly used databases are listed below: Used in biological sequence analysis: Genbank, UniProt Used in structure analysis: Protein Data Bank (PDB) Used in finding Protein Families and Motif Finding: InterPro, Pfam Used for Next Generation Sequencing: Sequence Read Archive Used in Network Analysis: Metabolic Pathway Databases (KEGG, BioCyc), Interaction Analysis Databases, Functional Networks Used in design of synthetic genetic circuits: GenoCAD
Adrenomedullin (ADM) is a peptide hormone that plays an important role in various physiological processes throughout the human body. Initially discovered in 1993 from a pheochromocytoma, a tumor of the adrenal medulla, this 52-amino acid peptide is now recognized for its diverse effects, including vasodilation, regulation of blood pressure, and maintenance of the vascular system. ADM is widely expressed in tissues and also found in the circulation, exerting its influence on the cardiovascular, lymphatic, and endocrine systems, as well as demonstrating anti-inflammatory and tissue-protective properties. In humans, ADM is encoded by the ADM gene. A similar peptide named adreomedullin2 was reported in rats in 2004, which exhibits a similar function.
Sources: en.wikipedia.org
Aspartate has many other biochemical roles. It is a metabolite in the urea cycle and participates in gluconeogenesis. It carries reducing equivalents in the malate-aspartate shuttle, which utilizes the ready interconversion of aspartate and oxaloacetate, which is the oxidized (dehydrogenated) derivative of malic acid. Aspartate donates one nitrogen atom in the biosynthesis of inosine, the precursor to the purine bases. In addition, aspartic acid acts as a hydrogen acceptor in a chain of ATP synthase. Dietary L-aspartic acid has been shown to act as an inhibitor of Beta-glucuronidase, which serves to regulate enterohepatic circulation of bilirubin and bile acids. Click on genes, proteins and metabolites below to link to respective articles. Aspartate (the conjugate base of aspartic acid) stimulates NMDA receptors, though not as strongly as the amino acid neurotransmitter L-glutamate does. Aspartate is the "A" in NMDA (N-methyl-D-aspartate receptor).
2-Aminoisobutyric acid is not one of the proteinogenic amino acids and is rather rare in nature (cf. non-proteinogenic amino acids). In the context of cell-free protein synthesis 2-aminoisobutyric acid is compatible with ribosomal elongation of peptide synthesis. Flexizymes and an engineered tRNA body enhance the affinity of aminoacylated Aib-tRNA species to elongation factor P. The result was an increased incorporation of Aib into peptides in a cell free translation system. Iqbal et al.. used an alternative approach of creating an editing deficient valine—tRNA ligase to synthesize aminoacylated Aib-tRNAVal. The aminoacylated tRNA was subsequently used in a cell-free translation system to yield Aib-containing peptides. Aib has been found in meteorites and some antibiotics of fungal origin, such as alamethicin and some lantibiotics.
After synthesizing and purifying the core, the carbohydrate layer is added to its surface. Common coating materials are typically polyhydroxy oligomers such as cellobiose, citrate, lactose, and sucrose. This layer seems to be important for the properties of aquasomes, as it influences several drug characteristics including adsorption, molecular stability, and conformation (shape), and acts as a dehydroprotectant. The addition of the carbohydrate layer to the surface of the nanocrystalline core is commonly carried out by passive adsorption through incubation and sonication. Similar to the processing of the core, the carbohydrate layer is subjected to centrifugation, washing, and further sonification followed by heated air drying. Finally, the bioactive molecule of interest is loaded into the carbohydrate layer. This process typically occurs through either lyophilization or passive adsorption, and the fully functionalized aquasome is then characterized.
Adesuwa Obasuyi (born February 1990) is a Nigerian environmentalist, climate change advocate, and the initiator of Sustainable Africa Cities and Communities Initiative - an environmental non-governmental organization that focuses on waste, and waste data management in Nigeria and Africa. She currently works as the Climate Change Policy Manager at the British High Commission, Abuja. She attended Delta State University, and obtained a bachelor's degree in Biochemistry in 2010; she went further to get a master's degree in Environmental Quality Management(2014 - 2017) from the University of Benin.
Sources: en.wikipedia.org
It measures the presence and amount of one or more compounds in a liquid sample. Separation occurs in a column, and detection produces a signal proportional to concentration. Identification usually requires comparison with a known reference standard under the same conditions.
In most cases the sample is consumed or altered during analysis, though some detectors are non-destructive. Fractions can be collected after separation for further study. Repeated testing therefore requires additional sample.
Run times range from under a minute for fast methods to over an hour for complex separations. Sample preparation, equilibration, and data review add time. Throughput depends on instrument configuration and method requirements.
HPLC testing measures the presence and amount of one or more compounds in a liquid sample. It separates mixture components and records detector responses as peaks, which are compared with reference standards. Results are usually reported as concentrations or relative percentages.