stationary phase raises a handful of sensible questions. This page answers them in order, starting with the fundamentals and moving to applications.
This page was last updated on 2025-11-14 and is reviewed periodically as new material appears.
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.
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.
| 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 |
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.
Key performance measures include retention time, peak area, peak height, resolution, tailing factor, and plate count. Retention time helps identify a peak under fixed conditions, but confirmation often requires a second method or detector. Peak area and height relate to concentration through calibration curves, which may be linear or nonlinear depending on the detector response. Resolution describes separation between adjacent peaks, while tailing factor and plate count describe peak shape and column efficiency. Performance checks verify these values before and during a run to confirm that the instrument is performing within limits.
High-performance liquid chromatography testing separates components of a liquid sample by forcing a mobile phase through a packed column. The stationary phase inside the column interacts with analytes to different degrees, so each compound exits at a characteristic retention time. A pump delivers solvent at controlled flow and pressure, while an injector introduces a precise sample volume. Detectors such as ultraviolet-visible, fluorescence, refractive index, or mass spectrometric instruments record the separated bands. The resulting chromatogram provides qualitative and quantitative information about the mixture.
Most routine HPLC testing uses reversed-phase columns, where the stationary phase is nonpolar and the mobile phase is a polar mixture such as water with an organic solvent. Analytes partition between the two phases according to polarity, size, and charge. Gradients that change solvent composition over time can separate compounds with broad retention ranges. Isocratic conditions keep solvent composition constant and suit simpler mixtures. The choice of column chemistry, pH, and temperature affects selectivity and peak shape.
Detection in HPLC testing commonly relies on ultraviolet-visible absorbance, fluorescence, refractive index, or mass spectrometry. UV detection is widely used because many organic compounds absorb light, but it requires a chromophore. Mass spectrometry provides mass-based identification and high sensitivity for trace analytes. Each detector has trade-offs in selectivity, cost, and compatibility with mobile phases. Quantification typically uses calibration curves prepared from reference standards. Results are reported as concentration, purity, or presence above a limit.
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.
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.
Linear RGD peptides suffer from low binding affinity, rapid degradation by proteases, and lack of specificity for integrin type. RGD can be cyclized, or made into a cyclic compound, via disulfide, thioether, or rigid aromatic ring linkers. This leads to an increase in binding affinity and selectivity for integrin αVβ3 relative to αIIBβ3. For example, the cyclic peptide ACDCRGDCFCG, also known as RGD4C, was shown to be 200-fold more potent than commonly used linear RGD peptides. The structural rigidity of cyclic RGD peptides improves their binding properties and prevents degradation at the highly susceptible aspartic acid residue, thereby increasing their stability. Many RGD derivative drugs and diagnostics are cyclized, including Eptifibatide, Cilengitide, CEND-1, and 18F-Galacto-RGD, and 18F-Fluciclatide-RGD.
The most common peptide aptamer selection system is the yeast two-hybrid system. Peptide aptamers can also be selected from combinatorial peptide libraries constructed by phage display and other surface display technologies such as mRNA display, ribosome display, bacterial display and yeast display. These experimental procedures are also known as biopanning. All the peptides panned from combinatorial peptide libraries have been stored in the MimoDB database.
Abraham White (March 8, 1908 – February 14, 1980) was a professor of biochemistry who made several important discoveries in his field during the middle of the 20th century and helped write a foundational textbook, Principles of Biochemistry, which was published in 1954. The book went through six editions before its authors retired. White was born in Cleveland, Ohio, to Morris and Lena White. His siblings were Essie and Julius ("Jay"). When he was about one year old, his family moved to Lafayette, Colorado, and then later to Denver. White earned his bachelor's and master's degrees at the University of Colorado and a Ph.D. degree in Physiological Chemistry at the University of Michigan in the laboratory of Howard B. Lewis. This was followed by a postdoctoral fellowship at the Yale School of Medicine with Hubert Bradford Vickery at the Connecticut Agricultural Experiment Station.
Cells of one type may release the 5(S)-HETE that they make to nearby cells of a second type which then oxidize the 5(S)-HETE to 5-oxo-ETE. This transcellular production typically involves the limited variety of cell types that express active 5-lipoxygenase, lack HEDH activity because of their high levels of NADPH compared to NADP+ levels, and therefore accumulate 5(S)-HETE, not 5-oxo-ETE, upon stimulation. This 5(S)-ETE can leave these cells, enter various cell types that possess 5-HEDH activity along with lower NADPH to NADP+ levels, and thereby be converted to 5-oxo-ETE. Transcellular production of 5-oxo-eicosatetraenoates has been demonstrated in vitro with human neutrophils as the 5(S)-HETE producing cells and human PC-3 prostate cancer cells, platelets, and monocyte-derived dendritic cells as the oxidizing cells. It is theorized that this transcellular metabolism occurs in vivo and provides a mechanism for controlling 5-oxo-ETE production by allowing it to occur or be augmented at sites were 5-lipoxygenase-containing cells congregate with cell types possessing 5-HEDH and favorable NADPH/NADP+ ratios; such sites, it is theorized, might include those involving allergy, inflammation, oxidative stress, and rapidly growing cancers.
Biochemical differences between different organisms and humans are useful for drug development. For instance, penicillin kills bacteria by inhibiting the bacterial enzyme DD-transpeptidase, destroying the development of the bacterial cell wall and inducing cell death. Thus, the study of binding sites is relevant to many fields of research, including cancer mechanisms, drug formulation, and physiological regulation. The formulation of an inhibitor to mute a protein's function is a common form of pharmaceutical therapy.
Sources: en.wikipedia.org
Enzymatic specificity provides useful insight into enzyme structure, which ultimately determines and plays a role in physiological functions. Specificity studies also may provide information of the catalytic mechanism. Specificity is important for novel drug discovery and the field of clinical research, with new drugs being tested for its specificity to the target molecule in various rounds of clinical trials. Drugs must contain as specific as possible structures in order to minimize the possibility of off-target affects that would produce unfavorable symptoms in the patient. Drugs depend on the specificity of the designed molecules and formulations to inhibit particular molecular targets. Novel drug discovery progresses with experiments involving highly specific compounds. For example, the basis that drugs must successfully be proven to accomplish is both the ability to bind the target receptor in the physiological environment with high specificity and also its ability to transduce a signal to produce a favorable biological effect against the sickness or disease that the drug is intended to negate.
Network Science, Part 5: Solvent-Accessible Surfaces AREAIMOL is a command line tool in the CCP4 Program Suite for calculating ASA. NACCESS solvent accessible area calculations. FreeSASA Open source command line tool, C library and Python module for calculating ASA. Surface Racer Oleg Tsodikov's Surface Racer program. Solvent accessible and molecular surface area and average curvature calculation. Free for academic use. ASA.py — a Python-based implementation of the Shrake-Rupley algorithm. Michel Sanner's Molecular Surface – the fastest program to calculate the excluded surface. pov4grasp render molecular surfaces. Molecular Surface Package — Michael Connolly's program. Volume Voxelator — A web-based tool to generate excluded surfaces. ASV freeware Analytical calculation of the volume and surface of the union of n spheres (Monte-Carlo calculation also provided). Vorlume Computing Surface Area and Volume of a Family of 3D Balls. GetArea Calculate solvent accessible surface area of proteins online. ProMS ProMS - Protein Molecular Surface Calculator
As a prototypical transaminase, AST relies on PLP (vitamin B6) as a cofactor to transfer the amino group from aspartate or glutamate to the corresponding ketoacid. In the process, the cofactor shuttles between PLP and the pyridoxamine phosphate (PMP) form. The amino group transfer catalyzed by this enzyme is crucial in both amino acid degradation and biosynthesis. In amino acid degradation, following the conversion of α-ketoglutarate to glutamate, glutamate subsequently undergoes oxidative deamination to form ammonium ions, which are excreted as urea. In the reverse reaction, aspartate may be synthesized from oxaloacetate, which is a key intermediate in the citric acid cycle. Two isoenzymes are present in a wide variety of eukaryotes. In humans:
In 1942, Hugh DeHaven published the classic Mechanical analysis of survival in falls from heights of fifty to one hundred and fifty feet. In 1947, the American Tucker was built with the world's first padded dashboard. It also came with middle headlight that turned with the steering wheel, a front steel bulkhead, and a front safety chamber. In 1949, SAAB incorporated aircraft safety thinking into automobiles making the Saab 92 the first production SAAB car with a safety cage. Also in 1949, the Chrysler Imperial Crown was the first car to come with standard disc brakes.
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.
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.