Fact-checked by Grok 2 weeks ago

LogP

LogP, also known as the logarithm of the , is a fundamental physicochemical parameter that quantifies the of a , defined as \log_{10} P, where P is the equilibrium ratio of the compound's concentrations in the immiscible octanol (lipophilic) and (hydrophilic) phases. This metric indicates a molecule's preference for partitioning into lipid-like environments over aqueous ones, making it a key descriptor for understanding , membrane permeability, and biological interactions in neutral, non-ionized forms. In medicinal chemistry and drug discovery, LogP plays a pivotal role in predicting absorption, distribution, metabolism, and excretion (ADME) properties, helping to optimize lead compounds for oral bioavailability and efficacy. For instance, Lipinski's Rule of Five specifies that a LogP value exceeding 5 is associated with poor permeability and solubility, increasing the risk of failure in clinical development for orally administered drugs. Beyond pharmaceuticals, LogP informs environmental toxicology by estimating bioaccumulation potential and persistence in ecosystems, as higher values correlate with greater partitioning into fatty tissues or sediments. However, its utility is limited for ionic or highly polar compounds, where it may underestimate interactions with biological membranes. LogP values are obtained experimentally through techniques like the shake-flask method, which involves equilibrating the compound between octanol and water, followed by analytical measurement of phase concentrations, or via chromatographic methods that correlate retention times to partitioning behavior. Computational prediction dominates early-stage screening, employing fragment-based algorithms (e.g., summing contributions from molecular substructures as in CLOGP) or atom-based approaches that account for electronic and , achieving accuracies within 0.5 log units for many datasets. Advanced models further refine these predictions by training on large empirical datasets, enhancing reliability for novel structures. The foundational ideas behind LogP trace to the late 19th century, when Charles Ernest Overton and Hans Meyer independently demonstrated that the potency of anesthetics correlated with their oil-water partitioning, establishing as a of . In the , Corwin Hansch and Toshio Fujita advanced this through quantitative structure-activity relationship (QSAR) analysis, introducing substituent constants (π values) to calculate LogP from molecular structure and standardizing the octanol-water system for broader applicability. By the 1970s, Albert Leo's development of the CLOGP program at formalized computational fragment methods, supported by extensive measured datasets, solidifying LogP as an indispensable tool in rational and chemical .

Definition and Concepts

Definition of LogP

LogP, or the logarithm of the partition coefficient, is defined as the base-10 logarithm of the ratio of the equilibrium concentrations of a (un-ionized) in the and phases, serving as a key measure of . Specifically, the partition coefficient P is given by P = \frac{[\text{solute}]_{\text{octanol}}}{[\text{solute}]_{\text{water}}}, where the concentrations refer to the form of the solute at in the two immiscible phases. Thus, the equation is: \text{LogP} = \log_{10} P = \log_{10} \left( \frac{[\text{solute}]_{\text{octanol}}}{[\text{solute}]_{\text{water}}} \right) This parameter is dimensionless, as it represents the logarithm of a ratio of like units (concentrations). The concept of LogP was introduced in the 1960s by Corwin Hansch, who coined the term in the development of quantitative structure-activity relationships (QSAR) for medicinal chemistry, building on earlier partition studies to correlate chemical structure with biological activity. In seminal work with T. Fujita, Hansch formalized LogP as a hydrophobic substituent constant (π) relative to a parent compound, enabling predictive modeling of drug potency. In interpretation, LogP quantifies a compound's for non-polar versus polar environments, with positive values indicating lipophilic preference for the octanol phase and negative values denoting hydrophilic in . Typical LogP values span from approximately -3 for highly hydrophilic substances to +10 for extremely lipophilic ones, providing a scale for assessing molecular partitioning behavior.

Octanol-Water Partition Coefficient

The , denoted as LogP or log K_{ow}, utilizes n-octanol as the organic phase due to its amphiphilic nature, which includes a polar hydroxyl group capable of and a long nonpolar alkyl chain that provides hydrophobic character, thereby mimicking key features of biological membranes. serves as the immiscible aqueous phase, representing the hydrophilic environment in biological systems. This two-phase system allows for the assessment of a solute's distribution based on its , with n-octanol selected over other alcohols for its low water solubility and ability to dissolve a wide range of organic compounds effectively. The measurement involves the of a neutral solute between the mutually saturated n-octanol and phases at 25°C and near infinite dilution to minimize solute-solute interactions and ensure ideality. The process assumes no chemical reactions, , or adsorption to the container walls, focusing purely on passive partitioning driven by differences. This standardization is outlined in Test Guideline 107, which specifies the shake-flask method at 25°C with low (typically using pure without added electrolytes unless justified for ). The octanol phase simulates the lipid bilayer structure of cell membranes, where the hydrophobic tail region corresponds to the alkyl chain and the polar headgroup interactions to the hydroxyl functionality, making LogP a reliable for passive membrane permeability and overall in biological contexts. As originally proposed by Hansch and Leo, this system correlates well with transport properties across barriers. To illustrate the range of LogP values, the following table provides examples for representative compounds, highlighting how nonpolar substances favor the octanol while polar ones prefer :
CompoundLogPSource
Benzene2.13Hansch and Leo (1979)
Ethanol-0.31NIST Compilation (2009)

Methods of Determination

Experimental Techniques

The shake-flask method, also known as the classical partition method, remains the reference technique for direct measurement of the octanol-water partition coefficient (LogP). In this approach, a solute is equilibrated between mutually saturated phases of n-octanol and water in a flask, typically by mechanical shaking for 30 minutes to several hours at controlled temperature (often 25°C), followed by phase separation and quantification of the solute concentration in each phase using techniques such as UV-Vis spectrophotometry, gas chromatography (GC), or high-performance liquid chromatography (HPLC). The LogP value is then calculated as the logarithm of the concentration ratio [octanol]/[water]. This method offers high accuracy, with typical reproducibilities of ±0.1 to 0.3 log units, but it is labor-intensive, requires relatively large sample volumes (1-10 mL per phase), and is limited to compounds with moderate solubility (avoiding very hydrophilic or lipophilic substances that may not equilibrate fully). High-performance liquid chromatography (HPLC)-based methods provide an indirect, faster alternative for estimating LogP, particularly suited for compounds with LogP values between 0 and 6 (extendable to 10 in some cases). These involve reversed-phase HPLC using a non-polar stationary phase (e.g., C18 column) and an aqueous mobile phase, where the retention time or factor (k) of the test compound is compared to reference standards with known LogP values. The relationship is modeled linearly as \log P = a (\log k) + b, with coefficients a and b derived from calibration. Analysis is typically via UV detection, offering throughput advantages over shake-flask but with slightly lower precision (±0.2-0.5 log units) due to reliance on correlations rather than direct partitioning. This method is standardized and widely adopted for regulatory purposes. For ionizable compounds, potentiometric or pH-metric methods determine apparent partition coefficients by monitoring changes during in the presence of octanol-water phases. The compound is titrated across a pH range (e.g., 2-12) using a biphasic system, where distribution equilibria between ionized and neutral forms are analyzed via the Henderson-Hasselbalch equation adapted for partitioning. This yields LogP for the neutral species and accounts for effects without needing , achieving accuracies of ±0.1-0.4 log units for weak acids and bases. It is particularly useful for pharmaceuticals but requires the compound to be titratable and soluble enough for response. The slow-stirring apparatus addresses limitations of vigorous shaking for volatile, high-LogP (>5), or surface-active compounds, minimizing emulsification and octanol droplet transfer into the aqueous phase. In this setup, phases are gently stirred (e.g., 100-200 rpm) in a or specialized vessel for extended periods (up to 24-48 hours) until equilibrium, followed by sampling and analysis similar to shake-flask. It extends reliable measurement to LogP up to 10 or higher, with reproducibilities around ±0.2-0.5 log units, and is recommended for substances prone to artifacts in traditional methods. Experimental LogP determinations are validated against reference datasets, achieving overall accuracies of ±0.1-0.5 log units depending on the method and compound class, with shake-flask serving as the benchmark for others. Databases such as the Data Bank provide curated experimental values from thousands of compounds for comparison and quality control. Post-2020 advancements include via robotic systems for , such as miniaturized shake-flask setups with sample pooling and integrated LC-MS analysis, enabling parallel processing of dozens to hundreds of compounds per day while maintaining accuracy within ±0.3 log units. These systems reduce manual intervention and sample needs, facilitating early-stage .

Predictive Models

Predictive models for LogP estimation rely on computational algorithms that approximate the without requiring physical experiments, enabling rapid screening in and chemical assessment. These methods evolved from early additive schemes based on molecular substructures to sophisticated approaches that incorporate three-dimensional molecular features and large datasets. They generally achieve accuracies within error (RMSE) values of 0.2 to 0.6 log units when validated against experimental databases like PHYSPROP, which contains approximately 13,500 curated LogP measurements. Fragment-based methods decompose a into predefined substructures, assigning additive hydrophobicity contributions to each fragment while applying correction factors for interactions such as electronic effects or steric hindrance. The seminal CLogP algorithm, developed by Albert Leo and Corwin Hansch, exemplifies this approach by using a library of fragment constants derived from on experimental data, with corrections for proximity and branching to handle non-additive behaviors. This method underpins many early computational tools and remains influential for its interpretability in quantitative structure-activity relationship (QSAR) studies. Atom-based methods extend additivity to individual atoms, classifying them by type, hybridization, and neighboring environments to compute partial charges and hydrophobicity contributions. The ALogP model by A. K. Ghose and G. M. Crippen assigns 120 atom types with regression-fitted coefficients, offering simplicity and broad applicability without explicit fragment rules, though it may overlook long-range interactions. These techniques prioritize computational efficiency for high-throughput predictions. Advanced predictive models leverage 3D-QSAR and to capture conformational and descriptor-based features beyond simple additivity. In 3D-QSAR, techniques like comparative molecular field analysis (CoMFA) align molecular fields to derive LogP correlations, while approaches—such as s or neural networks—train on datasets using inputs like molecular weight, , and topological indices. Graph neural networks, a recent , encode molecular graphs to learn representations, improving predictions for flexible or complex structures. Seminal implementations include models achieving good predictive performance on diverse datasets. Software tools implement these models for practical use, often combining multiple algorithms for robustness. ACD/LogP from Advanced Chemistry Development employs hybrid fragment and atom contributions with user-trainable options, supporting batch predictions. MarvinSketch by ChemAxon integrates similar methods into structure drawing interfaces, while open-source libraries like RDKit provide Crippen-based ALogP calculations via APIs. In the , AI-driven enhancements, particularly , have improved predictions by accounting for tautomerism and conformational ensembles. Validation confirms these gains, with models like graph convolutional networks showing superior generalization and RMSE around 0.45-0.6.

Applications

Drug Design and

LogP plays a pivotal role in , , , and excretion (ADME) properties during , influencing a compound's ability to cross biological membranes while balancing challenges. High LogP values facilitate passive across lipid bilayers, enhancing intestinal and tissue , but excessively lipophilic compounds (LogP > 5) often exhibit poor aqueous , leading to erratic and potential accumulation in non-target s. Conversely, moderately lipophilic drugs with LogP in the range of 1-3 are typically optimal for (CNS) penetration, as this range supports crossing the blood-brain barrier without compromising or increasing off-target effects, with median ClogP values around 2.8 observed in approved CNS therapeutics. In pharmacokinetics, LogP is a core criterion in , which predicts oral by requiring LogP < 5 alongside molecular weight ≤ 500 Da, ≤5 hydrogen bond donors, and ≤10 hydrogen bond acceptors; violations increase the likelihood of poor permeability or solubility, guiding early-stage candidate optimization to favor drug-like properties. This rule correlates LogP directly with membrane permeability, where values below 5 promote sufficient absorption, while integrating solubility assessments to avoid formulation hurdles in development. Quantitative structure-activity relationship (QSAR) models, pioneered by the , quantify LogP's impact on biological activity as a function of hydrophobic (π, related to LogP), electronic (σ), and steric factors, expressed generally as log(1/C) = a(log P) - b(log P)^2 + ρσ + steric terms + constant, where C is the concentration for biological response; this parabolic relationship highlights an optimal LogP for potency, beyond which activity declines due to reduced solubility or non-specific binding. Representative case studies illustrate these principles: , a beta-blocker with LogP ≈ 3.5, demonstrates excellent oral absorption (rapid and complete, with peak plasma levels in 1-3 hours) due to its balanced lipophilicity, enabling effective distribution without solubility issues. In contrast, highly lipophilic drugs like (LogP = 7.1), an antihistamine withdrawn in 1998 for QT prolongation and fatal arrhythmias, exemplify failures where extreme lipophilicity promoted off-target hERG channel blockade and poor metabolic clearance, underscoring the risks of LogP > 5 in clinical translation. Predicted LogP values are integral to in virtual libraries, where computational filters prioritize candidates with drug-like (e.g., LogP 1-5) to enrich for favorable profiles before synthesis, reducing attrition in lead optimization by integrating QSAR-derived predictions with scores. Regulatory guidelines from the FDA and incorporate LogP indirectly through the (BCS) for biowaivers, where LogP > 1.72 serves as a surrogate for high permeability in Class I (high , high permeability) drugs, allowing waiver of studies if criteria are met, thus streamlining generic approvals for compounds like .

Environmental Fate and Toxicity

LogP plays a critical role in evaluating the potential of organic chemicals in ecosystems, where higher values indicate greater partitioning into lipid-rich tissues of organisms. The bioaccumulation factor (BAF), which accounts for uptake from both and , correlates with LogP such that log BAF ≈ 0.7 LogP for many non-polar compounds in biota, reflecting the similarity between octanol and biological . Chemicals with LogP > 4 are typically flagged for concern due to their high , leading to elevated concentrations in organisms and potential trophic transfer. In and environments, LogP serves as a key input for quantitative structure-activity relationship (QSAR) models that predict the organic carbon-water (Koc), which quantifies to . These models, such as log Koc = 0.81 log Kow + 0.10 for non-ionic organics, demonstrate that higher LogP values enhance , reducing chemical mobility and leaching into while increasing persistence in terrestrial compartments. This partitioning behavior is essential for assessing long-term environmental exposure risks in ecosystems. Under the European Union's REACH regulations, LogP is integral to screening for persistent, , and toxic (PBT) substances, with a cutoff of LogP > 3 triggering further evaluation of bioaccumulation potential when direct factor data are unavailable. For PBT classification per Annex XIII, LogP ≥ 4.5 often indicates properties, prompting comprehensive fate assessments to mitigate ecological risks. Polychlorinated biphenyls (PCBs) exemplify the environmental implications of high LogP, as congeners like PCB-153 with LogP ≈ 6.8 exhibit strong in food chains, amplifying concentrations from to top predators such as and mammals. This trophic magnification heightens risks, contributing to reproductive and immunological impairments in wildlife. LogP indirectly influences volatilization processes through its relationship with constants, as hydrophobic compounds (high LogP) tend to have lower solubility, altering air- partitioning and reducing evasion from aqueous phases under certain conditions. Similarly, for , high LogP compounds often show slower degradation rates in due to preferential to solids, prolonging environmental persistence. LogP is integrated into advanced multimedia fate models like SimpleBox 4.0, which simulate chemical across air, water, soil, and sediment compartments to predict global exposure and persistence. These models use LogP-derived parameters to estimate transfer s, aiding regulatory evaluations of emerging contaminants.

LogD and pH Dependence

The , denoted as LogD, represents the logarithm of the ratio of the total concentration of a compound (including both and ionized species) in the octanol phase to its total concentration in the aqueous phase at a specified . Unlike LogP, which applies solely to the form of a , LogD accounts for the pH-dependent states, making it a more comprehensive measure of for ionizable compounds. This parameter is particularly relevant in biological contexts where pH variations influence molecular behavior. The pH dependence of LogD arises from the equilibria of ionizable groups, governed by the compound's values. For monoprotic acids, the relationship is given by: \log D = \log P - \log \left(1 + 10^{pH - pK_a}\right) For monoprotic bases: \log D = \log P - \log \left(1 + 10^{pK_a - pH}\right) These equations illustrate how LogD decreases as the pH moves away from the form's dominance, reflecting reduced partitioning into the non-polar octanol phase due to increased . Approximately 64% of pharmaceutical compounds are ionizable, underscoring LogD's importance over LogP for predicting real-world in physiological environments. LogD is commonly measured at 7.4 to mimic physiological conditions, such as , and is vital for assessing blood-brain barrier permeability, where values around 1–3 often correlate with favorable CNS penetration. Experimental determination typically involves -metric in an octanol-water system, where the compound is partitioned across a pH range, and distribution is refined via nonlinear least-squares analysis of curves to yield both LogP and values simultaneously. This method, often combined with shake-flask partitioning for validation, provides accurate LogD profiles without isolating neutral species. A representative example is acetylsalicylic acid (aspirin), with a LogP of 1.19 for its neutral form and a pKa of 3.5. At 7.4, aspirin's extensive results in a LogD of approximately -1.8, highlighting the dramatic shift in due to and reduced octanol of the anionic species.

Other Solvent Systems

Alternative solvent systems to the standard octanol-water partition provide specialized insights into solute by varying the organic phase to better mimic specific biological or environmental interactions or to isolate particular physicochemical properties. These systems are particularly useful when the hydrogen-bonding capacity of octanol leads to overestimation of partitioning for certain compound classes, such as those with strong H-bond acceptor groups. Alkane-water systems, such as hexadecane-water or cyclohexane-water, measure intrinsic hydrophobicity by minimizing in the , unlike octanol which can form H-bonds with solutes. This makes alkane-water logP values lower for polar molecules and more indicative of partitioning into non-polar environments like tails in membranes. For instance, the difference between octanol-water and alkane-water logP (ΔlogP) quantifies a solute's potential, with values up to 2 log units per internal H-bond. Correlations between these systems and octanol-water allow cross-prediction, such as approximate linear relations of the form logP_oct ≈ 1.1 logP_alk + 0.5 for neutral solutes, enabling estimation when direct data is scarce. Advantages include better accuracy for permeability predictions in bilayers, but limitations arise from less extensive experimental databases and challenges in compared to octanol-water. Chlorobenzene-water partitions have been explored for solutes with electron-donating groups, where the aromatic nature of enhances π-π interactions not captured well by aliphatic solvents. This system correlates moderately with octanol-water logP for such compounds, providing complementary data in quantitative structure-activity relationship (QSAR) studies for electron-rich aromatics. However, its use remains niche due to limited datasets and issues for highly polar solutes. Biomimetic systems like liposome-water or parallel artificial membrane permeability assay (PAMPA) use phospholipid-based barriers to directly estimate permeability rather than simple partitioning, offering logP-like metrics tailored to . Liposome-water partitions reflect interactions with bilayers, showing closer alignment with in vivo absorption for amphiphilic drugs than octanol-water, while PAMPA employs synthetic membranes to screen large libraries rapidly. These approaches excel for predicting passive across biological barriers but face challenges in and scaling to high-throughput formats without . Historical alternatives, such as vegetable oil-water (e.g., or ) and cyclohexane-water, were employed in early QSAR models to approximate tissue partitioning, particularly for fat-soluble compounds. systems mimic distribution, with logP values often 0.5-1 log unit lower than octanol-water for non-polar solutes, aiding predictions of . Cyclohexane-water, as a simple proxy, was used in foundational studies for its ease of handling and relevance to non-hydrogen-bonding environments. These older systems highlight the evolution toward more biologically relevant metrics but suffer from variability in oil composition and lack of modern validation.

References

  1. [1]
    [PDF] LogP—Making Sense of the Value - ACD/Labs
    LogP is the log of the partition coefficient, measuring a substance's tendency to dissolve in water or organic solvents. LogP = log10 (Partition Coefficient).
  2. [2]
    LogP | DrugBank Help Center - API Portal
    1. LogP is defined as the partition coefficient of a molecule between aqueous and lipophilic phases usually considered as octanol and water.
  3. [3]
    Prediction of logarithm of n-octanol-water partition coefficient (logP ...
    Feb 23, 2023 · The logarithm of n-octanol-water partition coefficient (logP) is frequently used as an indicator of lipophilicity in drug discovery, ...
  4. [4]
    Practical Understanding of Partition Coefficients | LCGC International
    Mar 1, 2023 · Partition coefficients (P or log P) are ratios of a compound's concentration at equilibrium between two immiscible phases, used in extraction ...
  5. [5]
    Octanol-Water Partition Coefficient - an overview - ScienceDirect
    In the early stage of the drug discovery process, lipophilicity is often ranked as one of the most important physicochemical properties to screen lead compounds ...
  6. [6]
    Lipinski's rule of five | DrugBank Help Center
    This rule helps to predict if a biologically active molecule is likely to have the chemical and physical properties to be orally bioavailable.
  7. [7]
    BDDCS, the Rule of 5 and Drugability - PMC - PubMed Central
    Lipinski's Rule of 5 was developed to set 'drugability' guidelines for NMEs [3]. In the drug discovery setting, the Rule of 5 predicts that poor absorption or ...
  8. [8]
    The octanol-water partition coefficient: Strengths and limitations
    Aug 6, 2025 · The logP value is a key factor used in drug discovery, environmental fate, and exposure modelling to predict absorption, distribution, and ...<|separator|>
  9. [9]
    The History of the Development of CLOGP - Daylight
    The first method of calculating log P from structure based on adding a substituent =BC value to the measured log P of a parent.
  10. [10]
    How medicinal chemists learned about log P - ResearchGate
    Aug 10, 2025 · Although log P is now recognized to be a key factor that determines the bioactivity of a molecule, the focus of medicinal chemists on ...<|separator|>
  11. [11]
    Octanol-water partition coefficient measurements for the SAMPL6 ...
    Octanol-water partition coefficients (Kow), or their logarithms (log P), are frequently used as a measure of lipophilicity in drug discovery. The partition ...1. Introduction · 2. Methods · 4. Discussion
  12. [12]
    The Hidden Crux of Correctly Determining Octanol–Water Partition ...
    Jul 3, 2025 · The partition coefficient log P is defined for the neutral species being partitioned between the two phases.
  13. [13]
    p-σ-π Analysis. A Method for the Correlation of Biological Activity ...
    A Method for the Correlation of Biological Activity and Chemical Structure. Click to copy article linkArticle link copied! Corwin. Hansch ...Missing: logP origin
  14. [14]
    Hansch analysis 50 years on - Martin - Wiley Interdisciplinary Reviews
    Apr 18, 2012 · The original Hansch–Fujita QSAR continues to be performed to this day, fifty years since its inception. In addition, it has inspired vigorous research.Missing: origin | Show results with:origin
  15. [15]
    [PDF] Octanol-Water Partition Coefficients of Simple Organic Compounds
    Octanol-water partition coefficients (log P) for 611 simple organic compounds repre- senting all principal classes have been retrieved from the literature.
  16. [16]
    A Simple, Robust and Efficient Computational Method for n-Octanol ...
    Jul 18, 2017 · In this paper, multiple linear regression (MLR) was used to build quantitative structure property relationship (QSPR) of n-octanol-water partition coefficient ...Missing: choice biomembranes
  17. [17]
    Logp - an overview | ScienceDirect Topics
    It is the measure of the lipophilicity or hydrophobicity of the compound. LogP > 0, states the drug is lipophilic and LogP < 0 states the drug being hydrophilic ...
  18. [18]
    [PDF] Octanol-Water Partition Coefficients of Simple Organic Compounds
    Oct 15, 2009 · range over many orders of magnitude (10- 2 to 106. ), it is ... trans-3-Phenyl-2-propenoic acid CAS # 140-10-3. pK = 4.44 . a. *2.13. D.
  19. [19]
    [PDF] Test No. 107: Partition Coefficient (n-octanol/water) - OECD
    Test 107 measures the partition coefficient (P) of a substance between n-octanol and water using a shake flask method, where solvents are mutually saturated.
  20. [20]
    Experimental Determination of Octanol–Water Partition Coefficients ...
    Feb 25, 2020 · Generally, neutral species showed higher affinity for the octanol phase than their respective (partly) ionized counterparts (Table 1). However, ...
  21. [21]
    [PDF] Partition Coefficient (n-octanol/water), HPLC Method (EN) - OECD
    Jun 30, 2022 · The Pow values depend on the environmental conditions such as temperature, pH, ionic strength etc, and these should be defined in the experiment ...
  22. [22]
    A robust, viable, and resource sparing HPLC-based logP method ...
    Sep 25, 2023 · LogP of selected reference substances ranged from 1.6 to 6.5. Their physicochemical properties, such as Biopharmaceutics Classification System ...Missing: benzene ethanol
  23. [23]
    pH-metric log P. 4. Comparison of partition coefficients determined ...
    The general applicability of the potentiometric technique to ionizable compounds of diversely varied structures was demonstrated by the study. Publication ...
  24. [24]
    Potentiometric determination of octanol–water and liposome–water ...
    This Letter describes a simple method for determining log P values (over a wide range from −0.8 to 5.3) for 12 organic weak acids and bases using potentiometric ...
  25. [25]
    [PDF] Test No. 123: Partition Coefficient (1-Octanol/Water) - OECD
    Jun 30, 2022 · 1-octanol/water partition coefficient (POW) values up to a log POW of 8.2 have been accurately determined by the slow-stirring method (1).
  26. [26]
    A comparison of log Kow (n-octanol–water partition coefficient ...
    Jan 9, 2019 · The solubility ratio method (referred to in OECD 107) is based on the log of the ratio of the n-octanol solubility and the water solubility, ...Missing: strength | Show results with:strength
  27. [27]
    Dortmund Data Bank - DDBST GmbH
    The DDB currently (2025-Nov-10) contains 11 million data tuples for approximately 115,680 components from 103,800 references (220,650 evaluated). The data bank ...Missing: values | Show results with:values
  28. [28]
    High-throughput screening of LogD by using a sample pooling ...
    Jun 20, 2023 · In this work, a new approach for screening LogD is presented. The method is based on the traditional shake flask method combined with rapid ...
  29. [29]
    High-Throughput HPLC Method for the Measurement of Octanol ...
    Jun 5, 2025 · The octanol–water partition coefficient (logP) is the most common measure for quantifying lipophilicity, for which the partitioning of a ...
  30. [30]
  31. [31]
    Prediction of Hydrophobic (Lipophilic) Properties of Small Organic ...
    This work describes an extensive reparametrization of the atomic log P values and a detailed comparison of the performance of ALOGP and CLOGP methods on the ...
  32. [32]
    Evaluating Machine Learning Models for Molecular Property ...
    Sep 15, 2025 · In this work, we investigate and evaluate the performance of 14 machine learning models, including classical approaches like random forests, as ...
  33. [33]
    Exploring the octanol–water partition coefficient dataset using deep ...
    Jun 14, 2021 · We have selected the octanol-water partition coefficient (log P) as an example, which plays an essential role in environmental chemistry and ...
  34. [34]
    JPlogP: an improved logP predictor trained using predicted data
    Dec 14, 2018 · The Ghose and Crippen atom-types are an expanded set and using our calculated training set 108 different atom-types are found and the model ...
  35. [35]
    A deep learning approach for the blind logP prediction in SAMPL6 ...
    Deep neural network is a promising choice for generating a model for logP prediction. It has recently been used in a number of fields including QSAR studies ...
  36. [36]
    Improved Lipophilicity and Aqueous Solubility Prediction with ... - MDPI
    We argue that combining models with different key aspects help make graph neural networks deeper and simultaneously increase their predictive power.
  37. [37]
    Defining Desirable Central Nervous System Drug Space through the ...
    Mar 25, 2010 · Examination of individual ADME properties (Papp, P-gp, CLint,u) suggested that for each property the drugs had on average a superior profile ...
  38. [38]
    Propranolol | C16H21NO2 | CID 4946 - PubChem - NIH
    9.5 Absorption, Distribution and Excretion. Absorption. Patients taking doses of 40mg, 80mg, 160mg, and 320mg daily experienced Cmax values of 18±15ng/mL, 52 ...
  39. [39]
    Terfenadine | C32H41NO2 | CID 5405 - PubChem - NIH
    3.2.5 LogP. 7.1 ... Withdrawn from US market, January, 1997. FDA; Talk Paper. T98-10. Feb 27, 1998. Seldane and generic terfenadine withdrawn from market.
  40. [40]
    Docking, virtual high throughput screening and in silico fragment ...
    The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more ...
  41. [41]
    Applying Biopharmaceutical Classification System (BCS) Criteria to ...
    In addition, in humans, a Do value greater than 1.0 is used to define a compound as highly soluble and a LogP value greater than 1.72 as high permeability.
  42. [42]
    [PDF] M9 Biopharmaceutics Classification System- Based Biowaivers - FDA
    This guidance provides recommendations to support the biopharmaceutics classification of drug substances and the BCS-based biowaiver of bioequivalence studies ...Missing: LogP | Show results with:LogP
  43. [43]
    Prediction of the bioaccumulation of persistent organic pollutants in ...
    Predictive correlations of the bioaccumulation factor of persistent organic pollutants in aquatic biota are presented as functions of their octanol/water ...Missing: LogP | Show results with:LogP
  44. [44]
    Are current regulatory log Kow cut-off values fit-for-purpose as a ...
    A chemical is Bioaccumulative when the Bioaccumulation factor (BAF), that considers uptake form food and water, or the BCF is ≥ 5000, or in the absence of such ...
  45. [45]
    Relationships between molecular properties and log P and soil ...
    The QSAR models based on van der Waals volume, dipole moment, and energy of lowest unoccupied molecular orbital produced estimates of log P and Koc that ...
  46. [46]
    PBT assessment using the revised annex XIII of REACH: A ...
    Oct 17, 2011 · Log KOW ≤ 4.5, Not B and not vB. Toxicity. Short-term aquatic ... • BCF > 2000 or Log Pow ≥ 3, Chronic NOEC < 0.01 mg/L, n/a. Guideline ...
  47. [47]
    Bioaccumulation Testing and Interpretation for the Purpose of ...
    Biomagnification is most likely to occur with persistent compounds having log Kows greater than 5, and with organisms that have long lives and probably are ...
  48. [48]
    Metabolism and metabolites of polychlorinated biphenyls (PCBs)
    The aim of this document is to provide an overview of PCB metabolism and to identify metabolites of concern and their occurrence.
  49. [49]
    Henry's law constants for a diverse set of organic chemicals
    The Henry's law constant (HLC) or air/water partition coefficient is a key property in the process of describing a chemical's environmental fate.
  50. [50]
    Determination of the Henry's law constants of low-volatility ...
    Sep 1, 2017 · Accurate Henry's law constants (H) are unavailable for the majority of organic pollutants, especially those having a low volatility.
  51. [51]
    A multimedia model to estimate the environmental fate of ... - NIH
    SimpleBox4Plastic (SB4P) is a multimedia model that links microplastic transport and concentrations in air, water, sediment, and soil, using mass balance ...Missing: 2020s | Show results with:2020s
  52. [52]
    [PDF] Lipophilicity Descriptors: Understanding When to Use LogP & LogD
    Lipophilicity is represented by the descriptors logP (also known as Kow or Pow) and logD, and is used, for example, to help predict in-vivo permeability of ...
  53. [53]
    LogD Contributions of Substituents Commonly Used in Medicinal ...
    For these reasons, measurement of the partition coefficient (logP) or its pH-dependent variant, the distribution coefficient (logD), is now routine in the ...
  54. [54]
    [PDF] Evaluation of log P, pKa, and log D predictions from the SAMPL7 ...
    Jun 24, 2021 · (15). logDpH = logP − log 1 + 10pKa−pH. (16). logDpH = logP − log 1 + 10pH−pKa. Fig. 2 For each molecule in the SAMPL7 pKa challenge we asked.
  55. [55]
    Effect of Drug Lipophilicity and Ionization on Permeability Across the ...
    LogP and logD are widely considered as effective molecular descriptors capable of predicting drug permeability and absorption.Missing: examples | Show results with:examples
  56. [56]
    LogD7.4 prediction enhanced by transferring knowledge from ...
    Sep 5, 2023 · Thus, logD, which is pH dependent and measures the lipophilicity of an ionizable compound in a mixture of ionic species, is more relevant to ...
  57. [57]
    pH-Metric log P. II: Refinement of Partition Coefficients and ...
    A generalized, weighted, nonlinear least squares procedure is developed, based on pH titration data, for the refinement of octanol- water partition ...
  58. [58]
    Alkane/Water Partition Coefficient Calculation Based on the ...
    Jun 24, 2021 · We introduce a physics-based model for calculating partition coefficients of solutes between water and alkanes, using a combination of a semi-empirical method ...
  59. [59]
    Parameterization of an empirical model for the prediction ... - PubMed
    In this work, we propose a parameterization of an empirical model for n-octanol/water, alkane/water (logP(alk)) and cyclohexane/water (logP(cyc)) systems.<|control11|><|separator|>
  60. [60]
    Parameterization of an empirical model for the prediction of n ...
    Aug 10, 2025 · In this work, we propose a parameterization of an empirical model for n-octanol/water, alkane/water (logP(alk)) and cyclohexane/water (logP(cyc)) ...
  61. [61]
    Estimation of alkane–water log P for neutral, acidic, and basic ...
    Partition coefficients can be measured directly using the “shake-flask” assay, but this method is cumbersome and it requires relatively large quantities of pure ...
  62. [62]
    Evaluation of the Ability of PAMPA Membranes to Emulate Biological ...
    Two parallel artificial membrane permeability assay (PAMPA) systems intended for emulating skin permeability have been characterized through the solvation ...
  63. [63]
    Using water–solvent systems to estimate in vivo blood–tissue ...
    Oct 16, 2015 · We suggest using the water/peanut oil system as a replacement system for blood–fat partition coefficients. The water–skin solvents tested also ...Missing: alternative | Show results with:alternative