There are various databases that provide the physical and chemical properties of the drug. Two of the most common links are given below:
✶ Log P
Log P refers to the lipophilicity of the drug. It is the logarithmic value of the partition coefficient between
oil/octanol and water. Log P provides insight into a compound's lipophilicity and its distribution across various
organs and tissues. Log P is useful in predicting a compound's ability to penetrate cell membranes and its
potential for bioavailability in pharmacology. It quantifies a molecule's lipophilicity or hydrophobicity, as
higher log P values indicate a greater affinity for the organic phase.
Useful link: ALOGPS, can be used to predict the log P, if the SMILES (Simplified Molecular Input Line Entry System) of the molecule is available (can be found from PubChem or DrugBank)
✶ Log Pvo:w
Pvo:w refers to the partition coefficient of a given drug between vegetable oil and water. The use of
LogP for the computation of tissue-to-plasma ratio of adipose tissue outputs has a higher fold-error compared to
Pvo:w. Therefore Pvo:w is often used to precisely compute the tissue-to-plasma ratio of adipose tissue.
If Log Pvo:wis unavailable, the subsequent equation will then be applied to compute the equivalent.1
Note: On entering Log P, the value of Log Pvo:w is automatically updated using the above equation. If the user wants to replace this value, please enter in the input box provided.
✶ Log D
D refers to distribution coefficient. Unlike log P, which is independent of pH, log D appropriately describes the distribution of ionizable compounds as this measure is pH dependant. It takes into account the fact that some compounds can ionize in aqueous solutions, depending on the pH. Log D provides information on how a compound distributes between octanol and an aqueous solution at a specific pH, reflecting the effects of ionization on the compound's lipophilicity.
The pH of a drug solution indicates whether the drug is an acid (pH < 7) , base (pH > 7) or a Neutral (pH = 7) compound. A monoprotic acid has one H⁺ in excess to donate and a diprotic has two. Similarly for bases, they have excess OH⁻ ions. A zwitterionic compound has equal number of H⁺ and OH⁻ ions. A neutral compound does not ionize and has a net charge of zero. Note: For monoprotic compounds, only the value in pKa1 is considered, pKa2 & pKa3 are allocated a value of zero.
pKa, or the "acid dissociation constant," is a numerical measure to describe the strength of an acid or a base. It represents the equilibrium constant for the dissociation of an acid (HA) into its conjugate base (A-) and a hydrogen ion (H+). In simpler terms, it quantifies the tendency of an acid to donate a proton (H+ ion) in a solution.
The pKa is expressed on a logarithmic scale. A lower pKa indicates a
stronger acid that readily donates protons, while a higher pKa indicates a weaker acid with less inclination to do
The model at present can take an input of only three pKa values. For Zwitterions, please enter the pKas in the specified order of the property.
Useful link: MolGpka can be used to predict the pKa(s) of a given compound using the SMILES of a compound (can be found from PubChem or DrugBank)
✶ Protein binding
Protein binding in drug pharmacokinetics refers to the attachment of a drug to proteins in the bloodstream,
primarily albumin. This binding affects a drug's distribution, as only the unbound (free) drug is
pharmacologically active. A high degree of protein binding can lead to reduced drug availability, as less free
drug is present to reach target tissues. Conversely, drugs with low protein binding have a larger fraction
available for action. Understanding and measuring protein binding is crucial in determining drug dosages and
predicting drug interactions, as drugs that compete for protein binding sites can impact each other's distribution
and efficacy within the body.
The value should be entered as percentage bound to proteins.
Child model only
The degree of protein binding exhibits age-related variations. A checkbox is available for users to indicate if
the provided input for protein binding pertains to an adult. When this checkbox is selected, the input is
considered as an adult protein binding value, and the system will then calculate the corresponding protein
binding value for children.
Note: Currently, only albumin binding would be scaled to children using the checkbox option. 1
✶ Blood-to-plasma ratio
The blood-to-plasma ratio (B/P ratio) is a measure to describe the distribution of a drug between the blood and the plasma in the circulatory system. It represents the concentration of a drug in whole blood compared to its concentration in plasma. Whole blood includes both the liquid plasma and the cellular components, such as red blood cells.
The B/P ratio is important because some drugs may bind to proteins or red blood cells in the blood, which can affect their distribution and availability in the body. A high B/P ratio indicates that more of the drug is bound to blood components, while a low B/P ratio suggests that a larger proportion of the drug is present in the plasma, where it is typically more readily available to exert its pharmacological effects.
The B/P ratio helps understand how a drug is distributed in the body and to help determine appropriate dosages and treatment strategies. Different drugs can have varying B/P ratios, which can influence their pharmacokinetics and therapeutic actions.
Child model only
Hematocrit level is a measure of the volume of red blood cells (RBCs) to the total volume of blood. The
hematocrit level plays a key role in drug distribution across the blood, plasma and various tissues. The normal
adult hematocrit level typically varies between 41-47% and this value can widely vary in paediatric population
according to age.2
The B/P ratio is affected by changes in both protein binding and hematocrit levels. The checkbox provided when ticked automatically computes the B/P ratio in children if an adult value is provided using the equation from Maharaj et al. 2013.3
- Johnson TN, Rostami-Hodjegan A, Tucker GT. Prediction of the Clearance of Eleven Drugs and Associated Variability in Neonates, Infants and Children. Clinical Pharmacokinetics. 2006 2006/09/01;45(9):931-56. https://doi.org/10.2165/00003088-200645090-00005.
- Irwin JJ, Kirchner JT. Anemia in children. Am Fam Physician. 2001;64(8):1379-86. https://www.ncbi.nlm.nih.gov/pubmed/11681780
- Maharaj AR, Barrett JS, Edginton AN. A workflow example of PBPK modeling to support pediatric research and development:case study with lorazepam. AAPS J. 2013;15(2):455-64. https://doi.org/10.1208/s12248-013-9451-0.