Skip to main content
Login | Suomeksi | På svenska | In English

Browsing by Subject "pharmacokinetic model"

Sort by: Order: Results:

  • Tissari, Anita (2011)
    QSPR (Quantitive structure property relationship) describes relationship between descriptors and biological activity. Therefore, QSPR models are useful tools in drug discovery. The literature review summarizes existing corneal, intestinal and blood brain barrier permeability models. The most common descriptors are hydrophobicity, polar surface and H-bonding capability. Also, the size of molecule may have influence on permeability even though the results are sometimes contradictory. Descriptors might have limiting values such as those presented in Lipinski's ‖rule of five‖. Drug candidate should not have 'rule of 5' values outside of the useful range, otherwise the per oral absorption of the compound may be compromised. In the literature review the transporter activity in cornea, intestine and blood brain barrier is described. Currently, many QSPR-models have been developed to predict interactions of drug candidates with transporters. The purpose of experimental part was to build in silico -model of corneal passive permeability for early ocular drug discovery. QSPR-model was built using permeability data and molecular descriptors of 54 molecules. Corneal permeability coefficients in rabbits were obtained from the literature. Octanol-water partitition coefficient at pH 7,4 (logD) and the total number of hydrogen bonds were the descriptors in the final model. The final equation was log(permeability coefficient) = -3,96791 - 0,177842*Htotal + 0,311963*logD(pH7,4). For this model R2 was 0,77 ja Q2 was 0,75. The model was evaluated using an external data set of 15 compounds and by pharmacokinetic modeling. Predicted permeability coefficients were used to simulate the aqueous humour concentrations of sevent compounds at steady-state. In addition corneal absorption coefficient (Kc) was simulated for 13 compounds and these values were compared to predicted permeability. The predicted permeability coefficients correlated well with experimental permeability coefficients. In addition aqueous humour concentrations can be simulated in steady state using predicted (QSPR) permeability coefficients. The final QSPR-model may be used in ocular drug discovery and development.
  • Juuti, Hanne (2010)
    The blood-brain barrier protects brain from xenobiotics that are in blood. Different in vivo and in vitro methods have been developed for studying blood brain barrier and those can be found in the literature. There are only few computational models pharmacokinetics of compounds in the brain. In this study permeability factors, which were measured in vitro or in vivo, were collected from literature. Additionally two different pharmacokinetic computer models of blood-brain barrier were described. One of which is called microdialysis model and the other efflux model. Microdialysis model is a very simple two compartmental model, the compartments being the blood and the brain. Five substances were simulated according to the values measured in vivo in rat. The model did not correlate well with the in vivo results, because of the simplicity of the model as the model missed the compartment of brain tissue and the kinetics of transporters. Efflux model has three compartments, blood, blood brain barrier endothelial cells and brain. The model was used to study the impact of the of efflux transporter at the luminal barrier of endothelial cells and passive permeability to the steady-state concentration of a compound in the brain extracellular fluid with theoretical simulations. The relation between free drug concentrations in blood and brain extracellular fluid (Kp,uu) was studied. The impact of Michaelis-Menten kinetics of efflux transporter to the concentration of compound was shown in the results. The efflux model is suitable for theoretical simulations. It is possible to add new active transporters. With theoretical simulations the results from in vitro and in vivo studies can be combined and the different factors can be studied in one simulation.