PKQuest: capillary permeability limitation and plasma protein binding – application to human inulin, dicloxacillin and ceftriaxone pharmacokinetics

BACKGROUND: It is generally assumed that the tissue exchange of antibiotics is flow limited (complete equilibration between the capillary and the tissue water). This assumption may not be valid if there is a large amount of plasma protein binding because the effective capillary permeability depends on the product of the intrinsic capillary permeability (PS) and the fraction of solute that is free in the blood (fw(B)). PKQuest, a new generic physiologically based pharmacokinetic software routine (PBPK), provides a novel approach to modeling capillary permeability in which the only adjustable parameter is the PS of muscle. METHODS: All the results were obtained by applying PKQuest to previously published human pharmacokinetic data. RESULTS: The PKQuest analysis suggests that the highly protein bound antibiotics dicloxacillin and ceftriaxone have a significant capillary permeability limitation. The human muscle capillary PS of inulin, dicloxacillin and ceftriaxone was 0.6, 13 and 6 ml/min/100 gm, respectively. The ceftriaxone protein binding is non-linear, saturating at high plasma concentrations. The experimental ceftriaxone data over a wide range of intravenous inputs (0.15 to 3 gms) was well described by PKQuest. PKQuest is the first PBPK that includes both permeability limitation and non-linear binding. CONCLUSIONS: Because of their high degree of plasma protein binding, dicloxacillin and ceftriaxone appear to have a diffusion limited exchange rate between the blood and tissue and are not flow limited as had been previously assumed. PKQuest and all the examples are freely available at

Haematogenous Staphylococcus aureus meningitis. A 10-year nationwide study of 96 consecutive cases

BACKGROUND: Haematogenous Staphylococcus aureus meningitis is rare but associated with high mortality. Knowledge about the disease is still limited. The objective of this study was to evaluate demographic and clinical prognostic features of bacteraemic S. aureus meningitis. METHODS: Nationwide surveillance in Denmark from 1991 to 2000 with clinical and bacteriological data. Risks of death were estimated by Cox proportional hazards regression analysis. RESULTS: Among 12480 cases of S. aureus bacteraemia/sepsis, we identified 96 cases of non-surgical bacteraemic S. aureus meningitis (0.8%). Incidence rates were 0.24 (95% confidence interval [CI], 0.18 to 0.30)/100 000 population between 1991–1995 and 0.13 (CI, 0.08 to 0.17)/100 000 population between 1996–2000. Mortality was 56%. After adjustment, only co morbidity (hazard ratio [HR], 3.45; CI, 1.15 to 10.30) and critical illness (Pitt score ≥ 4) (HR, 2.14; CI, 1.09 to 4.19) remained independent predictors of mortality. CONCLUSION: The incidence, but not mortality of bacteraemic S. aureus meningitis decreased during the study period. Co morbidity and critical illness were independent predictors of a poor outcome

Yeast Two-Hybrid: State of the Art

Genome projects are approaching completion and are saturating sequence databases. This paper discusses the role of the two-hybrid system as a generator of hypotheses. Apart from this rather exhaustive, financially and labour intensive procedure, more refined functional studies can be undertaken. Indeed, by making hybrids of two-hybrid systems, customised approaches can be developed in order to attack specific function-related problems. For example, one could set-up a "differential" screen by combining a forward and a reverse approach in a three-hybrid set-up. Another very interesting project is the use of peptide libraries in two-hybrid approaches. This could enable the identification of peptides with very high specificity comparable to "real" antibodies. With the technology available, the only limitation is imagination

The pharmacokinetics of the interstitial space in humans

BACKGROUND: The pharmacokinetics of extracellular solutes is determined by the blood-tissue exchange kinetics and the volume of distribution in the interstitial space in the different organs. This information can be used to develop a general physiologically based pharmacokinetic (PBPK) model applicable to most extracellular solutes. METHODS: The human pharmacokinetic literature was surveyed to tabulate the steady state and equilibrium volume of distribution of the solutes mannitol, EDTA, morphine-6-glucuronide, morphine-3-glucuronide, inulin and β-lactam antibiotics with a range of protein binding (amoxicillin, piperacillin, cefatrizine, ceforanide, flucloxacillin, dicloxacillin). A PBPK data set was developed for extracellular solutes based on the literature for interstitial organ volumes. The program PKQuest was used to generate the PBPK model predictions. The pharmacokinetics of the protein (albumin) bound β-lactam antibiotics were characterized by two parameters: 1) the free fraction of the solute in plasma; 2) the interstitial albumin concentration. A new approach to estimating the capillary permeability is described, based on the pharmacokinetics of the highly protein bound antibiotics. RESULTS: About 42% of the total body water is extracellular. There is a large variation in the organ distribution of this water – varying from about 13% of total tissue water for skeletal muscle, up to 70% for skin and connective tissue. The weakly bound antibiotics have flow limited capillary-tissue exchange kinetics. The highly protein bound antibiotics have a significant capillary permeability limitation. The experimental pharmacokinetics of the 11 solutes is well described using the new PBPK data set and PKQuest. CONCLUSIONS: Only one adjustable parameter (systemic clearance) is required to completely characterize the PBPK for these extracellular solutes. Knowledge of just this systemic clearance allows one to predict the complete time course of the absolute drug concentrations in the major organs. PKQuest is freely available

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases