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Hemodialysis (HD) removes nitrogenous waste products from patients’ blood through a semipermeable membrane along a concentration gradient. Near-infrared spectroscopy (NIRS) is an underexplored method of monitoring the concentrations of several molecules that reflect the efficacy of the HD process in dialysate samples. In this study, we aimed to evaluate NIRS as a technique for the non-invasive detection of uremic solutes by assessing the correlations between the spectrum of the spent dialysate and the serum levels of urea, creatinine, and uric acid. Blood and dialysate samples were taken from 35 patients on maintenance HD. The absorption spectrum of each dialysate sample was measured three times in the wavelength range of 700-1700 nm, resulting in a dataset with 315 spectra. The artificial neural network (ANN) learning technique was used to assess the correlations between the recorded NIR-absorbance spectra of the spent dialysate and serum levels of selected uremic toxins. Very good correlations between the NIR-absorbance spectra of the spent dialysate fluid with serum urea (R=0.91) and uric acid (R=0.91) and an excellent correlation with serum creatinine (R=0.97) were obtained. These results support the application of NIRS as a non-invasive, safe, accurate, and repetitive technique for online monitoring of uremic toxins to assist clinicians in assessing HD efficiency and individualization of HD treatments.

Antifungal agents are the group of drugs commonly prescribed in the treatment of fungal infections, which are widely spread among the global population. Their properties, such as absorption, distribution, metabolism, route of elimination or plasma protein binding (PPB), considerably influence their therapeutic success, while a number of the molecular physicochemical properties of the drug notably influence all these processes. Lipophilicity (log P), molecular weight (Mw), volume (Vol), polar surface area (PSA) and solubility (log S) play important roles in drug absorption, penetration into tissues, distribution and route of elimination or the degree of plasma protein binding. In this study, the relationships between these five molecular properties of eight antifungal drugs and their plasma protein binding data obtained from relevant literature were investigated. The Selected physicochemical molecular descriptors of the drug were calculated using software packages. The established relationships between PPB and PSA; Mw; Vol and log S were showed relatively poor correlation (r < 0.35). The best correlation was obtained for the relationship between PPB data and the lipophilicity descriptor X log P3 (correlation coefficient r = 0.55). In further investigation, multiple linear regression analysis was applied. The best correlation was obtained with application of lipophilicity with polar surface area (r = 0.918) and volume (r = 0.916) or molecular weight (r = 0.896) as independent variables. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. 172041]

The plasma protein binding (PPB) data of twelve antipsychotics (aripiprazole, clozapine, olanzapine, quetiapine, risperidone, sertindole, ziprasidone, chlorpromazine, flupentixol, fluphenazine, haloperidol, zuclopenthixol) were estimated using computed molecular descriptors, which included the electronic descriptor – polar surface area (PSA), the constitutional parameter – molecular weight (Mw), the geometric descriptor – volume value (Vol), the lipophilicity descriptor (logP) and aqueous solubility data (logS), and the acidity descriptor (pKa). The relationships between computed molecular properties of the selected antipsychotics and their PPB data were investigated by simple linear regression analysis. Low correlations were obtained between the PPB data of the antipsychotics and PSA, Mw, Vol, pKa, logS (R

In this study we investigated the relationship between the calcium channel blockers (CCBs), amlodipine, felodipine, isradipine, nicardipine, nifedipine, nimodipine, nisoldipine, verapamil and diltiazem, and their calculated molecular descriptors: polar surface area (PSA), molecular weight (Mw), volume value (Vol), aqueous solubility data (logS), lipophilicity (logP), acidity (pKa values) and plasma protein binding (PPB) data, obtained from relevant literature. The relationships between the computed molecular properties of selected CCBs and their PPB data were investigated by simple linear regression analysis that revealed very low correlations (R2

In the present study, we investigated the relationships between several molecular properties and bioavailability data for seven of the most commonly prescribed angiotensin II receptor antagonists (also known as angiotensin II receptor blockers (ARBs) or sartans), candesartan, eprosartan, irbesartan, losartan, olmesartan, telmisartan and valsartan. The molecular descriptors of ARBs are:, aqueous solubility (logS values), polar surface area (PSA), molecular weight (Mw), volume value (Vol), lipophilicity (logP values) and the acidity descriptor (pKa1). The respective descriptors were calculated using four different software packages. The relevant bioavailability data were obtained from literature. Among calculated molecular descriptors, simple linear regression analysis showed the best correlation between bioavailability data and the lipophilicity descriptor, logP (R2 = 0.568). Multiple linear regression established good correlations between bioavailability and the lipophilicity descriptor, logP, using the molecular weight, Mw, or the acidity descriptor, pKa1, as an additional, independent variable (with R2 0.661 and 0.682, respectively). Finally, excluding candesartan from the calculations resulted in a very good correlation (R2 = 0.852) between the remaining ARB bioavailability and molecular descriptors MlogP and Mw as independent variables, determined by multiple linear regression. [Projekat Ministarstva nauke Republike Srbije, br. TR34031]

Calcium channel blockers (CCBs) are among the most widely used drugs in cardiovascular medicine. In this study, nine CCBs (amlodipine, felodipine, isradipine, nicardipine, nifedipine, nimodipine, nisoldipine, verapamil and diltiazem) were investigated to assess the relationship between their molecular properties and elimination data obtained from literature. The descriptors of the molecular properties of CCBs were calculated using three software packages. The relationship between computed molecular properties and elimination data collected from relevant literature, initially investigated with simple linear regression analysis, showed poor correlation (R2

Angiotensin II receptor antagonists (ARBs) modulate the function of the renin-angiotensin-aldosterone system and are commonly prescribed antihypertensive drugs, especially in patients with renal failure. In this study, the relationship between several molecular properties of seven ARBs (candesartan, eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan) and their fecal elimination data obtained from the literature were investigated. The ARB molecular descriptors were calculated using three software packages. Simple linear regression analysis showed the best 2 correlation between fecal elimination data and lipophilicity descriptor, ClogP values (R2 = 0.725). Multiple linear regression was applied to examine the correlation of ARBs’ fecal elimination data with their lipophilicity and one additional, calculated descriptor. The best correlation (R2 = 0.909 with an acceptable probability value, P

The aim of this study was to compare different calculation methods to determine lipophilicity, expressed as logP value, of seven ACE inhibitors (enalapril, quinapril, fosinopril, lisinopril, cilazapril, ramipril, and benazapril) with significantly different structure. Experimentally determined n-octanol/water partition coefficients, logPO/W values, were obtained from relevant literature. The correlations between all collected logP values were studied and the best agreements between calculated logP and experimentally determined logPO/W values, were observed for KOWWINlogP or MilogP values (r = 0.999 or r = 0.974, respectively). The correlations between all collected logP values and chromatographically (reversed-phase thin-layer chromatography) obtained hydrophobicity parameters, RM0 and C0, were established. The good correlations (r > 0.90) were obtained in the majority of relationships. The KOWWINlogP was established as the most suitable hydrophobicity parameter of investigated group of ACE inhibitors with r = 0.981 for correlation with RM0 and r = 0.977 for correlation with C0 parameters (water-methanol mobile phase). Using multiple linear regressions, it was established that application of two selected logP, calculated by different mathematical approaches, led to very good correlation due to the benefits of both calculation methods. The good relationships indicate that the computed logP, with careful selection of method calculation, can be useful in ACE inhibitors lipophilicity evaluation, as high-throughput screening technique.

This paper presents the review of the methods used in research of the biological active substances hydrophobicity, a very important property. The biological activity of some substances depends on their pharmacokinetics and pharmacodynamics. These processes depend on the molecule's capability to interact with two different media: aqueous (cells interior) and non-aqueous (cells membrane), or on the molecule lipophilicity. Today, great attention is given to investigation and systematic determination of drugs lipophilicity. In these researches chromatography methods have an important role.