Prediction of absolute bioavailability for drugs using oral and renal clearance following a single oral dose: a critical view

Estimation of absolute oral bioavailability without performing an intravenous clinical study

The absolute oral bioavailability (BA) of drugs are yet to be determined, and intravenous pharmacokinetic studies are currently considered indispensable for determining the BA values of oral drugs. The aim of this study was to develop and validate a novel approach to estimating BA values without intravenous pharmacokinetic data. Based on the drug inclusion criteria, such as exhibiting a urinary recovery rate of (R_u) of ≥20% in a clinical study, 13 drugs were included in the present study, and pharmacokinetic data for them were collected from the literature. The fraction excreted unchanged into urine (f_e) was calculated for healthy subjects by dividing the R_u value by the total recovery rate. The contribution of renal excretion to total clearance from the systemic circulation (R_ren) was estimated by subjecting oral clearance and creatinine clearance to regression in subjects with normal and impaired renal function. BA was estimated as f_e/R_ren and compared with the observed BA (BA_obs). The predicted BA values for 9 drugs fell within ±20% of their BA_obs. The examined approach makes it possible to estimate BA values for drugs with mean renal excretion values in healthy subjects and oral clearance in subjects with various renal function, without intravenous pharmacokinetic data.

Massive Atenolol, Lisinopril, and Chlorthalidone Overdose Treated with Endoscopic Decontamination, Hemodialysis, Impella Percutaneous Left Ventricular Assist Device, and ECMO

BACKGROUND

Overdose of cardiovascular medications is increasingly associated with morbidity and mortality. We present a case of substantial atenolol, chlorthalidone, and lisinopril overdose treated by multiple modalities with an excellent outcome.

CONCLUSION

Aggressive medical intervention did not provide sufficient hemodynamic stability in this patient with refractory cardiogenic and distributive shock. Impella® percutaneous left ventricular assist device and extracorporeal membrane oxygenation provided support while the effects of the overdose subsided. We present concentrations demonstrating removal of atenolol with continuous venovenous hemodiafiltration. This is the first report of esophagogastroduo denoscopy decontamination of this overdose with a large pill fragment burden.

A prediction model for oral bioavailability of drugs using physicochemical properties by support vector machine

OBJECTIVE

A computational model for predicting oral bioavailability is very important both in the early stage of drug discovery to select the promising compounds for further optimizations and in later stage to identify candidates for clinical trials. In present study, we propose a support vector machine (SVM)-based kernel learning approach carried out at a set of 511 chemically diverse compounds with known oral bioavailability values.

MATERIAL AND METHODS

For each drug, 12 descriptors were calculated. The selection of optimal hyper-plane parameters was performed with 384 training set data and the prediction efficiency of proposed classifier was tested on 127 test set data.

RESULTS

The overall prediction efficiency for the test set came out to be 96.85%. Youden's index and Matthew correlation index were found to be 0.929 and 0.909, respectively. The area under receiver operating curve (ROC) was found to be 0.943 with standard error 0.0253.

CONCLUSION

The prediction model suggests that while considering chemoinformatics approaches into account, SVM-based prediction of oral bioavailability can be a significantly important tool for drug development and discovery at a preliminary level.

Prediction of human pharmacokinetics—evaluation of methods for prediction of hepatic metabolic clearance

Methods for prediction of hepatic clearance (CLH) in man have been evaluated. A physiologically-based in-vitro to in-vivo (PB-IVIV) method with human unbound fraction in blood (fu,bl) and hepatocyte intrinsic clearance (CLint)-data has a good rationale and appears to give the best predictions (maximum ∼2-fold errors; < 25% errors for half of CL-predictions; appropriate ranking). Inclusion of an empirical scaling factor is, however, needed, and reasons include the use of cryopreserved hepatocytes with low activity, and inappropriate CLint- and fu,bl-estimation methods. Thus, an improvement of this methodology is possible and required. Neglect of fu,bl or incorporation of incubation binding does not seem appropriate. When microsome CLint-data are used with this approach, the CLH is underpredicted by 5- to 9-fold on average, and a 106-fold underprediction (attrition potential) has been observed. The poor performance could probably be related to permeation, binding and low metabolic activity. Inclusion of scaling factors and neglect of fu,bl for basic and neutral compounds improve microsome predictions. The performance is, however, still not satisfactory. Allometry incorrectly assumes that the determinants for CLH relate to body weight and overpredicts human liver blood flow rate. Consequently, allometric methods have poor predictability. Simple allometry has an average overprediction potential, > 2-fold errors for ∼1/3 of predictions, and 140-fold underprediction to 5800-fold overprediction (potential safety risk) range. In-silico methodologies are available, but these need further development. Acceptable prediction errors for compounds with low and high CLH should be ∼50 and ∼10%, respectively. In conclusion, it is recommended that PB-IVIV with human hepatocyte CLint and fu,bl is applied and improved, limits for acceptable errors are decreased, and that animal CLH-studies and allometry are avoided.

Prediction of human pharmacokinetics — renal metabolic and excretion clearance

The kidneys have the capability to both excrete and metabolise drugs. An understanding of mechanisms that determine these processes is required for the prediction of pharmacokinetics, exposures, doses and interactions of candidate drugs. This is particularly important for compounds predicted to have low or negligible non-renal clearance (CL). Clinically significant interactions in drug transport occur mostly in the kidneys. The main objective was to evaluate methods for prediction of excretion and metabolic renal CL (CLR) in humans. CLR is difficult to predict because of the involvement of bi-directional passive and active tubular transport, differences in uptake capacity, pH and residence time on luminal and blood sides of tubular cells, and limited knowledge about regional tubular residence time, permeability (Pe) and metabolic capacity. Allometry provides poor predictions of excretion CLR because of species differences in unbound fraction, urine pH and active transport. The correlation between fraction excreted unchanged in urine (fe) in humans and animals is also poor, except for compounds with high passive Pe (extensive/complete tubular reabsorption; zero/negligible fe) and/or high non-renal CL. Physiologically based in-vitro/in-vivo methods could potentially be useful for predicting CLR. Filtration could easily be predicted. Prediction of tubular secretion CL requires an in-vitro transport model and establishment of an in-vitro/in-vivo relationship, and does not appear to have been attempted. The relationship between passive Pe and tubular fraction reabsorbed (freabs) for compounds with and without apparent secretion has recently been established and useful equations and limits for prediction were developed. The suggestion that reabsorption has a lipophilicity cut-off does not seem to hold. Instead, compounds with passive Pe that is less than or equal to that of atenolol are expected to have negligible passive freabs. Compounds with passive Pe that is equal to or higher than that of carbamazepine are expected to have complete freabs. For compounds with intermediate Pe the relationship is irregular and freabs is difficult to predict. Tubular cells are comparably impermeable (for passive diffusion), and show regional differences in enzymatic and transporter activities. This limits the usefulness of microsome data and makes microsome-based predictions of metabolic CLR questionable. Renal concentrations and activities of CYP450s are comparably low, suggesting that CYP450 substrates have negligible metabolic CLR. The metabolic CLR of high-Pe UDP-glucuronyltransferase substrates could contribute to the total CL.

Evaluation of a novel method to estimate absolute bioavailability of drugs from oral data

The goal of this investigation was to evaluate the performance of a novel method allowing estimation of absolute bioavailability from oral data only. In contrast to the traditional method, which compares areas under the drug concentration time curves after oral and intravenous administration in subjects with normal renal function, the novel method uses total and renal clearance values following oral administration from subjects with varying renal functions to estimate bioavailability. The novel method can also provide estimates for nonrenal clearance.Published data on total clearance and renal clearance of drugs obtained from subjects with variable renal functions were collected, the novel method applied, estimates of bioavailability and nonrenal clearance obtained and compared with reported estimates by the traditional methods. In addition computations were performed to assess various factors that could possibly affect the reliability of the novel method. The results indicated that the novel method provides accurate estimates for bioavailability of drugs meeting the prerequisites: linear kinetics, predominant renal excretion in normals, absence of metabolic polymorphism and independence of bioavailability and nonrenal clearance from renal function. The average (standard deviation) of the prediction error and bias of the bioavailability estimates by the novel method was 7.8 (6.0) and -1.4 (9.8)%, respectively. The estimates for nonrenal clearance by the novel method were less accurate. The computations confirmed that the estimates by the novel method are sensitive to renal-function dependent changes in nonrenal clearance and bioavailability and also depend on the extent of renal excretion of a drug. In conclusion, the novel method's main use is to diagnose absence or presence of changes in bioavailability and non-renal clearance of drugs in populations with varying renal function.