Protective action of glycine in cisplatin nephrotoxicity

Protective action of glycine in cisplatin nephrotoxicity. Because glycine is cytoprotective for kidney cells in vitro, we investigated its possible action in vivo to protect rats against cisplatin nephrotoxicity, a well-established experimental model of renal tubular injury. Glycine was infused at a dose of 1mmol per 100g body weight per hour for 75 minutes, starting 15 minutes before cisplatin, 5mg per kg, was injected intravenously. Plasma concentration of glycine rose to 3.5mmol per liter at the time cisplatin was injected. These rats were compared with cisplatin-treated animals treated with L-alanine or with isotonic saline. After five days plasma creatinine of saline-treated rats given cisplatin had risen threefold to 2.6 ± 1.5mg per 100ml (mean ± SD), as creatinine clearance fell to 25% of baseline (0.14 ± 0.05ml/min/100g). Morphological evaluation disclosed extensive damage involving all S3 segments in the outer medulla as well as the medullary rays of the cortex. In contrast, in rats treated with glycine, plasma creatinine rose only to 1.2 ± 0.2mg/100ml and creatinine clearance was maintained at 75% of baseline (0.35 ± 0.05ml/min/100g). Glycine also attenuated the weight loss, polyuria, increased fractional excretion of sodium and potassium, decreased urinary osmolality, and renal glycosuria observed in control, saline-treated rats after cisplatin, while substantially decreasing the percentage of S3 tubules with evident morphological injury. Renal platinum content was unaffected by glycine. The administration of L-alanine or the delayed infusion of glycine, starting one hour after cisplatin was given, did not prevent cisplatin toxicity. Thus, high plasma concentrations of glycine achieved during a brief period of time when cisplatin is administered, markedly attenuate cisplatin nephrotoxicity

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

The relationship of polymorphisms in ABCC2 and SLCO1B3 with docetaxel pharmacokinetics and neutropenia: CALGB 60805 (Alliance)

Docetaxel-related neutropenia was associated with polymorphisms in the drug transporters ABCC2 and SLCO1B3 in Japanese cancer patients. We hypothesized that this association is because of reduced docetaxel clearance, associated with polymorphisms in those genes. We studied 64 US cancer patients who received a single cycle of 75 mg/m2 of docetaxel monotherapy. We found that the ABCC2 polymorphism at rs-12762549 trended to show a relationship with reduced docetaxel clearance (P = 0.048), but not with neutropenia. There was no significant association of the SLCO1B3 polymorphisms with docetaxel clearance or neutropenia. We conclude that the relationship between docetaxel-associated neutropenia and polymorphisms in drug transporters identified in Japanese patients was not confirmed in this cohort of US cancer patients

Drug plasma monitoring in CML and GIST: A case-based discussion

Drug plasma monitoring has emerged as an important tool to obtain optimal levels of a particular drug among individual patients. Plasma monitoring of imatinib levels would appear to be practical in cases where there is lack of response, heightened toxicity, or evidence of poor adherence to therapy. However, the potential role of monitoring plasma drug concentrations in guiding treatment decisions and optimizing patient therapy has yet to be established. Currently, there are no clinical recommendations regarding how to incorporate imatinib drug plasma monitoring in patients with either chronic myeloid leukemia or gastrointestinal stromal tumors, indications for which imatinib is approved. Here, the latest research and evidence regarding imatinib drug plasma monitoring is discussed. Three cases are presented to illustrate the most common examples where monitoring imatinib plasma concentrations may help to guide treatment decisions. These cases include a suboptimal response to imatinib treatment, lack of patient adherence to imatinib, and imatinib-related toxicity. By understanding the potential role of monitoring plasma imatinib concentrations in patients with chronic myeloid leukemia or gastrointestinal stromal tumors, physicians can identify patients who may benefit from drug plasma monitoring and consider incorporating the data in order to improve patient outcomes