Biomedical subjects

Jogarao V S Gobburu

Publications and source records attributed to Jogarao V S Gobburu.

10 recordsLinked to original sources

PubMed2007

The role of SN-38 exposure, UGT1A1*28 polymorphism, and baseline bilirubin level in predicting severe irinotecan toxicity.

Irinotecan, an anticancer drug, is associated with severe and potentially fatal diarrhea and neutropenia. The objective of this analysis was to evaluate the role of SN-38 exposure, the active metabolite of irinotecan, UGT1A1 genotypes, and baseline bilirubin on the maximum decrease (nadir) in absolute neutrophil counts following irinotecan. This analysis extended the work of a previous study that examined the effect of UGT1A1 genotypes on the incidence of severe neutropenia in 86 advanced cancer patients following irinotecan treatment. Regression analysis showed that the absolute neutrophil count nadir depended on SN-38 exposure (AUC) and UGT1A1*28 homozygous 7/7 genotype. An increased SN-38 AUC and the 7/7 genotype were significantly associated with a lower absolute neutrophil count nadir (R2 = .49). An alternate model suggested that higher baseline bilirubin and the 7/7 genotype were also significantly associated with a lower absolute neutrophil count nadir, although with a lower coefficient of determination (R2 = .31). Based on these findings and other reports, the irinotecan label was modified to indicate the role of UGT1A1*28 polymorphism in the metabolism of irinotecan and the associated increased risk of severe neutropenia. The label modifications also included recommendations for lower starting doses of irinotecan in patients homozygous for the UGT1A1*28 (7/7) polymorphism.

Antineoplastic Agents, Phytogenic↗

PubMed2007

Population pharmacokinetic-based dosing of intravenous busulfan in pediatric patients.

The objective of this study was to characterize the pharmacokinetics (PK) of intravenous busulfan in pediatric patients and provide dosing recommendations. Twenty-four pediatric patients were treated with intravenous busulfan, 1.0 or 0.8 mg/kg for ages < or = 4 years or > 4 years, respectively, 4 times a day for 4 days. Dense PK sampling was performed. Body weight, age, gender, and body surface area were explored for effects on PK, and Monte Carlo simulations were performed to assess different dosing regimens. The PK of intravenous busulfan was described by a 1-compartment model with clearance of 4.04 L/h/20 kg and volume of distribution of 12.8 L/20 kg. Simulations indicated that the mg/kg and mg/m2 regimens were similar and achieved the desired target exposure in approximately 60% of patients. This model suggests that patients < or = 12 kg should be dosed at 1.1 mg/kg and those > 12 kg dosed at 0.8 mg/kg. Therapeutic drug monitoring and dose adjustment will further improve therapeutic targeting.

Age Factors↗

PubMed2006

Semi-mechanistic pharmacodynamic modeling for degarelix, a novel gonadotropin releasing hormone (GnRH) blocker.

An integrated semi-mechanistic pharmacodynamic (PD) model describing the relationship between luteinizing hormone (LH) and testosterone (T) after short-term administration of degarelix was developed. Data from three clinical studies involving, intravenous (IV) and subcutaneous (SC) dosing, in healthy male subjects were available. Degarelix pharmacokinetic (PK) data from all studies were modeled simultaneously. One intravenous study was used to develop the PD model and the two other studies (IV and SC dosing) were used to qualify the model. Degarelix PK follows a two-compartment model and exhibits flip-flop kinetics after subcutaneous dosing. Based on physiological mechanism, the gonadotropin releasing hormone (GnRH) time course was described using a pulsatile release model. A precursor-dependent pool model was used to describe the kinetics of LH in the pituitary and plasma compartment. In males, LH regulates T production in leydig cells. Degarelix inhibits the release of LH from the pool compartment to the plasma compartment leading to decreased T production. The plasma half-life of LH (2.6-3.3 hr) and T (2.7 hr) match well with the literature reports. The proposed PD model reasonably described the time course of LH and T including the LH rebound for short-term studies. The model predicted the time course of LH and T for the second IV and SC dosing studies very well. However, the long term simulations from the final model did not match with literature reports. A modification is suggested based on the physiological understanding of the system. The proposed novel modification to precursor models can be of general use for predicting long term responses.

Algorithms↗

PubMed2005

Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications.

The value of quantitative thinking in drug development and regulatory review is increasingly being appreciated. Modeling and simulation of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression is often referred to as the pharmacometrics analyses. The objective of the current report is to assess the role of pharmacometrics at the US Food and Drug Administration (FDA) in making drug approval and labeling decisions. The New Drug Applications (NDAs) submitted between 2000 and 2004 to the Cardio-renal, Oncology, and Neuropharmacology drug products divisions were surveyed. For those NDA reviews that included a pharmacometrics consultation, the clinical pharmacology scientists ranked the impact on the regulatory decision(s). Of about a total of 244 NDAs, 42 included a pharmacometrics component. Review of NDAs involved independent, quantitative evaluation by FDA pharmacometricians, even when such analysis was not conducted by the sponsor. Pharmacometric analyses were pivotal in regulatory decision making in more than half of the 42 NDAs. Of the 14 reviews that were pivotal to approval related decisions, 5 identified the need for additional trials, whereas 6 reduced the burden of conducting additional trials. Collaboration among the FDA clinical pharmacology, medical, and statistical reviewers and effective communication with the sponsors was critical for the impact to occur. The survey and the case studies emphasize the need for early interaction between the FDA and sponsors to plan the development more efficiently by appreciating the regulatory expectations better.

Data Collection↗

PubMed2005

A new equivalence based metric for predictive check to qualify mixed-effects models.

The main objective of any modeling exercise is to provide a rationale for effective decision making during drug development. The aim of the current simulation experiment was to evaluate the properties of predictive check as a covariate model qualification technique and, more importantly, to introduce and evaluate alternative criteria to qualify models.Original concentration-time profiles (yod) were simulated using a 1-compartment model for an intravenous drug administered to 25 men and 25 women. The typical clearance for male subjects (TVCLm) was assumed to be 5-fold higher than that for female subjects (TVCLf). Fifty such trials under the same design were generated randomly. Predictive check was used as the model qualification tool to study predictive performance of true (males not equal females) and false (males = females) models in the context of maximum likelihood estimation. For each yod, 200 replications were generated to study the properties of a discrepancy variable, a statistic that depends on the model, and a test statistic, a statistic that does not depend on the model. Several qualification criteria were evaluated in assessing predictive performance, such as, predictive p-value (Pp), probability of equivalence (peqv), and probability of rejecting the null hypothesis (data = model) using the Kolmogorov-Smirnov test (pks). The Pp value was calculated using sum of squared errors as a discrepancy variable. For both of the models, the Pp values uniformly ranged between 0 and 1. The pattern of Pp values suggests that qualification of the false model is unlikely. For both of the models, the range of peqv is about 0.95 to 1.0 for concentration at 0.5 hours. However, this is not the case for the concentration at 4 hours, which is primarily dependent on the clearance. The false model (0.35 to 0.50) has poor predictive performance compared with the true model (0.65 to 0.80) using peqv. The pks suggests no difference in the distributions of replicated and original concentrations at all of the time points for both of the models. Discrepancy variables cannot aid in rejecting false models, whereas the use of a test statistic can aid in rejecting false models. However, selection of an informative test statistic is challenging. As far as the qualification criteria are considered, the equivalence-based comparison of a test statistic is more informative than a significance-based comparison. No convincing evidence exists in the literature demonstrating the added advantages of predictive check as a routine model qualification tool over the existing tools, such as diagnostic plots or mechanistic reasoning. However, when a model is to be used for designing a trial, it should at least be able to regenerate the data used to build the model. In such cases, predictive check might offer insights into potential inconsistencies.

Humans↗

PubMed2005

Pemetrexed in malignant pleural mesothelioma.

PURPOSE: This report describes the data and analysis leading to the approval of pemetrexed (LY 231514, MTA, Alimta, Eli Lilly and Co., Indianapolis, IN) by the U.S. Food and Drug Administration (FDA) of a New Drug Application for the treatment of malignant pleural mesothelioma (MPM). EXPERIMENTAL DESIGN: The FDA review of the efficacy and safety of pemetrexed assessed in a randomized clinical trial of 448 patients with unresectable MPM comparing pemetrexed plus cisplatin with cisplatin alone, as well as preclinical pharmacology and chemistry data, are described. The basis for marketing approval is discussed. RESULTS: In one randomized, single-blind, multicenter international trial, 226 patients were randomized to the pemetrexed and cisplatin arm and 222 patients were randomized to cisplatin alone. Median survival times were 12.1 months for pemetrexed and cisplatin and 9.3 months for cisplatin (P = 0.021; hazard ratio, 0.766; 95% confidence interval, 0.61-0.96). Myelosuppression, predominantly neutropenia, was the most common toxicity of pemetrexed plus cisplatin. Other common adverse events were fatigue, leucopenia, nausea, dyspnea, vomiting, chest pain, anemia, thrombocytopenia, and anorexia. CONCLUSIONS: Pemetrexed in combination with cisplatin was approved by the FDA on February 4, 2004 for the treatment of patients with MPM whose disease is either unresectable or who are otherwise not candidates for curative surgery. The recommended dose of pemetrexed is 500 mg/m(2) intra venous infusion over 10 minutes on day 1 of each 21-day cycle in combination with 75 mg/m(2) cisplatin infused over 2 hours beginning 30 minutes after the pemetrexed infusion. Patients must receive oral folic acid and vitamin B(12) injections before the start and during therapy to reduce severe toxicities. Patients should also receive corticosteroids with the chemotherapy to decrease the incidence of skin rash. Approval was based on a demonstration of survival improvement in a single randomized trial. Response rates and time to tumor progression were not included in product labeling because of inconsistencies in assessments among the investigators, independent radiologic reviewers, and the FDA, reflecting the difficulty of radiographic assessments in malignant mesothelioma. Complete prescribing information is available on the FDA Web site at http://www.fda.gov/cder/approval/index.htm.

Adult↗

PubMed2005

Population pharmacokinetic-pharmacodynamic modeling of subcutaneous and pulmonary insulin in rats.

PURPOSE: To develop a population pharmacokinetic-pharmacodynamic (PKPD) model for insulin in rats. METHODS: Rats were administered insulin either subcutaneously (s.c) (0.26,1.3,2.6 U/kg) or by pulmonary route (spray-instillation (s.i)) (0.26,1.3,2.6,13,26 U/kg). Insulin (0.26,1.3,2.6 U/kg) combined with different combinations of hydroxy methyl amino propionic acid (HMAP: 5,10,16,25 mg/kg) was also administered by spray-instillation. Plasma insulin and glucose concentrations at pre-determined time points were measured. Population pharmacokinetic-pharmacodynamic modeling was performed using NONMEM. RESULTS: Insulin exhibited dose-disproportional PK across formulations and routes of administration. The kinetic model suggested monoexponential disposition with simultaneous first order (64%-dimeric form of insulin) - zero order (36%-hexameric form of insulin) absorption. Maximum relative bioavailability (relative to s.c - 0.26 U/kg) of spray-instilled insulin was 46%. Addition of HMAP increased the relative bioavailability of insulin administered via spray-instilled route by 40%. The insulin-glucose relationship was characterized using an indirect response model, wherein, insulin stimulation of glucose uptake into muscle cells was assumed. The basal zero order production rate of glucose (k(G, prod)) was estimated as 0.98 mg/dl/min. The SC50 was fixed at 80 mu U/ml based on literature reports and the S(max) was estimated to be 6. CONCLUSIONS: The proposed PKPD model satisfactorily describes insulin disposition and glucose concentrations across range of doses with and without HMAP.

Adjuvants, Pharmaceutic↗

PubMed2003

Considerations in analyzing single-trough concentrations using mixed-effects modeling.

The purpose of this study was to assess the effect of trial design and data analysis choices on the bias and precision of pharmacokinetic (PK) parameter estimation. NONMEM was used to simulate and analyze plasma concentrations collected according to a dense (five samples) or sparse (single-trough samples) sampling scheme for a one-compartment open model with intravenous administration. The results indicated that the bias on estimates of CL with only single-trough data was 17% compared to less than 1% for only dense data. The estimates of CL were improved by fixing all other parameters and estimating only mean and variance of CL (-11% to 1.4%, depending on the estimation method). Adding dense data led to further improvements (-2.3% to 0.3%, depending on further improvements). In these cases, first-order conditional estimation (FOCE) methods resulted in better estimates of CL than first-order (FO) methods. These steps also improved the Bayesian estimates of CL. These studies support the following recommendations: (1) avoid collecting single-trough concentrations unless there is reasonable knowledge about the PK of the drug; (2) if collecting single-trough concentrations is inevitable, avoid estimating all parameters when modeling single-trough concentration data; (3) use prior information by modeling the single-trough concentration data along with dense data from other studies; and (4) use Bayes estimates if the PK model and its parameters are known with reasonable certainty.

Bayes Theorem↗

PubMed2003

Approval summary for zoledronic acid for treatment of multiple myeloma and cancer bone metastases.

PURPOSE: This article summarizes data submitted to the United States Food and Drug Administration for marketing approval of zoledronic acid (Zol; Novartis Pharmaceuticals, East Hanover, NJ), a bisphosphonate drug for treating patients with bone metastases. EXPERIMENTAL DESIGN: We review the chemistry, toxicology, pharmacology, and clinical study results submitted to support the supplemental New Drug Application for Zol for treatment of patients with bone metastases. Four- and 8-mg Zol doses were selected for Phase III trials based on bone resorption markers and clinical efficacy parameters. Patients with bone metastases were randomized in three Phase III studies (prostate cancer, solid tumors, and multiple myeloma or breast cancer) to receive 4 or 8 mg of Zol or to a control arm. The control was a placebo in the prostate cancer study and the other solid tumor study and was 90 mg of pamidronate (Pam) in the study of breast cancer and multiple myeloma. Studies were amended twice because of renal toxicity, initially to increase Zol infusion time from 5 to 15 min and later to decrease the dose in the Zol 8-mg arm to 4 mg. The efficacy end point was skeletal-related events (SREs), a composite end point consisting of pathologic fracture, radiation therapy to bone, changes in antineoplastic therapy for bone pain (prostate cancer only), surgery to bone, or spinal cord compression. This end point was analyzed either as the proportion of patients with SRE or time to first SRE. The breast cancer and myeloma study used a noninferiority statistical analysis methods to determine efficacy. RESULTS: In prostate cancer, both the proportions analysis and time-to-SRE analysis showed significantly less bone morbidity on Zol (4 mg) than placebo, but no significant difference between Zol (8 mg) and placebo in either analysis. In the solid tumor study, the time to SRE analysis but not the proportions analysis showed significantly less skeletal morbidity on Zol (4 mg) than placebo, and Zol (8 mg) was significantly better than placebo in both analyses. The breast cancer and myeloma study demonstrated noninferiority of Zol compared with Pam, with Zol retaining at least 49.3% of the Pam treatment effect previously demonstrated in placebo-controlled trials. Zol was approved on February 22, 2002, by the United States Food and Drug Administration for the "treatment of patients with multiple myeloma and documented bone metastases from solid tumors, in conjunction with standard antineoplastic therapy. Prostate cancer should have progressed after treatment with at least one hormonal therapy." The recommended dose and schedule is 4 mg of Zol infused over 15 min every 3-4 weeks. Increased Zol doses and shorter infusions are not recommended because of potential renal toxicity.

Antineoplastic Agents↗

PubMed2002

Application of resampling techniques to estimate exact significance levels for covariate selection during nonlinear mixed effects model building: some inferences.

PURPOSE: One of the main objectives of the nonlinear mixed effects modeling is to provide rational individualized dosing strategies by explaining the interindividual variability using intrinsic and/or extrinsic factors (covariates). The aim of the current study was to evaluate, using computer simulations and real data, methods for estimating the exact significance level for including or excluding a covariate during model building. METHODS: Original data were simulated using a simple one-compartment pharmacokinetic model with (full model) or without (null model) covariates (one or two). The covariate values in the original data were resampled (using either permutations or parametric bootstrap methods) to generate data under the null hypothesis that there is no covariate effect. The original and permuted data were fitted to null and full models, using first-order and first-order condition estimation (with or without interaction) methods in NONMEM, to compare the asymptotic and conditional p-value. Target log-likelihood ratio cutoffs for assessing covariate effects were derived. RESULTS: The simulations showed that for sparse as well as dense data, the first-order condition estimation methods yielded the best results while the first-order method performs somewhat better for sparse data. Depending on the modeling objective, the appropriate asymptotic p-value can be substituted for the conditional significance level. Target log-likelihood ratio cutoffs should be determined separately for each covariate when exact p-values are important. CONCLUSIONS: Resampling methods can be employed to estimate the exact significance level for including a covariate during nonlinear mixed effects model building. Some reasonable inferences can be drawn for potential application to design future population analyses.

Adolescent↗