A randomised double-blind placebo-controlled phase II study of AGI004 for control of chemotherapy-induced diarrhoea.

BACKGROUND: AGI004 is a controlled-release transdermal patch preparation of mecamylamine. We conducted a randomised placebo-controlled phase II study of two dose levels of AGI004 in chemotherapy-induced diarrhoea (CID). METHODS: Adult patients receiving chemotherapy who had experienced diarrhoea (NCI grade 1-2) during previous cycles of chemotherapy were eligible. In all, 64 patients were randomised to receive AGI004 4 mg then 8 mg per 24 h transdermal patch or placebo for two sequential cycles of chemotherapy. Patients' severity of diarrhoea was physician-assessed using NCI grade of diarrhoea and patient-assessed using information recorded in daily diaries of bowel movements. RESULTS: Overall AGI004 doubled the odds of a response to treatment on the first day of chemotherapy based on physician assessment of NCI grade of diarrhoea compared with placebo (odds ratio=2.0, 90% confidence interval: 0.9-4.5) and there was a trend to improved response rates for AGI004 for the full treatment cycle although these results were not statistically significant. There was also evidence of significantly improved response rates based on patient assessment of diarrhoea both overall (P=0.05) and at the 8-mg dose level (P=0.02) compared with placebo. CONCLUSION: AGI004 demonstrated effectiveness in reducing chemotherapy-associated diarrhoea, with results suggesting response across multiple measurements of diarrhoea. Treatment was well tolerated with no drug-related adverse events. Further evaluation of this agent in the management of CID is warranted.

Pharmacokinetics of an immediate-release oral formulation of Fampridine (4-aminopyridine) in normal subjects and patients with spinal cord injury.

Plasma concentration profiles of the K+ channel-blocking compound Fampridine were obtained from (1) control subjects (n = 6) following oral administration of doses of 10, 15, 20, and 25 mg and (2) patients with spinal cord injury (SCI) (n = 11) following a single oral dose of 10 mg of an immediate-release formulation. Plasma concentrations were determined using a reversed-phase ion-pair high-performance liquid chromatography (HPLC) assay with ultraviolet light detection employing liquid extraction. The drug was rapidly absorbed with a tmax approximately 1 hour for both groups; tmax was independent of dose. Cmax and AUC0-infinity were linearly related to dose, and t 1/2 was 3 to 4 hours for both groups. There were no obvious differences in the (10-mg) plasma concentration profiles between control subjects and SCI patients. The drug was well tolerated, with only mild and transient side effects of light-headedness, dysesthesias, and dizziness.

In vivo-in vitro correlation (IVIVC) modeling incorporating a convolution step.

The purpose of in vivo-in vitro correlation (IVIVC) modeling is described. These models are usually fitted to deconvoluted data rather than the raw plasma drug concentration/time data. Such a two-stage analysis is undesirable because the deconvolution step is unstable and because the fitted model predicts the fraction of a dosage unit dissolved/absorbed in vivo which generally is not the primary focus of our attention. Interest usually centers on the plasma drug concentration or some function of it (e.g., AUC, Cmax). Incorporation of a convolution step into the model overcomes these difficulties. Odds, hazards, and reversed hazards models which include a convolution step are described. The identity model (which states that average in vivo and in vitro dissolution/time curves are coincident or directly superimposable) is a special case of these models. The odds model and the identity model were fitted to data sets for two different products using nonlinear mixed effects model fitting software. Results show that the odds model describes both data sets reasonably well and is a significantly better fit than the identity model in each case.

A steady-state evaluation of the bioavailability of chronotherapeutic oral drug absorption system verapamil PM after nighttime dosing versus immediate-acting verapamil dosed every eight hours.

To compare the steady state pharmacokinetics of the 200 mg verapamil PM CODAS (chronotherapeutic oral drug absorption system) formulation dosed nightly versus immediate-acting verapamil 80 mg tablets dosed three times daily, an open-label, single-dose, two-treatment, two-period, two-sequence, balanced, randomized crossover study was performed with a 7-day washout between two treatment periods. Twenty-four healthy male subjects completed the study. All subjects received CODAS verapamil PM 200 mg under fasting conditions dosed at nighttime or verapamil 80 mg dosed three times daily at 8-hour intervals in a randomized fashion. CODAS verapamil PM 200 mg dosed at night for 5 days results in a plasma profile with a lag time of approximately 4 hours suitable for nighttime dosing. Significantly lower plasma concentrations of both enantiomers of verapamil and norverapamil resulted in lower peak-to-trough fluctuations and should ensure the safety of the product. Both medications tested in this study were well tolerated by the group of healthy volunteers.

A new approach to modelling the relationship between in vitro and in vivo drug dissolution/absorption.

A major goal of the pharmaceutical scientist is finding a relationship between an in vitro characteristic of an oral dosage form and its in vivo performance. One such relationship between drug dissolution (or absorption) in vivo and that in vitro is known as an 'in vitro-in vivo correlation' (IVIVC) whose importance stems from the fact that it may be used to minimize the number of human studies required during product development, assist in setting meaningful in vitro dissolution specifications and justify biowaivers for scale-up and post approval changes. A number of ways of describing an IVIVC have been reported with 'level A' being the most informative and therefore most desirable. In the majority of cases reported to date, both the model and the statistical methods employed for level A IVIVC are very simplistic. The model assumes that the rate and extent of dissolution in vivo are the same as those in vitro. The statistical methods ignore the repeated measures nature of the data and use a response variable as an independent variable without accounting for measurement error. This paper describes some new models which include the simple model as a special case. The modelling approach is based on considering the time at which a drug molecule enters solution (in vitro or in vivo) to be a random variable. The in vitro and in vivo distributions are then related to one another using a proportional odds, proportional hazards or proportional reversed hazards model. The models can be extended by adding a linear time component which describes a time varying relationship. Following the addition of random effects to these structural models in order to account for the repeated measures nature of the data collected, the models may be described as generalized linear mixed effects models. The models were fitted to some data sets using a maximum likelihood based method and the results indicate that these models have potential for describing an in vitro-in vivo relationship which cannot be described using the currently available models.

Assessment of risk reduction strategies for the management of agricultural nonpoint source pesticide runoff in estuarine ecosystems.

Agricultural nonpoint source (NPS) runoff may result in significant discharges of pesticides, suspended sediments, and fertilizers into estuarine habitats adjacent to agricultural areas or downstream from agricultural watersheds. Exposure of estuarine fin fish and shellfish to toxic levels of pesticides may occur, resulting in significant declines in field populations. Integrated pest management (IPM), best management practices (BMP), and retention ponds (RP) are risk management tools that have been proposed to reduce the contaminant risk from agricultural NPS runoff into estuarine ecosystems. Field studies were conducted at three sites within coastal estuarine ecosystems of South Carolina (SC) from 1985 to 1990 that varied in terms of the amount and degree of risk reduction strategies employed. An intensively managed (IPM, BMP, and RP) agricultural treatment site (TRT) was studied for pesticide runoff impacts. From 1985 to 1987, there were minimal (some IPM and BMP) management activities at TRT, but from 1988 to 1990, TRT was managed using an intensive risk reduction strategy. A second unmanaged agricultural growing area, Kiawah (KWA), was also studied and compared with TRT in terms of pesticide runoff and the resulting impacts on grass shrimp (Palaemonetes pugio) and mummichogs (Fundulus heteroclitus). A third, non-agricultural, reference site (CTL) was used for comparing results from the managed and unmanaged agricultural sites. In situ toxicity tests and field samples of the grass shrimp populations were conducted at each site and compared in terms of survival and the effectiveness of current risk reduction strategies. Significant runoff of insecticides (azinphosmethyl, endosulfan, and fenvalerate) along with several fish kills were observed at TRT prior to the implementation of rigorous risk reduction methods. A significant reduction of in stream pesticide concentrations (up to 90%) was observed at TRT following the implementation of strict NPS runoff controls, which greatly reduced impacts on estuarine fish and shellfish. At the unmanaged KWA, continued impacts due to the runoff of these insecticides were observed, along with several fish kills. Additional monitoring indicated that gravid female grass shrimp populations from KWA had elevated levels of P-glycoprotein (P-gp), a multidrug resistance protein, which may transport various pesticides across cellular membranes. Comparison of field results with laboratory toxicity tests established that pesticide exposure was the primary cause of observed field impacts at each site. These findings clearly indicate the value of an integrated risk reduction strategy (BMP, IPM, and RP) for minimizing impacts from NPS agricultural pesticide runoff.

Artificial neural networks applied to the in vitro-in vivo correlation of an extended-release formulation: initial trials and experience.

Artificial neural networks applied to in vitro-in vivo correlations (ANN-IVIVC) have the potential to be a reliable predictive tool that overcomes some of the difficulties associated with classical regression methods, principally, that of providing an a priori specification of the regression equation structure. A number of unique ANN configurations are presented, that have been evaluated for their ability to determine an IVIVC from different formulations of the same product. Configuration variables included a combination of architectural structures, learning algorithms, and input-output association structures. The initial training set consisted of two formulations and included the dissolution from each of the six cells in the dissolution bath as inputs, with associated outputs consisting of 1512 pharmacokinetic time points from nine patients enrolled in a crossover study. A third formulation IVIVC data set was used for predictive validation. Using these data, a total of 29 ANN configurations were evaluated. The ANN structures included the traditional feed forward, recurrent, jump connections, and general regression neural networks, with input-output association types consisting of the direct mapping of the dissolution profiles to the pharmacokinetic observations, mapping the individual dissolution points to the individual observations, and using a "memorative" input-output association. The ANNs were evaluated on the basis of their predictive performance, which was excellent for some of these ANN models. This work provides a basic foundation for ANN-IVIVC modeling and is the basis for continued modeling with other desirable inputs, such as formulation variables and subject demographics.

Level A in vivo-in vitro correlation: nonlinear models and statistical methodology.

Some new nonlinear models for the relationship between the fraction of drug dose dissolved (absorbed) in vivo and that dissolved in vitro are described. The models are empirical in nature and are generalizations of the linear model that, at present, is the most commonly used model. The modeling approach is based on considering the time at which a drug molecule goes into solution (in vitro or in vivo) to be a random variable and relating the distribution functions using proportional odds, proportional hazards, and proportional reversed hazards models. The models are further extended by allowing the parameter that relates in vivo and in vitro to be a function of time. A statistical model for the data is developed and used as the basis for a statistical methodology for fitting these models. The methods are shown to be generalized linear mixed effects model (GLMM) methods. The models are fitted to some data sets, and the results demonstrate that these models have potential.