Biomedical subjects

Raymond Miller

Publications and source records attributed to Raymond Miller.

6 recordsLinked to original sources

PubMed2006

Population pharmacokinetics of artesunate and dihydroartemisinin following intra-rectal dosing of artesunate in malaria patients.

BACKGROUND: Intra-rectal artesunate has been developed as a potentially life-saving treatment of severe malaria in rural village settings where administration of parenteral antimalarial drugs is not possible. We studied the population pharmacokinetics of intra-rectal artesunate and the relationship with parasitological responses in patients with moderately severe falciparum malaria. METHODS AND FINDINGS: Adults and children in Africa and Southeast Asia with moderately severe malaria were recruited in two Phase II studies (12 adults from Southeast Asia and 11 children from Africa) with intensive sampling protocols, and three Phase III studies (44 children from Southeast Asia, and 86 children and 26 adults from Africa) with sparse sampling. All patients received 10 mg/kg artesunate as a single intra-rectal dose of suppositories. Venous blood samples were taken during a period of 24 h following dosing. Plasma artesunate and dihydroartemisinin (DHA, the main biologically active metabolite) concentrations were measured by high-performance liquid chromatography with electrochemical detection. The pharmacokinetic properties of DHA were determined using nonlinear mixed-effects modelling. Artesunate is rapidly hydrolysed in vivo to DHA, and this contributes the majority of antimalarial activity. For DHA, a one-compartment model assuming complete conversion from artesunate and first-order appearance and elimination kinetics gave the best fit to the data. The mean population estimate of apparent clearance (CL/F) was 2.64 (l/kg/h) with 66% inter-individual variability. The apparent volume of distribution (V/F) was 2.75 (l/kg) with 96% inter-individual variability. The estimated DHA population mean elimination half-life was 43 min. Gender was associated with increased mean CL/F by 1.14 (95% CI: 0.36-1.92) (l/kg/h) for a male compared with a female, and weight was positively associated with V/F. Larger V/Fs were observed for the patients requiring early rescue treatment compared with the remainder, independent of any confounders. No associations between the parasitological responses and the posterior individual estimates of V/F, CL/F, and AUC0-6h were observed. CONCLUSIONS: The pharmacokinetic properties of DHA were affected only by gender and body weight. Patients with the lowest area under the DHA concentration curve did not have slower parasite clearance, suggesting that rectal artesunate is well absorbed in most patients with moderately severe malaria. However, a number of modelling assumptions were required due to the large intra- and inter-individual variability of the DHA concentrations.

Administration, Rectal↗

PubMed2005

How modeling and simulation have enhanced decision making in new drug development.

The idea of model-based drug development championed by Lewis Sheiner, in which pharmacostatistical models of drug efficacy and safety are developed from preclinical and available clinical data, offers a quantitative approach to improving drug development and development decision-making. Examples are presented that support this paradigm. The first example describes a preclinical model of behavioral activity to predict potency and time-course of response in humans and assess the potential for differentiation between compounds. This example illustrates how modeling procedures expounded by Lewis Sheiner provided the means to differentiate potency and the lag time between drug exposure and response and allow for rapid decision making and dose selection. The second example involves planning a Phase 2a dose-ranging and proof of concept trial in Alzheimer's disease (AD). The issue was how to proceed with the study and what criteria to use for a go/no go decision. The combined knowledge of AD disease progression, and preclinical and clinical information about the drug were used to simulate various clinical trial scenarios to identify an efficient and effective Phase 2 study. A design was selected and carried out resulting in a number of important learning experiences as well as extensive financial savings. The motivation for this case in point was the "Learn-Confirm" paradigm described by Lewis Sheiner. The final example describes the use of Pharmacokinetic and Pharmacodynamic (PK/PD) modeling and simulation to confirm efficacy across doses. In the New Drug Application for gabapentin, data from two adequate and well-controlled clinical trials was submitted to the Food and Drug Administration (FDA) in support of the approval of the indication for the treatment of post-herpetic neuralgia. The clinical trial data was not replicated for each of the sought dose levels in the drug application presenting a regulatory dilemma. Exposure response analysis submitted in the New Drug Application was applied to confirm the evidence of efficacy across these dose levels. Modeling and simulation analyses showed that the two studies corroborate each other with respect to the pain relief profiles. The use of PK/PD information confirmed evidence of efficacy across the three studied doses, eliminating the need for additional clinical trials and thus supporting the approval of the product. It can be speculated that the work by Lewis Sheiner reflected in the FDA document titled "Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New Medical Products" made this scientific approach to the drug approval process possible.

Alzheimer Disease↗

PubMed2005

Highly specific urine-based marker of bladder cancer.

OBJECTIVES: Bladder cancer represents a major health problem throughout the world, but advances in tumor biomarker development are revolutionizing how physicians diagnose the disease. We previously used an indirect immunoassay to demonstrate that the bladder cancer specific biomarker, BLCA-4, is present in urine samples from patients with bladder cancer, but not in samples from healthy individuals. In this study, a sandwich immunoassay was used to measure BLCA-4 in urine samples from patient populations with various urologic conditions and healthy individuals. METHODS: Urine was collected from healthy individuals and from patients with bladder cancer, benign urologic conditions, or prostate cancer. BLCA-4 levels were evaluated by a sandwich immunoassay using two antibodies directed against distinct epitopes on BLCA-4. RESULTS: Using a prospectively determined cutoff of an absorbance unit (OD) of 0.04, 67 of the 75 samples from patients with bladder cancer were positive for BLCA-4, resulting in an assay sensitivity of 89%. Also, 62 of the 65 samples from individuals without bladder cancer were negative for BLCA-4, resulting in an assay specificity of 95%. CONCLUSIONS: The high sensitivity and specificity of the sandwich BLCA-4 immunoassay may allow for earlier detection and treatment of disease, thus greatly improving patient care.

Adult↗

PubMed2003

Exposure-response analysis of pregabalin add-on treatment of patients with refractory partial seizures.

OBJECTIVE: Our objectives were to describe the exposure-response relationship of pregabalin add-on treatment for refractory partial seizures after multiple dosing in patients and to identify the factors that influence this relationship. METHODS: A mixed-effects model was used to characterize the relationship between monthly seizure frequency over a 3-month period and pregabalin daily dose (0, 50, 150, 300, and 600 mg) as add-on treatment in 3 double-blind, parallel-group studies in patients with refractory partial seizures (N = 1042). Seizure frequency was modeled as a Poisson process expressed as a function of baseline seizures, drug treatment, placebo effect, and subject-specific random effects. The model included a parameter that partitioned the population into subpopulations with respect to response. RESULTS: Seventy-five percent of patients showed an asymptotic decrease in seizure frequency with increasing doses of pregabalin, whereas 25% did not demonstrate a significant decrease in seizure frequency from baseline. In patients who demonstrated a dose-related decrease in seizure frequency from baseline, the maximal percentage of seizure reduction from baseline was 100% for women and 80% for men, with a 186-mg daily dose decreasing seizures on average to 50% of maximum. Age, race, and menopausal status did not significantly affect seizure frequency. CONCLUSION: Pregabalin add-on treatment demonstrates a dose-response relationship in 3 out of 4 patients with refractory partial seizures. A dose of 186 mg pregabalin daily is expected to decrease the seizure rate by 50% of maximum from baseline. Age, race, and menopausal status of women did not affect the dose-response relationship.

Adult↗

PubMed2003

Evaluation of mixture modeling with count data using NONMEM.

Mixture modeling within the context of pharmacokinetic (PK)/pharmacodynamic (PD) mixed effects modeling is a useful tool to explore a population for the presence of two or more subpopulations, not explained by evaluated covariates. At present, statistical tests for the existence of mixed populations have not been developed. Therefore, a simulation study was undertaken to evaluate mixture modeling with NONMEM and explore the following questions. First, what is the probability of concluding that a mixed population exists when there truly is not a mixture (false positive significance level)? Second, what is the probability of concluding that a mixed population (two subpopulations) exists when there is truly a mixed population (power), and how well can the mixture be estimated, both in terms of the population parameters and the individual subjects classification. Seizure count data were simulated using a Poisson distribution such that each subject's count could decrease from its baseline value, as a function of dose via an Emax model. The dosing design for the simulation was based on a trial with the investigational anti-epileptic drug pregabalin. Four hundred and forty seven subjects received pregabalin as add on therapy for partial seizures, each with a baseline seizure count and up to three subsequent seizure counts. For the mixtures, the two subpopulations were simulated to differ in their Emax values and relative proportions. One subpopulation always had its Emax set to unity (Emax hi), allowing the count to approach zero with increasing dose. The other subpopulation was allowed to vary in its Emax value (Emax lo = 0.75, 0.5, 0.25, and 0) and in its relative proportion (pr) of the population (pr = 0.05, 0.10, 0.25, and 0.50) giving a total of 4.4 = 16 different mixtures explored. Three hundred data sets were simulated for each scenario and estimations performed using NONMEM. Metrics used information about the parameter estimates, their standard errors (SE), the difference between minimum objective function (MOF) values for mixture and non-mixture models (MOF (delta)), the proportion of subjects classified correctly, and the estimated conditional probabilities of a subject being simulated as having Emax lo (Emax hi) given that they were estimated as having Emax lo (Emax hi) and being estimated as having Emax lo (Emax hi) given that they were simulated as having Emax lo (Emax hi). The false positive significance level was approximately 0.04 (using all 300 runs) or 0.078 (using only those runs with a successful covariance step), when there was no mixture. When simulating mixed data and for those characterizations with successful estimation and covariance steps, the median (range) percentage of 95% confidence intervals containing the true values for the parameters defining the mixture were 94% (89-96%), 89.5% (58-96%), and 95% (92-97%) for pr, Emax lo, and Emax hi, respectively. The median value of the estimated parameters pr, Emax lo (excluding the case when Emax lo was simulated to equal 0) and Emax hi within a scenario were within +/- 28% of the true values. The median proportion of subjects classified correctly ranged from 0.59 to 0.96. In conclusion, when no mixture was present the false positive probability was less than 0.078 and when mixtures were present they were characterized with varying degrees of success, depending on the nature of the mixture. When the difference between subpopulations was greater (as Emax lo approached zero or pr approached 0.5) the mixtures became easier to characterize.

Computer Simulation↗

PubMed2003

A two-part mixture model for longitudinal adverse event severity data.

We fit a mixed effects logistic regression model to longitudinal adverse event (AE) severity data (four-point ordered categorical response) to describe the dose-AE severity response for an investigational drug. The distribution of the predicted interindividual random effects (Bayes predictions) was extremely bimodal. This extreme bimodality indicated that biased parameter estimates and poor predictive performance were likely. The distribution's primary mode was composed of patients that did not experience an AE. Moreover, the Bayes predictions of these non-AE patients were nearly degenerative, i.e., the predictions were nearly identical. To resolve this extreme bimodality we propose using a two-part mixture modeling approach. The first part models the incidence of AE's, and the second part models the severity grade given the patient had an AE. Unconditional probability predictions are calculated by mixing the incidence and severity model probability predictions. We also report results of simulation studies, which assess the predictive and statistical (bias and precision) performance of our approach.

Bayes Theorem↗