Biomedical subjects

Shein-Chung Chow

Publications and source records attributed to Shein-Chung Chow.

16 recordsLinked to original sources

PubMed2003

In vitro bioequivalence testing.

A statistical test is proposed for in vitro bioequivalence testing between drug products such as nasal aerosols and nasal sprays. The proposed test generalizes the one recommended in the FDA 1999 guidance to the situation where replicated observations obtained from each sampled canister or bottle of the drug product are available. The technique developed by Hyslop, Hsuan and Holder is used so that the proposed test is asymptotically accurate. The type I error probability and power of the proposed test are investigated through a simulation study. A method for determining the required sample size to achieve a desired power is also proposed. A numerical example is given for illustration.

Administration, Intranasal↗

PubMed2003

Examining outlying subjects and outlying records in bioequivalence trials.

The problem of detecting outliers in bioequivalence trials is considered. We formulate the problem as a hypothesis-testing problem under a mean-shift model and propose a test procedure based on the likelihood function. The test statistic has two components: one is to detect whether a specific pharmacokinetic measurement of a subject for certain formulation/drug product is an outlying value; the other is to test whether a subject as a whole is an outlying subject (with unusual high or low bioavailability for all formulations/drug products). Under normality assumption, the proposed procedure is most powerful. The small sample distribution of the proposed test statistic is derived. A numerical example illustrates the use of the procedure. The proposed test is then compared in a simulation study against the Hotelling T2 test, recommended by Liu and Weng (1991) for the use of outlier detection in bioequivalence studies. The results from the simulation study show that the proposed test is more powerful than the Hotelling T2 test.

Biological Availability↗

PubMed2003

Stability analysis with discrete responses.

We consider the estimation of shelf life of a drug product when the stability data are discrete. When there is no batch-to-batch variation, the proposed shelf life estimator is an approximate 95% lower confidence bound of the true shelf life. In the presence of batch-to-batch variation, the proposed shelf life estimator is an approximate 95% lower prediction bound of the shelf life of future batches. As a result, the proposed shelf life is applicable to all future batches of the same drug product. Testing for batch-to-batch variation based on discrete responses is also discussed.

Confidence Intervals↗

PubMed2003

Pharmacokinetics of doxorubicin administered i.v. as Myocet (TLC D-99; liposome-encapsulated doxorubicin citrate) compared with conventional doxorubicin when given in combination with cyclophosphamide in patients with metastatic breast cancer.

Myocet (TLC D-99) is a liposomal formulation of the anti-neoplastic drug doxorubicin with an improved therapeutic index compared with conventional doxorubicin. The objective of this study was to assess the plasma disposition of doxorubicin when administered i.v. as TLC D-99 and to compare this to conventional drug. Metabolite (doxorubicinol) plasma levels were also quantitated in both treatment groups. Plasma was collected during the first course of treatment from 10 patients receiving TLC D-99 60 mg/m and 10 receiving conventional doxorubicin 60 mg/m2, each with cyclophosphamide 600 mg/m2. Samples were assayed for total doxorubicin (all doxorubicin regardless of whether it is encapsulated or not), encapsulated doxorubicin (TLC D-99 group only) and doxorubicinol using high-performance liquid chromatography. Plasma concentrations of total doxorubicin were higher in patients receiving TLC D-99 than in patients receiving conventional doxorubicin. The clearance of total doxorubicin after administration of TLC D-99 was lower (approximately 9-fold) and the volume of distribution at steady state was less (25-fold) than that of doxorubicin after conventional drug. Doxorubicinol was detected in the plasma of all patients in both treatment groups. The mean AUC(0-infinity) of doxorubicinol for patients receiving TLC D-99 (1.5+/-0.4 M x h) was not statistically different than that in patients receiving conventional doxorubicin (1.8+/-0.4 M x h), although the appearance of the peak doxorubicinol concentration occurred later and was lower in patients receiving TLC D-99. There was a correlation between the plasma AUC(0-infinity) of total doxorubicin and the degree of myelosuppression in patients receiving conventional doxorubicin, but this correlation was not found in patients receiving TLC D-99.

Adult↗

PubMed2002

A practical approach for comparing means of two groups without equal variance assumption.

In this paper we consider two-groups of i.i.d. normally distributed random variables (N(mu(x),sigma(x) (2)) and N(mu(y),sigma(y) (2))) without assuming equal variance (sigma(x) (2) = sigma(y) (2)). We propose a simple method for constructing confidence bounds based on Howe's approximation I. Its applications in parallel clinical trial (testing H(0) : mu(x)-mu(y)=0 versus H(1) : mu(x)-mu(y)<0) and parallel bioequivalence (BE) trial (testing H(0):mid R:mu(x)-mu(y)mid R:delta versus H(1):mid R:mu(x)-mu(y)mid R:<delta) are studied. Sample size calculation formulae for both cases are derived. Their performances are evaluated by simulation. Our study shows that the proposed procedure can control type I error satisfactorily compared with Cochran-Cox's and Satterthwaite's approximations while maintaining a relatively high power. The proposed approach is not only simple for constructing the confidence limit, but also provides a simple and accurate formula for sample size calculation.

Analysis of Variance↗

PubMed2002

Reproducibility probability in clinical trials.

For marketing approval of a new drug product, the United States Food and Drug Administration (FDA) requires that substantial evidence of the effectiveness of the drug product be provided through the conduct of at least two adequate and well-controlled clinical trials. The purpose of conducting the second clinical trial is to study whether the clinical result from the first trial is reproducible in the second trial with the same study protocol. Under certain circumstance, the FDA Modernization Act of 1997 includes a provision to allow data from one adequate and well-controlled clinical trial investigation and confirmatory evidence to establish effectiveness for risk/benefit assessment of drug and biological candidates for approval. In this paper, we introduce the concept of reproducibility probability for a given clinical trial, which is useful in providing important information for regulatory agencies in deciding whether a single clinical trial is sufficient and for pharmaceutical companies in adjusting the sample size in a future clinical trial. Three approaches, the estimated power approach, the method of confidence bounds and the Bayesian approach, are studied in evaluating reproducibility probabilities under several study designs commonly used in clinical trials.

Adult↗

PubMed2002

Individual bioequivalence testing under 2x3 designs.

In recent years, as more generic drug products become available, it is a concern not only whether generic drug products that have been approved based on the regulation of average bioequivalence will have the same quality, safety and efficacy as that of the brand-name drug product, but also whether the approved generic drug products can be used interchangeably. In its recent draft guidance, the U.S. Food and Drug Administration (FDA) recommends that individual bioequivalence (IBE) be assessed using the method proposed by Hyslop, Hsuan, and Holder to address drug switchability. The FDA suggests that a 2x4 cross-over design be considered for assessment of IBE, while a 2x3 cross-over design may be used as an alternative design to reduce the length and cost of the study. Little or no information regarding the statistical procedures under 2x3 cross-over designs is discussed in the guidance. In this paper, a detailed statistical procedure for assessment of IBE under 2x3 cross-over designs is derived. The main purpose of this paper, however, is to derive an IBE test under an alternative 2x3 design and show that the resulting IBE test is better than that under a 2x3 cross-over design and is comparable to or even better than that under a 2x4 cross-over design. Our conclusions are supported by theoretical considerations and empirical results. Furthermore, a method of determining the sample sizes required for IBE tests to reach a given level of power is proposed.

Computer Simulation↗

PubMed2002

A note on statistical methods for assessing therapeutic equivalence.

The two one-sided tests procedure and the confidence interval approach are two commonly used statistical approaches for testing therapeutic equivalence or assessing bioequivalence. However, some confusion arises. For example, what is the difference between the two approaches, given the fact that in some cases the two approaches produce the same test? Should we use level 1-alpha or 1-2alpha when applying the confidence interval approach? When different confidence intervals are available, which confidence interval should be used? The purpose of this paper is to clarify this confusion. It is shown that the approach of using 1-alpha confidence intervals produces level alpha tests, but the sizes of these tests may be smaller than alpha, and that the use of 1-2alpha confidence intervals generally does not ensure that the corresponding test be of level alpha, although there are exceptional cases. The sizes of several tests obtained using different confidence intervals are also evaluated.

Clinical Trials as Topic↗

PubMed2002

Probability lower bounds for USP/NF tests.

In the pharmaceutical industry, a number of tests such as content uniformity and dissolution testing are usually performed at various stages of drug manufacturing process to ensure that the drug product meets standards for identity, strength, quality, purity, and stability of the drug product as specified in the United States Pharmacopedia and National Formulary (USP/NF). The USP/NF provides requirements for sampling plans, testing procedures, and acceptance criteria for these tests. To ensure that there is a high probability of passing the USP/NF tests, the sponsors usually establish in-house specification limits based on some lower bounds of the probabilities of passing USP/NF tests for future samples. In this article, we derive some probability lower bounds for USP/NF tests. It is shown that the proposed probability lower bounds are better than the existing ones and are very close to the true probabilities in a broad range of the population mean and variance of the test sample.

Drug Compounding↗

PubMed2002

On statistical power for average bioequivalence testing under replicated crossover designs.

In its recent guidance on bioequivalence, the U.S. Food and Drug Administration (FDA) recommends a two-sequence, four-period (2 x 4) replicated crossover design be used for assessment of population and individual bioequivalence [FDA. Guidance for Industry on Statistical Approaches to Establishing Bioequivalence; Center for Drug Evaluation and Research, Food and Drug Administration: Rockville, MD, 2001]. The recommended replicated crossover design not only allows estimates of both the inter-subject and the intra-subject variabilities and the variability due to subject-by-formulation interaction, but also provides an assessment of average bioequivalence (ABE). In this article, power function for assessment of ABE under a general replicated crossover design (i.e., a 2 x 2m replicated crossover design) based on the traditional analysis of variance model and the mixed effects model as suggested by the FDA are studied. It is found that the power of a 2 x 2m replicated crossover design depends upon the variability due to subject-by-formulation interaction and the number of replicates. Based on the derived power function, formula for sample size calculation for assessment of ABE under a 2 x 2m replicated crossover design is also provided.

Algorithms↗

PubMed2002

On the assessment of similarity for dissolution profiles of two drug products.

The assessment of similarity between dissolution profiles of two drug products is considered. After reviewing some existing approaches, we propose a statistical method of assessing local and global similarities based on a time series model for the ratio of the dissolution results from two drug products and a polynominal model for the mean of the ratio. An example is presented for illustration.

Algorithms↗

PubMed2002

Bridging studies in clinical development.

Global development of pharmaceutical products has become the key to the success of any pharmaceutical sponsors. It is therefore crucial to address the efficacy and safety variations of a new test pharmaceutical product among different geographic regions due to ethnic factors. Recently, geotherapeutics has attracted much attention from sponsors as well as regulatory authorities from different geographic regions. To address this issue, the International Conference on Harmonization (ICH) has published a guideline entitled "Ethnic Factors in the Acceptability of Foreign Clinical Data," which is known as ICH E5 guideline. The ICH E5 guideline provides a general framework for evaluation of the impact of ethnic factors on the efficacy, safety, dosage, and dose regimen. We provide an overview of ICH E5 guideline including ethnic sensitivity, necessity of bridging studies, types of bridging studies, and assessment of similarity between regions based on bridging evidence. In addition, challenges on the establishment of regulatory requirements, the assessment of bridging evidence, and design and analysis of bridging studies are addressed.

Algorithms↗

PubMed2002

Assessing sensitivity and similarity in bridging studies.

In pharmaceutical industry, the sponsors are interested in bringing their drug products from one region (e.g., the United States of America) to another region (e.g., Asian Pacific) to increase the exclusivity of the drug products in the marketplace. However, it is a concern whether the clinical results can be extrapolated from the target patient population in one region to a similar but different patient population in a new region due to a possible difference in ethnic factors. The International Conference on Harmonization (ICH) recommends that a bridging study may be necessarily conducted to extrapolate the clinical results between regions. However, little or no information regarding the criterion for determining whether a bridging study is necessary based on the evaluation of the complete clinical data package is provided by the ICH. Furthermore, no criterion on the assessment of similarity of clinical results between regions is given. In this paper, we propose the use of a sensitivity index as a possible criterion for regulatory authorities in the new region to evaluate whether a bridging clinical study should be conducted and the sample size of such a bridging clinical study. A criterion and a statistical method for assessment of similarity of clinical results between regions are also proposed, using the concept of population bioequivalence [FDA. Guidance for Industry--Statistical Approaches to Establishing Bioequivalence, Center for Drug Evaluation and Research, Food and Drug Administration: Rockville, MD, 2001] assuming that study site is random.

Algorithms↗

PubMed2002

A note on sample size calculation for mean comparisons based on noncentral t-statistics.

One-sample and two-sample t-tests are commonly used in analyzing data from clinical trials in comparing mean responses from two drug products. During the planning stage of a clinical study, a crucial step is the sample size calculation, i.e., the determination of the number of subjects (patients) needed to achieve a desired power (e.g., 80%) for detecting a clinically meaningful difference in the mean drug responses. Based on noncentral t-distributions, we derive some sample size calculation formulas for testing equality, testing therapeutic noninferiority/superiority, and testing therapeutic equivalence, under the popular one-sample design, two-sample parallel design, and two-sample crossover design. Useful tables are constructed and some examples are given for illustration.

Algorithms↗

PubMed2002

On sample size calculation based on odds ratio in clinical trials.

Sample size calculation formulas for testing equality, noninferiority, superiority, and equivalence based on odds ratio were derived under both parallel and one-arm crossover designs. An example concerning the study of odds ratio between a test compound (treatment) and a standard therapy (control) for prevention of relapse in subjects with schizophrenia and schizoaffective disorder is presented to illustrate the derived formulas for sample size calculation for various hypotheses under both a parallel design and a crossover design. Simulations were performed to assess the adequacy of the sample size calculation formulas. Simulation results were given at the end of the paper.

Algorithms↗

PubMed2002

Tests for inter-subject and total variabilities under crossover designs.

In this paper, we consider statistical tests for inter-subject and total variabilities between treatments under crossover designs. Since estimators of variance components for inter-subject variability and total variability in crossover design are not independent, the usual F-test cannot be applied. Alternatively, we propose a test based on the concept of the extension of the modified large sample method to compare inter-subject variability and total variability between treatments under a 2 x 2 m replicated crossover design. An asymptotic power of the proposed test is derived. A sensitivity analysis is performed based on the asymptotic power to determine how the power changes with respect to various parameters such as inter-subject correlation and intra-class correlation. Also the two methods for sample size calculation for testing total variability under 2 x 4 crossover design are discussed. The method based on the Fisher-Cornish inversion shows better performance than the method based on the normal approximation. Several simulation studies were conducted to investigate the finite sample performance of the proposed test. Our simulation results show that the proposed test can control type I error satisfactorily.

Analysis of Variance↗