Establishment of an Equivalence Acceptance Criterion for Accelerated Stability Studies

In this article, the use of statistical equivalence testing for providing evidence of process comparability in an accelerated stability study is advocated over the use of a test of differences. The objective of such a study is to demonstrate comparability by showing that the stability profiles under nonrecommended storage conditions of two processes are equivalent. Because it is difficult at accelerated conditions to find a direct link to product specifications, and hence product safety and efficacy, an equivalence acceptance criterion is proposed that is based on the statistical concept of effect size. As with all statistical tests of equivalence, it is important to collect input from appropriate subject-matter experts when defining the acceptance criterion.     

初匀速法预测复方枸橼酸钠注射液的有效期

目的:以初匀速法预测复方枸橼酸钠注射液有效期。方法:采用7个温度对样品进行加速试验,考察葡萄糖降解反应初均速(V0)与开尔文温度的倒数(1/T)的关系,并计算反应活化能、药物反应速度常数及有效期。结果:回归方程为lgV0=18.15—6774.6×1/T(r=—0.9375),复方枸橼酸钠注射液的反应活化能为31.0Kcal·mol-1,20℃药物反应速度常数为1.1×10-5h-1,有效期为1.09y。结论:本方法操作简便,可准确预测复方枸橼酸钠注射液的有效期。     

Multivariate Mixed-Effects Kinetic Models for Multiple Correlated Quality Attributes From Accelerated Stability Studies

Abstract

Stability study is a critical component for the submission and market authorization of a new drug or biological product. Long-term stability studies are required to establish the stability profile and shelf life of the drug product. Accelerated stability studies may provide insight into degradation pathways and help expedite the development of formulation and packaging. Accelerated stability studies are also useful to identify the stability-indicating attributes and appropriate assay methods for measuring degradation. Selection and specifications of critical quality attributes are imperative for ensuring the quality, safety, and efficacy of the drug. For individual attributes, Arrhenius equation has been used to combine accelerated stability data with long-term stability data to predict the degradation rates under long-term storage conditions. In practice, multiple stability-indicating critical attributes are available. The multiple attributes are intrinsically correlated because they are all indicators of drug quality. We propose a multivariate mixed-effects kinetic model, which can both combine the accelerated and long-term stability data using Arrhenius equation and incorporate lot-to-lot variability and between-attribute correlations with random effects. Simulation studies show that the multivariate modeling of the correlated attributes may provide more accurate estimates of degradation rates. The proposed model may provide insight on how to select the stability-indicating attributes. The stability data of three quality attributes for a therapeutic protein are analyzed for illustration.     

A Chi-Square Goodness-of-Fit Test for Autoregressive Logistic Regression Models with Applications to Patient Screening

We propose a chi-square goodness-of-fit test for autoregressive logistic regression models. General guidelines for a two-dimensional binning strategy are provided, which make use of two types of maximum likelihood parameter estimates. For smaller sample sizes, a bootstrap p-value procedure is discussed. Simulation studies indicate that the test procedure satisfactorily approximates the correct size and has good power for detecting model misspecification. In particular, the test is very good at detecting the need for an additional lag. An application to a dataset relating to screening patients for late-onset Alzheimer’s disease is provided.     

Multiple Polyexponentials and Quasipolynomials as Empirical Nonlinear Regression Models: A Case Study with HIV Viral Load Data

Measurements of HIV1-RNA plasma concentrations are an important method of assessing patient response to anti-HIV1 treatment, and in most clinical trials of such treatments HIV1-RNA levels are assessed at regular intervals of time. HIV1-RNA levels in successfully treated patients tend to follow a standard pattern of biphasic decline—a rapid early decline in viral load, followed by a period of slower decline or a steady level. Fitting nonlinear regression models to these patterns of declining HIV1-RNA levels can be of value in comparing different treatment regimes and in predicting treatment outcome. Simple exponential-decline models can give an adequate fit to the typical pattern of HIV1-RNA decline, but we have explored the extent to which curve-fitting can be improved by using two novel nonlinear model forms. Specifically, we describe the fitting of multiple polyexponential and quasipolynomial forms to longitudinal HIV1-RNA plasma data collected in two recent trials of the novel anti-HIV1 treatment Fuzeon®. We comment on the practicalities of fitting these nonlinear models, and compare the fit using various criteria.     

Stability testing of pharmaceuticals by high-sensitivity isothermal calorimetry at 25°C: cephalosporins in the solid and aqueous solution states

Present methodology for preliminary stability testing requires high temperatures and therefore suffers from the uncertainty of extrapolation of results to the temperature of interest. Clearly, a rapid method for estimating chemical decomposition rates at the temperature of interest would be of great utility. The recent introduction of a high-sensitivity isothermal calorimeter, the LKB 2277 thermal activity monitor (TAM), allows measurement of the rate of heat production, or thermal activity, from a sample (i.e., arising from a chemical reaction) with a sensitivity of about 10⁴ greater than is possible with a conventional differential scanning calorimeter. Since the power is equal to the product of the reaction rate and the heat of reaction, ΔH_r, the sensitivity of a calorimetric method depends on the magnitude of ΔH_r. From TAM and chemical assay data on the same samples, ΔH_r data were evaluated for a number of cephalosporins in aqueous solution and in various solid forms (i.e., crystalline forms and the amorphous form at selected water contents). Heats of reaction are exothermic and large in magnitude, several hundred kj/mol for the solids, yielding a sensitivity to detect decomposition rates as low as ≈ 1% year with an overnight experiment. For crystalline solids and amorphous samples of low to moderate moisture content, ΔH_r is roughly independent of temperature, water content, and polymorphic form. High-moisture amorphous solids and aqueous solutions of all concentrations have a heat of reaction about a factor of 5 less than the corresponding “dry” samples. However, variations in ΔH_r for a series of samples, including solutions, is less than the variation in chemical stability. Consequently, decomposition rate correlates well with thermal activity for a given compound, and TAM data are generally a valid measure of chemical stability. Exceptions to this generalization may arise when thermal activity from physical changes dominate, and if systems which undergo parallel endothermic and exothermic reactions are studied. The stability studies suggest two generalizations of particular interest. (1) The decomposition rates of amorphous cephalosporins increase with increasing water content in highly non-linear fashion, the rates increasing sharply as the water content increases beyond “intermediate” levels. (2) Stability in a series of crystalline pseudo-polymorphs is found to be quantitatively related to the heat of crystallization, and a theoretical model is proposed to interpret this observation.     

A sequential procedure for determining the number of regimes in a threshold autoregressive model

Summary In this paper, we propose a sequential method for determining the number of regimes in threshold autoregressive models. The proposed method relies on the superconsistency of sequential threshold estimates and uses general linearity tests to determine the number of thresholds. A simulation study is performed in order to find out the finite‐sample properties of our procedure and to compare it with two other procedures available in the literature. We find that our method works reasonably well for both single and multiple threshold models.     

血药曲线下面积预测及其模型内部验证方法的比较研究

目的:以口服硫普罗宁为实例,建立血药曲线下面积(AUC)预测模型,比较该模型的内部验证方法。方法:20名健康志愿者单剂量口服硫普罗宁胶囊,以有限抽样法建立多元回归模型预测AUC,用rmse和Pe比较模拟法、Bootstrap法、Jackknife法验证回归模型的效果。结果:模拟数据验证回归模型(AUC0～48=9.36 1.81C3 23.28C8)预测性良好。经模拟法、Bootstrap法、Jackknife法扩大样本量后,估算的回归模型参数分别为Intercept=17.58、9.33、9.84,C3的回归参数M1=1.01、1.76、1.84,C8的回归参数M2=6.17、23.14、21.36,并用原始数据计算其rmse分别为3.87、1.94、2.23。结论:用模拟的c-t数据预测AUC,可用于验证LSS回归模型,但不能通过模拟的c-t数据估算LSS回归模型参数达到这一目的;Bootstrap法和Jackknife法可验证LSS回归模型,结果相近。     

Pharmacodynamic Models: Parameterizing the Hill Equation,Michaelis-Menten,the Logistic Curve,and Relationships Among These Models

The Hill equation is often used in dose-response or exposure-response modeling. Aliases for the Hill model include the Emax model, and the Michaelis-Menten model. There is confusion about the appropriate parameterization, how to interpret the parameters, what the meaning is of the various parameterizations found in the literature, and which parameterization best approximates the statistical inferences produced when fitting the Hill equation to data. In this paper, we present several equivalent versions of the Hill model; show that they are equivalent in terms of yielding the same prediction for a given dose, and are equivalent to the four-parameter logistic model in this same sense; and deduce which parameterization is optimal in the sense of having the least statistical curvature and preferable multicollinearity.     

Accelerated Conditions for Stability Assessment of Bulk and Formulated Cefaclor Monohydrate

ABSTRACT

The stability of cefaclor monohydrate drug substance and formulated products was studied under accelerated conditions in order to provide a rapid indication of differences that might result from a change in manufacturing process or source of the sample. The USP stability-indicating related substances assay was used to assess the extent of sample degradation. An Arrhenius study of drug substance stability from 45 to 70°C predicted a degradation rate consistent with that observed in room-temperature studies. Qualitative degradation profiles of samples held at 65° C for 2 weeks were also very similar to those of samples held at room temperature for 2 years. Based on these results, additional studies were conducted at 65°Cfor 2 weeks. on drug substance and formulated product samples. Stability differences were observed among some capsule formulations that had also exhibited real time differences. In some studies, rapid degradation after 5 days was observed at 65 °C followed by a slower rate from 5 to 15 days. Similar behavior was observed for cefaclor monohydrate containing high amounts of amorphous cefaclor, suggesting that differences in amorphous content could be an explanation for stability differences observed in various samples. The accelerated conditions were shown to differentiate samples and can provide a rapid indication of relative stability.     

Equivalence Tests for Shelf Life and Average Drug Content in Stability Studies

Stability testing is a procedure frequently used in the pharmaceutical industry to estimate the shelf life of a drug. Hereby, a standard problem of interest is whether or not to pool a given number of batches to assign a single shelf life for the combined batches. In this paper, we propose two modified methods for the pooling process. One is based on the relative average drug contents of batches at a target shelf life, which basically involves specification of thresholds in relative terms, and the other is tests for the equivalence of shelf lives (using ratios of shelf lives) at a specified lower acceptance criteria of label claim. For both approaches, marginal and simultaneous confidence intervals are established. The methods will be illustrated using two different stability data. A simulation study is conducted to investigate the coverage probability of the proposed methods.     

民营中小医药企业新药研发模式探析

目的探讨现阶段适合我国民营中小医药企业发展的新药研发战略模式。方法分析我国医药行业和民营中小医药企业研发现状,研究现有的3种研发模式——开拓性创新、模仿创新和完全仿制各自的优劣及所适合的企业类型。结果通过SWOT分析发现,民营中小医药企业大多具有行为优势,但不具备资源优势,资金、技术以及人力等资源投入都不足。结论根据民营中小医药企业的综合实力,现阶段选择模仿创新战略更具可行性,可更有效发挥有限资源的使用效率、减小风险;实施过程中要注意选题方向、立项调研评估、专利战略等问题。     

Optimal Design Criteria for Discrimination and Estimation in Nonlinear Models

Nonlinear models are common in pharmacokinetics and pharmacodynamics. To date, most work in design in this area has concentrated on parameter estimation. Here, we introduce the idea of optimization of both estimation and model selection. However, experimental designs that provide powerful discrimination between a pair of competing model structures are rarely efficient in terms of estimating the parameters under each model. Conversely, designs which are efficient for parameter estimation may not provide suitable power to discriminate between the models. Several different methods of addressing both of these objectives simultaneously are introduced in this paper and are compared to an existing optimality criterion.     

Potential Improvement in the Shelf Life of Parenterals Using the Prodrug Approach: Bacampicillin and Talampicillin Hydrolysis Kinetics and Utilization Time

The utilization time for a parenteral prodrug solution with a bioavailable fraction of unity was defined as the time during which the total of the prodrug concentration and the drug concentration equals or exceeds 90% of the initial prodrug concentration. This utilization time was calculated as a function of pH, buffer, and temperature using the experimentally determined rate expressions for bacampicillin and talampicillin. The results were compared to the shelf life of ampicillin solutions under identical storage conditions. First-order rate constants were determined for conversion of the prodrugs to ampicillin (k _c), for -lactam degradation of the prodrugs (k _nc), for the overall loss of prodrugs (k _sum), and for -lactam degradation of ampicillin (k _h) in aqueous solutions at 25.0 to 60.0°C, µ = 0.5, in the pH range 0.90 to 8.4. Loss of bacampicillin proceeded primarily by degradation at pH levels below 4 but was due predominantly to conversion at pH levels above 5. Loss of talampicillin was due primarily to conversion throughout the entire pH range. While the prodrug utilization times were approximately twice the shelf life of ampicillin in acidic solutions, ampicillin was significantly better in neutral solutions. The results illustrate the potential for increased prodrug storage periods when utilization time is defined on the basis of the bioactivity rather than on the prodrug concentration alone.     

Experimental and Computational Screening Models for Prediction of Aqueous Drug Solubility

Purpose. To devise experimental and computational models to predict aqueous drug solubility. Methods. A simple and reliable modification of the shake flask method to a small-scale format was devised, and the intrinsic solubilities of 17 structurally diverse drugs were determined. The experimental solubility data were used to investigate the accuracy of commonly used theoretical and semiexperimental models for prediction of aqueous drug solubility. Computational models for prediction of intrinsic solubility, based on lipophilicity and molecular surface areas, were developed. Results. The intrinsic solubilities ranged from 0.7 ng/mL to 6.0 mg/mL, covering a range of almost seven log₁₀ units, and the values determined with the new small-scale shake flask method agreed well with published solubility data. Solubility data computed with established theoretical models agreed poorly with the experimentally determined solubilities, but the correlations improved when experimentally determined melting points were included in the models. A new, fast computational model based on lipophilicity and partitioned molecular surface areas, which predicted intrinsic drug solubility with a good accuracy (R ²of 0.91 and RMSE_tr of 0.61) was devised. Conclusions. A small-scale shake flask method for determination of intrinsic drug solubility was developed, and a promising alternative computational model for the theoretical prediction of aqueous drug solubility was proposed.     

Nonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials

Most clinical trials have heterogeneous treatment effect among patient individuals. It is desirable to identify a patient subpopulation, which has a stronger treatment effect than the rest of patients, so that researchers will be able to determine who will benefit the most or the least from the treatment and design treatment strategies accordingly. This paper develops a nonparametric method for predicting clinical response and identifying subpopulations. The method first selects predictors using kernel-based local regression and a forward procedure via F-tests. It then defines subpopulations with enhanced treatment effects based on the selected predictors and the nonparametric model of the clinical response. Simulation examples and a pharmacogenomics study of bortezomib in multiple myeloma demonstrate the proposed method and show favorable performances compared to other existing methods. The proposed method provides an alternative way to define subpopulations and is not limited by parametric models and their possible misspecification for the clinical response.     

Improvement of the Prediction Power of the CoMFA and CoMSIA Models on Histamine H3 Antagonists by Different Variable Selection Methods

The aim of this study is to enhance the predictivity power of CoMFA and CoMSIA models by means of different variable selection algorithms. The genetic algorithm (GA), successive projection algorithm (SPA), stepwise multiple linear regression (SW-MLR), and the enhanced replacement method (ERM) were used and tested as variable selection algorithms. Then, the selected variables were used to generate a simple and predictive model by the multilinear regression algorithm. A set of 74 histamine H₃ antagonists were split into 40 compounds as a training set, and 17 compounds as a test set, by the Kennard-Stone algorithm. Before splitting the data, 17 compounds were randomly selected from the pool of the whole data set as an evaluation set without any supervision, pretreatment, or visual inspection. Among applied variable selection algorithms, ERM had noticeable improvement on the statistical parameters. The r² values of training, test, and evaluation sets for the ERM-MLR model using CoMFA fields were 0.9560, 0.8630, and 0.8460 and using the CoMSIA fields were 0.9800, 0.8521, and 0.9080, respectively. In this study, the principles of organization for economic cooperation and development (OECD) for regulatory acceptability of QSARs are considered.     

药品标准物质基本特性与规范生产有关质量管理要求

目的：为规范药品标准物质的研制生产提供参考。方法：结合ISO导则34,根据药品标准物质的基本特性,探讨在全面质量管理新形势下,药品标准物质在均匀性、稳定性、准确性和程序合规性等几方面应遵循的有关要求。结果与讨论：规范和完善药品标准物质生产技术要求和质量管理,是标准物质量值准确、稳定、可靠的保障。     

Effects and Detection of Raw Material Variability on the Performance of Near-Infrared Calibration Models for Pharmaceutical Products

The impact of raw material variability on the prediction ability of a near-infrared calibration model was studied. Calibrations, developed from a quaternary mixture design comprising theophylline anhydrous, lactose monohydrate, microcrystalline cellulose, and soluble starch, were challenged by intentional variation of raw material properties. A design with two theophylline physical forms, three lactose particle sizes, and two starch manufacturers was created to test model robustness. Further challenges to the models were accomplished through environmental conditions. Along with full-spectrum partial least squares (PLS) modeling, variable selection by dynamic backward PLS and genetic algorithms was utilized in an effort to mitigate the effects of raw material variability. In addition to evaluating models based on their prediction statistics, prediction residuals were analyzed by analyses of variance and model diagnostics (Hotelling's T² and Q residuals). Full-spectrum models were significantly affected by lactose particle size. Models developed by selecting variables gave lower prediction errors and proved to be a good approach to limit the effect of changing raw material characteristics. Hotelling's T² and Q residuals provided valuable information that was not detectable when studying only prediction trends. Diagnostic statistics were demonstrated to be critical in the appropriate interpretation of the prediction of quality parameters.     

Correlation and Prediction of Moisture-Mediated Dissolution Stability for Benazepril Hydrochloride Tablets

PURPOSE: This report investigated dissolution stability of benazepril hydrochloride tablets. METHODS: Reduction in dissolution rate was observed for benazepril hydrochloride tablets when they were subjected to stressed storage condition (40 degrees C/75% RH) for prolonged periods of time (1-3 months). Moisture contents of initial and stressed tablets were measured by Karl Fischer method. Comparative thermal and physical characterizations of initial and stressed tablets were also performed. A mathematical model that was used to predict possible reduction in dissolution rate was proposed and validated using experimental data. RESULTS: It was found that there was a direct correlation between moisture content of benazepril hydrochloride tablets and their percentage of dissolution at 10 min. At moisture content below 3.5%, there were no significant changes in dissolution values. Beyond that point, however, a close to linear decrease in dissolution was observed as a function of increase in moisture content. Results from thermal and X-ray analysis have ruled out possible changes in drug substance. Other physical characterization, such as scanning electron microscope and mercury porosimetry measurements, revealed changes in core structure of stressed tablets vs. initial tablets. Based on results from these measurements, "preactivation" of disintegrant was identified as the mechanism for reduction in dissolution rate above critical moisture content. A simple physical model for moisture uptake of benazepril hydrochloride tablets was also proposed for predicting when, based on water vapor transmission and critical moisture content, dissolution rate will decline. CONCLUSIONS: Physical changes of tablets mediated by moisture were the main cause for reduction in dissolution. Inclusion of desiccant, although beneficial, cannot prevent reduction in dissolution completely. The simple physical model proposed in this report was found to be useful in predicting the dissolution stability of the dosage form.