Low-LET-induced radioprotective mechanisms within a stochastic two-stage cancer model

A stochastic two-stage cancer model with clonal expansion was used to investigate the potential impact on human lung cancer incidence of some aspects of the hormesis mechanisms suggested by Feinendegen (Health Phys. 52 663-669, 1987). The model was applied to low doses of low-LET radiation delivered at low dose rates. Non-linear responses arise in the model because radiologically induced adaptations in radical scavenging and DNA repair may reduce the biological consequences of DNA damage formed by endogenous processes and ionizing radiation. Sensitivity studies were conducted to identify critical model inputs and to help define the changes in cellular defense mechanisms necessary to produce a lifetime probability for lung cancer that deviates from a linear no-threshold (LNT) type of response. Our studies suggest that lung cancer risk predictions may be very sensitive to the induction of DNA damage by endogenous processes. For doses comparable to background radiation levels, endogenous DNA damage may account for as much as 50 to 80% of the predicted lung cancers. For an additional lifetime dose of 1 Gy from low-LET radiation, endogenous processes may still account for as much as 20% of the predicted cancers (Fig. 2). When both repair and scavengers are considered as inducible, radiation must enhance DNA repair and radical scavenging in excess of 30 to 40% of the baseline values to produce lifetime probabilities for lung cancer outside the range expected for endogenous processes and background radiation.     

Markov switching stochastic frontier model

Summary In this paper, we propose a new approach to stochastic frontier models, viz., a Markov switching structure to accommodate cross‐sectional parameter heterogeneity and temporal variation in the parameters and technical inefficiency distributions. The Markov Chain Monte Carlo techniques are developed and implemented for Bayesian inferences on parameters and technical efficiency. We illustrate new methods by estimating world production frontiers using international panel data on 59 countries observed for 26 years.     

1例Beagle犬的糖尿病建模分析

糖尿病模型的建立是糖尿病治疗研究的重要内容,本研究根据文献报道的方法,采用链脲佐菌素和四氧嘧啶联合给药进行Beagle犬糖尿病造模的建立。结果造模后Beagle犬血糖呈先下降后升高变化,血糖由于饮食变化而有较大波动,体重持续下降,最后造模26日后因长期不进食死亡。采用文献方法建模药物的剂量可能偏大,建议可分剂量多次注射,以降低药物对犬机体的损伤。     

A database model for integrating and facilitating collaborative ethnomedicinal research

A model for a database system that provides a standardized environment for submission, storage, and retrieval of ethnomedicinal data was developed. The model is based on object oriented database technology, and is suitable for not only storing data, digital images, sound and video, but also for modeling domain knowledge associated with plant-based medicinal preparations utilized in systems of traditional medicine. The model incorporates both linguistic and semantic elements. Terms in natural language are mapped to database objects that represent knowledge in various ethnomedicinal domains. The distributed object infrastructure permits integration with other authoritative taxonomic databases and includes an interface capable of supporting existing and emerging standards of data. The model provides a foundation for a globally current dynamic data resource that encourages comparative ethnomedicinal research through direct contributions by members of the research community. Examples of integrated domain models are presented incorporating medical terminology, plant systematics, ecology, and pharmacology.     

Applications of a recirculatory stochastic pharmacokinetic model: Limitations of compartmental models

General equations for the time integral on [0, ) of the venous drug concentrationtime function after intravenous and oral drug administration are derived. A physiologically realistic stochastic recirculating model is applied in the derivations. The quotient of the intravenous drug dose and the integral on [0, ) of the resulting venous blood drug concentration function is equivalent to a summation of organ clearances only provided that drug elimination does not occur in the pulmonary system, and in general it is not equivalent to total body clearance. In general, mammillary compartmental models are not isomorphic with recirculating models. A necessary condition for isomorphism is that the pulmonary system be conservative toward the drug. Equations for the pulmonary first-pass effect derived via the compartmental analysis are invalid. A valid expression for the pulmonary first-pass effect is derived. General equations derived via compartmental analysis for the extent of hepatic metabolism and the hepatic first-pass effect are shown to be valid. A generally applicable expression for the advantage of close intraarterial drug administration is derived. The limitations of compartmental models for representing drug distribution and elimination are discussed, and the advantages of recirculating models are emphasized.     

A stochastic version of corticosteriod pharmacogenomic model

The purpose of this study was to develop a stochastic version of corticosteriod fifth generation pharmacogenomic model. The Gillespie algorithm was used to generate the independent time courses of the receptor messenger RNA (mRNA). Initial parameters for the stochastic simulation were adapted from the study by Jin et al. The result obtained from the proposed stochastic model showed an overall agreement with the deterministic fifth generation model. This study suggested that because the stochastic model takes into account the "noise" nature of gene regulation, it would have potential application in pharmacogenomic modeling.     

Numerical validation and properties of a rapid binding approximation of a target-mediated drug disposition pharmacokinetic model

Target mediated drug disposition (TMDD) describes the phenomenon where high affinity binding of a drug to its pharmacological target (enzymes or receptors) significantly alters the pharmacokinetic profile of the drug. A rapid binding model replaces the often inestimable binding micro-constants (k _on and k _off) of TMDD models with the equilibrium dissociation constant (K _D) by assuming rapid binding of the drug to its target. The purpose of this study is to examine the validity of the rapid binding assumption and the pharmacokinetic properties of this model. Temporal profiles of free drug in plasma and a non-specific distribution site, free receptor, and the pharmacodynamically relevant, drug–receptor complex obtained from the rapid binding model compared favorably with the full TMDD model for small values of the parameter ɛ, which represents the ratio of the time required for drug–receptor binding relative to the time required for drug to be cleared from the system. The effect of escalating drug doses on the temporal characteristics and the comparison between the two models has been numerically investigated. A closer match between the full and rapid binding models is observed for high doses. Analysis for very large doses (Dose/V _c) relative to endogenous steady-state receptor concentration (R _ss), reveals that the rapid binding model reduces to a standard two compartmental model with a plasma compartment with linear drug elimination and a peripheral compartment. Decreasing clearance with increasing dose and decreasing R _ss indicates that for drugs exhibiting TMDD, the relative ratio of R _ss and dose is an important determinant of the pharmacokinetic properties rather than the individual parameters alone. An analytical solution derived for clearance shows that the primary elements of the apparent clearance of the drug are the linear clearance given by k _el V _c, the non-linear clearance due to drug–receptor complex internalization (k _int), and the ratio of AUC values of the receptor complex to that of free drug. Overall, simulations and analytical techniques applied here provide a better understanding of the validity of the rapid binding model and provide guidelines for its application. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

药物体内吸收动力学的随机模型

本文用随机模型分析零级兼一级并存的混合级吸收动力学特性,并将保证率曲线图的方法,用于判定体内吸收过程属于单纯零级或单纯一级吸收还是混合级吸收,同时通过概率的方法估计在混合级吸收过程中零级及一级吸收各占比例的范围。     

A stochastic markov model of cellular response to radiation

A stochastic model based on the Markov Chain Monte Carlo process is used to describe responses to ionizing radiation in a group of cells. The results show that where multiple relationships linearly depending on the dose are introduced, the overall reaction shows a threshold, and, generally, a non-linear response. Such phenomena have been observed and reported in a number of papers. The present model permits the inclusion of adaptive responses and bystander effects that can lead to hormetic effects. In addition, the model allows for incorporating various time-dependent phenomena. Essentially, all known biological effects can be reproduced using the proposed model.     

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q? = 4.9 % and q? = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data.     

Concordance between criteria for covariate model building

When performing a population pharmacokinetic modelling analysis covariates are often added to the model. Such additions are often justified by improved goodness of fit and/or decreased in unexplained (random) parameter variability. Increased goodness of fit is most commonly measured by the decrease in the objective function value. Parameter variability can be defined as the sum of unexplained (random) and explained (predictable) variability. Increase in magnitude of explained parameter variability could be another possible criterion for judging improvement in the model. The agreement between these three criteria in diagnosing covariate-parameter relationships of different strengths and nature using stochastic simulations and estimations as well as assessing covariate-parameter relationships in four previously published real data examples were explored. Total estimated parameter variability was found to vary with the number of covariates introduced on the parameter. In the simulated examples and two real examples, the parameter variability increased with increasing number of included covariates. For the other real examples parameter variability decreased or did not change systematically with the addition of covariates. The three criteria were highly correlated, with the decrease in unexplained variability being more closely associated with changes in objective function values than increases in explained parameter variability were. The often used assumption that inclusion of covariates in models only shifts unexplained parameter variability to explained parameter variability appears not to be true, which may have implications for modelling decisions.     

Use of a pharmacokinetic model for individualizing intravenous doses of aminophylline

Summary A reliable method for individualizing intravenous doses of aminophylline is reported. Individual kinetic parameters, half-life (t_1/2), volume of distribution (V_d), and theophylline clearance (Q_b) were established for 13 patients from serum level-time data obtained after an initial intravenous load. Using a one-compartment open model predictions of serum concentrations after initiation of a constant infusion were made. Follow-up serum concentrations [32] were measured for comparison with predicted levels. A good correlation (r=0.83) was obtained. Ninety-five percent confident interval of y on x= ±2.81 µg/ml. No cases of aminophylline toxicity were observed.Supported in part by a grant from the University of Minnesota Graduate School     

Estimation of the stochastic conditional duration model via alternative methods

Summary This paper examines the estimation of the Stochastic Conditional Duration model by the empirical characteristic function and the generalized method of moments when maximum likelihood is unavailable. The joint characteristic function for the durations along with general expressions for the moments are derived, leading naturally to estimation via the empirical characteristic function and generalized method of moments. In a Monte Carlo study as well as an empirical application, these alternative methods are compared with quasi maximum likelihood. These experiments reveal that the empirical characteristic function approach outperforms the quasi maximum likelihood and generalized method of moments in terms of both bias and root mean square error.     

Use of a failing rabbit heart as a model to predict torsadogenicity.

Humans with underlying cardiovascular disease are at greater risk than humans with normal hearts for developing torsade de pointes (TdP) following exposure to some drugs that prolong ventricular repolarization. This study was designed to test the hypothesis that rabbits with ischemic myocardial failure are at similarly increased risk of developing QTc prolongation and TdP following exposure to escalating doses of drugs, which is known to have a capacity to induce TdP in humans. Coronary artery ligation was performed in 28 rabbits, causing significant (p < 0.05) reduction in left ventricular shortening fraction and systolic myocardial dysfunction 4 weeks after ligation in all operated animals compared to 38 normal, nonoperated controls. All studies were performed on rabbits anesthetized with ketamine (35 mg/kg) and xylazine (5 mg/kg). Rabbits were exposed to escalating doses of amiodarone (3, 10, 30 mg/kg/10 min), cisapride (0.10, 0.25, 0.50 mg/kg/10 min), clofilium (0.1, 0.2, 0.4 mg/kg/10 min), dofetilide (0.005, 0.01, 0.02, 0.04 mg/kg/10 min), quinidine (3, 10, 30 mg/kg/10 min), and verapamil (0.25, 0.5, 1.0 mg/kg/10 min). A greater percentage of rabbits with failing hearts developed TdP following intravenous infusion of escalating doses of dofetilide (85%), clofilium (100%), or cisapride (50%) than did normal rabbits exposed to the same drug protocol (20, 33, and 0%, respectively). None of the rabbits in either group developed TdP when exposed to escalating doses of amiodarone, verapamil, or quinidine. Two out of four test articles lengthened QTc more in rabbits with myocardial failure than in normals, and TdP occurred in 13 out of 28 rabbits with myocardial failure as opposed to only four out of 38 rabbits with normal myocardial function.     

Use of the ferret for a myocardial ischemia/salvage model

Exploratory work was undertaken in the anesthetized ferret to determine if it is an applicable species for use as an in vivo ischemic model and suitable for recovery surgical procedures.Experimental protocols utilizing varying combinations of left anterior descending (LAD) coronary artery occlusion (30, 60, 90 min) and reperfusion (4, 6, 18–24 hr) were evaluated. The results indicated that a 90-min/6-hr combination led to the production of an infarct equivalent, or slightly greater, in size to that observed following coronary artery occlusion either with and without reflow during an 18–24-hr recovery period prior to sacrifice. A combination of 90 min occlusion/4 hr reperfusion yielded an infarct area ca. 50% of that associated with 6 hr interval of reflow. An occlusive interval of 60 min or less combined with any reperfusion interval lack reproducibility.The administration of saline in varying volumes by different routes (IV versus left atrial) had no influence on either the absolute or, more especially, the relative (i.e., as a percent of left ventricle) tissue damage provoked by a 90-min/6-hr occlusion/reperfusion maneuver of the LAD coronary artery. When evaluated as a reference standard, Superoxide dismutase (SOD) infused via the left atrium at a dose of 5 $\text{mg}\text{kg}$ afforded a 36% reduction in the area of ischemic damage in this model.These studies demonstrated that the ferret represents a useful species for initial, rapid, and economic—both in terms of cost and drug substance utilization—in vivo myocardial salvage screening assessments. The model permits an interpretation of potential test agent efficacy, dosage requirements, and hemodynamic actions, and it is suitable for basing a go/no-go decision that continued experimental development in more labor intense preparations is warranted.     

Alternative ways of facilitating nutritional support without a nutrition support team

In the absence of a formal nutritional support team, a group of physicians, pharmacists, dietitians, and nurses at the authors' institution organized to devise alternative ways to facilitate nutritional support. The efforts of this group led to the redesign of the Pharmacy Department's parenteral nutrition order form into a clinical tool for the prescribing physician, and the development of a system for daily patient monitoring by dietitians and pharmacists for patients receiving specialized nutritional products. The delivery of parenteral nutrition was also streamlined to coordinate with the daily patient monitoring. A future goal is to increase three-way communication and teamwork among the physicians, dietitians, and pharmacists. These methods may be practical alternatives to facilitating nutritional support without the benefit of a support team.     

Impact of dose selection on parameter estimation using a rapid binding approximation model of target-mediated drug disposition

The purpose of this study was to examine the role of dose selection on population pharmacokinetic (PK) parameter estimation using a rapid binding approximation of a target-mediated drug disposition (TMDD) model previously developed for interferon-β (IFN-β). A total of 50 replicate datasets each containing 100 subjects were created using NONMEM^®. The study design included IV injection of IFN-β followed by the SC route in a crossover manner, with each dose and route of administration separated by a 1,000 h washout period. Serial plasma PK samples were simulated up to 48 h for all subjects following each dose. Population mean PK parameters were re-estimated in NONMEM^® for each simulated dataset using the same TMDD model after including the following doses (MIU/kg): (A) 1, 3 and 10 (original study); (B) 1, 3 and 7; (C) 1, 3 and 5; (D) 1, 3 and 4; (E) 1 and 3; (F) 3 and 10; or (G) 10 MIU/kg only. Bias in the model fit was assessed by calculating the percent prediction error (PE%) for each of the population mean PK parameters relative to the estimates obtained from the fit to the 1, 3, and 10 MIU/kg doses (Case A). Relatively unbiased population mean PK parameter estimates (median PE% <8%) were obtained only when the study design included 1, 3 and a minimum higher dose of 7 MIU/kg. Bias increased for various parameters when the highest dose was less than 7 MIU/kg along with 1 and 3 MIU/kg being the low and intermediate dose levels. An increase in the bias for binding capacity, R_tot, and the equilibrium dissociation constant, K _D, was observed as the highest dose included in the dataset was reduced from 5 to 3 MIU/kg (median PE% ranged from ?4.71 to ?23.9% and ?4.76 to ?34.6%). Similar increases in the range of median PE% were also observed for other model parameters as the highest dose was reduced from 5 to 3 MIU/kg. Severely biased results were obtained from the study design that included only the 10 MIU/kg dose (Case G) suggesting that it is not sufficient to study just a high dose group. This bias was greatly reduced (median PE% <14%) for all parameters except K _D when the 3 and 10 MIU/kg doses were co-modeled (Case F). Plots of the PE% for R_tot and K _D versus the molar ratio of maximum dose to R_tot suggest that study designs should evaluate at least one IFN-β dose 3.5- to 4-fold higher than R_tot along with the 1 and 3 MIU/kg dose levels to obtain unbiased population PK parameter estimates. In summary, for the IFN-β model and study design, dose selection influences the ability to generate relatively unbiased population mean TMDD parameter estimates, which is based on maximum dose levels relative to R_tot. This simulation study highlights the role of dose selection in optimal study design strategies for drugs such as IFN-β that exhibit TMDD properties.