Adaptive control of drug dosage regimens: basic foundations, relevant issues, and clinical examples

Population Pharmacodynamic Modeling of Epoetin Alfa in End-Stage Renal Disease Patients Receiving Maintenance Treatment Using Bayesian Approach

The ability to control dosage regimens of erythropoiesis-stimulating agents (ESAs) to maintain a desired hemoglobin (HGB) target is still elusive. We utilized a Bayesian approach and informative priors to characterize HGB profiles, using simulated drug concentrations, in patients with end-stage renal disease receiving maintenance doses of epoetin alfa. We also demonstrated an adaptive Bayesian method, applied to individual patients, to improve the accuracy of HGB predictions over time. The results showed that sparse HGB data from daily clinical practice were characterized successfully. The adaptive Bayesian method effectively improved the accuracy of HGB predictions by updating the individual model with new data accounting for within-subject changes over time. The Bayesian approach presented leverages existing knowledge of the model parameters and has a potential utility in clinical practice to individualize dosage regimens of epoetin alfa and ESAs to achieve target HGB. Further studies are warranted to develop an application for practical use.

Paediatric models in motion: requirements for model-based decision support at the bedside

Optimal paediatric pharmacotherapy is reliant on a detailed understanding of the individual patient including their developmental status and disease state as well as the pharmaceutical agents he/she is receiving for treatment or management of side effects. Our appreciation for size and maturation effects on the pharmacokinetic/pharmacodynamic (PK/PD) phenomenon has improved to the point that we can develop predictive models that permit us to individualize therapy, especially in the situation where we are monitoring drug effects or therapeutic concentrations. The growth of efforts to guide paediatric pharmacotherapy via model-based decision support necessitates a coordinated and systematic approach to ensuring reliable and robust output to caregivers that represents the current standard of care and adheres to governance imposed by the host institution or coalition responsible. Model-based systems which guide caregivers on dosing paediatric patients in a more comprehensive manner are in development at several institutions. Care must be taken that these systems provide robust guidance with the current best practice. These systems must evolve as new information becomes available and ultimately are best constructed from diverse data representing global input on demographics, ethnic / racial diversity, diet and other lifestyle factors. Multidisciplinary involvement at the project team level is key to the ultimate clinical valuation. Likewise, early engagement of clinical champions is also critical for the success of model-based tools. Adherence to regulatory requirements as well as best practices with respect to software development and testing are essential if these tools are to be used as part of the routine standard of care.

Dashboard systems: Pharmacokinetic/pharmacodynamic mediated dose optimization for monoclonal antibodies

Many marketed drugs exhibit high variability in exposure and response. While these drugs are efficacious in their approved indications, finding appropriate dose regimens for individual patients is not straightforward. Similar dose adjustment problems are also seen with drugs that have a complex relationship between exposure and response and/or a narrow therapeutic window. This is particularly true for monoclonal antibodies, where prolonged dosing at a sub-therapeutic dose can also elicit anti-drug antibodies which will further compromise safety and efficacy. Thus, finding appropriate doses quickly would represent a substantial improvement in healthcare. Dashboard systems, which are decision-support tools, offer an improved, convenient means of tailoring treatment for individual patients. This article reviews the clinical need for this approach, particularly with monoclonal antibodies, the design, development, and testing of such systems, and the likely benefits of dashboard systems in clinical practice. We focus on infliximab for reference.

Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

Background

Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.

Methods

Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.

Results

The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.

Conclusion

The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.

Selective and validated spectrophotometric methods for the determination of nicorandil in pharmaceutical formulations

Two simple and sensitive validated spectrophotometric methods have been described for the assay of nicorandil in drug formulations. Method A is based on the reaction of the drug with phloroglucinol-sulfanilic acid reagent in sulfuric acid medium to give yellow-colored product, which absorbs maximally at 425 nm. Method B uses the oxidative coupling of 3-methyl-2-benzothiazolinone hydrazone hydrochloride (MBTH) with DL- 3,4 - dihydroxyphenylalanine (DL-dopa) in the presence of nicorandil as oxidant in sulfuric acid medium to form an intensely colored product having maximum absorbance at 530 nm. Beer's law is obeyed in the concentration range 2.5 to 50.0 and 1.0 to 15.0 microg mL(-1) with methods A and B, respectively. Both methods have been successfully applied for the analysis of drug in pharmaceutical formulations. The reliability and the performance of the proposed methods are established by point and interval hypothesis and through recovery studies. The experimental true bias of all samples is smaller than +/-2%.

Renal elimination of amikacin and the aging process

OBJECTIVE

Although amikacin is primarily eliminated via glomerular filtration, drug concentrations are not consistently predicted in all patients. To better describe the relationship between amikacin clearance and both age and renal function, we used a new heuristic approach involving statistical analysis of dependence.

DESIGN AND SETTING

Retrospective pharmacokinetic study using data from seven centres in France.

PARTICIPANTS

634 patients with sepsis aged between 18 and 98 years of age who received intravenous amikacin.

METHODS

Clearance of amikacin was modelled using the NonParametric EM algorithm for a two-compartment model (NPEM2) with intravenous infusion.

RESULTS

A total of 2499 serum amikacin determinations was available for analysis. The relationship between the clearance of amikacin and age was weak. Interestingly, the Z method, which filters data based on dependence criteria, selected data that were best fitted by a polynomial function (r = 0.90; p < 0.001). This representation of the polynomial function was similar to a previously proposed theoretical model describing covariations between the clearance of amikacin and age. However, the polynomial function applied to only 33% of the patients that were selected by the Z method. The correlation between the clearance of amikacin and renal function was also relatively low (r = 0.39). The Z method exhibited a continuous and strong dependence pattern between the clearance of amikacin and age for 49% of the patients.

CONCLUSIONS

The Z methodology, which filters data using dependence criteria, confirms that age, renal function and amikacin clearance are strongly related, but only in less than half of a large sample of patients with sepsis without renal pathology. These results suggest that other variables should be taken into account in order to improve the description of the behaviour of amikacin. The Z methodology improved the classical description of relationships between variables, and should be applied to better select pertinent variables in pharmacokinetic studies.

Determination of celiprolol and oxprenolol in human plasma by high-performance liquid chromatography and the analytical error function

Two reversed-phase HPLC methods with UV detection to quantify celiprolol and oxprenolol in human plasma are described. The analytical methods for the determination of both drugs used the same reversed-phase HPLC column, mobile phase and extraction procedure. Linearity was obtained in the ranges 15.63-1000 and 25-800 ng/ml for celiprolol and oxprenolol, respectively. Intra-day and inter-day variation was lower than 14%. After validation of the methods, analytical error functions were established as S.D. (ng/ml)=3.096+0.041C for celiprolol and S.D. (ng/ml)=8.906+8.075x10(-8)C3 for oxprenolol.

Error structure for the HPLC analysis for atenolol, metoprolol and propranolol: a useful weighting method in parameter estimation

Three reversed-phase high performance liquid chromatography (HPLC) methods with UV detection were developed and fully validated for the quantification of three beta-blockers: atenolol, metoprolol and propranolol. After validation, error structures for the HPLC analysis were established using a convenient and practical procedure. The mean percentage of relative standard deviation (RSD) of the experimental concentrations (C), were less than 4.29% for proportionality and less than 3.68% for precision for any of the drugs, which allowed the quantitation of beta-blockers assayed at concentrations in the range 25-0.78 micrograms.ml-1. The error structures for the HPLC analysis were: SD (micrograms.ml-1) = 5.02 x 10(-2) C for atenolol, SD (micrograms.ml-1) = 4.55 x 10(-2) + 0.63 x 10(-2) C - 7.58 x 10(-6) C3 for metoprolol and SD (micrograms.ml-1) = 2.73 x 10(-2) C - 3.49 x 10(-4) C2 for propranolol. The reciprocal of the square of the SD of the drug concentrations measured within the calibration curve could be used as weighting methods in parameter estimation by non-linear regression.

Population pharmacokinetics in veterinary medicine: potential use for therapeutic drug monitoring and prediction of tissue residues

Population pharmacokinetics can be defined as a study of the basic features of drug disposition in a population, accounting for the influence of diverse pathophysiological factors on pharmacokinetics, and explicitly estimating the magnitude of the interindividual and intraindividual variability. It is used to identify subpopulations of individuals that may present with differences in drug kinetics or in kinetic/dynamic responses. Rooted in procedures used in engineering systems, population pharmacokinetics methods were conceived as a means to determine the pharmacokinetic profile in populations in which a sparse number of samples were obtained per individual, such as those in late stage human clinical trials. This is the situation commonly encountered in all aspects of veterinary medicine. The exploratory nature of this technique allows one to probe relationships between clinical factors (such as age, gender, renal function, etc.) and drug disposition and/or effect. Similarly, the utilization of these techniques in the clinical research phases of drug development optimize the determination of efficacy and safety of drugs. Given the observational nature of most studies published so far, statistical methods to validate the population models are necessary. Simulation studies may be conducted to explore data collection designs that maximize information yield with a minimum expenditure of resources. The breadth of this approach has allowed population studies to be more commonly employed in all areas of drug therapy and clinical research. Finally, in veterinary medicine, there is an additional field in which population studies are potentially ideally suited: the application of this methodology to the study of tissue drug depletion and drug residues in production animals, and the establishment of withdrawal times tailored to the clinical or production conditions of populations or individuals. Such application would provide a major step toward assuring a safe food supply under a wide variety of dose and off-label clinical uses. Population pharmacokinetics is an ideal method for generating data in support of the implementation of flexible labelling policies and extralabel drug use recently approved under AMDUCA (Animal Medicinal Drug Use Clarification Act. 21 CFR Part 530).

Using therapeutic drug monitoring to dose the antimycobacterial drugs

The available data suggest that selected patients with tuberculosis and MAC fail to respond to therapy because they malabsorb their medications. In particular, patients with AIDS and known gastrointestinal diseases have problems absorbing these drugs. In addition, because MDR-TB and MAC are so difficult to treat, TDM with the antimycobacterial drugs offers the clinician a chance to ensure that the patient achieves serum concentrations above the MIC of the pathogen. TDM has become the standard of practice at the National Jewish Center for Immunology and Respiratory Medicine. By combining specific and sensitive assays, carefully collected samples, and clinical expertise, we are able to control and optimize antimycobacterial drug therapy. We continue to refine our approach with ongoing pharmacokinetic and pharmacodynamic research, including the development of population pharmacokinetic models. We hope that these efforts will provide insight into the nature of current therapeutic problems. We also hope they will help us improve the clinical outcomes of our patients.

Determination of analytical error function for beta-blockers as a possible weighting method for the estimation of the regression parameters

Three analytical methods have been developed and validated for the quantification of beta-blockers (celiprolol, bisoprolol and oxprenolol) using high performance liquid chromatography (HPLC) with UV detection. The methods were determined to be linear, precise and accurate (RSDs were lower than 5%), which allowed the quantitation of beta-blockers assayed at concentrations in the range 25-0.78 micrograms ml-1. After validation of reversed-phase HPLC methods, their analytical error functions were established by a rapid, simple and economical procedure. The discrimination of the best function for each active principle was performed by an appropriate polynomial statistical analysis, yielding SD (microgram ml-1) = 0.0295 + 0.0124C - 3.88 x 10(-4)C2 for celiprolol, 0.0199 + 0.011C - 1.27 x 10(-5)C3 for bisoprolol; and 0.0183 + 0.0089C - 9.68 x 10(-6)C3 for oxprenolol. These analytical error functions are an alternative to the weighting methods used in parameter estimation of beta-blockers.