Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

A New Imaging Software To Evaluate The Centration Of Capsulorhexis And Intraocular Lens (IOL) After Cataract Surgery

Purpose: IOL centration and stability after cataract surgery is of high interest for cataract surgeons and IOL-producing companies. We present a new imaging software to evaluate the centration of the rhexis and the centration of the IOL after cataract surgery.Methods: We developed, in collaboration with the Biomedical Imaging Group (BIG), EPFL, Lausanne, a new working tool in order to assess precisely outcomes after IOL-implantation, such as ideal capsulorhexis and IOL-centration. The software is a plug-in of ImageJ, a general-purpose image processing and image-analysis package. The specifications of this software are: evaluation of the rhexis-centration and evaluation the position of the IOL in the posterior chamber. The end points are to analyze the quality of the centration of a rhexis after cataract surgery, the deformation of the rhexis with capsular bag retraction and the centration of the IOL after implantation.Results: This software delivers tools to interactively measure the distances between limbus, IOL and capsulorhexis and its changes over time. The user is invited to adjust nodes of three radial curves for the limbus, rhexis and the optic of the IOL. The radial distances of the curves are computed to evaluate the IOL implantation. The user is also able to define patterns for ideal capsulorhexis and optimal IOL-centration. We are going to present examples of calculations after cataract surgery.Conclusions: Evaluation of the centration of the rhexis and of the IOL after cataract surgery is an important end point for optimal IOL implantation after cataract surgery. Especially multifocal or accommodative lenses need a precise position in the bag with a good stability over time. This software is able to evaluate these parameters just after the surgery but also its changes over time. The results of these evaluations can lead to an optimizing of surgical procedures and materials.

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

Evaluation of errors in alpine skiing video analysis

INTRODUCTION: Video records are widely used to analyze performance in alpine skiing at professional or amateur level. Parts of these analyses require the labeling of some movements (i.e. determining when specific events occur). If differences among coaches and differences for the same coach between different dates are expected, they have never been quantified. Moreover, knowing these differences is essential to determine which parameters reliable should be used. This study aimed to quantify the precision and the repeatability for alpine skiing coaches of various levels, as it is done in other fields (Koo et al, 2005). METHODS: A software similar to commercialized products was designed to allow video analyses. 15 coaches divided into 3 groups (5 amateur coaches (G1), 5 professional instructors (G2) and 5 semi-professional coaches (G3)) were enrolled. They were asked to label 15 timing parameters (TP) according to the Swiss ski manual (Terribilini et al, 2001) for each curve. TP included phases (initiation, steering I-II), body and ski movements (e.g. rotation, weighting, extension, balance). Three video sequences sampled at 25 Hz were used and one curve per video was labeled. The first video was used to familiarize the analyzer to the software. The two other videos, corresponding to slalom and giant slalom, were considered for the analysis. G1 realized twice the analysis (A1 and A2) at different dates and TP were randomized between both analyses. Reference TP were considered as the median of G2 and G3 at A1. The precision was defined as the RMS difference between individual TP and reference TP, whereas the repeatability was calculated as the RMS difference between individual TP at A1 and at A2. RESULTS AND DISCUSSION: For G1, G2 and G3, a precision of +/-5.6 frames, +/-3.0 and +/-2.0 frames, was respectively obtained. These results showed that G2 was more precise than G1, and G3 more precise than G2, were in accordance with group levels. The repeatability for G1 was +/-3.1 frames. Furthermore, differences among TP precision were observed, considering G2 and G3, with largest differences of +/-5.9 frames for "body counter rotation movement in steering phase II", and of 0.8 frame for "ski unweighting in initiation phase". CONCLUSION: This study quantified coach ability to label video in term of precision and repeatability. The best precision was obtained for G3 and was of +/-0.08s, which corresponds to +/-6.5% of the curve cycle. Regarding the repeatability, we obtained a result of +/-0.12s for G1, corresponding to +/-12% of the curve cycle. The repeatability of G2 and G3 are expected to be lower than the precision of G1 and the corresponding repeatability will be assessed soon. In conclusion, our results indicate that the labeling of video records is reliable for some TP, whereas caution is required for others. REFERENCES Koo S, Gold MD, Andriacchi TP. (2005). Osteoarthritis, 13, 782-789. Terribilini M, et al. (2001). Swiss Ski manual, 29-46. IASS, Lucerne.

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computer-assisted two-dimensional preoperative planning for total hip arthroplasty: clinical evaluation.

The purpose of this study is to clinically validate a new two-dimensional preoperative planning software for cementless total hip arthroplasty (THA). Manual and two-dimensional computer-assisted planning were compared by an independent observer for each of the 30 patients with osteoarthritis who underwent THA. This study showed that there were no statistical differences between the results of both preoperative plans in terms of stem size and neck length (<1 size) and hip rotation center position (<5 mm). Two-dimensional computer-assisted preoperative planning provided successful results comparable to those using the manual procedure, thereby allowing the surgeon to simulate various stem designs easily.

Business model design: an evaluation of paper-based and computer-aided canvases

In recent years, Business Model Canvas design has evolved from being a paper-based activity to one that involves the use of dedicated computer-aided business model design tools. We propose a set of guidelines to help design more coherent business models. When combined with functionalities offered by CAD tools, they show great potential to improve business model design as an ongoing activity. However, in order to create complex solutions, it is necessary to compare basic business model design tasks, using a CAD system over its paper-based counterpart. To this end, we carried out an experiment to measure user perceptions of both solutions. Performance was evaluated by applying our guidelines to both solutions and then carrying out a comparison of business model designs. Although CAD did not outperform paper-based design, the results are very encouraging for the future of computer-aided business model design.