title: Benchmarking therapeutic drug monitoring software: a review of available computer tools.
abstract: Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. 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 account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.
authors.affiliation: Division of Clinical Pharmacology, Service of Biomedicine, Department of Laboratory, Hôpital de Beaumont, Centre Hospitalier Universitaire Vaudois and University of Lausanne, 1011, Lausanne, Switzerland.
authors.forename: Aline
authors.initials: A
authors.lastname: Fuchs
authors.forename: Chantal
authors.initials: C
authors.lastname: Csajka
authors.forename: Yann
authors.initials: Y
authors.lastname: Thoma
authors.forename: Thierry
authors.initials: T
authors.lastname: Buclin
authors.forename: Nicolas
authors.initials: N
authors.lastname: Widmer
mesh_terms: D001499:Bayes Theorem; D003365:Costs and Cost Analysis; D004305:Dose-Response Relationship, Drug; D016903:Drug Monitoring / Q000295:instrumentation*; D006801:Humans; D016247:Information Storage and Retrieval; D008954:Models, Biological; D012984:Software; D014584:User-Computer Interface