The specific benchmark requirements listed below require a "C-" or better for all science and math courses and are based on the semester in the major unless specified otherwise. Students with questions about benchmark requirements should contact their academic advisor.Students who do not successfully pass benchmark requirements risk being dismissed from their major.The exact benchmark courses and timeframe for completion vary by major.Students are expected to successfully pass important benchmark courses by certain semesters to ensure they are on track to graduate in a timely fashion.Students are expected to create and update a four year plan towards graduation.Full-time degree-seeking students are expected to graduate in four years.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.As part of the campus Student Academic Success-Degree Completion Policy, undegraduates are expected to make satisfactory completion of benchmark requirements. Programs should be easy and fast for routine activities, including for non-experienced users. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs vary in complexity and might not fit all healthcare settings. Most other programs evaluated had good potential while being less sophisticated or less user friendly. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. 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. 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. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. A weighting factor was applied to each criterion of the grid to account for its relative importance. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. All programs were tested on personal computers. The literature and the Internet were searched to identify software. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. In recent decades computer programs have been developed to assist clinicians in this assignment. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations.
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