Comparison of an assumption-free Bayesian approach with Optimal Sampling Schedule to a maximum a posteriori Approach for Personalizing Cyclophosphamide Dosing.

Study Objective: Variable metabolism, dose-dependent efficacy, and a narrow therapeutic target of cyclophosphamide (CY) suggest that dosing based on individual pharmacokinetics (PK) will improve efficacy and minimize toxicity. Real-time individualized CY dose adjustment was previously explored using a maximum a posteriori (MAP) approach based on a five serum-PK sampling in patients with hematologic malignancy undergoing stem cell transplantation. The MAP approach resulted in an improved toxicity profile without sacrificing efficacy.

Validation of a novel approach for dose individualization in pharmacotherapy using gabapentin in a proof of principles study.

Study Objective: To demonstrate the premise of individualized dosing charts (IDCs) as a clinical-bedside decision-support tool to individualize dosage regimens for drugs in which the interpatient variability is controlled by the pharmacokinetic (PK) behavior of the patient, to calculate the optimal sampling schedule (OSS), which minimizes the number of blood samples per patient. The approach is illustrated with available PK data for gabapentin.

Design: Retrospective proof of principles study using gabapentin PK data from a published clinical trial.

Probability model for estimating colorectal polyp progression rates.

According to the American Cancer Society, colorectal cancer (CRC) is the third most common cause of cancer related deaths in the United States. Experts estimate that about 85% of CRCs begin as precancerous polyps, early detection and treatment of which can significantly reduce the risk of CRC. Hence, it is imperative to develop population-wide intervention strategies for early detection of polyps.

Purdue ionomics information management system. An integrated functional genomics platform.

The advent of high-throughput phenotyping technologies has created a deluge of information that is difficult to deal with without the appropriate data management tools. These data management tools should integrate defined workflow controls for genomic-scale data acquisition and validation, data storage and retrieval, and data analysis, indexed around the genomic information of the organism of interest. To maximize the impact of these large datasets, it is critical that they are rapidly disseminated to the broader research community, allowing open access for data mining and discovery.

Target volume uncertainty and a method to visualize its effect on the target dose prescription.

Purpose: To consider the uncertainty in the construction of target boundaries for optimization, and to demonstrate how the principles of mathematical programming can be applied to determine and display the effect on the tumor dose of making small changes to the target boundary.

Methods: The effect on the achievable target dose of making successive small shifts to the target boundary within its range of uncertainty was found by constructing a mixed-integer linear program that automated the placement of the beam angles using the initial target volume.

Results: The method was demonstrated using contours taken from a nasopharynx case, with dose limits placed on surrounding structures.