Features and Functions | TransMed Systems

By: Xb Transmed  09-12-2011
Keywords: Data Analysis, Clinical Trials

The XB Bio-Integration Suite™ platform is a powerful analysis and discovery tool with more than six years dedicated to its development at the Van Andel Institute. Features currently available are graphically represented and briefly discussed below.


Figure 1: A possible use map of XB Bio-Integration Suite™ features

Protocol Tracking

In addition to tracking samples, XB Bio-Integration Suite supports the tracking of protocols used for experimental procedures. This feature of the program allows the user to enter default values for crucial run variables within the protocol (i.e. experimenter, incubation temperature, incubation time, etc.). After the protocol is used for an experiment, the scientist can then confirm or change these variables, creating an additional set of data tied to the experiment. Later statistical analysis of these run variables can identify and track data-altering variables and user-specific issues, and these identifications can be correlated to experiments.

Data Analysis

XB Bio-Integration Suite includes many standard statistical and graphical tools for analysis such as t-tests, Chi squared tests, Mann Whitney tests, Wilcoxon tests, ANOVA tests, and Kappa Meyer graphics and clustergrams of related data. To help further populate a user's data sets, XB Bio- Integration Suite captures data from public databases including GeneBank, Ensembl, PubMed, and MedLine. When studying a large data set populated by both user-derived data and public data, XB Bio-Integration Suite allows the user to select patient and clinical records based upon any number of features for further analysis. The data are then analyzed, statistically significant results compiled, and correlations between samples identified for further study.

For example, in the context of a large clinical trial, the investigator may want to compare molecular attributes of patients who responded the most favorably to a given treatment versus those who responded the least favorably to a given treatment before processing all patient samples (an expensive undertaking). XB Bio-Integration Suite™ readily identifies these so-called "outlier" subsets of patients and builds hypotheses around them that can then be applied to additional samples in later experiments.

Interestingly, even in the absence of molecular data, statistical analysis of clinical information alone can produce significant epidemiological results relating multiple clinical and/or environmental events. For example, incidence of lung cancer correlates to tobacco smoking history, and platelet count correlates with aggressive stage of mesothelioma. The XB Bio-Integration Suite can compare samples in a laboratory's possession with epidemiological data in public databases, offering the potential for further study definition well before sample analysis begins.

Molecular Pathway Mapping

Many users are also interested in mechanisms of action—for example how a drug effects the cell—or in mapping individual molecular events to signaling pathways. The XB Bio-Integration Suite can readily map genes/proteins identified during analysis to molecular networks, allowing the user to identify key points of convergence or divergence within pathways that may represent excellent therapeutic targets.

Hypothesis Generation

One of the key features of XB Bio-Integration Suite™ is its ability to generate probable hypotheses explaining correlations between sample sets for later validation within the laboratory. As diagramed below, after initial analysis XB Bio-Integration Suite™ defines a set of preliminary hypotheses for validation with further data analysis based on the initial hypotheses. Following this second set of analysis, a second set of hypotheses are generated for exploration within the laboratory. This capability enables the seamless, circular flow of laboratory experimentation to data analysis and back to laboratory experimentation again.


Figure 2: Flow chart of hypothesis generation capabilities

Drug Discovery: XB Bio-Integration Suite™

XB offers an integrated support solution throughout the drug discovery process. Specifically, the platform can

  • Target discovery from disparate internal and third party data sources
  • Target discovery and validation in preclinical and clinical trials
  • Identify biomarkers of early disease and surrogate markers of therapeutic index
  • Identify optimum combinational drug therapies
  • Identification of novel indications for existing or orphan drugs as therapies for new diseases
  • Identify and develop companion diagnostics for prediction of diagnosis, prognosis and therapeutic response.

As discussed previously, XB Bio-Integration Suite™ has the ability to iterate data from disparate subjects and disparate experiments. Furthermore, the molecular pathway mapping capabilities discussed above provide the ability to hypothesize directly where an agent (such as a drug) is acting within a pathway. This ability to navigate seamlessly across these model systems (for example, in comparing data from mouse models to human clinical trials) and between the various molecular platforms will be essential in the optimization of the drug-discovery pipeline.

We hope to soon partner with pharmaceutical companies to study effects of existing drugs, validate proposed effects of proposed drugs, and find new uses for orphan drugs. Furthermore, by characterizing these drugs individually, XB Bio-Integration Suite™ will enable users to hypothesize optimal combinational drug cocktails. These proposed collaborations represent one of the most exciting future uses of XB Bio-Integration Suite.™

Keywords: Clinical Trials, Data Analysis

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