Combining Medical Informatics and Bioinformatics toward Tools for Personalized Medicine

Modeling complex workflow in molecular diagnostics: design specifications of laboratory software for support of personalized medicine

One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency.

A Computational Positron Emission Tomography Simulation Model for Imaging ?-Amyloid in Mice

PURPOSE

We aimed to develop a computational simulation model for beta-amyloid (Abeta) positron emission tomography (PET) imaging.

PROCEDURES

Model parameters were set to reproduce levels of Abeta within the PDAPP mouse. Pharmacokinetic curves of virtual tracers were computed and a PET detector simulator was configured for a commercially available preclinical PET-imaging system.

RESULTS

We modeled the effects of Abeta therapy and tracer affinity on the ability to differentiate Abeta levels by PET. Varying affinity had a significant effect on the ability to quantitate Abeta. Further, PET tracers for Abeta monomers were more sensitive to the therapeutic reduction in Abeta levels than total brain amyloid. Following therapy, the decrease in total brain Abeta corresponded to the slow rate of change in total amyloid load as expected.

CONCLUSIONS

We have developed a first proof-of-concept Abeta-PET simulation model that will be a useful tool in the interpretation of preclinical Abeta imaging data and tracer development.

Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care

In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.