Design and evaluation of an ontology-based drug application database

Alignment of two standard terminologies for dosage form: RxNorm from the National Library of Medicine for the United States and EDQM from the European Directorate for the Quality in Medicines and Healthcare for Europe

BACKGROUND

There is currently no system that aligns pharmaceutically equivalent medicinal products across nations, creating obstacles to transnational medication prescribing and medical research. EDQM has been internationally recognized as the leading system in systematic pharmaceutical product descriptions. RxNorm is a critical terminology based in the US and used widely in applications internationally that would benefit from alignment with EDQM-based dosage form descriptions.

GOAL

Demonstrate a method for alignment of RxNorm dosage forms with EDQM terminologies and with EDQM dosage forms. Describe obstacles and advantages of such an alignment for ultimate application in calculating universal Pharmaceutical Product Identifiers.

METHODS

A pharmaceutical sciences student and a clinical pharmacology expert in dosage forms used definitions supplied by RxNorm and EDQM technical documentation to align the 120 RxNorm dose forms to EDQM-based dosage form description terms. The alignment of RxNorm to EDQM was then used to fit the RxNorm dose forms into an ontology based on EDQM.

RESULTS AND CONCLUSIONS

The alignment of RxNorm and EDQM requires further validation but provides a potential method of establishing interoperability between the two terminologies without cumbersome manual reclassification. There remain ambiguities within each dosage form nomenclature that create obstacles to integrating medication databases rooted in EDQM and RxNorm into a single worldwide database.

A computational protocol for the discovery of lead molecules targeting DNA unique to pathogens

With the rapid emergence of drug resistant pathogens, it has become imperative to develop alternative medications as well as find new drug targets to overcome this crisis. Hence, this has become prime focus of several academic laboratories and pharmaceutical companies. Here, we report a computational protocol for identifying unique DNA sequence(s) in the pathogen which is absent in human and related non-pathogenic strains of the microbe. In order to use the unique sequence as drug target, the protocol, in the second step, uses virtual screening against a million compound library to identify candidate small molecules which can bind to these unique DNA targets in the pathogen only. Theoretically the molecules identified after screening should not bind to human DNA. This methodology is demonstrated on Mycobacterium tuberculosis H37Rv, wherein a new octamer sequence present only in H37Rv has been identified and a few candidate small molecules as potential drug have been proposed. Being fast and cost effective, this protocol could be of importance in generating new potential drug candidates against infectious organisms for further experimental studies. This methodology is freely available at http://www.scfbio-iitd.res.in/PSDDF/.

OWLing Clinical Data Repositories With the Ontology Web Language

Background

The health sciences are based upon information. Clinical information is usually stored and managed by physicians with precarious tools, such as spreadsheets. The biomedical domain is more complex than other domains that have adopted information and communication technologies as pervasive business tools. Moreover, medicine continuously changes its corpus of knowledge because of new discoveries and the rearrangements in the relationships among concepts. This scenario makes it especially difficult to offer good tools to answer the professional needs of researchers and constitutes a barrier that needs innovation to discover useful solutions.

Objective

The objective was to design and implement a framework for the development of clinical data repositories, capable of facing the continuous change in the biomedicine domain and minimizing the technical knowledge required from final users.

Methods

We combined knowledge management tools and methodologies with relational technology. We present an ontology-based approach that is flexible and efficient for dealing with complexity and change, integrated with a solid relational storage and a Web graphical user interface.

Results

Onto Clinical Research Forms (OntoCRF) is a framework for the definition, modeling, and instantiation of data repositories. It does not need any database design or programming. All required information to define a new project is explicitly stated in ontologies. Moreover, the user interface is built automatically on the fly as Web pages, whereas data are stored in a generic repository. This allows for immediate deployment and population of the database as well as instant online availability of any modification.

Conclusions

OntoCRF is a complete framework to build data repositories with a solid relational storage. Driven by ontologies, OntoCRF is more flexible and efficient to deal with complexity and change than traditional systems and does not require very skilled technical people facilitating the engineering of clinical software systems.

An ontology-based annotation of cardiac implantable electronic devices to detect therapy changes in a national registry

The patient population benefitting from cardiac implantable electronic devices (CIEDs) is increasing. This study introduces a device annotation method that supports the consistent description of the functional attributes of cardiac devices and evaluates how this method can detect device changes from a CIED registry. We designed the Cardiac Device Ontology, an ontology of CIEDs and device functions. We annotated 146 cardiac devices with this ontology and used it to detect therapy changes with respect to atrioventricular pacing, cardiac resynchronization therapy, and defibrillation capability in a French national registry of patients with implants (STIDEFIX). We then analyzed a set of 6905 device replacements from the STIDEFIX registry. Ontology-based identification of therapy changes (upgraded, downgraded, or similar) was accurate (6905 cases) and performed better than straightforward analysis of the registry codes (F-measure 1.00 versus 0.75 to 0.97). This study demonstrates the feasibility and effectiveness of ontology-based functional annotation of devices in the cardiac domain. Such annotation allowed a better description and in-depth analysis of STIDEFIX. This method was useful for the automatic detection of therapy changes and may be reused for analyzing data from other device registries.

Development of a standardized knowledge base to generate individualized medication plans automatically with drug administration recommendations

AIMS

We aimed to develop a generic knowledge base with drug administration recommendations which allows the generation of a dynamic and comprehensive medication plan and to evaluate its comprehensibility and potential benefit in a qualitative pilot study with patients and physicians.

METHODS

Based on a literature search and previously published medication plans, a prototype was developed and iteratively refined through qualitative evaluation (interviews with patients and focus group discussions with physicians). To develop the recommendations for safe administration of specific drugs we screened the summary of product characteristics (SmPC) of different exemplary brands, allocated the generated advice to groups with brands potentially requiring the same advice, and reviewed these allocations regarding applicability and appropriateness of the recommendations.

RESULTS

For the recommendations, 411 SmPCs of 140 different active ingredients including all available galenic formulations, routes of administrations except infusions, and administration devices were screened. Finally, 515 distinct administration recommendations were included in the database. In 926 different generic groups, 29,879 allocations of brands to general advice, food advice, indications, step-by-step instructions, or combinations thereof were made. Thereby, 27,216 of the preselected allocations (91.1%) were confirmed as appropriate. In total, one third of the German drug market was labelled with information.

CONCLUSIONS

Generic grouping of brands according to their active ingredient and other drug characteristics and allocation of standardized administration recommendations is feasible for a large drug market and can be integrated in a medication plan.