Object-Oriented Modeling and Terminologies for Drug Contraindications

Designing concept maps for a precise and objective description of pharmaceutical innovations

BACKGROUND

When a new drug is launched onto the market, information about the new manufactured product is contained in its monograph and evaluation report published by national drug agencies. Health professionals need to be able to determine rapidly and easily whether the new manufactured product is potentially useful for their practice. There is therefore a need to identify the best way to group together and visualize the main items of information describing the nature and potential impact of the new drug. The objective of this study was to identify these items of information and to bring them together in a model that could serve as the standard for presenting the main features of new manufactured product.

METHODS

We developed a preliminary conceptual model of pharmaceutical innovations, based on the knowledge of the authors. We then refined this model, using a random sample of 40 new manufactured drugs recently approved by the national drug regulatory authorities in France and covering a broad spectrum of innovations and therapeutic areas. Finally, we used another sample of 20 new manufactured drugs to determine whether the model was sufficiently comprehensive.

RESULTS

The results of our modeling led to three sub models described as conceptual maps representingi) the medical context for use of the new drug (indications, type of effect, therapeutical arsenal for the same indications), ii) the nature of the novelty of the new drug (new molecule, new mechanism of action, new combination, new dosage, etc.), and iii) the impact of the drug in terms of efficacy, safety and ease of use, compared with other drugs with the same indications.

CONCLUSIONS

Our model can help to standardize information about new drugs released onto the market. It is potentially useful to the pharmaceutical industry, medical journals, editors of drug databases and medical software, and national or international drug regulation agencies, as a means of describing the main properties of new pharmaceutical products. It could also used as a guide for the writing of comprehensive and objective texts summarizing the nature and interest of new manufactured product.

Design and evaluation of an ontology-based drug application database

OBJECTIVES

Several recently published cases of preventable adverse drug reactions were associated with flaws in drug application. However, current clinical decision support (CDS) systems do not properly consider drug application issues and thus do not support effective prevention of such medication errors. With the aim to improve CDS in this respect, we developed a comprehensive model precisely describing all aspects of drug application.

METHODS

The model consists of 1) a schema comprising all relevant attributes of drug application and 2) an ontology providing a hierarchically structured vocabulary of terms that describe the possible values of the schema's attributes. Finally, medical products were annotated by a semi-automatic term assignment process. For evaluation, we developed an algorithm that uses our model to compute a meaningful similarity between medicinal products with respect to their drug application characteristics.

RESULTS

Our schema consists of 22 attributes. The ontology contains 248 terms, textual descriptions, and synonym lists. More than 58,700 medicinal products were automatically annotated with >386,600 terms. 2,450 drugs were manually reviewed by experts, adding >4500 terms. The annotation and similarity measure allow for (similarity) searches, clustering, and proper discrimination of drugs with different drug application characteristics. We demonstrated the value of our approach by means of a set of case studies.

CONCLUSION

Our model enables a detailed description of drug application, allowing for semantically meaningful comparisons of drugs. This is an important prerequisite for improving the ability of CDS systems to prevent prescription errors.

Design of a graphical and interactive interface for facilitating access to drug contraindications, cautions for use, interactions and adverse effects

BACKGROUND

Drug iatrogeny is important but could be decreased if contraindications, cautions for use, drug interactions and adverse effects of drugs described in drug monographs were taken into account. However, the physician's time is limited during consultations, and this information is often not consulted. We describe here the design of "Mister VCM", a graphical interface based on the VCM graphical language, facilitating access to drug monographs. We also provide an assessment of the usability of this interface.

METHODS

The "Mister VCM" interface was designed by dividing the screen into two parts: a graphical interactive one including VCM icons and synthetizing drug properties, a textual one presenting on demand drug monograph excerpts. The interface was evaluated over 11 volunteer general practitioners, trained in the use of "Mister VCM". They were asked to answer clinical questions related to fictitious randomly generated drug monographs, using a textual interface or "Mister VCM". When answering the questions, correctness of the responses and response time were recorded.

RESULTS

"Mister VCM" is an interactive interface that displays VCM icons organized around an anatomical diagram of the human body with additional mental, etiological and physiological areas. Textual excerpts of the drug monograph can be displayed by clicking on the VCM icons. The interface can explicitly represent information implicit in the drug monograph, such as the absence of a given contraindication. Physicians made fewer errors with "Mister VCM" than with text (factor of 1.7; p = 0.034) and responded to questions 2.2 times faster (p < 0.001). The time gain with "Mister VCM" was greater for long monographs and questions with implicit replies.

CONCLUSION

"Mister VCM" seems to be a promising interface for accessing drug monographs. Similar interfaces could be developed for other medical domains, such as electronic patient records.

A formal framework of knowledge to support rational psychoactive drug selection

Rational psychoactive drug selection is a data and knowledge intensive task which requires true expertise from clinical, pathophysiological and pharmacotherapeutic knowledge. This paper presents a framework of knowledge, which relates concepts from several disciplines required for psychoactive drug selection in a formal way. A framework, when based on formal semantics, avoids ambiguity and gives conceptual clarity and supports precise use of terminology which is required when many domain experts (clinicians, pharmacologists and basic science researchers) are involved. A formal framework permits linking of existing classification systems. It furthermore can serve as a knowledge base for drug selection decision support systems.