The long-term objective of this research is to increase the clinical trial enrollment of US patients via a semi-automated, Natural Language Processing (NLP) based, interactive and patient-centered informaticsapplication. The study design is prospective observational study. Scope is limited to cancer patients. There arethree specific aims for this project.
The first aim i s to identify concepts that overlap between the electronicmedical record's (EMR) clinical notes and the free text of clinical trial announcements. The PI will use theconcepts to develop mapping frames that connect concepts in the text of trial announcements to those found inclinical notes in the medical record. When he has the mapping frames he will build the NLP module for theapplication. In the software development work he will utilize as many publicly available software componentsas possible. He will experiment with UIMA, GATE, MetaMap, Stanford Parser, NegEx algorithm and others.The PI will develop the tool around the National Library of Medicine's Unified Medical Language Systemknowledgebase. He will use Java for programming.
The second aim i s to create an algorithm that automaticallygenerates questions to request information directly from the patient if the information is not available oraccessible in the records.
The third aim i s to evaluate the in-vitro, laboratory performance of the application.For performance evaluation purposes the PI will recruit cancer care specialists to generate the gold standardlists of eligible clinical trials for study patients. He will publicly release the developed code at the end of thegrant period. This K99/R00 project will serve the foundation for future R01 grant applications. The PI is fullycommitted to become faculty in the Clinical Research Informatics domain with a specialization in biomedicalNLP. The support of the K99/R00 grant will enable him to acquire substantial formal training in ComputationalLinguistics while contributing to the body of knowledge of the Clinical Research Informatics field. The five-yeargrant support will ensure success in his endeavor. The proposed work is highly significant because the dismalclinical trial accrual rates (2-4 % nationally) hampers timely development of new drugs. In addition, studiesshow that physicians have statistically significant bias against elderly and minority patients to inviteparticipation in clinical trials. The proposed project is synergistic with physician-centered efforts but the goal isto provide individualized, EMR based clinical trial recommendations directly to the patients. The results of thisresearch will empower the patients and elevate their role in the decision making process.
The long-term objective of this research is to increase the clinical trial enrollment of US patients via a semi- automated, Natural Language Processing (NLP) based, interactive and patient-centered informatics application. The proposed work is highly significant because the dismal clinical trial accrual rates (2-4 % nationally) hampers timely development of new drugs. In addition, studies show that physicians have statistically significant bias against elderly and minority patients to invite participation in clinical trials. The proposed project is synergistic with physician-centered efforts but the goal is to provide individualized, electronic medical record based clinical trial recommendations directly to the patients. The results of this research will empower patients and elevate their role in the decision making process.
Showing the most recent 10 out of 24 publications