Summary

The Clinical Research Associate will accurately and efficiently extract information from medical records for AI and Human Virtual Modelling research purposes. This position will be responsible for conducting retrospective chart reviews of the Gastrointestinal and Liver Clinics at BCM and affiliates utilizing Electronic Medical Records (EMR) Systems. The Clinical Research Associate will collaborate closely with the clinical research and engineering teams to support the project objectives, summarize clinical insights for the AI/Engineering team and design a retrospective study for validation of novel AI and Virtual Modelling.

The Clinical Research Associate will take part on projects in which we aim to revolutionize clinical testing by developing a virtual twin models of the Gastrointestinal Tract and the Liver from biologic details of healthy and diseased states. This model will assess drug-induced liver toxicity, improve drug development safety and efficiency, and reduce reliance on traditional testing methods. It will also support more inclusive clinical trials by integrating diverse patient data and addressing research disparities. Additionally, the virtual twins of the Gastrointestinal tract will serve as an educational tool for students, clinicians, and patients, with an open-source model available for future research, education, and clinical care.

Job Duties

• Conducts retrospective chart reviews for the research projects assigned.
• De-identifies patient data in compliance with privacy regulations.
• Manages and maintains research project databases, ensuring data integrity, and security.
• Structures medical record data following project requirements and standards.
• Works with engineering teams to develop Virtual Twin models of the liver and gastrointestinal tract using relevant software
• Collaborates closely with the clinical research and engineering teams to support project objectives.
• Ensures adherence to regulatory requirements and compliance with HIPAA laws.
• Participates actively in project meetings.
• Assists with institutional regulatory affairs: prepare standard operating procedures (SOPs) and case report forms; review and update documents for IRB, PRMC, and DRC; ensure quality control and maintain site certifications
• Supports investigators and clinical research staff with reporting and study monitoring.
• Accurately and efficiently extracts information from medical records for AI and Human Virtual Modelling research purposes.
• Special attention will be needed in storing, analyzing, and labeling clinical data based on AI/Engineering team (GI and/or Hepatology background required).
• Accurately communicates with AI/Engineering team to understand clinical metrics to extract for model training and validation.
• Coordinate clinical insights from clinical stakeholders and summarize clinical insights for AI/Engineering team.
• Design retrospective study for validation of novel AI and Virtual Human Modelling study and validation.
• Performs other job-related duties as assigned.
  

Minimum Qualifications

• Bachelor\'s degree.
• Two years of relevant experience.

Preferred Qualifications

• Bachelor\'s degree in a clinical or scientific discipline required. Undergraduate background or prior experience in biomedical or software engineering is a plus.
• Minimum of 2 years of experience with medical terminology across different specialties (Gastroenterology preferred).
• Significant experience in reading and interpreting medical records, including but not limited to imaging, pathology, functional studies, endoscopy, and laboratory reports.
• Experience with EPIC (preferred) or other EMR systems.
• Proficient in using computer databases, spreadsheets, and word-processing software.
• Demonstrated understanding of digital clinical data format and processing (dicom, stl, jpg, png, tif, csv, xlxs.)
• Demonstrated ability to quickly learn and master computer programs.
• Familiarity with HIPPA laws and regulations regarding patient data privacy.
• Comfortable working with technology in a fast, innovative environment.
• Detail-oriented and highly organized.