Automated eligibility screening and monitoring for genotype-driven precision oncology trials

Abstract

The Information Systems Department at Memorial Sloan Kettering Cancer Center developed the DARWIN Cohort Management System (DCMS). The DCMS identifies and tracks cohorts of patients based on genotypic and clinical data. It assists researchers and treating physicians in enrolling patients to genotype-matched IRB-approved clinical trials. The DCMS sends automated, actionable, and secure email notifications to users with information about eligible or enrolled patients before their upcoming appointments. The system also captures investigators input via annotations on patient eligibility and preferences on future status updates. As of August 2015, the DCMS is tracking 159,893 patients on both clinical operations and research cohorts. 134 research cohorts have been established and track 64,473 patients. 51,192 of these have had one or more genomic tests including MSK-IMPACT, comprising the pool eligible for genotype-matched studies. This paper describes the design and evolution of this Informatics solution.

Implementing Genome-Driven Oncology

“…Furthermore, robust methods for connecting patients with rare actionable alterations to clinical trials targeting these genomic variants are needed. Within our own institution, we have developed a system that automatically identifies, tracks, and recruits patients with qualifying genomic alterations to the appropriate genome-driven study (Eubank et al, 2016). This system has allowed treating physicians to rely on domain experts to interpret the actionability of individual genomic alterations and identify relevant and immediately available treatment opportunities for their patients.…”

Genomic expertise in action: molecular tumour boards and decision‐making in precision oncology

“…In such a scenario, treating physicians would be able to routinely access a set of resources managed by dedicated decision support teams and encompassing patient cohort management software, knowledge bases and data visualisation and analysis software (e.g. Eubank et al 2016, Johnson et al 2015. In other words, the peculiar MTB configurations we investigated in this paper will probably transit to new models, but the issues and problems we discussed in this paper, in particular the search for actionable interpretations, will continue to pose significant challenges to the clinic of variants.…”

A Curated Cancer Clinical Outcomes Database (C3OD) for accelerating patient recruitment in cancer clinical trials

“…Although recent years have seen significant innovation aimed at improving the efficiency of patient screening, 10 , 14–19 most previous systems have not been specifically tailored to cancer patients, and for those that have, such focused systems have seen some of the greatest success in adoption. 14 To automate and improve patient screening for clinical trials conducted at KUCC, we developed the Curated Cancer Clinical Outcomes Database (C3OD). Electronically discovered information, such as patient history, physician encounters, demographics, medication logs, diagnosis from the tumor registry, and bio-specimen data are curated directly from the source system into C3OD repository.…”