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Konstantinos Leventakos

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    Lunch & Poster Display session (ID 58)

    • Event: ELCC 2019
    • Type: Poster Display session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 4/11/2019, 12:30 - 13:00, Hall 1
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      200P - Implementation of artificial intelligence (AI) for lung cancer clinical trial matching in a tertiary cancer center (ID 253)

      12:30 - 13:00  |  Presenting Author(s): Konstantinos Leventakos

      • Abstract


      Cognitive computing has promising potential to assist trial matching efficiency and accuracy by utilizing natural language processing and performing background analytics. The Watson for Clinical Trial Matching (CTM) cognitive system derives patient and tumor attributes from unstructured text in the electronic health record that can be matched to complex eligibility criteria in trial protocols. The Watson for CTM system was trained by Mayo Clinic subject matter experts in collaboration with IBM computer scientists/engineers and implemented in the Breast Oncology practice in July 2016. Metrics have shown an average monthly enrollment increase of 84% for breast systemic therapy trials.

      a9ded1e5ce5d75814730bb4caaf49419 Methods

      Training of Watson for CTM has continued with inclusion of additional cancers and expansion of trial types including Phase 1, supportive care, biomarker and observational trials. Watson for CTM was piloted in Lung Oncology in July 2018 and fully implemented in October 2018. Clinical research coordinators (CRCs) validated Watson-derived clinical trial matches on the day prior to patient clinic visits. A list of matched trials for each patient was given to providers to facilitate treatment decision making at point of care. Screening and timing metrics were tracked and compared with manual screening methods.

      20c51b5f4e9aeb5334c90ff072e6f928 Results

      Watson for CTM facilitated screening of all lung cancer patients against 42 trials. Based on preset criteria, matches were validated by CRCs and provided to lung oncology providers in 69% (1818/2637) of patients’ visits from July through December 2018. Watson CTM-assisted patient matches resulted in a more complete list of potentially eligible trials and were completed in less than 50% of the time as compared to the traditional manual method. Enrollment data to define the impact of Watson for CTM and a screening team in the lung oncology practice is immature and will be subsequently reported.

      fd69c5cf902969e6fb71d043085ddee6 Conclusions

      Implementation of the Watson for CTM system with a screening team enabled high volume patient screening for a large number of clinical trials in an efficient manner and promoted awareness of clinical trial opportunities within the lung oncology practice.

      b651e8a99c4375feb982b7c2cad376e9 Legal entity responsible for the study

      The authors.

      213f68309caaa4ccc14d5f99789640ad Funding

      Mayo Clinic.

      682889d0a1d3b50267a69346a750433d Disclosure

      A.S. Mansfield: Funding to institution for participation on advisory boards: AbbVie, Genentech, BMS; Research funding to institution: Verily, Novartis. T. Halfdanarson: Research support: Ipsen, Thermo Fisher Scientific, Agios, ArQule; Consultancy (advisory boards): Lexicon, Advanced Accelerator Applications, Novartis, Curium. S. Coverdill: Employment: IBM Watson Health; Stock Ownership: IBM. M. Rammage: Employment: IBM Watson Health; Patent, royalties or other intellectual property: IBM. T. Haddad: Past consultant: TerSera Therapeutics; Research funding: Takeda Oncology. All other authors have declared no conflicts of interest.