What is clinical trial recruitment with AI?

Using natural language processing and the analysis of unstructured and structured data to analyze both patient records and trial inclusion/exclusion criteria, clinical trial recruitment with AI enables oncologists to quickly review a list of potential trials for every patient, while supporting the clinical trial office in reaching enrollment numbers.

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How can AI help to improve the cancer clinical trial recruitment process?

There is good news. An artificial intelligence-based clinical trial recruitment support system can help you change the game by:

natural language processing

Using natural language processing to understand both structured and unstructured patient data

Automating manual steps

Automating manual steps to help increase the speed of trial identification

helping find viable trial options

Helping find viable trial options for each patient

enabling a boost in clinical trial enrollment

Enabling a boost in clinical trial enrollment to meet recruitment goals and support the advancement of cancer treatments

learning and improving over time

Learning and improving over time

increasing efficiency

Increasing efficiency through connections across multidimensional, siloed sources

In oncology and clinical trial coordination, you know the odds

3 per cent

of adults with cancer participate in clinical trials

of US clinical trials fail to meet recruitment timelines

1 in 4 statistic

cancer research trials falter due to low patient recruitment

The frustration of recruiting patients for cancer research begins with data — and ends with AI.

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IBM Clinical Development

IBM Clinical Development is a cloud EDC that supports your studies with integrated Medical Coding, ePRO and more.

1 National Cancer Clinical Trials System for the 21st Century: Reinvigorating the NCI Cooperative Group Program,” ncbi.nlm.nih.gov/books/NBK220370.

2 Daniel Garrun, "Clinical trial delays: America’s patient recruitment dilemma," Drug Development-Technology, July 18, 2012, https://www.drugdevelopment-technology.com/features/featureclinical-trial-patient-recruitment/.

3 Go RS, Meyer CM, et al., Journal of Clinical Oncology 2010, 28:15s (suppl; abstr 6069).

4 T. Haddad, J.  Helgeson, et.al., “Impact of a cognitive computing clinical trial matching system in an ambulatory oncology practice,” Presentation at ASCO 2018.