SCOPE 2019

Saama adds new AI-based capabilities to its analytics platform

By Melissa Fassbender

- Last updated on GMT

(Image: Getty/Metamorworks)
(Image: Getty/Metamorworks)

Related tags: AI, NLP, machine learning, Clinical development, analytics, Technology

Saama Technologies today unveiled three new machine learning-based capabilities, extending the functionality of its life science analytics cloud.

The new virtual assistant, operational and financial risk mitigation, and drug efficacy and patient safety analytics capabilities were released during the 10th Annual Summit for Clinical Ops Executives (SCOPE) in Orlando, FL.

Saama uses artificial intelligence (AI) across its life science analytics cloud (LSAC) platform “to overcome obstacles historically associated with clinical development,”​ said Amit Gulwadi, senior vice president, clinical innovations, Saama Technologies.

“Each of Saama’s three new capabilities are perfect examples of how AI is being leveraged to enhance various areas of the development experience from the user experience, managing operational and financial risks during study conduct and analyzing key patient data during the trial to enhance patient safety,”​ he told us.

Among the new capabilities is an expansion of LSAC’s deep learning intelligent assistant, DaLIA, which Gulwadi said provides “a unique conversational experience with your data that is more dynamic than using pre-canned analytics dashboards.”

“The significance of the announcement is that DaLIA gets an expansion of its capacity for identifying the intent (what you would like to do or know) of the query and enhancing the level of conversational user engagement,”​ he added.

Additionally, the operational and financial risk mitigation feature now uses AI to predict when key performance indicators (KPIs), such as first site activated, will be achieved. Gulwadi said this eliminates the need for clinical teams to approximate these milestones.

For drug efficacy and patient safety, the new capability “fundamentally changes clinical trial medical monitoring, enabling researchers to identify previously undetectable patient deviations, as well as potential corresponding safety and efficacy issues, sooner than ever before,”​ explained Gulwadi.

With the industry continuing to adopt AI across various aspects of the business, Saama has voiced its commitment to deploying the technology is a targeted and pragmatic way. This means Saama will focus on using AI where “appropriate and beneficial,”​ Gulwadi said, “throughout the layers of its platform to enhance user workflows and generate deeper insights.”

As part of this commitment, the company will be incorporating front-end speech-to-text conversion, among other features to be launched throughout 2019.

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