Life Sciences

AI investments are yielding strong returns for life sciences organizations, from expediting drug discovery and clinical trials to personalizing telemedicine. In biomedical and healthcare applications, Modzy allows organizations to leverage trusted, explainable AI solutions.

Look to Modzy’s secure platform to power AI-enabled applications with embedded explainability and governance 

From enterprise healthcare applications, drug discovery, personalized medicine, automating back office processes and more, AI is transforming the life sciences industry. Now is the time for organizations need to ensure that they can trust the AI powering critical applications and decisions, which is why Modzy’s patent-pending explainability solutions ensure results you can trust.

AI is Powering Transformations within Life Sciences


With a 10-20% rise in adverse event reports each year, manual review is too slow and expensive. AI offers a better way to quickly assess incoming information, and identify and prioritize the right path forward, all while yielding cost savings and improving overall response.
  • Extract and classify critical data to assess events
  • Expedite processing, reporting, and predicting
  • Enable real-time detection of safety signals to enhance patient safety and minimize risk


Even the best AI won’t see the light of day if users don’t understand how it makes predictions. Explainability offers insight into how an AI-enabled decision was reached, providing transparency and trust into the process.

  • Provide insight into how your AI models make predictions
  • Establish trust with users by embedding explainability throughout all AI deployments


Improving how and when cancer and other illnesses are diagnosed can alter the course of a patient’s life. Deep learning and image classification models are already transforming image-based diagnostics, due to AI’s ability to identify patterns or anomalies hidden in large troves of data faster and more accurately than humans ever could.

  • Detect medical conditions and make recommendations to physicians for potential course of treatment
  • Combine disparate data across doctors’ notes, pathology reports, operating notes, etc. into unified patient profiles to identify potential patients as good fits for match trial criteria

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