CIT - AI

Cancer Immunotherapy Treatment Response Using Artificial Intelligence

Our goal is to leverage genomic and histopathological data to develop predictive models of response to immunotherapy for these cancers even before commencing treatment.

The techniques to be employed include state of the art machine learning methodologies for pre-processing of the high dimensional data, imputation of missing values and for the discovery of patterns or motifs related to cancer relapse or recurrence. In addition to the machine learning predictive tools, a user-friendly graphical user interface (GUI) for the developed software tools will be made according to the specifications of existing software platforms and user specifications.

Our Platform will serve as a decision support tool for cancer clinicians and allied medical professionals

We are currently at the Proof of Concept stage.

Leveraging anonymised immunotherapy patient data:

  • Genomic - Transcriptomic, epigenomic, proteomic, metabolomic.

  • We already have proprietary immunotherapy patient data and will be collecting more data.

Predictive Model Development:

  • By our in-house machine learning specialists

  • Collaboration between AI engineers and oncologists

  • Validate with our NHS partners

Graphical User Interface (GUI):

  • Simple and easy-to-use software tools 

  • Quick clinical roll-out of our product