Cell Dynamics Prediction for a Leading Pharmaceutical Company

  • Published: March 28, 2024



Discover how Reveal helped a leading pharmaceutical company identify the right drugs to advance to late-stage clinical trials.


Drug Trials Cost Money & Time

Clinical trials are expensive and take many years. Our client had developed multiple drugs to treat lupus. The clinical trial results of these drugs were mixed. Despite investing several years and significant funds into drug development, they did not have conclusive data to proceed to further stages of the trial.

Using Machine Learning Models to Predict Clinical Outcomes Accurately

After understanding the company’s challenge in detail, Reveal set about training machine learning models. These models were trained to predict primary and secondary clinical outcomes (e.g. renal recovery) at the end of a clinical trial. A novel, neural ordinary differential equations (ODE) model was developed based on early time series data of the clinical trials to predict cell dynamics.

Expected Impact on Clinical Trial

Currently, the Reveal-designed model is being validated in a phase-3 clinical trial. Once it is validated, it will be used by the company for selecting drugs from the pipeline to advance into later stages of clinical trials.