Predict clinical trials with AI

The clinical trial prediction (CTP) engine empowers your decision-making

Predict the probability of
clinical trial success

investment decisions

Track clinical trial KPIs and identify critical path

Leverage AI to predict clinical trial outcomes

There are a lot of statistics about drug development – and all of them show that the process is inefficient and expensive:

  • Pharma companies spend more than USD 1 Billion on developing a new drug
  • Drug candidates pass the clinical stage with a success rate as low as 10-15%
  • Of all US clinical studies, 86% fail to meet the recruitment targets on time
  • Dropout rates of clinical trials commonly range between 15-40%
  • Of failed trials, 57% show limited efficacy; poor statistical endpoints or underpowered samples

However, clinical trial failures can be modeled by applying Artificial Intelligence techniques on real-world, outside-trial, and biomedical data sets. Innoplexus’ Clinical Trial Prediction engine leverages advanced deep learning techniques trained on publicly available trial data as well as on real-world events that are continuously crawled, aggregated, and analyzed by our proprietary technology.

The CTP engine serves various stakeholders keen on the prediction of clinical trial outcomes

Investment Management

A pharma or biotech company’s stock performance depends heavily on the outcome of its pipeline. Prior knowledge of approval probability of a trial can help investors gain an edge!

Life Science

CTP helps CROs, pharma, and biotech companies to track clinical trial KPIs, optimize their clinical trial recruitment strategies, and mitigate operational and financial risks. CTP empowers companies to make the decisions and course corrections before obstacles delay a trial.

The CTP engine leverages advanced AI and analytics technology

Advanced deep learning techniques trained on publicly available trial data and real-world events that are continuously crawled, aggregated, and analyzed by Innoplexus’ proprietary technology.

A neural network trained on various drug compound characteristics, clinical trial features, and sponsor track records, provides insights for optimizing study designs.

Fully automated, continuous, and real time analysis enables Innoplexus to calculate predictions by accounting for new information which might impact a trial endpoint.

We connect more than 350+ attributes based on our life science data ocean




Clinical Trials






Congress Articles




Chemicals & Drugs


Theses & Dissertation

  • World´s largest Life Science Ontology with 31M+ biomedical terms
  • Connecting drugs, indications, study design, trial information, patients, authors, and sponsors with real-world events
  • Structuring unstructured data
  • Real time predictions

Experience more Aha! Moments

Experience the power of artificial intelligence and continuous analytics as a service through our platforms. Book a free online consultation today and start developing your custom solution.

Download Technology Capabilities