Pivotal clinical trials cost an average of $48 million, however, only 10% succeed.  
Clinical trials stand as the cornerstone of medical advancement, a necessary step for any new drug or medical device before it is brought to the market. Yet, traditional methods employed in designing these trials have remained stagnant for over three decades. In the race against time and resource constraints, biopharmaceutical companies and clinical research organisations often find themselves outpaced by the rapid spread of diseases.  

Responding to this pressing challenge, Opyl leverages predictive analytics and machine learning via TrialKey to boost efficiency and reduce both time and expenses associated with clinical trials.  

By utilising AI, specifically GPT-4, to dissect real-world trial data, TrialKey equips clients with: 

  • Access to 65,000+ clinical trials analysed in over 700 variables 
  • Estimates of a trial’s percentage probability of success  
  • Detailed explanations on criteria that comprise the prediction 
  • Actionable insights to optimise trial design 
  • Identification of promising research avenues and closest competitor trials 
  • Detailed timelines and success probabilities for ongoing trials in a specific research area 
  • Access to a pharmaceutical company’s portfolio  
  • Prediction on pharmaceutical inflection points 
  • A clinical trial simulator that allows the facilitation of virtual trials 

Our approach embodies a commitment to ongoing real-world data collection and analysis through AI, furnishing researchers, pharmaceutical companies, and medical investors with factual information and dependable predictions.  

These insights empower stakeholders to make informed decisions, optimise resource allocation, and expedite the delivery of treatments. By leveraging TrialKey’s technology, stakeholders are equipped with the right tools towards smarter decisions, efficient resource management, and accelerated medical advancements. 


Patients become partners in a new digital health research paradigm.