Pharmaceutical companies spend billions of dollars on developing a new drug. However, only 10-15% of drug candidates pass the clinical stage.
Innoplexus’ Clinical Trial Prediction engine leverages a proprietary domain-specific AI based model trained on millions of data points. Innoplexus can crawl up to 5 billion web pages a day, extracting relevant information into their Life Science AI engine. Additionally, it leverages EOS Blockchain to integrate unpublished data, data behind paywalls and data trapped in silos to discover the deep, dense and diverse data ocean for accelerated drug discovery and development.
“Each trial is assigned a probability of meeting its endpoints. All of this is done on a fully automated, continuous and real-time basis. This is enabling us to assess success probabilities for all ongoing trials - automatically accounting for new information that might impact the probability of a trial meeting its endpoints”, explains Dr. Gunjan Bhardwaj, CEO and Founder of Innoplexus, on how they harness Artificial Intelligence.
One of the funds testing and evaluating the engine’s trial related prediction for investing purposes is Acatis Investment KVGmbH, an asset manager which leverages artificial intelligence to their portfolio management strategies since 2017.
Dr. Hendrik Leber, Managing Director of Acatis Investment emphasizes: “We are evaluating the prediction engine’s capability combined with other regulatory and market information for better stock selection in pharma, biotech space. He mentions that predictions on Biogen’s trial were made correctly by the engine as part of the current evaluation before the actual announcement.”
Besides the most recent Biogen trial, Innoplexus already predicted the outcome of further clinical trials in the past. Thus, the Clinical Trial Prediction Engine already predicted the failure of Bristol-Myers-Squibb’s Nivolumab to treat small cell lung cancer in October 20183, as well as Janssens most recent success in the development of a multiple myeloma treatment at the beginning of December last year4.
The Clinical Trial Prediction engine not just creates high value by supporting investment decisions in the asset management industry, it also supports consultants guiding their clients through M&A decisions. Moreover, it helps pharmaceutical companies and CROs to track clinical trial key performance indicators (KPIs) and optimize their clinical trial recruitment strategies to manage and mitigate operational and financial risks - enabling them to overcome the high failure rates due to missed recruitment targets and dropout rates. Innoplexus empowers companies to make the decisions and course corrections before obstacles delay a trial.