There has never been a probability of success (POS) that is precise enough, accurate enough, and transparent enough to be a key factor in how:
There is such a POS now.
Nobody knows exactly which drugs will work. Diviner calculates the real odds. Along with clear, detailed rationale.
Better than the sharpest KOL, the best drug hunter, or the brightest fund manager.
How? A smart crowd, when leveraged properly, is a better forecaster than the smartest individuals.
Because it is not enough to apply the judgment of brilliant people.
Key opinion leaders, like all people, struggle to recognize their biases – with targets, modalities, approaches in their field of expertise.
And collaborative assessments fail to draw the best wisdom out of their members. The loudest voice in the room, the corporate agenda, groupthink — these all hinder group intelligence.
The science of collective intelligence forecasting has advanced rapidly in the last two decades. Diviner is the first to apply it to drug development. We’ve drawn on the most promising, proven techniques to create a novel, proprietary method. We apply the collective wisdom of our own network of biopharma veterans to assign measurable, precise, testable, transparent probability of success (POS) scores to drug candidates.
Our first use of our proprietary method is forecasting Phase 2 and Phase 3 clinical trial outcomes, measuring our track record, and monetizing the capability.
We forecast the results of new Phase 2 or Phase 3 clinical trials every month. New molecular entities, mostly novel mechanisms, mostly small-cap biotech trials. More than 40 of these trials have now announced results, and the stocks have moved an average of 40% on those results. These are trials with high uncertainty.
While nobody knows which ones will work, we’ve been right a lot more than we’ve been wrong: our accuracy is over 70%.
Below are three examples of the more than 50 forecasts we have made. In each forecast, approximately 20 of our Diviners, averaging 22 years of industry experience, come together to help us assign a probability of success to the trial outcome.
Were these tough trials to predict? Where is the evidence that these forecasts generate value? The Evidence
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