Leveraging data to reduce the cost, time to market and failure rate of the traditional drug discovery process
It is a commonly quoted statistic that the average cost to bring a new drug to market is 2.6bn, and that only 10% of drug candidates make it to market after phase 1 trials.
Given its potential to spot patterns that would take researches significantly longer to do, Artificial Intelligence has the potential to both accelerate and reduce the cost of discovering new drugs.
With that in mind, PharmaIQ Live: Transforming Drug Discovery through AI will be focused on:
Target identification – combing existing data to identify potential drug targets
Compounds – identifying existing compounds that might prove useful, ruling out those with undesirable characteristics and predicting the properties of potential compounds
Data integration – effectively integrating data from disparate sources such as patient data, research papers to identify patterns and opportunities
Enhancing efficiency – by removing the burden of high volume, low value tasks in the lab
Training – upskilling existing drug development scientists on how best to use AI to best effect
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