Predicting oral bioavailability is better with AI says PharmaInformatic

By Gareth Macdonald

- Last updated on GMT

AI-based tech offers more accurate bioavailability predictions. (picture credit London Weekend Television)
AI-based tech offers more accurate bioavailability predictions. (picture credit London Weekend Television)
Artificial intelligence can aid lead optimisation according to the German firm behind a new structure-based drug oral bioavailability prediction technology. 

In popular culture artificial intelligence is more often associated with homicidal robots, self-aware computer systems hell bent on global destruction or defeated chess grandmasters than positive health outcomes.

But in the real world AI is a force for medical good according to Wolfgang Boomgaarden from PharmaInformatic, who told us his AI-based IMPACT-F system helps drugmakers identify candidates with the best oral bioavailability profiles during lead development.

IMPACT-F is an in-silico method which solely needs the compound structures of interest to forecast oral bioavailability in humans​” said Boomgaarden, explaining that the system is based on an extensive database of drug bioavailability information he put together.

That knowledgebase took 10 years to develop. I applied different methods from AI technology such as neural networks or decision trees to develop predictive models. At the end I combined the best models and that yielded to the expert system IMPACT-F​.”

Boomgaarden claimed the system is more accurate than animal model-based bioavailability predictions, explaining that: “Often animal drug-uptake is used to predict human outcome, but there are large differences in human and oral bioavailability​.”

Cost saving

The other advantage for drug developers is cost according to Boomgaarden, who said: “Since it is a structure based approach, no additional costs such as assays, further experimental tests or compound synthesis are needed​.”

At present Emden, Germany-based PharmaInformatic provides IMPACT-F as a service, using the technology to assess structural diagrams of candidate compounds provided by customers in the pharma, biotechnology and contract research sectors.

However, a licensing model is planned according to Boomgaarden, who said: “In future, customers can do the calculations in-house, so they do not have to disclose compound structures.​”

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