How AI is combating pharmaceutical waste

For every one kilogram of drug production there is 25 to 43 kilograms of waste left behind according to the European Union Drugs Agency.

How is it that AI can stop that waste and make drug testing more effective?

Well a new AI platform called Heisenberg which was launched on the 12th of February is trying to battle the problem. Developed by Famous Lab, a small molecule drug discovery company.

Heisenberg was created and designed to assist the drug discovery teams in reducing experimental waste, prioritising discovery, new ideas and speeding up processes whilst learning from each experiment.

So AI is testing what experiments and drug tests are the most efficient, costly and amount of time needed on them which impacts whether a drug program will advance or not.

Ryan Noorbehesht, Head of Molecular AI at Famous Labs and founder of the Heisenberg platform said: "Chemistry super intelligence won't come from scaling molecular volume in silico.

It will come from learning more from each synthesis. By combining quantum-derived molecular insight with large-scale chemical reasoning, Heisenberg enables a form of chemistry super intelligence defined by context, speed, and learning efficiency."

The system is able to do drug testing at an atomic level and know its molecular geometry. Meaning we are able to look at a molecule like lets say H2O (water).

Using molecular geometry software like Heisenberg we would be able to see the H2O's bond lengths, angles of the bond and the atoms within the molecule.

This process is called electron-density-derived molecular where Heisenberg is able to layer and represent the molecules in its images back to the drug testing team by also using the traditional fingerprint space.

This new AI is able to expand more on chemical spacing plus a physics-native axis too. Meaning tiny quantum information from the atoms can directly influence which molecules should be used and not be used in the next drug trail.

Each testing carried out is to either reduce uncertainty, answer a specific scientific question or confirming a hypothesis so that a programme of testing can advance.

Therefore there may be some good to what AI can do for the pharamasitical space and if it is able to reduce waste plus keep costs down it seems like the better thing to do.