University of Hyderabad researcher develops new drug model that provides better results, faster recovery

Hyderabad: Ever wondered why the medicine you take does not often give the desired result? However potent a drug is, its action on the body depends on what scientists call bio availability, or the ability of the drug to be absorbed in the body. Many medicines have poor bio availability and now a researcher from the University of Hyderabad has developed a new accelerated model that will help increase bio availability. This will help the body to use most of the drug for better results and faster recovery.

Prof Ashwini Kumar Nangia of the department of chemistry at the University of Hyderabad said 80 per cent of drugs formulated as tablets or capsules suffer from poor bio availability. This is because of their low solubility and or low permeability.

Even during clinical research, 90 per cent of the pharmaceutical lead compounds show a low bio availability.

Taking this concern, Prof Ashwini Kumar carried out research on how to overcome the problem of low bio availability and make the medicines to be fully absorbed and available to the body.

The result of the research study on the novel approach to accelerate the discovery and development of high bio availability drugs was published as a scientific perspective in Wiley international journal, Angewandte Chemie, of the German Chemical Society.

According to Prof Ashwini Kumar, in order to address overcoming the bioavailability challenge in drug molecule lead discovery and optimization of a marketable formulation, the new model proposed by him invoked the supramolecular hetero-synthon in addition to the molecular pharmacophore.

"By refining both molecular functional groups and hydrogen bonding synthons, with the latter imparting high solubility and permeability in the same molecule, the overall drug discovery cycle will be accelerated compared to the traditional two stage process. By searching drug molecules and crystal structure databases and culling the voluminous data using artificial intelligence and machine learning tools, a medicinal chemist should be able to rationally sift the structural information and reach the target drug molecules of high bio availability more efficiently and with higher success rate," he said.