A pre-eminent multidisciplinary endeavour from researchers at the University of Manchester has led to strides towards perfect drug combinations. This breakthrough could aid the recovery of stroke, heart attack and cancer patients.
Researchers were led by Professor Douglas Kell, Professor of Bioanalytical Science at the university, to design a computer program capable of developing ideal drug combinations to quell the inflammatory response of the body’s immune system.
Most non-infectious diseases are worsened by inflammation, which is the body’s natural defence mechanism towards infections. This mechanism can prolong suffering and worsen the damage imposed by long-term diseases. To block this inflammation quickly, for example after a stroke, would greatly alleviate injury incurred by the stroke and increase the chances of survival.
Biosystems specialists and computer scientists worked together to develop software based on an evolutionary algorithm: an algorithm which suggests new drug combinations from previous ones by re-mixing their components. Much like natural selection, it is the best drug combinations which progress to the next stage of testing.
According to Professor Kell: “The new drug combinations are then tested and the best are selected to continue generating new ones. In each experiment we tested 50 drug combinations, then the software would tell us which new ones to test in the next experiment.”
The software rapidly assessed 9 billion drug combinations to determine the most effective, tailored solution. By identifying these ideal drug combinations precision targeting by the drug in the body is enhanced, allowing smaller doses of the more effectively directed drug to be administered, a reduction which minimises toxicology concerns for the patient.
Professor Kell commented: “Most diseases have complex causes. This makes their analysis a problem of systems biology…we have devised a strategy, based on Darwinian evolution, to make this considerably easier. Although our immediate interest is inflammation and conditions such as stroke, our approach is universal and is thus applicable to all complex diseases.”
These distinguished findings undoubtedly highlight the necessity of confluence between several disciplines to develop scientific understanding. The complexities of bioanalytical science and application of software development illustrate that the concept of simple distinct lines easily demarcating the subjects of science is archaic, unhelpful and that these lines have long been broken.
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