Researchers develop model to predict side-effects of drugs
If the researchers at University of California, San Diego have their way; soon it will be possible to predict the side-effects of a drug as well as the effectiveness of the said medicine. This group of researchers is reported to have developed a model that could be used to predict a drug’s side-effects on different patients.
What makes this model totally unique is its expected ability to measure the drug reaction of a particular medicine on different patients. As implicated by the one of the researchers professor Bernhard Palsson, side-effects are very personalised. Two different people can take the same drug, but one person might experience side-effects while the other does not,”
“We are not just interested in predicting the efficacy of a drug, but its side-effects as well,” he further reinstated.
The model predicts how variations in different people’s genes impact how they metabolise a drug.
Researchers used data from different people’s genotypes and metabolism to build personalised models that simulate how a drug will affect a particular set of cells in the body.
“This is a unique approach to obtain personalised, predictive and mechanistic descriptions of people’s physiology based on their genetic and metabolic makeup,” Palsson explained.
Researchers said this predictive model would be extremely useful for pharmaceutical companies during the drug development stage.
For example, pharmaceutical companies could conduct predictive screenings for drugs before clinical trials and determine which groups of patients would experience side-effects and which ones would not.
“This study is a step forward in demonstrating that patients could be precisely treated based on their genetic makeup,” Palsson said.
The findings appeared in the journal Cell Systems.
What makes this model totally unique is its expected ability to measure the drug reaction of a particular medicine on different patients. As implicated by the one of the researchers professor Bernhard Palsson, side-effects are very personalised. Two different people can take the same drug, but one person might experience side-effects while the other does not,”
“We are not just interested in predicting the efficacy of a drug, but its side-effects as well,” he further reinstated.
The model predicts how variations in different people’s genes impact how they metabolise a drug.
Researchers used data from different people’s genotypes and metabolism to build personalised models that simulate how a drug will affect a particular set of cells in the body.
“This is a unique approach to obtain personalised, predictive and mechanistic descriptions of people’s physiology based on their genetic and metabolic makeup,” Palsson explained.
Researchers said this predictive model would be extremely useful for pharmaceutical companies during the drug development stage.
For example, pharmaceutical companies could conduct predictive screenings for drugs before clinical trials and determine which groups of patients would experience side-effects and which ones would not.
“This study is a step forward in demonstrating that patients could be precisely treated based on their genetic makeup,” Palsson said.
The findings appeared in the journal Cell Systems.
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