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Translational quantitative systems toxicology to improve the understanding of the safety of medicines - Sofia: 116030

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Gaining new insights into drug-induced toxicity

Many drugs cause unexpected toxicity when reaching human clinical trials, so scientists are integrating computer modelling to better predict when this might happen.

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Creating new drugs is difficult. The overall success rate is low: Only around 10 % of new candidates eventually make it to market. One reason behind this is adverse effects – such as toxicity – that can happen unexpectedly when drugs reach human clinical trials. “Very often a side effect will occur in the first in-human studies, which would have been entirely unpredictable,” explains Christopher Goldring, chair in Pharmacology & Therapeutics at the University of Liverpool and TransQST project academic coordinator. In the EU and industry-funded TransQST project, scientists developed an innovative approach to predicting potential toxicity from candidate drugs, which incorporates in vivo data with advanced computer modelling. TransQST, a public-private consortium involving 23 partners, set out to show that this kind of modelling could improve both the speed and safety of developing new drugs.

Challenges of drug development

Most preclinical trials rely on animal studies, which carry ethical implications and aren’t a perfect match for human testing. Predicting individual human responses to a new drug is also very difficult. And when testing a candidate drug for the first time, researchers must figure out what the optimum dose is – to give maximum efficacy while avoiding toxicity. “For the people carrying out the first in-human trials, the very first tests of a new agent, it’s historically been extremely difficult to elucidate what the first dose will be,” adds Goldring.

Predicting toxicology in key organs

Striving to overcome these challenges, the TransQST project focused its efforts on gathering new data on four organs most commonly affected by toxicity: the heart, liver, kidneys and gastrointestinal (GI) system. “There is a major problem of toxicity in the GI tract,” Goldring adds, though prior to this project there was a lack of data for potential toxic reactions there. “So for the GI system, we used very modern approaches, to begin to tackle this issue of how to try to predict toxicity in the GI tract,” he says. The team used a cutting-edge organoid model, in which tissues can be grown from just a few adult-derived stem cells in the laboratory. This allowed them to test their new modelling approaches on different parts of the GI tract, including the intestine and stomach. Through these approaches, the project was able to both improve on existing models for drug testing, and develop a range of new ones. Beyond this achievement, the TransQST project also gathered vast amounts of data to support the creation of new tools. These tools can identify, quantify and predict potential toxic mechanisms in candidate drugs, and are now being tested by consortium partners from the pharmaceutical industry in drug safety assessments. All the models, tools and data from the project have been made openly available and can be accessed through the TransQST website.

Building on a successful collaboration

The team hopes that a key legacy of the project will be a new European training network for toxicology, as the project revealed that more scientists are needed in this field. “Some of our pharma companies are really interested in building on our efforts in this area,” he notes. Goldring praises the successful involvement and collaboration of so many different partners, from universities, hospitals, research centres and pharmaceutical businesses. It was a: “really healthy, very dynamic, very collaborative, cooperative mix of scientists from the pharmaceutical companies, and other leading academics across Europe,” says Goldring. “I think it will act as a catalyst for positive change in the nature of drug development.”


TransQST, drug, development, model, computer, consortium, toxicology, organs, gastrointestinal tract

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