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The Humane Research Trust is funding a research project at Liverpool John Moores University to develop alternative models for drug testing. The researchers will use in silico techniques to predict the effects of drugs on the body. By validating the results from computer models, they will show how these tools can replace animal testing in drug development.
Drugs need to reach their target site in sufficient concentration to be effective. This journey involves several stages: absorption, distribution, metabolism, and excretion, known as ADME. Pharmacokinetic (PK) studies track these stages to determine how much of the drug is present in the body over time. This provides crucial information such as the maximum concentration in the blood, which is highly indicative of a drug’s effects.
Physiologically based kinetic (PBK) models take this a step further. Such models simulate the concentration of a drug in an organ of interest, such as the drug’s target site. This is essential in drug development, helping to optimise both the drug’s effectiveness and its ability to reach its target. By providing detailed ADME/PK data early in the development process, PBK models ensure only promising drug candidates move forward.
Traditionally, creating PBK models required extensive animal testing. This would include administering drugs to animals and analysing their organs at various time points. The data from such animal studies were then extrapolated to predict ADME/PK properties in humans. However, many scientists are looking for alternatives to these cruel experiments, which often fail to translate to findings that apply to humans.
“In drug development, failure to optimise the pharmacokinetic properties of drug candidates early in the process can lead to late-stage failure,” explains Prof Judith Madden, Professor of In Silico Chemical Assessment at Liverpool John Moores University. “This means animals, time, and money are wasted testing drugs that would never progress to human studies because their pharmacokinetic properties are unfavourable.”
The Humane Research Trust is funding a research project at Liverpool John Moores University to develop human models for drug development using in silico methods. The researchers will use a range of computer modelling techniques to predict the ADME/PK properties of drugs. By comparing the generated data to results from previous studies, the researchers will validate the use of in silico tools to replace animal testing.
Prof Madden and her team of researchers plan to review an existing dataset of PBK models, including around 1,200 compounds. They will identify a class of drugs with well-established PBK models for both humans and animals,. During this process, they will focus on treatments for cardiovascular disease.
The scientists will use a range of technologies to reproduce the human PBK models in silico. This includes quantitative structure-activity relationship (QSAR) models, which predict a drug’s properties based on its chemical structure. They will also apply read-across methods, which use data from similar compounds to make predictions. By comparing the predicted ADME/PK properties with results from previous studies, the researchers can validate the reliability of these in silico methods.
Their goal is to create a validated, animal-free approach that scientists can apply early in drug development. This will save vital time and resources, streamlining the drug development process. They hope to expand this methodology to other drug classes and applications. This has the potential to transform the applications of PBK models in industries ranging from pharmaceuticals to cosmetics.
Prof Judith Madden
Principal investigator
Prof Judith Madden is a Professor of In Silico Chemical Assessment at Liverpool John Moores University. Her research group is focused on developing micro-physiological models of the human body to better understand bodily processes such as tissue regeneration and ageing, including how diseases develop and progress.
Alessio Gamba
Postdoctoral researcher
Alessio is a Postdoctoral Researcher who holds a PhD in Biochemical Sciences and a further academic background in Bioinformatics and Data Science. In his recent work as a computational toxicologist, Alessio has harnessed machine learning techniques and systems biology approaches to investigate the toxicity of chemicals.
