New tech could speed drug development and use fewer mice

Instead of just one antibody, the new technology allows 25 drug candidates to be tested simultaneously in a single mouse. (Credit: Frank Brüderli/UZH)

Researchers have developed a technology that can be used to test around 25 antibodies simultaneously in a single mouse.

New active ingredients such as antibodies are usually tested individually in laboratory animals.

The new work should not only speed up the research and development pipeline for new drugs, but also hugely reduce the number of laboratory animals required.

Many modern drugs are based on antibodies. These proteins very specifically identify a certain structure on the surface of cells or molecules and bind onto it—this may be a receptor protruding from the cell envelope. For antibodies and other protein-based biotherapeutics, extensive preclinical tests need to be conducted on animals before they can be tested on humans.

Currently, antibody candidates are analyzed individually in animal models. A large number of laboratory animals are normally used to conduct each test. This is why preclinical tests account for a large proportion of the animals used in the pharmaceutical industry.

One possible solution would be to test several substances simultaneously in a single animal. However, up until now this method was restricted to a maximum of four active ingredients per animal.

Researchers at the University of Zurich (UZH) led by Markus Seeger from the Institute of Medical Microbiology and Johannes vom Berg from the Institute of Laboratory Animal Science have now managed to overcome this restriction.

“The approach we developed allows us to test 25 different antibodies simultaneously in a single mouse. This speeds up the process and reduces the number of animals required,” says vom Berg. To conduct this study, the team used antibodies that are already approved as a drug or those undergoing clinical development.

Drugs need to have several properties to be successful: the active ingredient is only released slowly and can therefore develop its effect in the body for a prolonged period of time. It binds precisely to a specific target structure and accumulates in the corresponding organ. In addition, the substance only spreads to a limited extent in other tissues and organs, which reduces the risk of side effects.

To allow individual analysis of the properties of the antibodies from the complex plasma or tissues samples from the mice, the researchers developed a form of barcodes. They are made up of defined protein fragments—known as flycodes—that can be used to mark each antibody individually. Once they have been administered to the mouse, the individual antibody candidates can be separated from the mixture and analyzed separately.

“Our results show that the flycode technology delivers high-quality preclinical data on the investigated antibodies. We get much more data with fewer mice and the data is of a better quality because the analyses can be compared directly,” says Seeger.

The researchers also demonstrated that the antibodies find their target structures correctly in the animals’ body: for example, two of the antibodies used in cancer medicine reliably identified the EGF receptor which the tumor cells primarily carry on the surface. The targeted accumulation in the tumor tissue also worked in a mixture with 20 other antibodies. This demonstrates that flycodes do not compromise the efficacy of the antibodies in a living organism.

In addition, the team used flycodes to analyze the properties and data for a series of 80 drug-like synthetic biomolecules—known as sybodies—efficiently in a single experiment.

“Using minimal resources, the flycode technology allows a direct comparison of drug candidates under identical experimental conditions. It is set to advance preclinical discovery pipelines much more efficiently in the future,” says Markus Seeger.

All the data in this study originates from just 18 mice. In principle, this new method can reduce the number of animals required by a factor of up to 100.

The research appears in PNAS.

Source: University of Zurich