“What our lab is trying to do is to move from screening for these compounds and selecting during the normal pipeline to shift that into actually designing agents based on computational simulations to predict exactly what properties are going to have efficacy in the clinic” Thurber commented.
Thurber and his team are using classic equations for drug delivery and drug transport to understand how the different properties of antibodies and the payloads that they carry impact the distribution and efficacy of the drug product. On the experimental side, the team tests the efficacy of molecular simulation predictions in animal models. They use molecular imaging to track how much drug is getting into a tumor, where it’s going inside the tumor, and what cells the payload is being delivered to.
Importantly, the cycle continues as the researchers then take the results of the animal experiments and feed it back into computational models that will iteratively result in more effective agents. This cycle allows the team to very quickly to screen through thousands of different possibilities very quickly and easily with the computational model select only a few promising agents that will ultimately are predicted to have an impact in the clinic.
According to Thurber the key challenges with ADCs are they are complex agents that require a team of collaborators to bring together all the different design pieces such as protein engineering, monoclonal antibody affinity targeting, and medicinal chemistry. A further complicating factor is the interaction that ADCs have with the immune system and how immunology drives efficacy.
There is a great deal of excitement in the ADC space, with seven drug approvals in the past three years. Prior to this, it took 14 years for the first ADC drug to achieve U.S. Food and Drug Administration (FDA) approval.
“I think there's a lot more that can come from it,” Thurber commented about the ramp up in the number of approvals. “Now that we understand some of the principles that are required to get the effect that.”
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