Speaker
Description
In traditional pharmacology, dose-response relationships have long been the gold standard for selecting optimal therapeutic doses. Typically, these relationships are monotonic. However, in recent years hormetic, bell-shaped relationships have become more common. This is the case of, for example, bispecific T-cell engager (TCE) drugs, treatments where anti-drug antibodies (ADAs) may act as cross-linkers, or multi-valent molecular targets.
These non-monotonic "hook effects" arise from the unique requirement for complex active structures, such as ternary or higher-order complexes, which are highly sensitive to stoichiometric imbalances. This work demonstrates how mechanistic mathematical modelling can decode the origins of these responses by formulating the kinetics of complex formation through systems of ordinary differential equations.
We explore how different molecular architectures, drive self-inhibition at high concentrations. By simulating the drug-target synapsis, we show that the peak of the bell-shaped curve is a predictable function of the relative concentrations and binding affinities of the molecular species involved. The non-linear nature of these interactions, including non trivial hormetic behaviour, impose a shift towards mechanistic modelling, which can powerfully define the underlying biological drivers rather than describing the observed output, providing an important tool for drug development.
