Tumour necrosis factor alpha (TNFα) is a pro-inflammatory cytokine acting as a promising target for treatment against immune-mediated diseases . Since TNFα is often undetectable in plasma in healthy organisms, pro-inflammatory challengers such as lipopolysaccharides (LPS) are used to induce release of TNFα. These LPS challenge studies are commonly used in drug discovery, and several pharmacokinetic and pharmacodynamic models have been created to describe this stimulatory and inhibitory relationship between LPS and drug in TNFα response data (see for example ). However, many of the current models keep the description of LPS stimulation simple, although LPS challenge studies are confounded by high batch-to-batch and inter-occasion variability [2,3]. It is thus questionable how well the stimulatory effect of LPS in TNFα response data is characterized, which in turn questions the reliability of the pharmacodynamic effects estimated from these models.
The goal with this work is to produce a framework of how to model TNFα response in LPS challenge studies in vivo and demonstrate its general applicability regardless of occasion or type of drug. With this framework we want to:
1) Accurately distinguish the stimulatory effect of LPS from the inhibitory effect of the drug, to get robust and reliable estimates of the pharmacodynamic parameters,
2) Introduce a model structure that considers inter-occasion variability and allows for testing of multiple drugs,
3) Fill the existing knowledge gaps concerning LPS challenge models from a biological perspective.
Poster presentation: https://youtu.be/C6JS1OfDtD4