Introduction/Objectives: Quantitative Systems Pharmacology (QSP) models aim at offering a detailed mechanistic understanding of the biological processes underlying health, disease…
Read morePoster: Methodology - New Modelling Approaches
Incorporating complex drug PK with multiple binding targets into a QSP model to predict combined PD effects
Objectives: More antibody drugs are being made in di- and trimer forms to bind multiple targets in a pathway or…
Read moreStructural model development with compartmental pharmacokinetic models for a range of small molecule subcutaneous data
Objectives: The development of pharmacokinetic (PK) and pharmacodynamic (PD) models demands considerable time from highly skilled scientists, and the need for…
Read moreA modelling framework for in vitro/in vivo translation of PROTACs PK/PD and PK/Efficacy: accelerating drug discovery of targeted protein degraders
Objectives: PROTACs [1] are novel small molecules which violate not only the optimal, well-understood physicochemical design space [2], but also…
Read moreAn integrated modelling approach for targeted degradation: insights on optimisation, data requirements and PKPD predictions from semi- or fully-mechanistic models and exact steady state solutions
Objectives: This work proposes a novel pragmatic modelling approach for targeted protein degradation which captures the essence of the mechanism…
Read morePopulation pharmacokinetic modelling for vancomycin using Bayesian model averaging approach
Introduction: Vancomycin has been used as a first-line standard treatment against methicillin-resistant Staphylococcus aureus for over 60 years [1]. More…
Read moreComparative Study of Target Mediated Drug Disposition Approximation Methods Based on Validity Conditions: Application to Clinical Trial Studies
Objectives: Target-Mediated Drug Disposition (TMDD) is a phenomenon that occurs when a potent and specific drug binds to the target site…
Read moreNon-linear autoregressive exogenous modelling to predict individual haematotoxicity during chemotherapy
Objectives: Cytotoxic cancer therapies frequently result in severe haematotoxic side-effects. Predicting a patient’s haematologic response to treatment is of high…
Read moreCombining biological knowledge and machine learning for predicting dynamics of haematotoxcity after chemotherapy: a comparative analysis
Objectives: Cytotoxic treatment in cancer therapy is frequently accompanied by dose-limiting haematotoxic side-effects. Predicting an individual’s risk holds significant clinical…
Read morePredicting Motor function scores using uHex4 biomarker effect in Pompe disease
Objectives: Text regarding objectives. Methods: Text regarding methods. Results: Text regarding results. Conclusions: Text regarding conclusions. References: [1] Text for…
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