Objectives: Quantification of pharmacodynamic (PD) drug interactions is challenging. When reviewing current approaches, published PD interaction models [1] display several…
Read moreOral: Methodology - New Modelling Approaches
A liver model for chemoprotection against malaria
Introduction: Chemoprotective drugs are developed to protect people from being infected by plasmodium, and in particular by P. falciparum, the…
Read moreIdentifiability of Population Pharmacokinetic-Pharmacodynamic Models
Background: Mathematical models are routinely used in clinical pharmacology to study the time course of concentration and effect of a…
Read moreHandling frequent observations of composite scores: Application to PROs in COPD
Objectives: Chronic obstructive pulmonary disease (COPD) is an inflammatory disease of the lung, characterised by not-fully reversible airflow obstruction that…
Read moreSimplification of multi-scale systems models for data-driven analyses: what has progressed in these 5 years?
Objectives: Bridging multi-scale systems models and pharmacometrics has resulted in models that are highly complex and often not amenable to further…
Read moreBeyond disease progression – Item response theory modelling to gain structural insights into disease facets underlying clinical score assessments
Objectives: Diseases are commonly multifactorial, complicating the choice of appropriate diagnostic and clinical endpoints. Clinical scores, often summarised to composite…
Read moreRelationship between the dose of therapeutic antibodies and the inhibition of cytoplasmic and nuclear growth factor signalling
Objectives: Inhibition of growth factor signalling is a promising strategy in cancer treatment because of the importance of such signals…
Read moreModelling of classified individual tumor lesions in metastatic colorectal cancer (mCRC) patients using delay differential equations.
Objectives: Standard practice in pharmacometrics applied to oncology since publication of the Claret’s paper [1] has been to model the relationship…
Read moreA strategy for residual error modeling incorporating both scedasticity of variance and distribution shape
Objectives: Implement a new error modeling strategy including dynamic transform both sides [1,2] with dynamic scedasticity (dTBS) and t-distributed residuals…
Read moreModel-based analyses for pivotal decisions, with an application to equivalence testing for biosimilars
Objectives: In a drug development context, non-linear mixed effects models (NLME) are routinely used for exploratory analyses. These methods are…
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