PURPOSE: Drug development in chronic obstructive pulmonary disease (COPD) has been characterised by unacceptably high failure rates. In addition to the poor sensitivity in forced expiratory volume... Show morePURPOSE: Drug development in chronic obstructive pulmonary disease (COPD) has been characterised by unacceptably high failure rates. In addition to the poor sensitivity in forced expiratory volume in one second (FEV1), numerous causes are known to contribute to this phenomenon, which can be clustered into drug-, disease- and design-related factors. Here we present a model-based approach to describe disease progression, treatment response and dropout in clinical trials with COPD patients. METHODS: Data from six phase II trials lasting up to 6months were used. Disease progression (trough FEV1 measurements) was modelled by a time-varying function, whilst the treatment effect was described by an indirect response model. A time-to-event model was used for dropout RESULTS: All relevant parameters were characterised with acceptable precision. Two parameters were necessary to model the dropout patterns, which was found to be partly linked to the treatment failure. Disease severity at baseline, previous use of corticosteroids, gender and height were significant covariates on disease baseline whereas disease severity and reversibility to salbutamol/salmeterol were significant covariates on Emax for salmeterol active arm. CONCLUSION: Incorporation of the various interacting factors into a single model will offer the basis for patient enrichment and improved dose rationale in COPD. Show less
The objective of the investigations described in this thesis was the development of novel PK-PD modelling for the characterisation and prediction of the effects of anti-migraine drugs in clinical... Show moreThe objective of the investigations described in this thesis was the development of novel PK-PD modelling for the characterisation and prediction of the effects of anti-migraine drugs in clinical investigations. The Markov approach has first been applied to migraine data by Hassani and Ebutt. They used a two-state approach that distinguished between headache and no headache. This approach is appropriate for describing the pain free response, but not the pain relief response, as this endpoint would require that an additional state be included. Moreover, this model does not consider a relationship between drug concentration and transition rate. Rather, dose was used as a predictor of pain resolution. Markov models and other state-space models have always enjoyed much appeal in the analysis of disease progression. However, they have seen little application in PK-PD modelling. The current series of studies attempts to evaluate the usefulness of Markov models in determining the PK-PD relationships of 5-HT1B/1D receptor agonists. Show less
