Clinical trial simulations of the interaction between cannabidiol and clobazam and effect on drop-seizure frequency.

With this study, we aim to test the hypothesis that the effect of cannabidiol on drop-seizure frequency in patients with Lennox-Gastaut syndrome and Dravet syndrome could be attributed to a drug-drug interaction with clobazam. We performed clinical trial simulations for the effect of 20 mg/kg/day cannabidiol on drop-seizure frequency in patients with Lennox-Gastaut syndrome. We assumed that patients taking 10 or 20 mg clobazam would have a 2- to 7-fold increase in N-desmethylclobazam exposure, whereas patients not taking clobazam would have a median reduction in drop-seizure frequency and a variability in the percent reduction similar to the placebo group.

Population pharmacokinetic-pharmacodynamic modelling of the relationship between testosterone and prostate specific antigen in patients with prostate cancer during treatment with leuprorelin.

Aims: This investigation aimed to quantitatively characterize the relationship between the gonadotropin-releasing hormone agonist leuprorelin, testosterone (T) and prostate specific antigen (PSA) concentrations over time, to aid identification of a target T concentration that optimises the balance of the benefits of T suppression whilst reducing the risk of side effects related to futile over-suppression.

Methods: Data from a single dose study to investigate the effect of leuprorelin in a 6-month depot formulation on T and PSA in prostate cancer patients were analysed using a population pharmacokinetic-pharmacodynamic modelling approach. The developed model was qualified using external data from 3 studies, in which the effect of different formulations of leuprorelin on T and PSA was evaluated in prostate cancer patients.

The application of mathematical modelling to the design of bispecific monoclonal antibodies.

Targeting multiple receptors with bispecific antibodies is a novel approach that may prevent the development of resistance to cancer treatments. Despite the initial promise, full clinical benefit of this technology has yet to be realized. We hypothesized that in order to optimally exploit bispecific antibody technology, thorough fundamental knowledge of their pharmacological properties compared to that of single agent combinations was needed.

Development of a restricted state space stochastic differential equation model for bacterial growth in rich media.

In the present study, bacterial growth in a rich media is analysed in a Stochastic Differential Equation (SDE) framework. It is demonstrated that the SDE formulation and smoothened state estimates provide a systematic framework for data driven model improvements, using random walk hidden states. Bacterial growth is limited by the available substrate and the inclusion of diffusion must obey this natural restriction.