Clinical Trial Simulation in Drug Development

Abstract

The simulation of therapeutic models and clinical trial simulation have recently attracted attention as emerging techniques for developing new active molecules and the exploration of possible clinical trial results. Such approaches have benefited from fundamental progress in the development of 'in silico' models, as well as progress in nonlinear mixed-effect pharmacokinetic-pharmacodynamic models. Mixing the two approaches allows simulation of 'virtual' patients, who receive virtual treatments or placebo. These have various uses, such as proof of concept, decision analysis or experimental design optimisation. Also, the effect of departures from protocol on clinical trial results can easily be evaluated by the use of simulation. This technique is now implemented by the pharmaceutical industry for optimising phase II and III experimental designs when a good biomarker or a clinical outcome model is available, but the use of an in silico therapeutic model as a proof of concept is only just beginning. In order to see such methodologies used more widely in drug development, multidisciplinary efforts need to be initiated, new modelling and simulation tools developed, and sound modelling and simulation practice documents need to be adopted. A reduction in the number of failed clinical development projects, the number of negative phase II and III clinical trials, or in just their cost and duration, are among the expected benefits of modelling and simulation in clinical drug development.

A computational multiscale agent-based model for simulating spatio-temporal tumour immune response to PD1 and PDL1 inhibition

“…If such models have been developed by other laboratories, they can be incorporated into the present model via readily available interfaces; otherwise these modules have to be built de novo and connected to the core model. Particularly, with the implementation of PK/PD modules and rigorous model calibration and validation, the model can be used as a platform for in silico drug discovery and conducting virtual clinical trials [ 62 ].…”

Exploring different approaches to improve the success of drug discovery and development projects: a review

“…Pharmacodynamic and pharmacokinetic models are used to predict optimal dosage levels in the various phases of clinical trials as well as in special populations including pediatrics, geriatrics, pregnant women, and others with constrained physiological conditions that will impact on drug disposition. The application of modeling improves the effectiveness of clinical trials with enormous cost and time saving [89,90]. Successful application of computer-based drug design is exemplified by several drugs in clinical use including nelfinavir, imatinib, zanamivir, saquinavir, and norfloxacin [91].…”

Critical Considerations about Clinical Trials Simulation

“…[30,31] Recent years have seen tremendous advances in CTS at large, [32][33][34][35][36][37] even to the extent of impacting on multimodal areas of clinical trials, [38,39] such as medical devices, [40] training by virtual reality [41,42] and medical historical analysis. [43][44][45] Currently CTS addresses several aspects of drug innovation and development, [46][47][48] such as dose selection, [49][50][51][52] vaccine responses, [53] cost effectiveness, [54][55][56][57][58][59] therapeutic endpoints, [60][61][62][63] sample-size recruitment/drop-outs, [64][65][66][67][68] paediatrics enrolment, [69,70] AIDS cocktail drugs [71,72] and logistics/supplies. [73] …”