Regardless of the options for the use of M&S by regulatory guidelines, empiricism still plays a main role in drug development. As recently shown by our group, a keyword-based search performed on 95 European Public Assessment Reports reveals that only 22 out of the 95 documents analysed refer to the usage of M&S methodologies. Furthermore, these EPARS do not include keywords, such as biosimulation, PKPD modelling or clinical trial simulation. Modelling and simulation In addition for the insight into the underlying pharmacological mechanisms and dynamics of a biological system, M&S also enable the assessment of important statistical elements. The integration of these elements is currently known as pharmacometrics. In pharmacometric research, three important components are characterised, namely: a drug model, a disease/placebo model and the implementation model . Whilst modelling enables translation of the relevant features of a system into mathematical language , simulation allows the assessment of a system’s performance under hypothetical and real-life scenarios , yielding information about the implication of different experimental designs and quantitative predictions about treatment outcome, dosing requirements and covariate effects kinase inhibitors . In this regard, the great advantage of using M&S in paediatric drug development is the possibility of exploring relevant scenarios before enrolling children into a clinical protocol. Simulations allow evaluation of a range of parameter values , including an assessment of critical scenarios, such as overdosing, that cannot be generated in real-life studies . Most importantly, it enables systematic assessment of the impact of uncertainty. Modelling and simulation can be used not only as a learning and decision-making tool, but also as a design optimisation and data analysis Sodium valproate tool. Consequently, it can support the selection of candidate drugs and streamline decisions regarding first-time human, PKPD and safety/efficacy clinical studies . Furthermore, great attention is being paid to study design before the implementation of an experiment or clinical protocol. In brief, M&S can be applied to the development of a new drug from the first steps in discovery to the approval stage. Later in therapeutics and clinical practice, M&S can guide dose adjustment for specific subgroups of a population and enable the evaluation of the implications of relevant factors, such as treatment adherence, changes in formulation and drug combinations . Like all sciences, best practices should be followed when performing M&S. To fulfil this objective the following issues must be clearly defined a priori: 1. The objective of the M&S exercise 2. The criteria for data selection and the exclusions or limitations of the dataset 3. Assumptions and rationale for model selection or simulation features 4.