Remarkably, the far reaching impact of chaos in MD has not been widely recognised. The book by Leimkuhler and Matthews is notable because it does pay attention to chaotic behaviour, although it does not address the impact of dynamical chaos on uncertainty quantification. The only way to deal with this feature is to use ensemble based approaches which ensure the statistical reproducibility of results. Although when we first advocated these methods we encountered resistance, it is noticeable that many practitioners now acknowledge that results based on one-off simulations may be grossly unreliable * and it is becoming more common to read of authors performing several "repeats" of calculations in order to estimate the uncertainty in their results (often without recognizing our previous work in this context). For instance, Groot et al. perform 3 repeats in their recent free energy estimation studies. On the other hand, the same authors (the set of people common in all these studies) advocate 20 repeats when studying the effect of box sizes on thermodynamic properties which betrays a lack of consistency and systematic approach in addressing uncertainty estimation. Indeed, for not unrelated reasons we are still not at a stage where RBFE methods can be routinely applied with confidence in the pharmaceutical industry let alone by clinicians to predict drug resistance in personalised medicine. There are many associated factors that need to be addressed in order to ensure that these methods can be employed in a routine fashion by end-users. Quality of force field and ligand parameters, choice of alchemical region and the topology scheme (single, dual or mixed), handling of charge-changing transformations, protein starting structure, ligand pose placement, tautomerisation and ionisation states are all issues that affect the quality of results.