Integrating biomarkers to predict renal and cardiovascular drug efficacy: PRE score applications from drug registration to personalized medicine

The prevalence of chronic kidney disease is increasing worldwide, and forecasts for 2030 indicate that the number of patients requiring renal replacement therapies will more than double. The increase in requirement of renal replacement therapies and the availability of only few proven effective therapies highlight the need to develop new drugs and intervention strategies. In the current drug development and registration process a single renal risk marker is selected and a drug is targeted towards that risk marker. However, there are multiple causes of renal disease that may not all be captured by a single risk marker alone, and drugs have multiple effects beyond the target risk marker (so-called off-target effects). There have been several examples of medications that show a beneficial effect on a risk marker (e.g. blood pressure), but did not improve clinically meaningful outcomes (e.g. myocardial infarction, stroke). Better prediction of drug effects on clinical outcomes may be achieved by risk scores that integrate the effect on multiple risk markers, instead of using single markers alone. In this thesis we determined whether an approach that integrates medication response in multiple risk markers (the so-called PRE score) can be implemented in drug development. We show that the PRE score does a consistently better job at predicting long-term drug effects, compared to using single risk markers alone. The PRE score could be used to provide an early assessment of a medicine’s clinical efficacy and therefore has promising implications for implementation in practice, such as in clinical drug development or regulatory decision-making.