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Individualizing statin therapy by using a systems pharmacology decision support algorithm

Periodic Reporting for period 2 - IndiviStat (Individualizing statin therapy by using a systems pharmacology decision support algorithm)

Reporting period: 2019-02-01 to 2020-07-31

Statin drugs are widely used in the treatment of hypercholesterolemia. Although statins are effective and safe in most patients, many users experience poor or no efficacy and adverse drug reactions. Major factors contributing to this variability in drug response include differences in individual characteristics such as genetics, sex, age, weight, renal function, and concomitant medications. The IndiviStat project aims to develop a systems pharmacology algorithm considering these factors to predict statin response in individual patients, and to investigate whether selecting the statin based on the algorithm improves treatment adherence. The algorithm will integrate data from laboratory, biobank and clinical studies. In the final stage of the project, the ability of the algorithm to improve adherence will be investigated in patients. If successful, the IndiviStat project may significantly increase patient adherence to statin therapy and improve the overall efficacy and safety of cholesterol-lowering therapy, thus preventing cardiovascular morbidity and mortality.
Laboratory experiments are ongoing and expected to finish within this year. These experiments examine the effects of drug-metabolizing enzymes and drug-transporting proteins on statins, and, conversely, the pharmacological and toxicological effects of statins. For the first time, comparable metabolism data for all statins have been attained, and transport experiments have resulted in novel findings. Preliminary systems pharmacology algorithms for fluvastatin, rosuvastatin and simvastatin have been developed. An observational clinical study in patients is active, but recruitment of new subjects is temporarily on hold due to the COVID-19 pandemic. Biobank data is currently under analysis.
Systems pharmacology models are increasingly applied in drug development, for example to predict the effects of organ dysfunction on drug concentrations. If successful, the IndiviStat project will be the first to use systems pharmacology predictions to guide clinical drug therapy, thus going beyond the state-of-the-art. The comprehensive research approach of IndiviStat, including laboratory, biobank and clinical studies together with computer modelling, can be expected to generate a vast amount of new data that may benefit treatment of hypercholesterolemia.