Periodic Reporting for period 4 - IndiviStat (Individualizing statin therapy by using a systems pharmacology decision support algorithm)
Okres sprawozdawczy: 2022-02-01 do 2023-07-31
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 aimed 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 integrates large amount of data from laboratory, biobank and clinical studies. Overall, the algorithm development proved to be more demanding and required more in-house laboratory data than originally estimated. Therefore, the final stage of the project was dedicated to finalizing the algorithm. The ability of the algorithm to improve adherence will be investigated in patients in the future. If successful, the use of the algorithm 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.
The Project Laboratory experiments produced data on the effects of drug-metabolizing enzymes and drug-transporting proteins on statins, and, additionally, on the pharmacological and toxicological effects of statins. For the first time, comparable data for all statins have been attained, and the experiments resulted in novel findings. The laboratory experiments provided essential data for the systems pharmacology algorithm. In addition, the Project included an observational clinical study that recruited patients who initiated a statin treatment for the first time. The patients were followed up for a one-year period. The data from this study is utilized for modelling purposes in the algorithm. A biobank study was included to the Project to study the effects of genetic variants on statin treatment outcome in a real-world setting. This biobank study investigated, e.g. the roles of certain genetic variants in statin intolerance, and found associations between genetic variants and intolerance to simvastatin and pravastatin. A physiologically based core model has been developed for all statins, consisting of interlinked physiological compartments, allowing the drug to be absorbed and move in the blood circulation to the various organs. The model accounts for metabolism and active transport in the gut and liver, and their changes due to drug-drug interactions and genetic variants. The intracellular liver compartments and the muscle compartment, and the established concentration-response relationships are used to estimate cholesterol-lowering efficacy and risk of muscle toxicity. Several articles, which cover widely the Project results, have already been published and several are currently being prepared for publication.
Systems pharmacology models are increasingly applied in drug development, for example to predict the effects of organ dysfunction on drug concentrations. The IndiviStat Project is among the first to develop systems pharmacology models to guide clinical drug therapy, going beyond the state-of-the-art. The comprehensive research approach of IndiviStat, including laboratory, biobank, and clinical studies together with computer modelling, has generated a vast amount of new data and models that can benefit treatment of hypercholesterolemia and cardiovascular diseases.