Polypharmacy, multimorbidity and genetic heterogeneity can affect drug efficacy, raise the risk for adverse drug reactions (ADRs) and increase healthcare costs. ADRs are among the leading causes of death in developed countries and a major cause of hospitalization. Drug-drug interactions (DDIs) and drug-gene interactions (DGIs) are highly interconnected and require a holistic approach to improve safety of our citizens. However, investigations on real-life drug-drug-gene interactions (DDGIs) in clinical trials are unfeasible due to combinatorial explosion, high costs and ethical concerns. Hence, significant knowledge gaps exist. Furthermore, the lack of participation in managing their conditions might be excessively demanding for polymedicated and multimorbid citizens. SafePolyMed will develop a novel and innovative framework to define, assess and manage DDGIs for physicians and individual patients resulting in education and empowerment of citizens as well as in reduced healthcare costs by improving patient safety. The main objectives of SafePolyMed are (1) development of a novel, evidence-based risk scoring system using machine learning on large realworld datasets to identify patients at risk; (2) identification and validation of patient reported outcome measures for multifactorial patient safety in collaboration with European patient organizations; (3) development of an electronic tool to empower patients by allowing them to properly manage their therapies, check for and educate about DD(G)Is and collect their patient reported outcomes; (4) mathematical modelling of clinically relevant compounds to derive individualized dose adaptations for safe and effective dose regimens in case of DDGIs, accessible via a web-based decision support system with tailored information for either citizens or physicians and (5) validation of the developed safety tools in a ?proof-of-principle? study including representative patient cohorts from different European clinical sites.
The main objectives of SafePolyMed are: ● To increase patient safety and equip HC providers with innovative tools for tackling future challenges of our health systems via the development of a novel, evidence-based risk scoring system using machine learning (ML) on large real-world datasets to identify patients at risk considering polypharmacy, multimorbidity, genetic variations as well as demographic and disease related factors. ● To increase citizen participation and resilience in HC via the identification and validation of PROMs for multifactorial patient safety and a patient engagement hub including training in close collaboration with European patient organisations. ● To empower patients/citizens to proactively manage their own HC by equitably accessible health relevant information via the development of a digital, citizen-centred MMC serving as comprehensive, sustainable knowledge hub in Europe, integrating, harmonising and standardising polymedication data. ● To increase patient safety towards personalised treatment plans in complex pharmacotherapeutic situations via the establishment of a model library of clinically relevant compounds to derive individualised precision dose adaptations for safe and effective dose regimens in case of DDGIs with the help of physiologically based pharmacokinetic (PBPK) modelling techniques. ● To support development and uptake of innovative HC services in Europe via the validation of the in SafePolyMed developed HC tools in a clinical case study, serving as a “proof-of-principle” including representative patients from different clinical sites from different European countries, and providing a blueprint of such participative trials in polymedication.
