Periodic Reporting for period 1 - SafePolyMed (Improve Safety in Polymedication by Managing Drug-Drug-Gene Interactions)
Período documentado: 2022-06-01 hasta 2023-11-30
To analyse free text in the RWD, natural language processing was applied for data analysis, and dictionaries, query lists as well as fact extraction pipelines were established to extract information on treatment outcome or ADR from the free text.
To increase overall citizen participation in health care, SafePolyMed aims to develop PROMs regarding patient safety as well as patient training in cooperation with patient organisations. Therefore, a patient engagement hub (PEH) was established, involving patient organisations with different fields of expertise. The PEH will be consulted throughout the project to ensure that patients are actively engaged and that the developed tools effectively consider patients’ needs.
For the development of safety PROMs, an initial list of side effect symptoms was curated based on symptoms reported in clinical studies conducted by the polypharmacy outpatient clinic of partner UKA and in the real-world databases available to partner UTARTU. Within a currently ongoing DELPHI process, a final set of relevant PROMs will be selected from the list of symptoms by patients and healthcare professionals.
In collaboration with the PEH, the content for a patient training curriculum has been defined that has the overall aim of educating patients on actively managing their polymedication. The training addresses D(D)GIs, side effects, regulatory aspects, GDPR and patient-led evidence generation.
The foundation for the development of the MMC was laid by specifying the architecture of the system and its core components and main use scenarios. Here, the patient's perspective and needs were taken into consideration, using a user-centered approach. Based on these specifications, a vertical prototype of the MMC as well as a user interface were established.
Compounds for mathematical modelling were selected based on information derived from real-world data and literature analyses. PBPK models of mirtazapine, atorvastatin, methotrexate as well as amitriptyline and nortriptyline are currently under development. PBPK models of carbamazepine, metformin, tacrolimus, simvastatin and rosuvastatin are readily available in the PBPK model library of USAAR and will be refined to describe SafePolyMed-relevant DD(G)I scenarios.
Overall, SafePolyMed aims to develop a framework to empower citizens, focusing on improving citizen education and their understanding of complex drug therapies, as well as to improve exchange between citizens and healthcare professionals.
The development of respective novel tools is currently ongoing. To ensure future uptake and success of the developed tools, considering the patient’s perspective and needs is substantial. Therefore, a patient engagement hub has been established which will be consulted throughout the project to ensure that the innovative tools consider relevant aspects and are easy to use.