The project focused on advancing smart implant technology by integrating battery design, mechanical modelling, and data management into a unified framework. A key technical achievement was the creation of a generic, object‑oriented data format implemented in MATLAB, named “Inputclass.m.” This format consolidates battery metadata, raw test data from diverse systems (Maccor, Basytec, and in‑house BTS and QSI devices), and processed data generated by built‑in methods. The data‑processing pipeline includes a Data‑Set‑List‑Reader that ingests metadata, a BatTestData‑Reader‑Lib that links raw files to this metadata, a Pulse Cutter that extracts discrete pulse events, a Pulse Fitter that parametrises equivalent circuit models, and a Char Val Extractor that produces data extracts for downstream analysis. The resulting structured dataset enables consistent comparison across different designs and production batches.

Parallel to test‑data handling, the team developed a generic “DataMart” for manufacturing and usage data. This mart stores only essential identification fields for the implant and its battery, allowing on‑demand retrieval of detailed production parameters such as serial numbers, model numbers, and process measurements. For usage data, the DataMart accommodates all active implant types—including ICDs, IPMs, and ICMs—by organising information into user, message, therapy, battery, and implant categories. The integration of manufacturing process data from Litronik, which records numerous process‑step measurements during battery fabrication, demonstrates the system’s flexibility. By linking these process metrics with in‑field usage data, the project enables a comprehensive assessment of how production variations influence long‑term performance.

The scientific scope extended beyond data handling. Structural‑mechanical modelling of the battery as part of the miniaturised implant geometry was performed, allowing numerical simulation of mechanical behaviour under worst‑case scenarios. Micro‑structural analysis of battery compartments examined ageing and discharge state effects, while material studies evaluated anti‑inflammatory packaging and coatings. An adhesion assay using human monocytic THP‑1 cells co‑cultured with endothelial EA.hy926 cells assessed haemocompatibility. Results indicated that none of the tested materials exhibited increased inflammatory potential, and Sirolimus‑enriched coatings produced a measurable positive effect on cell adhesion, suggesting reduced thrombosis risk without compromising implant function.

The project was carried out under the umbrella of the RESPONSE programme, specifically the “Smart Implants” initiative (Forschungsvorhaben 16A). Funding was provided by the German Federal Ministry of Education and Research (BMBF). Collaboration involved multiple partners: Biotronik supplied test data and expertise in implant design; Litronik contributed manufacturing process data and validation of the DataMart; academic partners developed the data formats, ETL processes, and mechanical simulations. The effort spanned roughly two years, from 2017 to 2019, and was structured to bridge the entire value chain—from concept to clinically deployed medical device—while addressing regulatory and quality‑assurance requirements.

Overall, the project delivered a robust, reusable data infrastructure that unifies experimental, manufacturing, and clinical data for active implants. Coupled with advanced mechanical modelling and biocompatibility testing, these results lay the groundwork for safer, more reliable smart implants and provide a scalable platform for future research and development in the field.