e:Med PG Data Security and Ethics

Data security and ethics are the focus of the project group (PG) of the same name, which is dedicated to the e:Med cross-sectional topics of data security, data access, legal foundations as well as ethical aspects: For example, in the handling (sharing and publishing) of human (gene)omics data, patient information, patient education as well as consent forms and their withdrawal. PD Dr. Witt (Head of the Molecular Genetics Laboratory and Biobank, ZI Mannheim) and Professor Baumbach (Head of CDL 3 and Working Group Leader Computational Systems Biology (CSB), Uni Hamburg( lead the project group and are supported by Professor Rietschel (ZI Mannheim, IntegraMent) in an advisory capacity.

Data Security:

The success of systems medicine, and thus also of the e:Med program, depends to a large extent on the ability to apply machine learning and artificial intelligence methods to large amounts of molecular data (so-called
omics data). Large cloud systems are available for this purpose, but they require a centralization of partly directly identifying data (e.g. images, gene sequences, or meta-data such as age and gender) in order to be able to machine-learn prognostic models, for example. This presents us with ethical as well as legal challenges, which the *PG* will illuminate and address.
There is a concrete need for action in the development and application of methodological approaches that ensure "by-design" compliance with the German Data Protection Regulation and the European General Data Protection Policy (GDPR). Tools from the field of so-called privacy-enhancing technologies (PETs) such as promoted learning (FL), homomorphic encryption (HE) as well as Secure Multiparty Computation
(SMC) or Differential Privacy (DP) can be used here.
Contact details: Found here: www.cosy.bio/head

Ethics:

The system-oriented research of diseases in e:med also brings up a number of ethical and data protection aspects, which we address in this project group and work on in a solution-oriented way. Topics include the need for adjustments to data protection concepts, broad patient consent, data sharing and integration, and the handling of incidental findings. As translational research in systems medicine develops at a rapid pace, the question of how to inform patients and participants about research approaches and the significance of results becomes increasingly important (keyword: genetic counseling). 
In addition, the success of systems medicine, and thus also of the e:Med program, depends to a large extent on the ability to apply machine learning and artificial intelligence methods to large amounts of molecular data (so-called omics data). Large cloud systems are available for this purpose, but they require a centralization of partly directly identifying data (e.g. images, gene sequences, or meta-data such as age and gender) in order to be able to machine-learn prognostic models, for example. This presents us with ethical as well as legal challenges, which the *PG* will illuminate and address. There is a concrete need for action in the development and application of methodological approaches that ensure "by-design" compliance with the German Federal Data Protection Act (BDSchG) and the European General Data Protection Regulation (EU-DSGVO). Tools from the field of so-called privacy-enhancing technologies (PETs) such as promoted learning (FL), homomorphic encryption (HE) as well as secure multiparty computation (SMC) or differential privacy (DP) can be used here.

All e:Med members are welcome to participate in the PG. Please contact Dr. Ann-Cathrin Hofer (a.hofer@dkfz.de) at the e:Med office if you are interested.