AI-MetaBloQ

AI-MetaBloQ is a DLT-Marketplace with a Reactive Artificial Intelligence Tool for the use cycle of data related to human biosamples. The DLT-Marketplace applies Blockchain technologies to the exchange of data in the field of human biospecimens and patient data, provides service exchange and data transfer services to all members of the chain. The incorporated AI tool produces real time quality assessment of biosamples with simultaneous prediction of appropriate secondary use for a given research activity.

The system contains the creation of AI-MetaBloQ platform, includes a “Distributed Ledger Technology” online Marketplace that promotes sharing of data, characterizing biosamples and patients, distributing trust between entities in the biosample usage chain, in a regulatory compliant manner, acting as a decentralized digital identity along with privacy preserving exploration of distributed sensitive medical data using strong collective encryption and Distributed Digital Identity. With AI-MetaBloQ, data sharing becomes a positive side effect of patient use and control of data, with a “Ledger of Me” approach.

The goal is to be the standard in the Biobanking industry. AI-MetaBloQ includes a smart tool, based on Reactive Artificial Intelligence, with the aim of fully developed, interoperable, synchronized and ontologically unified Quality Management of biospecimens of human origin, which automatically ranks biospecimens in terms of qualitative completeness, depending on pre-analytical data collected in real time from different sources and entities and simultaneously predicts and recommends the suitability of the selected biospecimens by researchers for their research activities, as well as their individual derivatives, depending on the type of research activities set from the beginning. AI-MetaBloQ’s Reactive AI engine observes live actions of members of the usage chain and reacts to them. The smart engine narrows down choices of biospecimens for research use based on how it rates their handling and quality.

Motivation for the project: We aim for patients to gain from the research capital spent, within the drug developmental cycle, be actively engaged in their data procurement and clinical trial involvement; and simultaneously address challenges in human biospecimen sourcing human by reducing cost and time in basic research.
Generic use case description: Patients can donate biosample and related data, gain participation in clinical trial or even drug discounts, while biobanks have direct communication and access to patients for meta, real-world data and even follow on donations, while researchers are provided with high value characterized biosamples.
Essential functionalities: Quality control validation system to characterize biospecimen by type, assess the quality of their derivatives for specific downstream analyses, consume and provide biospecimen and patient related data, monetize upon donations, audit donations and transactions.
How these functionalities can be integrated within the software ecosystem: Within AI-MetaBloQ metadata can be managed, resources can be uploaded and hosted, monetization achieved through a robust transaction mechanism, inventory managed, user activity and logging monitored. AI oriented search and query activities will lead to biosample quality assessment via a reactive tool.
Gap being addressed: Patients engagement over many years is resource-intensive.
Expected benefits achieved with the novel technology building blocks: Donors gain from flow of bio-data and biospecimen controlled donors; scalable and secure data exchange; authenticity and integrity for all users; transparency and harmonization of all data; measurable representation of biosample quality; holistic service model, towards biobanks and research centers.