The Use of RFID in Biobanking: a Focus on Tracking and Storing Organoids

Source: Michael Schwarzenberger, no changes made, CC0 Creative Commons.

Radio-frequency identification (RFID) automatically identifies and tracks tags attached to objects. The tags can contain various electronically stored information. The advantage of RFID over a barcode is that the tags may be embedded within the tracked object, as the reader does not require a direct line of sight.

The tags are read with an RFID reader using radio waves. Passive tags draw power from the radio waves of the reader, necessitating close proximity. Active tags have their own power source, such as a battery, and can operate up to hundreds of meters from the reader.

RFID is used by multiple industries including biobanks

RFID chips are used by many industries for payment (cards), inventory, and quality control purposes, often during manufacture. For example, a tag can be attached to a car as it progresses through the assembly line. Tagged pharmaceuticals can be identified and tracked inside warehouses. They can even be implanted into living systems, for example farm livestock can be tagged in the field, or pets can be tagged for guaranteed identification, should they go astray.

Nice University Hospital in France uses RFID to track samples in the hospital’s biobank. Patient samples are stored in cryogenic vials, which are kept in liquid nitrogen banks. The base of these vials can incorporate passive RFID chips for rapid vial identification, along with the associated patient records.

According to Raguhu Das of IDTechEx the global RFID market was worth USD $11.2 billion in 2017, has an estimated 10% annual growth, and will result in an anticipated value of USD $18.68 billion by 2026.

Recent advances in miniaturization have resulted in ultra-compact RFID microchips that range in size from 10-600 micrometers.

RFIDs for organoids

Organoid cultures derived from donor’s pluripotent stem and banked cell lines are used in the biotechnology and pharmaceutical industries for various applications including toxicology and therapeutic efficacy studies. Ultracompact RFID chips can be incorporated into organoids.

A recent study, whose senior author was Takanori Takebe of the Division of Gastroenterology, Hepatology & Nutrition, Developmental Biology, Center for Stem Cell and Organoid Medicine (CuSTOM), Cincinnati Children’s Hospital Medical Center, USA, demonstrated that ultracompact passive RFID chips can be integrated into induced pluripotent stem cell (iPSC) derived endoderm spheroids. The 460×480 micrometer chips had 512-bit memory and could be scanned from up to 2 millimeters away. The study was published in the journal iScience.

These RFID chips remained functional after autoclaving, freeze thawing organoids from liquid nitrogen, and pH’s between 1-6.

Applications in identification and high-throughput screens

Wolman disease is a rare lysosomal acid lipase deficiency that results in the body not producing enough active lysosomal acid lipase (LAL) enzyme. It plays an important role in breaking down cholesteryl esters and triglycerides (fats). The disease manifests in fatty liver, spleen, gut, and also blood vessels. Symptoms include failure to thrive due to poor nutrient uptake from the gut, and eventual liver failure.

The research team demonstrated the utility of RFID tagged organoids by comparing stem cells donated from Wolman disease patients and healthy volunteers. RFID tagged organoids were generated and their growth media was supplemented with free fatty acids. The organoids were then stained with a lipid specific fluorescent dye.

An automated high-throughput system was setup in which single organoids were passed through a fluorescent microscope laser detection beam and, shortly after, an RFID reader, therefore the fluorescent intensity of the organoid was coupled to its identity and automatically recorded. As expected those organoids that were derived from Wolman patients had the highest fluorescent intensity.

The advantage of this setup was that the organoids could be experimentally stained for lipid in a single reaction tube. The organoids from different individuals were pooled together. This can increase consistency, as all the organoids receive the same batch of dye, and greatly reduces processing time.

RFID organoids could facilitate personalized medicine

The use of RFID allows donors with specific disease phenotypes to be identified without genome sequencing, which is a significant cost saving. The authors speculate that this could have applications in personalized medicine using what they describe as a “forward cellomics” approach.

Organoids can also be derived from cancers. In a large screening facility within a hospital oncology department, multiple patient organoids could be screened against standard cancer drugs before the commencement of treatment.

These organoids could be banked for future retrieval using the RFID chip as an identifier, should the initial automated screenings fail to yield a viable treatment path.

Future: LIMS integrated real-time tracking

Ideally RFID tags would allow staff to identify the location of patient samples simply from the computer record. Tanks can change location without computer systems being updated and storage issues can also occur such as the vial coming loose and floating in the tank, which is very difficult to detect. To someone searching for the sample in the racks it would simply appear that it was missing.

It would be nice if a sample vial could “report” itself as present, which is not possible with passive tags as the reader must be in close proximity. If tags were self-reporting it would also save on paperwork as those who utilize the samples would no longer be obliged to update the system.

This would require two things; active tags that are small enough and cheap enough to be attached to the base of cryovials, and a LIMS system that was capable of monitoring and reporting tag status in real-time.



David is a consultant/medical writer for a number of ongoing healthcare initiatives including for Athla LLC/ HealthLabs, a discovery automation company for Big Data leveraging Big Compute. He has a number of years experience in academic R&D and healthcare related projects including the fields of oncology and immunotherapy.