I was attracted to a seminar sponsored by CSIRO and DLA Piper in January 2018 entitled, “Digital transformation: how robotics and blockchain are shaping the future of industries.” I had many questions, including: Why is CSIRO lecturing on blockchain in San Francisco, CA? After all, CSIRO is Australia’s powerful technology catalyst that uses science to solve real issues … in Australia. DLA Piper is a global law firm involved in helping clients with legal issues in technology and business, such as patents and partnerships.
The seminar discussed how firms can combine robotics, artificial intelligence (AI), and blockchain technology (BCT) (see Figure 1) as a foundation for restructuring complex workflows. Greatly improved data reliability and security is a compelling driving factor.
Figure 1 – Blockchain consists of a chain of individual blocks involving a network of computers. The work product (block) is added to the ongoing chain in the participating computers. Distributed processing and archiving, including time-stamping, provides redundancy and hence security.In the sciences, AI has been around since at least the 1960s. We have seen papers in which an AI program was trained on a data set, and then tested with a larger sample database. A successful AI experiment would show new associations such as biomarkers, etc.
But what about blockchain? I had seen it as a fancy program that somehow supported crypto currencies such as Bitcoin. However, the panel at the meeting predicted that BCT can do much more. They envisage that the large banks will use BCT to become payment-transfer organizations in addition to the traditional repository for wealth.
But how will this impact labs? The regulatory functions of the FDA are particularly focused on data integrity. They seem to fear that current computer systems and databases can be manipulated for commercial gain. A system that inherently detects and records manipulation of data in a database should provide superior detection of data adulteration. BCT builds upon the prior data in the file, which is time-stamped. A change in a data file is detected as a software fork. The change is visible in many computers in the network. Thus, one can detect additional tests, which would indicate the prohibited “repeated assays to find a data that support the desired outcome.” BCT is expected to improve testing rigor and decision objectivity.
With BCT, it is easy to see that the workflow is consistent with prior executions of the approved suitability and performance qualifications. For example, NIST expects that: “When the results of an entire run, including sample tests, are rejected, it may increase suspicions during an audit about testing into compliance. (Analysts have been accused of deliberately failing system suitability tests for analyses, which might not meet specification.) With a properly written SOP, if the system fails a readiness or suitability check before samples are collected, or, at a minimum, before any processing of data and creation of detailed knowledge of the outcome, then the decision to invalidate a result is done in an unbiased manner irrespective of the test result.”
So, what is blockchain?
From the glossary section of the NIST report:
- Blockchain: A distributed digital ledger of cryptographically signed transactions that are grouped into blocks. Each block is cryptographically linked to the previous one after validation and undergoing a consensus decision. As new blocks are added, older blocks become more difficult to modify. New blocks are replicated across all copies of the ledger within the network, and any conflicts are resolved automatically using established rules.
So, what are the downsides of BCT? The largest is reduction in transactional throughput capacity. Transactions using blockchains are more complex and hence slower. Power consumption for the network is another fear. Bitcoin is rumored to consume huge amounts of electrical power.
The number of supported transaction types is small, but growing rapidly. Not all are open source. For example, one program provides trusted time-stamping, which can prove that certain information existed at a given point. BCT allows a party to prove they had access to a piece of data in a way that cannot be repudiated, for example, if a person wanted to prove he/she had possession of a file. This might be useful in establishing dates in patent litigation, or fraud.
I can see BCT being integrated with the Internet of Things (IoT) in the laboratory to provide improved workflow compliance and operational efficiency.
Robert L. Stevenson, Ph.D., is Editor Emeritus, American Laboratory/Labcompare; e-mail: [email protected]