Babbitt Column | Cai Weide: 2018 US Edition "Unified Weights and Measures" – Chain Network Medicine Supply Chain Management

2018 is the first year of blockchain applications, and one of the most important applications is supply chain management. Supply chain management has recently been discussed in the United States in large numbers, and the discussion is whether the blockchain is really useful. There are two important applications in supply chain management. One is transportation and the other is medical tracking.

Why is medical tracking so important? In 2012, there was a counterfeit drug incident in the United States. A fake drug actually appeared in 1,000 hospitals in 48 states, causing many casualties. Prior to this, the United States had established a fairly good anti-counterfeiting system. It is very difficult to enter the hospital in general, but this has actually happened, and it has entered the hospital through a licensed unit. In order to prevent such serious incidents, the US Congress enacted the Drug Quality and Security Act in 2013. The second paragraph of the bill is the Drug Supply Chain Security Act. Protect consumers. The Pharmaceutical Supply Chain Security Act covers the entire life cycle of pharmaceuticals, including the entire supply chain from manufacturers, logistics, wholesalers, pharmacies, and hospitals.

Figure 1 2012 US counterfeit drug incident

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One solution is to require all relevant units in a pharmaceutical supply chain to see all of the drug's trading information, including the units involved in the supply chain and the information they trade. For example, in a pharmaceutical supply chain, manufacturers can see information about logistics companies, wholesalers, pharmacies, and hospitals. For example, how much medicine is used from one unit to another. Even if the unit does not know the relevant logistics or hospital, where the drug is logistics, where it is retailed, and where it can be used, it can be tracked.

US Congress passed legislation to pass the Medical Quality and Safety Act

According to the US DSCSA Decree, after 10 years, in 2023, every drug must be tracked, which is a very strict requirement. From Figure 2, it is the development period from 2015 to 2023. For this Act, the US Food and Drug Administration (FDA), in collaboration with the Center for Supply Chain Studies, has launched three blockchain-based reference models [1] to address drug tracking issues. These three reference models primarily use medical transaction information and transaction documents to track medicine.

Figure 2 DSCSA Act

Pharmaceutical supply chain transaction types

There are many kinds of transactions in the pharmaceutical supply chain, but the most important are the two transactions:

Transaction: refers to the transfer of drugs from one unit to another. For example, from the manufacturer to the transportation company, although it is a transportation job, this is a transaction in the supply chain, and the transaction is given by the manufacturer to the transportation company.

Refund: Limited to medicines that can be used. For example, a drug that has not been used during the shelf life can be returned to the manufacturer or transferred to another pharmacy or hospital.

How do fake drugs enter US hospitals?

According to the incident analysis, this fake drug came from Egypt (but Egypt may not be the place where fake drugs were produced). The drug passed the Egyptian wholesaler, Swiss wholesaler, Danish wholesaler, British wholesaler, American wholesaler, and finally by the United States. The business eventually entered 1,000 hospitals. Although most of the intermediate wholesalers are licensed medical wholesalers with local laws and regulations, there are black-hearted doctors who cooperate to eventually enter the US hospital.

Figure 3 The flow of fake medicines

Solution proposed by the United States

The US Supply Chain Research Center uses the following diagram to explain the blockchain to solve the problem of counterfeit drugs. After 2023, each unit in the US pharmaceutical supply chain must record and track each drug at the time of the transaction to ensure that the information on the entire chain can be queried. For example, in the figure below, the medicine (last user) can find all the transaction information of a drug until the manufacturer (starting unit).

Figure 4 New pharmaceutical supply chain process

In such a supply chain process, counterfeit drugs are quickly identified. For example, the hospital can find the drug from a wholesaler. The wholesaler may provide fake manufacturer information, but in such a supply chain, the hospital also has manufacturer information at the same time. It was found.

Information sharing and privacy issues

In this solution, information sharing is required, but privacy is also protected. If the drug is not made by you or not, you will not be able to see the relevant information. This is a strong contrast:

• If a unit is related to a certain drug, the unit can see information about the entire supply chain of the drug.
• If a unit has nothing to do with this medicine, the unit will not know any information, which is to protect privacy.

Why do you have to see the full chain information once you have a relationship? Because in the event of a later incident, the above-mentioned participating units will definitely try to attribute the problem to other units, so each relevant unit must see the same information (all white) to prevent this from happening. But other units that don't matter are not visible (all black). This is a key issue and a problem not encountered in traditional computer systems:

[Whole White Data Sharing] For an object, any unit that has processed the object can see complete information during its life cycle. For example, a drug can be seen from the manufacturer (A) to the logistics company (B), from the logistics company to the wholesaler (C), and finally from the wholesaler to the medicine (D), A, B, C, D. Complete information such as all transaction dates, product names and numbers, recipients and her information. Since A to B occur first, B occurs after C, but A can know the information of C. If A finds a problem with C, A can immediately give an early warning. For example, if a drug is placed in a wholesaler for too long, the drug is about to expire, and the manufacturer can notify the wholesaler. When the wholesaler delivers to D, D will see the warning sent by A.

[All Black Information Privacy] For drugs of the same kind but different processes, or a drug from manufacturer (A) to logistics company (B), then logistics company to wholesaler (E), and finally from wholesaler to hospital ( F). Because this is a different process of drugs, A and B can see the two pieces of process information, but E and F do not see the information of the first process, and C and D do not see the information of the second process. Although A and B can see the information of the two processes, they cannot share the information because it is illegal to deliberately disclose commercial confidential information.

This "all black + all white" data processing mode is different from the traditional system. On a traditional system, each company has its own database that stores transaction information for both parties to the transaction, and both parties to the transaction store a transaction contract or transaction information. For example, a manufacturer of a drug gives the goods to a wholesaler, the drug dealer and the wholesaler have information, the wholesaler deals with the pharmacy, the wholesaler and the pharmacy have this information, but the drug dealer may not have this article. information. That is, in this process, only the parties to the direct transaction have transaction information, and the transaction information on the supply chain is not automatically transmitted to the participants in the chain. The use of this system in the United States resulted in counterfeit drugs entering US hospitals through multiple legally compliant foreign wholesalers.

However, using the "all white + all black" model of the tracking system, fake drugs will be discovered, the flow of drugs and the information of the participants are clearly recorded and can not be tampered with, participants can access relevant data at any time. Even after a number of intermediate (foreign) businesses, the hospital can still trace the authenticity of the drug. The gap between the “all white + all black” model and the traditional model is as follows:

Figure 4 shows the relationship of the above table. It can be seen that the manufacturer can look forward, the logistics company can look forward and backward, the hospital can look back, but manufacturers, logistics, hospitals can not go to the side (other manufacturers, other logistics, other hospitals) .

Figure 5 Schematic diagram of information that manufacturers, wholesalers, and hospitals can see

It can be seen that the "all white + all black" model has the following characteristics:

• Use the blockchain consensus mechanism to ensure that participants can only put data into the blockchain database after consensus. This ensures that every participant in the supply chain has the same information, which addresses the core issue of the 2012 fake drug incident. Because this concept is new, the author is called "SupplyChain Data Consistency SCDC" and is different from "Transaction Consistency". If there are only two participants in a supply chain, the two definitions will have the same result, but once there are more than two participants in a chain, the two definitions will have different results.
• In the blockchain, the data cannot be changed, thus ensuring that each participating unit cannot cheat.
• In addition to the information that participants can see on one chain, all other information is private.

Data consistency

Data consistency is the technology of traditional computer databases. In the previous article, the relationship between data consistency and blockchain was mentioned. In the supply chain, data consistency also affects the strength of the supply chain.

Figure 6 Database consistency

Consensus mechanism : The consensus mechanism of “supply chain consistency” is different from the traditional blockchain consensus mechanism. Traditional blockchain consensus requires 1) most voters agree on block height; 2) most voters agree to the transaction information. However, "supply chain consistency" also requires 3) the information of this transaction is consistent with the previous transaction information, especially the information such as the number and source of the transaction must be consistent with the previous transaction number and source. If it is not the same, this transaction will fail. The third message is added to the "supply chain consistency." For example, the manufacturer sent a batch of medicines. When it came to the wholesaler, from the wholesaler to the pharmacy, the information about the batch of drugs was found to be inconsistent with the manufacturer and sent to the wholesaler. This means that the batch of drugs may have been fake. From the pharmacy to the hospital.

Weak chain : The database consistency protocol is used, which is a mutual trust between nodes, such as Paxos algorithm, Raft algorithm and so on. In this type of protocol, there are no malicious nodes and no false messages are sent to other nodes [2, 12].

True Chain : Using the Byzantine General Agreement as a consensus mechanism requires at least three rounds of voting. Nodes and nodes are independent and do not trust each other. The protocol provides fault tolerance for (n-1)/3.

Figure 7 Byzantine General Agreement Consistency

Supply chain weak consistency : In the "all white + all black" model tracking system, the database consistency protocol is used. That is to say, the weak chain is used in the supply chain, and there is no guarantee that the node does not lie. Once the node lie, the incorrect data may exist in the blockchain system, which will cause system paralysis in the future.

Figure 8 Supply chain weak consistency

Strong consistency in the supply chain: In the tracking system of the “all white + all black” model, the Byzantine General Agreement is used. Consistently follow the three rounds of voting in the agreement to complete the consensus and effectively prevent the nodes on the chain from lying. After inspection by the Byzantine General Agreement, the encrypted data cannot be changed in the blockchain system. On the medicinal supply chain system, an enhanced protocol can also be used, which is 100% node consent, rather than 67% node consent.

Figure 9 Supply chain consistency

All participant voting models : All participants in the chain participate in the voting each time the transaction is made, because the voting is timely and all participating units receive the same information at the same time. Participants must not only verify the correctness of the transaction, but also verify that the transaction is consistent with previous transactions in order to maintain “supply chain consistency”.

This verification can be done using a smart contract. For example, each participating unit system is provided by a single unit, but the smart contract is provided by the supervisory unit. This way, the voting has a two-tiered guarantee mechanism, which is first checked by the unit system and then checked by a smart contract.

The problem is that the supply chain may be dynamic. When the drug starts, it is not known to be sent to the wholesaler, pharmacy, or hospital, and may be returned and transferred to another unit. So when I started voting, I didn't know which unit would participate. This is not the same as cross-border payment by each bank. From the beginning, we know that the bank will participate, so we can establish a channel to participate in this vote. The pharmaceutical supply chain is different. When you start, you may not know which unit you will pass. This channel must be established while walking. If a drug goes too long in the supply chain, the number of units participating in the voting will increase.

In order to support this model, the blockchain system requires a "dynamic supply chain establishment and voting" mechanism, that is, the voting nodes will always change while running and only "increase" is not reduced.

Figure 10 All participant voting models

Voting model of both sides of the transaction : At the time of each transaction, only the transaction is double-played to participate in the voting. The former participants are only notified afterwards. Because the units that voted before can't change the previous voting records, they must vote for "approval" when voting this time. Otherwise, the transaction will not happen at all. In addition, the relevant data and voting records are also recorded on the blockchain and cannot be changed, so the previously voted units do not need to vote again. In this way, only the parties to the transaction participate in the supervision of each transaction, and rely on the inability to change the blockchain system to maintain the complete supervision of the supply chain. This is the first layer of protection.

At the same time, the system's smart contract can be activated to check whether the voting transaction is consistent with the past chain data. If not, the smart contract can immediately block the transaction. This is the second layer of protection.

If they do not vote this time, they will not know the result of the vote immediately. However, the end of the pharmaceutical supply chain is the hospital, the hospital can see all the information in this chain, and the data can not be changed. If you are not at ease, you can contact the manufacturer to confirm. Manufacturers and other units can also view the chain information at any time because of the chain. For example, you can query some data on the blockchain every hour. This is the third layer of protection.

Therefore, there are three layers of mechanisms for using the voting mechanism of both parties to ensure that the transaction is a genuine drug.

Figure 11: Voting model of the trading parties

Is the blockchain a solution that can be used?

From 2017 to 2019, the United States has been discussing whether the blockchain is the solution? If so, is it the best way? This problem has been plaguing many people. At the beginning, most medical institutions in the United States hesitated to use blockchain. Their troubles are mainly in the following three points:

1. There is no blockchain infrastructure at the moment, which is inconvenient to use;

2. There is no blockchain standard right now, and it is accurate that there is no blockchain standard that is “can act”;

3. Do not believe that blockchain, a “trust machine” technology, can build a trusted pharmaceutical supply chain.

The first point is correct. The blockchain infrastructure is not yet extensively built or there is not enough infrastructure. This will improve every year.

The second point is also correct, because blockchain standards are now mostly "reference models." The reference model can be referenced and discussed, but there is no uniform action detail or process. For example, many blockchain standards indicate that there is a consensus mechanism, but there is no indication of how the consensus mechanism has a detailed mechanism and how to verify it. Even with the same algorithm, there may be many different architectures and practices. In this case, some weak and pseudo chains appear. For example, the consensus used by the superbook is the Kafka consensus mechanism, but this mechanism is a weak chain mechanism, but the second is a centralized consensus mechanism. In addition, even if there is an algorithm, the same algorithm can have different architectures. In Tiande, the same algorithm, we have experimented with more than 50 different architectures, and the performance is different.

The third point is mainly public cognition and psychological problems, because most of the medical participants do not understand the blockchain. This problem can be solved with education. Another very important issue, too many people today think that the blockchain business is the most important and the technology is not important. If you use a chain, use an open source chain, such as a super-book, although everyone knows that this is a pseudo-chain, as long as the regulator does not deny it, then use a pseudo-chain. The problem is that today we are talking about using the blockchain system to check drugs, using weak chains or pseudo-chains. In the event of an accident, who is responsible for this life? Pharmaceutical supply chain company? Blockchain company? Is it also responsible for the regulatory unit that approves the use of pseudo-chains? False drugs may cause many casualties. Is there such a thing happening in China? The previous Sanlu milk incident, and the recent vaccine incident, have caused huge losses.

Blockchain is a must-have technology?

Why is the US eventually using blockchain technology? If you don't use blockchain technology, what other techniques or tools can you use? The United States has had a lot of open discussions in this area and has proposed other technologies, such as the Internet of Things (IOT) and big data.

The Internet of Things is a very important tool, but the Internet of Things itself does not guarantee that data cannot be tampered with, so the Internet of Things can be combined with blockchain. In the pharmaceutical supply chain, only the Internet of Things can collect data but the data may be changed.

In addition, big data can be used for analysis, processing, and forecasting. However, big data does not have data immutability. Therefore, only big data systems cannot ensure the safety of medicines through the whole process of drug tracking.

So whether it is big data or the Internet of Things, they are not the core of solving problems. The core still needs blockchain technology. In addition to the inability to change the data, the blockchain also has a very important concept. This concept mentioned in the author's "Blockchain China Dream 4" that the use of blockchain can solve the existing problems of regulatory technology [7].

[Mutual Consensus Supervision] Blockchain participants can reach a consensus before putting data on the chain. At the time of consensus, the participants actually supervise each other.

And once the consensus is reached, the data cannot be changed. “Mutual consensus supervision + no changeability” makes the blockchain system very different from the previous system [10, 11]. In the past, each unit maintained its own data, and units could communicate by file or email. Participants can use their own data to defend themselves if they later have a bad idea, but the communication file is either “naturally disappeared”, “naturally blurred”, or altered. However, "mutual consensus supervision + no change of sex" makes this cheating phenomenon unsuccessful.

Pharmaceutical supply chain reference model

These three models do not have a blockchain standard, nor do they require any function of the blockchain. They only define trading information for drugs and transaction documents.

What are the benefits of this? The benefit is that any type of blockchain can be used, and in the future it can still be tracked using blockchains in the face of new blockchains or different structures or even different infrastructures. Tracking is a full trace from the manufacturer to the hospital. This process went through intense discussions because some people thought that the blockchain could not solve the problem well, but ultimately decided to use the blockchain.

Take a look at the first reference architecture. The first reference architecture is to put transaction information and transaction files on the blockchain. The following figure is its complete process [1].

Figure 12 Reference model

Figure 13 verification model

After defining the data structure, it is equal to a unified weights and measures, and has the following characteristics:

• Data interoperability, regardless of the hospital, manufacturer, retailer, logistics must comply with this data;
• There are data and verification details, which are different from other blockchain standards that do not have details and verification procedures. If this feature is not available, it is a waste of time for the FDA. The purpose of the FDA is to verify the authenticity of the drug. This process needs to be approved by the relevant company and the unit, so it must be accurate and not ambiguous.

Different systems can be used in the process, but the data structure is consistent. Related companies include pharmaceutical companies, IT companies, pharmacies and other companies of different nature, but the FDA believes that in the pharmaceutical field are similar companies, that is, "medicine-related companies", subject to the same blockchain supervision. If the FDA's reference architecture details are vague, the companies use different blockchain systems. Although the functions are the same, they cannot be verified or interacted. This is the concept of the blockchain empire we have been emphasizing in the past. The FDA is establishing a US medical blockchain empire. Units that are interested in participating can legally do business in the United States, and units that are not interested in participating may not be able to survive in the market. This is also the concept of a sovereign blockchain, which is the empire of the US medical blockchain.

These standards have undergone several corrections, but the United States has established the world's first practical medical blockchain reference architecture. Other countries may follow.

There are some gaps in the three reference architectures, such as the first is to put data on the blockchain; the second is to put the hash value of some data on it; the third does not save the data or hash, and It is to put the relevant information after the smart contract processing on the blockchain.

This reference model project is started in 2017 by a number of related companies (manufacturers, logistics, hospitals, etc.). The entire work has been completed in half a year, and system experiments began in 2019. But the obvious three reference architectures are just initial work and will change in the future. But once these architectures are used, they are likely to become world standards.

Medical supply chain management system is huge

A closer look at this reference architecture will reveal that the amount of data in this system is staggering. This is done according to an exchange. For example, every kind of drug and every manufacturer, every warehouse or every logistics, as well as pharmacies, hospitals and patients, those are multiplications, which is a multiplication. Huge numbers.

According to the statistics of Drugbank.ca (drugbank.ca), there are now about 12,000 drugs in the United States, of which 3,700 are approved by the government and 5,700 are being tested. There are 8400 hospitals or clinics in the United States, including 5627 hospitals. There are more than 200 pharmaceutical manufacturers and 67,000 pharmacies in the United States. We have the following combinations:

Number of medicines X Number of manufacturers X Number of hospitals X Number of pharmacies = 3700 X 200 X 8400 X 67000 ≈ 4 x 1014

This does not include data on logistics transactions. And the above data is for each drug, but the practice transaction is every drug. A drug may arrive at a patient after multiple transactions. These are not estimated, so the above is an underestimation.

Let's compare the SWIFT and IBM collaborative experiments with the world-famous financial institution in March 2018, which has 34 international banks involved in cross-border payments. Most of the cross-border payments are in several important currencies, such as the US dollar, the pound, the euro, the yen, the renminbi, and possibly the Swiss franc in Europe. There are far fewer types of items traded than the pharmaceutical supply chain (3,700 drugs), and there are far fewer participating units (34). It took a million dollars, and the SWIFT experiment showed that the superbook could not support such a workload. SWIFT did not consider the transaction currency during this experiment, so the number of bank interactions in the experiment was

(number of banks -1) X (number of banks -2) / 2 = 528 combinations

In the experiment, a combination is implemented with one channel, which is to establish 528 channels. As a result, in this experiment, the super-book could not support 528 channels. SWIFT said that if all participating banks are required to be placed in the blockchain system, a total of more than 100,000 channels are required [4].

If the pharmaceutical supply chain also uses a channel to practice a combination, the number is too great! This means that the pharmaceutical supply chain is 4 x 108 times larger (4 x 1014/1000000) than the SWIFT system (100,000 channels), which is 400 million times larger than SWIFT's experiment in 2018 (4 x 1014 / 528). This is not a chain that can be solved, nor is it a multi-chain solution, but a blockchain internet solution is needed!

Panda blockchain internet

This problem can be solved by using the Panda model we proposed in 2016 [9]. The Panda model was originally designed for digital currency. In this system, all financial institutions in a country can participate because the panda model is scalable. The chain inside the Panda model is divided into an account chain or a transaction chain. The account chain only manages accounts. The transaction chain processes transactions. The account chain can be extended by shards. The transaction chain is expanded by increasing the number of transaction chains. Chains can be expanded indefinitely.

So in this issue every drug manufacturer, every hospital, every pharmacy or every logistics company and warehouse can be an account chain. 67,000 pharmacies can have their own account chains, 8,000 hospitals have their own account chains, and manufacturers can have their own account chains.

Then there are various trading chains that are in the middle of the account chain and handle transactions between them. It can be seen that the number of chains looks large, but in terms of the number of combinations, it is still very small. These chains may add up to 100,000 chains, but the combination is 4 x 1014, and 100,000 is a very small number. Another group of hospitals, or a group of pharmacies, can use the same account chain. For example, there are many pharmacies under Walgreens in the United States, and these pharmacies can be managed in a unified manner. Some United hospitals in the United States also manage many hospitals. For example, in a city, a joint hospital can manage more than a dozen hospitals, which can also be managed in a unified manner. These will also reduce the number of blockchains.

The US regulatory agency FDA can have a node on each chain to collect all data for regulation. Today's blockchain big data platform can handle such data volume data, and Tiande has launched this blockchain big data platform in 2017.

In 2017, this big data platform worked with Guangdong Clearing House to handle the liquidation of commodity trading, which is equivalent to the trading volume of the London Stock Exchange in the past 16 years. This big data platform uses a 4-D (4 Distributed) architecture and is implemented in a big data blockchain. Below is the architecture of the Panda Blockchain Internet.

Figure 14 Panda Blockchain Internet Model

Use the golden monkey model

If the market does not fully follow the panda model, but uses multiple different chains, but these chains will use the panda model, but the entire pharmaceutical supply chain still needs to be connected. In this case, we need a heterogeneous chain network, a golden monkey model can be used, and a golden monkey model can connect several panda chains [5, 6, 8].

Conclusion

Many units or companies around the world have already begun to pay attention to the development of the pharmaceutical supply chain. In addition to the release of the reference model in 2018, the FDA announced a new pilot program in early 2019 to help track drug flows. The participating units are manufacturers, drug dealers, wholesalers and other units that can access the drug. The purpose of this project is to find a best way to solve the security problems in the supply chain.

This layout has also attracted the attention of the investment group. Goldman Sachs, the world's top investment group, supports the TraceLink team [13]. This not only responds to the FDA's pilot program, but also brings an important message that a new blockchain industry in foreign countries will be launched. Also optimistic about the US capital community.

Of course, the pharmaceutical supply chain is still in the experimental stage, and there is still a lot of work to be prepared. The use of blockchain technology to solve the safety problems of the pharmaceutical supply chain is worthy of further discussion and research.

references

[1]. Jeff Denton, Thomas Pizzuto, Heather Zenk, etc., “The Drug Supply Chain Security Act and Blockchain”, Center for Supply Chain Studies, June 21, 2018.

[2]. Cai Weide et al., "Pro, what is your chain?"

[3]. Cai Weide et al., “Several important pits of blockchain technology (top)”

[4]. Cai Weide et al., “The lessons of tens of millions of dollars – the difficulties and solutions SWIFT encountered”

[5]. Cai Weide et al., “Blockchain Internet Series (2): Blockchain Internet Needs New Agreement”

[6]. Cai Weide et al., “Blockchain Internet”, 2017.6.3

[7]. Cai Weide et al., “The Chinese Dream of Blockchain: RegTech Weaves a Comprehensive Security Dream”

[8]. Cai Weide et al., “One of the Chinese Dreams of Blockchain: Blockchain Internet Leads China's Science and Technology Progress”

[9]. Cai Weide et al., “Panda-CBDC Central Bank Digital Currency Model”

[10]. Cai Weide, Jiang Xiaofang, Li Qi. Dear, don't tease, “The blockchain is the biggest financial technology innovation in 500 years?”

[11]. Cai Weide, Jiang Xiaofang. The blockchain brings “a revolution that changes the world” – rereading the report of the UK’s chief scientific adviser”

[12]. Cai Weide et al., “The wind blows, what does it blow?”

[13]. Ledger Insights, “Goldman Sachs backed TraceLink creates pharma blockchain”, May 22. 2019.

Author Cai Weide: Digital Society and Blockchain Laboratory of Beijing University of Aeronautics and Astronautics, Beijing Tiande Technology Co., Ltd., National Big Data (Guizhou, Integrated Experimental Zone Blockchain Internet Lab, Tianmin (Qingdao) International Sandbox Research Institute, Competition Di (Qingdao) Blockchain Research Institute. He Juan: Master of Science in Beijing University of Aeronautics and Astronautics, research blockchain direction.

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