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Blockchain technology in (life) sciences
The document provides an overview of blockchain technology, focusing on its mechanisms, strengths, weaknesses, and applications, particularly in life sciences. It touches upon decentralized management, immutable audit trails, and the potential for enhanced data security in sectors like healthcare and education. It also highlights current research areas and practical implementations while discussing challenges and best practices to avoid ineffective blockchain projects.
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Blockchain technology in (life) sciences
- 1. Blockchain technology in (life)sciences November 2017 Slides on slideshare.net (bdcvanschaik)
- 2. Blockchain ● Technology – How doesit work? – Strong points and weaknesses ● Applications – Current applications – Applications in (life) sciences – Avoiding the pointless blockchain project
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- 4. What is ablockchain? ● Technology behind Bitcoin ● Distributed ledger (peer-to-peer) ● No central authority (trustless system) ● Transactions are transparent and traceable
- 5. Transactions Public key Private key Balance_R= 10 Public key Private key Balance_B = 2 Public key Private key Balance_G = 0 https://en.wikipedia.org/wiki/Public-key_cryptography
- 6. Transactions Public key Private key Balance_R= 10 Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 Public key Private key Balance_B = 2 Public key Private key Balance_G = 0 https://en.wikipedia.org/wiki/Public-key_cryptography
- 7. Transactions Public key Private key Balance_R= 8 Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 Public key Private key Balance_B = 4 Public key Private key Balance_G = 0
- 8. Transactions Public key Private key Balance_R= 8 Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 Public key Private key Balance_B = 4 Public key Private key Balance_G = 0 Transaction: Send 3 to green public key Sign with blue private key Balance_B = Balance_B – 3 Balance_G = Balance_G + 3
- 9. Transactions Public key Private key Balance_R= 8 Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 Public key Private key Balance_B = 1 Public key Private key Balance_G = 3 Transaction: Send 3 to green public key Sign with blue private key Balance_B = Balance_B – 3 Balance_G = Balance_G + 3
- 10. Transactions Public key Private key Balance_R= 8 Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 21 November 2017 Public key Private key Balance_B = 1 Public key Private key Balance_G = 3 Transaction: Send 3 to green public key Sign with blue private key Balance_B = Balance_B – 3 Balance_G = Balance_G + 3 24 November 2017 Check if balance is enough Verify if sender is allowed to send Transactions are timestamped Everyone gets a copy of all transactions If keys are not linked to persons it is anonymous
- 11. Transaction Satoshi Nakamoto (2008)Bitcoin: a peer-to-peer electronic cash system Owner digitally signs hash of previous transaction and public key of next owner
- 12. Timestamp server Block Previous hash Hash 21Nov 2017 Tx1 Tx2 Tx3 . . Txn Block Previous hash Hash 22 Nov 2017 Tx1 Tx2 Tx3 . . Txn Block $Previous_hash Hash $Date $Transactions Publicly announce hash of block to be timestamped Publicly announce new transactions
- 13. Proof-of-work (mining) Scan fora value (nonce), when hashed (e.g. SHA-256) it begins with a number of zero bits A.k.a. Keep computers busy for a while. More CPUs = more chance to win the competition Computationally hard to repeat, but easy to verify Add new block to the chain (link to previous hash) and announce Others verify if block is correct and add block too (majority vote) Incentive: winner gets a reward (e.g. a bitcoin + transaction fees) https://en.wikipedia.org/wiki/SHA-2
- 14. Network 1. Broadcast newtransactions to all nodes 2. Each node collects transactions in a block 3. Each node works on proof-of-work for this block 4. Proof-of-work found → broadcast block to all nodes 5. Nodes accept block when transactions are valid and not already spent 6. Acceptance by working on creating a new block based to the previous block 7. Longest chain is the correct one 8. 51% rule: majority decides what is correct
- 15. Other points inbitcoin paper ● Reclaim disk space – Data compression with Merkle tree ● Simplified payment verification – You don't need the entire blockchain for verification ● Splitting values – Return the change and add transaction fees ● Privacy – No link between person and keys ● Probability of building in malicious blocks – Unlikely that a malicious node keeps up with longest chain Satoshi Nakamoto (2008) Bitcoin: a peer-to-peer electronic cash system
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- 17.
- 18. Screenshot Data can beadded to a transaction
- 19. Blockchain variants ● Several variantssimilar to bitcoin ● Some focus on anonymity, others on efficiency ● Other data structures: block-graph i.s.o. block-chain ● Generalization of transactions
- 20. Ethereum: programming platform onblockchain a.k.a. smart contracts Transaction: Send 2 to blue public key Sign with red private key Balance_R = Balance_R - 2 Balance_B = Balance_B + 2 A transaction can be about anything Function can be more complex than “add” and “subtract” Multi-signature possibilities Examples: ● Two (or more) people need to sign before transfer takes place ● Transfer of money, a house, energy, karma points, votes, supplies, etc ● Temporary transfer of a room, a car, a bike, etc https://github.com/ethereum/wiki/wiki/White-Paper (2015)
- 21. Things that makepeople nervous
- 22. Forks● Softforks are forward compatible –Old nodes accept new blocks created with later version of software – Miners need to upgrade ● Hardforks are not forward- compatible – Everyone needs to upgrade (miners, users, merchants) Examples of hardforks Ethereum: bug in smart contract Funds were stolen and community decided to fix that and return funds Some did not agree: new coin Ethereum classic went on separately with original rules Bitcoin: upgrades suggested to improve transaction speed Some wanted to increase blocksize faster: new coin Bitcoin cash https://bitcoin.stackexchange.com/questions/30817/what-is-a-soft-fork Software A Software B
- 23. Hacks, scams andbugs Private keys were stolen and/or server was hacked PCs were hackedRansom via bitcoin Software bug insmart contract Pyramid scheme List of weaknesses and how likely they are: https://en.bitcoin.it/wiki/Weaknesses
- 24. Strong points andweaknesses ● Traceability ● Transparency ● Data redundancy ● Strong crypto ● Can be anonymous (not always the case) ● Data storage not efficient ● Mining expensive (lots of energy wasted) ● No single authority (refunds) ● Miners have more power than users ● Don't loose or give away your private keys
- 25.
- 26. Supply chain @port of Rotterdam https://www.ad.nl/rotterdam/rotterdamse-haven-experimenteert-met-blockchain-technologie~a2bda56a/(2017) Image: IBM
- 27. Solar energy @Amsterdam https://spectral.energy/about/news/jouliette-at-deceuvel/ (2017)
- 28.
- 29. Applications in (life)sciences ● Where is current research on blockchain technology? ● Education ● Open science ● Biomedical/health care ● BioCommons
- 30. Blockchain research Yli-Huumo etal. (2016) Where is current research on blockchain technology? - A systematic review. PloS one 41 papers included in study 80.5% about bitcoin challenges and limitations 19.5% about other topics
- 31. Education ● Digital record ofachievements – Certificates issued by university to students ● Proof of intellectual work – Public records of ideas – Can not be modified, new revision can be submitted ● Intellectual currency – Micro-payment for contribution – Reputation points (e.g. nr of citations, reviews) Sharples and Domingue (2016) The blockchain and kudos: a distributed system for educational record, reputation and reward. European conference on technology enhanced learning Image:Ibrandify-Freepik.com
- 32. Blockchain-enabled open scienceframework ● Store protocols, metadata, publications and reviews on blockchain – Minimum publishing standards – Data sharing/discovery – Publish everything – Provenance / track progress ● Reputation award system (credits, funding) ● Software development needed https://www.oreilly.com/ideas/blockchain-enabled-open-science-framework (2016) Furlanello et al. (2017) Towards a scientific blockchain framework for reproducible data analysis. https://arxiv.org/abs/1707.06552
- 33. Biomedical/health care applications Blockchainversus distributed database management systems 1) Decentralized management 2) Immutable audit trail 3) Data provenance 4) Robustness/availability 5) Security/privacy Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA Use cases 1) Medical record management 2) Insurance claim process 3) Clinical/biomedical research: data sharing 4) Biomedical/health care data ledger For each case examples and potential benefits are described
- 34. Medical record management 1)Decentralizedmanagement 2)Immutable audit trail 3)Data provenance 4)Robustness/availability 5)Security/privacy Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA 1) Patient-managed health care records 2) Unalterable patient records 3) Records are signed 4) Decentralized: reduced risk of data leaks (e.g. institute hacks) 5) Data is encrypted. Only patient can decryptWhat if... You need to migrate to stronger keys? The patient loses the private key?
- 35. Clinical/biomedical research: data sharing 1)Decentralizedmanagement 2)Immutable audit trail 3)Data provenance 4)Robustness/availability 5)Security/privacy Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA 1) Improved care data sharing and analysis without ceding control (peer-to-peer between institutes) 2) Trackable and timestamped patient-generated data 3) Provenance for medical research data 4) Availability and access to real-time data 5) Secured and privacy-preserving health care data sharing
- 36. Challenges and proposedsolutions ● Blockchain provides pseudo-anonymity – Encrypt the information – Store sensitive data off-chain and a link on-chain ● Speed and scalability – Blockchain as index of health data, not data itself – Alternative blockchain solutions ● Threat of a 51% attack – Implement as private or consortium blockchain Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA
- 37. Ideas at BioCommonsworkshop ● Reputation ● Voting ● Personal authentication ● Secure anonymity ● Crowdfunding campaigns ● Contracts between project partners ● Decentralized storage (e.g. MaidSafe) ● Encryption of sensitive data (e.g. DNA.bits) https://pdfs.semanticscholar.org/6f24/8a10c94b74e8eecf478363b3be999a899958.pdf (2014)
- 38.
- 39. Avoiding the pointlessblockchain project https://www.multichain.com/blog/2015/11/avoiding-pointless-blockchain-project/ Checklist: ✔ Blockchain is for shared databases ✔ There are multiple writers ✔ Absence of trust: writers need to be verified ✔ Desire to cut out trusted third party (reduce costs, remove single point of failure) ✔ Transactions depend on each other Also important: ✔ Set the rules: put constraints on transactions ✔ Pick your validators: public, private and consortium blockchains ✔ Back your assets: what does the digital unit represent in the real world? Alternatives that might be better suited • Regular file storage • A centralized database • Master-slave databases • Multiple databases to which users can subscribe
- 40. Slides on slideshare.net(bdcvanschaik)
- 41. Insurance claim process 1)Decentralizedmanagement 2)Immutable audit trail 3)Data provenance 4)Robustness/availability 5)Security/privacy Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA 1) Real-time claim processing 2) Improved claim auditing and fraud detection 3) Verifiable records for claim qualification 4) Enhanced accessibility of patient data (iso data silos) 5) Increased security of medical insurance information
- 42. Biomedical/health care dataledger 1)Decentralized management 2)Immutable audit trail 3)Data provenance 4)Robustness/availability 5)Security/privacy Kuo et al. (2017) Blockchain distributed ledger technologies for biomedical and health care applications. JAMIA 1) Decentralized health data backbone 2) Unchangeable log of clinical research protocols 3) Ensure original manufacturer and ownership transferring in pharmaceutical supply chain 4) Improved robustness for counterfeit drug prevention/detection systems in pharmaceutical supply chain 5) Patients are able to add consent statements at any point in their care journey
- 43.
Editor's Notes
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- #3 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #5 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #6 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #7 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #8 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #9 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #10 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #11 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #12 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #13 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #14 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #15 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #16 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #17 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #18 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #19 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #20 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #21 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #23 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #24 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #25 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #27 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #28 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #29 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #30 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #31 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #32 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #33 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #34 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #35 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #36 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #37 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #38 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #39 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #40 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #41 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #42 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #43 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>
- #44 Not only the sequences are in a different format, the quality scores are different too. I will explain in the next slides what the scoring scheme is of the different machines. <number>