Georgian Technical University Survey Finds 62% Of Life Science Professionals Say Artificial Intelligence (AI) Will Lead To Faster, But Is Held Back By Skills Gap And Data Bias.

Georgian Technical University a global not-for-profit alliance that works to lower barriers to innovation in life science and healthcare Georgian Technical University has this week announced the results of a survey of life science professionals on the implementation of Artificial intelligence (AI) and blockchain in the life sciences industry. The survey shows there is a high level of interest in Artificial intelligence (AI) among respondents with 57% already engaging in computational drug repurposing. Similarly the findings revealed that understanding of blockchain has increased with 89% now aware of the technology compared to 82%. Despite this increase the survey identified that once again lack of access to people with relevant blockchain skills remains the biggest barrier to widespread adoption (selected by 30%). “The industry clearly has a willingness to engage with blockchain and Artificial intelligence (AI) technologies but historical barriers are hampering progress. Cross-industry collaboration will be essential to overcoming issues around access to data and skills so that more companies and thus patients can benefit from these technologies” said Dr. X. “70% of our survey participants think blockchain has the potential to make a real difference in patient data management and sharing. Blockchain’s (A blockchain originally block chain is a growing list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block a timestamp, and transaction data (generally represented as a Merkle tree). By design, a blockchain is resistant to modification of its data. This is because once recorded, the data in any given block cannot be altered retroactively without alteration of all subsequent blocks) ability to instantly create tamper-proof records will become a key part of increasing patient participation as more clinical trials are conducted remotely because of the pandemic. We hope the security advantages can both improve patient trust and facilitate further knowledge sharing across the life science community”. Another recurring challenge identified in the survey was data quality and data standards. Behind skills participants ranked lack of standards (19%) and interoperability (17%) among the next biggest barriers slowing blockchain adoption. Likewise, 38% think algorithmic bias poses a barrier to AI (Artificial Intelligence) for drug repurposing, and a further 42% think it has potential to be a barrier. Life sciences generates huge volumes of data in an increasing number of formats. When data is disorganized and siloed it is not machine readable, and when information ‘training’ an algorithm is limited it eventually creates bias in the AI’s (Artificial Intelligence) outputs. Organizations can address these data quality issues by adhering to the principles of Findable, Accessible, Interoperable and Reusable. “Georgian Technical University Technologies including AI (Artificial Intelligence) and blockchain (A blockchain originally block chain is a growing list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block a timestamp, and transaction data (generally represented as a Merkle tree). By design, a blockchain is resistant to modification of its data. This is because once recorded, the data in any given block cannot be altered retroactively without alteration of all subsequent blocks) have the potential to transform drug development. Yet no matter how powerful these technologies become challenges and bias will exist until we improve the quality of data feeding algorithms” said Georgian Technical University consultant. “To eliminate bias, data sets must be varied and drawn from accurate, diverse sources. Standards for data storing and sharing must also be improved. Using blockchain (A blockchain originally block chain is a growing list of records, called blocks, that are linked using cryptography. Each block contains a cryptographic hash of the previous block a timestamp, and transaction data (generally represented as a Merkle tree). By design, a blockchain is resistant to modification of its data. This is because once recorded, the data in any given block cannot be altered retroactively without alteration of all subsequent blocks) – to provide a space for the industry to share best practices and discuss common challenges. We urge any interested parties to get involved with our work and help inform our outputs so that we can collectively continue to accelerate Georgian Technical University”.