Fredrik Dyrkell is the CTO of 1928 Diagnostics. His expertise is within software development, bioinformatics, user experience, quality and regulatory. His daily job is to lead the software development team and he feels that working with 1928 Diagnostics is a unique opportunity to use his knowledge to create a product that can make a real difference.
The company was founded to stop the spread of antibiotic resistance globally, and to save the power of antibiotics, and what we offer is a cloud service that analyze resistance markers in bacteria from whole genome sequencing. We look for resistance markers within the bacteria and also do a relational analysis between samples. And that relational analysis you can use to look for possible outbreaks at an early stage, and improve an active infection control.
Fredrik explains that the price of whole genome sequencing has decreased dramatically the past years, and continues to do so. He means that this will drive the adoption of whole genome sequencing in clinical routine, and with more data 1928 Diagnostics can do even more advanced analysis, and learn more about resistance and pathogens.
And it’s quite easy for hospital to try the platform for analysis, once they have started using whole genome sequencing on bacterial samples. The output from the WGS is a set of files with the entire dna of the bacteria, and it is out of that data that 1928 analyze and extract useful information.
A bioinformatician will start by uploading the sample files to the cloud platform and the analysis begins automatically. The results will be available within an average of 15 minutes. But what actually happens during the 15 minutes?
When the samples are uploaded there need to be a quality assessment, to make sure that we have sufficient sequence depth and the right information to do a correct analysis. The first part of the analysis is resistance prediction, which is looking for genes and mutations correlating with the resistance. Then comes infection control analysis, where we create a phylogenetic tree with the relations between the samples and you can use that to detect outbreaks. The types of information that you will find in the results are things like sequence types, virulence factors, and for the resistance markers we link to the research literature with a clinical relevance. All of this can help improve the hospitals infection control and proactivity in detecting outbreaks and hospital acquired infections.
Fredrik likes to point out that the team put a lot of emphasis on quality control, and that they are heavily invested in automated testing and verification that the platform meet the right criteria. The 1928 staphylococcus aureus product is CE marked, meaning it is approved to do diagnostics based on the results that comes out of the platform. It is also GDPR compliant, for hospitals to put patient data for analysis through the platform in a safe way.
And for the future, the software development team have projects right now working on long-read sequencing and analysis of those, with hybrid technologies between long-read and short-read. They are also working on machine-learning models to predict antibiotic resistance using learning algorithms, as well as meta-genomic analysis where they are looking at typing bacteria within meta-genomic samples.
Apart from the obvious benefits of using the technology, 1928 is a smart choice from a business perspective. Since the platform is a cloud software, the company can operate at scale and with a high level of service. Using a SaaS model there is no upfront investment for the hospitals, and you only pay for what you use.
There are already several hospitals in Europe and the USA that are getting value out of the 1928 platform. So if you are starting to do WGS, we will be happy to provide the analysis for you.