Thousands of diseases have no standard of care, and millions of people are affected by this. This is in part because we have an incomplete understanding of which part of our DNA plays a role when it comes to a particular disease. Identifying these parts is one of the first steps in developing a drug. Based on understanding what these parts trigger in the organism, an attempt can then be made to develop a drug to counteract this.

When scientists use genetic data to find associations with a disease, the traditional and well-established approach is to use Single Nucleotide Polymorpisms (SNPs). These are changes at individual positions of our DNA. Every person carries approx. 4.5 million SNPs. Acquiring this data for an individual is relatively cheap and has already been done for large populations.

Searching for the data link in DNA

Thanks to the advent of Long Read Sequencing technology, Structural Variants (SVs) are increasingly becoming a novel addition for research. Like SNPs, SVs represent changes in our genome and researchers are just beginning to fully understand them. One aspect is already clear: SVs can help in finding connections between our DNA and diseases and accordingly could become very valuable for identifying targets in the future.

But as Long Read Sequencing is rather new, the cost per individual to get SVs is yet prohibitive for very large efforts and such, very little data is available. So far, there have been large databases with cheap but exhausted SNPs and small databases with expensive but novel SVs. A link between these different genome abnormalities could not be established so far. If only there were a way to predict which SVs an individual is carrying based on the SNPs that we already know. And this is exactly what Genomic Lens is doing – linking the world of SNPs and SVs!

The team made the difference

The team embarked on the endeavor to use abundantly available SNP data to predict which SVs an individual is carrying to open this whole new dimension of genomic data to Boehringer Ingelheim to support target discovery. With the whole field of SVs being rather new, there are a lot of uncertainties concerning tooling, benchmarking, and data. In direct communication with authors of established tools and supported by Boehringer Ingelheim IT colleagues, the team was fast to develop a data product that yielded first, promising results. And after only a few months, the team celebrated the finding of first independent signals that prove the value of the product and with this the indication of a link to a disease.

The collaboration between the Boehringer Ingelheim Digital Innovation Unit, Global Computational Biology & Digital Sciences and BI X, the Boehringer Ingelheim Digital Lab, has resulted in a promising product that brings Boehringer Ingelheim at the forefront of this development in genomics. Complementary skills and diverse professional backgrounds just as computational biologists, data scientists, agile coaches or software developers formed the product team and drove this rapid development.