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Drug discovery and development is such an arduous process; it typically takes more than a decade to achieve a single approval. But researchers can save a lot of time by just starting with optimal targets. One powerful new approach gaining favor is to combine next-generation sequencing and disease phenotyping. So much of this data is now available that truly population-scale projects can be done. The key is to make certain to start with high-quality data and have the analytical capacity to do these large and complex studies.
One company leading efforts to deliver on this strategy is Boston-based, Genuity Science (formerly WuXi NextCODE). The company’s heritage as a technology platform for mining massive genomic datasets translates to a unique understanding of the need for not just information but data that drives insight. Genuity Science has evolved significantly since it spun off from deCODE genetics in 2013. It now has the resources and expertise to create well-designed clinical omics datasets, and advanced analytics built on multiomic and phenotypic data. This is just the right recipe for accelerating drug discovery and development. Recent research, in fact, has shown that therapies discovered in large part on patient genetic data are twice as likely to gain FDA approval as those mainly supported by tests in mice, other animal models, or petri dishes. In 2018, more than a dozen drugs approved had human genetic data to support their further study.
“The most common reason for a drug to fail is lack of efficacy because it isn’t aimed at the right target,” says Jeffrey Gulcher, MD, PhD, co-founder and chief scientific officer at Genuity Science. “In our drug target and biomarker discovery programs, we harness human genetics of large in vivo clinical populations, not cell lines or animal models. That allows us to better define the underlying disease mechanisms.” The company also has a scaleable informatics system that allows teams to combine and share data and analysis results. In addition, most of Genuity Science’s programs include parallel multiomics datasets of disease tissues, including analysis using artificial intelligence.
Landmark Partnership
One of these partnerships is a landmark population genomics alliance between AbbVie, Genomics Medicine Ireland (GMI), and WuXi NextCODE. (WuXi NextCODE and Genomics Medicine Ireland are now Genuity Science.) This ambitious long term collaboration was launched in 2017 to focus on major chronic diseases within oncology, neuroscience, and immunology.
Vice President, Genomic Research and Data Integration, AbbVie
The alliance will result in the sequencing of 45,000 genomes from volunteers across Ireland to provide novel insights into the biological processes that underlie several common diseases that lack adequate therapies. AbbVie is using GMI’s growing research database, which contains detailed phenotypic data captured from collaborating disease experts. Genuity Science’s integrated genomics analysis platform is being used to organize and mine a secure, scalable database of whole-genome sequence and medical data.
For those on the frontlines, these developments are very encouraging. “The biggest recent change has been the quality of the clinical phenotypes available and the ability to follow-up with patients,” says Howard Jacob, PhD, Vice President, Genomic Research and Data Integration at AbbVie. But the quality and depth of sequencing is also crucial.“ The ability to do whole-genome sequencing is very important,” he adds.
Co-Founder, Chief Scientific Officer, Genuity Science
Gulcher says that a key strategy is to compare severe disease subtypes with less severe subtypes to define which genes and drug targets are driving the phenotypic differences such as, primary progressive versus relapsing-remitting Multiple Sclerosis patients. “This head-to-head comparison has the advantage of focusing on the differences between disease subtypes while filtering out what they have in common,” says Gulcher.
Whole-genome sequencing is key to finding rare variants with big effects. Meanwhile, detailed clinical information is required to define severe and less severe subtypes of any given disease. “Unfortunately, the majority of genetics projects today only study the top-line disease as it may be difficult to extract and harmonize clinical information,” says Gulcher. “In contrast, Genuity Science captures information across our clinical sites so subsets can be well defined in terms of disease course, outcomes, and complications.”
For more information visit genuitysci.com.
