Challenge: A biotech company needed to efficiently select and prioritize potential protein targets for drug discovery
A biotech start-up that specializes in drug discovery by therapeutically targeting proteins with specific structural features faced the daunting task of efficiently selecting and prioritizing potential targets.
The complexity of this challenge necessitated the development of a sophisticated in silico target prioritization platform. This platform had to seamlessly integrate multi-omics and disease association data, along with protein structure predictions, on a large scale using academic tools—a considerable undertaking.
Action: Diamond Age collaborated to design and build a comprehensive in silico target selection and prioritization platform
Recognizing the firm’s reputation for customized analyses, the client engaged Diamond Age (DA) to collaboratively design and build a comprehensive in silico target selection and prioritization platform.
DA assembled a bioinformatics consulting team of senior scientists and engineers. It combined expertise in genomics, proteomics, metabolomics, data modeling, and cloud engineering.
The Diamond Age team worked closely with the client’s internal scientists and academic advisors. The internal team provided in-depth knowledge on the biological impact of structural features and the company’s therapeutic strategy.
DA built a scalable cloud system for running simulations. It integrated the public data and protein structure predictions into a user-friendly dashboard. This empowered the client to effortlessly search and prioritize protein targets for further development.
Result: Client’s Continued Success in Drug Discovery
The combination of Diamond Age’s technical prowess in data integration, data modeling, cloud/software engineering, and expertise in biology and the various omics technologies, along with the client’s domain expertise, ensured the development of a tailor-made solution aligned with the company’s specific challenges and goals. By combining diverse genomics and proteomics datasets and leveraging advanced predictive modeling, the platform emerged as a powerful tool for streamlining the identification and prioritization of potential therapeutic targets.
This not only addressed the initial challenge of target protein selection, but also positioned the company for continued success in drug discovery. The platform played a pivotal role in the selection of one of the client’s current drug programs.
Reach out to Diamond Age if you need bioinformatics consulting help for drug discovery at your biotech or pharma company.