Data science is becoming increasingly important to help our clients identify new targets, indications, drug assets, technologies and companies.
Our approach combines academic databases in the genomics and proteomics field with clinical and commercial databases. This gives us a holistic perspective that enables us to identify and prioritize:
- Novel drug targets based on customized screening criteria
- Re-purposing opportunities – eg. optimal matching of existing drugs (active or discontinued) with novel drug targets / biomarkers
- Indications with the best mix of scientific confidence, development feasibility and commercial opportunity
- Hidden gem assets available for licensing or acquisition
- Underappreciated companies to acquire
All of the above require the automatic or semi-automatic screening of large amounts of data. Key to successful screening is our long-term experience in curating data in a way that makes it machine-readable and high quality. We integrate traditional bio-informatics approaches with novel AI such as natural language processing (NLP) to tackle problems that would have been unsolvable just a few years ago.
We use these tools to combine with the deep expertise of our clients to create competitive advantage – that often makes the difference in successful fund-raising rounds, IPO readiness or significant partnering or even M&A.