Effectively navigating and utilizing huge volumes of internal and external data remains aspirational for many large pharmaceutical organizations, and this hinders innovation. In the life-sciences, data is typically unstructured, and language is ambiguous, making keyword-based search and analytics unreliable.
Contextualizing the data by mapping key terms and concepts back to ontologies, public standards, or proprietary terminology enables this complex data to be found, accessed, and used interoperably to support downstream applications.
In this webinar, learn how Pfizer is driving scientific innovation using internal compound search as an exemplar use case. SciBite and Sinequa are supporting this at an enterprise-wide scale through our ongoing partnership.
We partner with leading enterprise search platforms to enhance real-time big data analytics for pharma and biotech companies. Semantic search capabilities improve the accuracy of search results allowing companies to make data-informed decisions. Find out more about how SciBite’s solutions can help unlock the potential of the R&D data in your business.
Sam leads partnerships and alliances at SciBite, working collaboratively with existing partners and developing new partnerships aligned to SciBite’s strategic goals. He has a strong technical background in the life sciences, with a PhD in Protein Biochemistry from the University of Nottingham and post-doctoral training in bioinformatics within the department of Neurosurgery at the University of California San Francisco.
Prior to Joining SciBite he held technical sales and commercial roles at Carl Zeiss and most recently led business development at Repositive, building relationships with contract research organisations, biotech’s and pharma companies, facilitating data exchange and search across multiomic datasets. He has a good grasp of the challenges of dealing with unstructured scientific data, and collaboratively developing practical solutions to overcome these.