Optibrium Appoints Head of North American Operations to Support Growing Demand
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Optibrium has announced the appointment of Dr Tamsin Mansley in a new role as Head of North American Operations. The appointment marks the opening of Optibrium’s new office in Cambridge, MA, USA and represents the next phase in the company’s expansion plans and business growth, driven by the rapid adoption of its StarDrop™ software.
Tamsin will be responsible for Optibrium’s operations in North America, supporting the company’s existing client base and leading the development of new business opportunities for StarDrop and the company’s full range of products for small molecule design, optimization and data analysis. Tamsin has over 10 years of experience developing, supporting and selling computational modelling and chemoinformatics software.
Tamsin’s passion for supporting project teams, enabling them to gain the best value from their software, is complemented by her post-doctoral research at the University of Texas and experience as a medicinal chemist at Eli Lilly and UCB Research.
Tamsin commented, “I am excited to join Optibrium and looking forward to working with both existing and new clients, and supporting the Optibrium community across North America. I have a great respect for Optibrium’s strong scientific focus and vision for the future development of its products.”
Matthew Segall, CEO of Optibrium, commented, “Engaging with and supporting our users is Optibrium’s top priority and this exciting development enables us to enhance our ability to provide local support in North America. Tamsin’s appointment and the expansion of our team of scientists, celebrates the company’s success.”
Optibrium’s StarDrop software suite helps researchers to deliver optimally balanced, successful compounds. It brings confidence and intuitive simplicity to decision making; guiding and validating the direction taken by project teams and which compounds are prioritized.
StarDrop works by evaluating project teams’ complex data, which is often uncertain because of experimental variability or predictive error. Its interactive tools then enable researchers to efficiently explore ways to further improve their chosen compounds.
