BioSymetrics Joins Accenture’s INTIENT Network

BioSymetrics, a biomedical artificial intelligence company that helps researchers develop drugs with greater speed and precision, announced it has joined Accenture’s partner ecosystem, designed to help independent software vendors (ISVs) and life science companies integrate more effectively to accelerate drug discovery efforts and improve patient outcomes. The ecosystem is an integral part of Accenture’s INTIENT cloud-based research & development platform, which has been designed to help life sciences organizations improve end-to-end productivity, efficiency, and innovation from drug discovery through clinical and patient services.

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Accenture is currently working with BioSymetrics and a select number of other software partners and organizations to integrate their technology, content and processes into Accenture’s INTIENT platform. The inclusion of BioSymetrics’ technology will make it easier for life sciences companies to better understand how small molecules work, leveraging their own experimental datasets, public datasets, INTIENT partner data sets, and BioSymetrics’ own proprietary data. “The ultimate aim of our approach is to deliver safer, more effective medicines to patients, while reducing the long timelines associated with drug discovery,” said BioSymetrics CSO Dr. Gabriel Musso.

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“Our open partner network is one of the ways we’re differentiating our market approach and bringing innovation to our clients through Accenture INTIENT,” said Joe Donahue, managing director, Accenture Life Sciences. “BioSymetrics’ participation in the ecosystem and integration with INTIENT will give scientists another important capability to help interpret the growing volumes of rich and diverse data that is being generated in drug discovery.”

“We are honored to join the INTIENT platform,” said Anthony Iacovone, chairman of BioSymetrics. “The combination of our platform with other companies in the INTIENT network will create a powerful ecosystem of AI services designed to solve the most complex biological challenges in drug discovery.”