AI Drug Discovery Startup Exscientia Raises $26M and Partners with Roche

AI Drug Discovery Startup Exscientia Raises $26M and Partners with Roche
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Exscientia recently created an artificial intelligence (AI) platform for augmenting drug discovery in both biotech and pharmaceutical.

“We can reduce at least 4- to 5-fold the time and cost of drug discovery as compared to the industry standard,” said Andrew Hopkins, the CEO of Exscientia.

Andrew Hopkins said that the funds raised would help in taking the company to another level; after de-risking and validating its technology, it is Exscientia’s time to concentrate on scaling up.

Exscientia is expected to begin building its own portfolio, as opposed to limiting itself to working with biotech and pharma partners. “We are interested in areas with strong, novel biological concepts, such as cancer evolution and rare diseases,” said Hopkins.

In its plans to scale up, Exscientia looks forward to expanding its pipeline and taking some programs into clinical testing.

The company also aims at expanding its operations into Asia.

Recently, Exscientia opened some offices in Japan and is currently looking forward to expanding into China, thanks to the ongoing changes in the country’s pharmaceutical landscape that are simplifying things for European-based companies.

Having already collaborated with big companies in the industry such as Evotec and Celgene, which also participated in the funding round, Exscientia has lured Roche into a partnership that is said to be worth a maximum of €60M.

Further details on the partnership deal are yet to be disclosed.

Hopkins is convinced that AI is currently in the same level that molecular biology was four decades ago, especially when firms like Genentech, Biogen and Amgen were established.

Currently, molecular biology is everywhere in pharma.

With artificial intelligence (AI), biotechnology firms could shift from working on one or even two projects whose progress the company entirely relies on, to having broader pipelines as well as additional efficient capital use.

“AI will only be adopted if it proves to be more efficient than the current paradigm. It’s the only metric that matters,” said Hopkins.


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