By Oliver Haill
Date: Friday 22 Jun 2018
LONDON (ShareCast) - (Sharecast News) - Cancer-focused biopharma company Autolus Therapeutics priced its Nasdaq initial public offer at the top end of its $15-17 indicated range ahead of its trading debut on Friday, giving a boost for London-listed backers Syncona, Woodford Patient Capital fund and Arix Bioscience.
London-based Autolus priced the IPO at $17 per American Depositary Share, each of which representing one ordinary share, for total gross proceeds of roughly $150.0m and an estimated market cap of $660m.
For Syncona, which helped University College London haematologist Dr Martin Pule to found Autolus with initial financing in 2014 and had a 38% shareholding coming into the IPO, saw the value of its stake increase in value from the £86.7m last recorded value to £156m.
FTSE 250-listed Syncona has also agreed to buy $24m (£18.1m) of the new shares being issued in the IPO in order to retain a 33.8% stake in the business that will be valued at $231m (£174.4m).
Another shareholder, Woodford Patient Capital Trust, which owns a 20% stake of Autolus that makes up 4.35% of the trust's investments, said the confirmation of the IPO pricing increased the value of its stake by 51% to $104.7m for the trust's retained stake of 15.9%.
London-listed Arix said the value of its Autolus shares had increased by 73% to give an aggregate value of $53.7m. Arix had retained a stake of 8.2%, having agreed to invest $7.2m in the IPO.
Autolus is Arix's largest holding, accounting for 24.7% of invested and committed capital to date, having first invested in 2016.
Autolus is developing programmed T-cell therapies designed to target cancer by recognising cancer cells, breaking down their defence mechanisms and eliminate the cells. The company has a pipeline of product candidates in development for the treatment of haematological malignancies and solid tumours and is developing a commercial platform to support the rollout of these programmes, including currently investing in building an integrated end-to-end service model.
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