Parallel Bio
Parallel Bio

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TLDR

Contribute to human-first drug discovery using organoids and AI, helping accelerate new medicines by joining an mission-driven and inclusive team.

The Mission

Drug discovery has a translation problem: more than 95% of drugs that succeed in animal models fail in humans. We're building the alternative: human-first drug discovery, powered by organoids and AI, running on real human biology from the very first experiment.

Our platform is 87% concordant with clinical patient data - a vast improvement over the 3% translational success rate of animals. We’ve demonstrated the ability to model immunotoxicology, immunogen stimulation, and two autoimmune diseases with more on the way. Numerous pharma partners including 3 Fortune 500 companies are already using the platform. We've raised ~$30M from AIX Ventures, Marc Benioff, Jeff Dean, and Y Combinator. With the FDA Modernization Act 3.0 and the FDA's March 2026 validation framework, the regulatory tailwinds only continue to get stronger.

The opportunity ahead of the company is generational: build the first scaled engine for generating real human biological data, and use it to fundamentally change how medicines are discovered.

You may not see a role that applies to your experience now, however, we are always looking for exceptional talent to join our mission.

Submit your resume and tell us what you’re looking for so we can reach out as soon as a relevant position opens up.

Parallel Bio is an equal opportunity employer committed to fostering an inclusive and respectful workplace. We encourage applications from individuals of all backgrounds, regardless of age, gender, ethnicity, religion, disability, or sexual orientation.

Parallel Bio is transforming drug discovery with a human-first platform that leverages patient-derived immune organoids and advanced AI to produce real human biological data. By addressing the high failure rate of drugs in human trials, this approach accelerates development timelines and eliminates the need for animal testing, making it a more ethical and efficient alternative for the pharmaceutical industry.

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