18.06.2026 | Published by bit.bio
18.06.2026 | Published by bit.bio
New human iPSC-derived hepatocytes are built for predictive reproducibility, chronic toxicity studies, and enhanced clinical translation in preclinical drug development
Cambridge, UK – 18th June 2026: bit.bio, the Cambridge-based pioneer in human cell programming, has today announced the launch of a new human iPSC-derived hepatocyte, called ioHepatocytes, designed to address some of the biggest limitations in liver toxicity testing and preclinical drug development.
Developed using bit.bio’s proprietary opti-ox™ technology, the firm’s deterministic cell programming technology, ioHepatocytes are designed to behave like mature human liver cells for extended periods of time.
Solving one of the major challenges associated with primary human material; sourcing sufficient high quality cells, the technology enables cell manufacturing on a massive scale, with unprecedented levels of consistency between batches. The functionality and the consistency of the cells allows researchers to conduct longer-term toxicity studies earlier in the drug development process and generate more reproducible data without relying on expensive and technically complex models.
“Traditional in vitro liver models inherently compromise on either biological relevance, reproducibility, cost, or scalability, " said Emma Pepperell, CEO of bit.bio. “With ioHepatocytes, we are helping to remove these bottlenecks to transform preclinical drug safety and discovery.”
The launch comes as the pharmaceutical industry faces growing pressure to improve reproducibility and generate more predictive human-relevant data. Industry estimates suggest that up to 95% of drugs fail during clinical development, with hepatotoxicity remaining a major contributing factor. It marks a major strategic expansion for bit.bio beyond its traditional focus on neuroscience and into the significantly larger toxicology and metabolism market.
Hepatocytes are the main functional cells of the liver, responsible for critical processes including drug metabolism, detoxification and metabolic regulation. Current in vitro liver modelling relies heavily on primary human hepatocytes. Despite being the conventional industry gold standard, they rapidly lose function once cultured, limiting their usability to just a few days. In addition, differences between donors can lead to significant variability between lots, necessitating costly and time-consuming lot revalidation. Alternative immortalised liver cell lines offer greater scalability but do not accurately replicate the biology of a healthy human liver.
ioHepatocytes have been developed to address these limitations by providing a scalable, reproducible human liver model that maintains functional maturity for extended periods in simpler 2D culture systems. bit.bio’s opti-ox™ deterministic cell programming platform enables the tightly controlled and consistent generation of cells, reducing experimental variability across experiments and streamlining research timelines.
Consequently, the lot-to-lot consistency of bit.bio's cells enables standardised data generation across entire drug discovery pipelines. This uniform quality is critical for pharmaceutical and biotech companies leveraging artificial intelligence to predict clinical outcomes, as these predictive AI models must be trained on exceptionally clean and consistent human data from day one.
Pepperell continued: “Researchers need models that not only reflect human biology more accurately, but are consistent across experiments, teams and sites over a longer period, as well as integrating with high-throughput screening and AI-discovery tools. The reproducibility and consistency of the experimental input is critical if we want to improve confidence in preclinical data and ultimately help bring safe, effective medicines to patients faster.”
The launch also reflects growing momentum across the life sciences industry toward reducing reliance on animal models and instead increasing the use of models that are predictive of human biology in drug development.
Pepperell concluded: “This launch represents an important milestone for bit.bio as we expand beyond neuroscience into toxicology and metabolism, opening up new opportunities to support drug discovery workflows with scalable, human-relevant cell models.”