So, where are we now, and what’s next? Startups have been one of the key driving forces behind the drug-discovery drive, with fierce ambition, agility and willingness to tackle the unknown. Our passionate and determined startup leaders are pushing the boundaries of what’s possible in healthcare.

Let’s take a moment to spotlight three standout companies: Ochre Bio, Qureight, and Antiverse – all using highly targeted AI/ML approaches across complex disease challenges.

Building AI models on human data and testing it in human models

Ochre Bio is taking a fresh approach to chronic liver disease, combining advanced AI with human data to tackle one of the world’s most pressing health crises. Unlike traditional methods that rely heavily on animal models or simulations, Ochre focuses entirely on real human data, data that reflects the complexities of actual disease biology.

At the core of their work are three types of human discovery data: genetic screens, tissue atlases, and clinical atlases. Together, these datasets allow Ochre to build machine learning models that map disease pathways and identify promising therapeutic targets. With $15 million invested into developing these resources, the goal is clear: create AI systems capable of connecting genes, tissue behaviour, and clinical outcomes in ways that weren’t previously possible.

But the innovation doesn’t stop at the data. Ochre’s labs in New York and Taipei are setting a new standard for liver research. By using discarded donor livers, organs that would otherwise go to waste, they’ve created a unique testing environment. These livers are kept alive, genetically engineered, and used to explore disease progression and test RNA-based therapies. The work offers insights into liver disease biology that lab-grown cells or animal models simply can’t replicate.

Chronic liver disease is a growing crisis. Over the past 20 years, premature deaths due to liver disease have risen by 63.6%, and it’s now the only major chronic disease with incidence rising year-on-year. While emerging treatments are coming to market for earlier stages of disease, transplant remains the only treatment option for late stage disease. By focusing on non-invasive RNA therapies for chronic disease treatment, Ochre Bio aims to shift this paradigm – offering new ways to understand and treat late-stage liver disease. The hope is to intervene earlier and prevent the need for liver transplants, addressing a health crisis that impacts millions, and showing what’s possible when AI and biology meet in the lab.

Curating data in new ways and improving clinical trials

Clinical trials are the lifeblood of medical innovation, but data tracking through a complex trial can be fragmented, especially for diseases like idiopathic pulmonary fibrosis (IPF) and other lung conditions, where there are different forms of data to collate. The process often suffers from outdated workflows, and a lack of clear insights into how treatments actually impact patients.

Enter Qureight, a Cambridge-based company founded in 2018, that’s tackling this challenge head-on. With its AI-driven platform, Qureight is redefining how data is curated and used in clinical trials. The company’s technology integrates imaging data, clinical records, and biomarkers into a cohesive view of disease progression. This unified approach allows pharmaceutical companies to design smarter trials and uncover insights that were previously out of reach.

One of Qureight’s standout features is its advanced imaging analysis. For diseases like IPF, where progression is often subtle and difficult to track, their tools can detect minute changes in lung tissue over time. These precise measurements offer a clearer picture of how drugs affect patients, bridging a critical gap in the trial process.

Qureight’s platform helps ensure that trials enrol the right patients and measure the right outcomes. The result? Faster, more efficient trials that could accelerate the drug development timeline for some of the world’s most challenging diseases.

Using generative AI to tackle challenging targets in antibody discovery

Antibody development is a cornerstone of modern medicine, however, traditional discovery methods are often inefficient and ineffective for some of the most promising yet complex drug targets, like GPCRs (G-Protein Coupled Receptors) and ion channels. These targets are vital for treating a wide range of diseases, from cancer to neurological disorders. Yet, their dynamic and intricate structures have made them notoriously difficult to address using conventional approaches.

Traditional approaches to drug discovery using small molecules can suffer from low bioavailability and off-target side effects, which have hampered progress for decades. By harnessing structural and sequence data, Cardiff-based techbio company Antiverse uses generative AI to design “antibody libraries” with higher predictive accuracy – dramatically increasing the likelihood of discovering antibodies that bind to many challenging drug targets, when compared to traditional ‘trial-and-error’ discovery campaigns. Antiverse’s approach reduces the antibody discovery process from years to approximately six months.

Antiverse’s mission is clear: to expedite the discovery of precision antibodies that address unmet patient needs. By bridging the gap between biology and technology, Antiverse is creating a new frontier in drug development – unlocking potential in some of the hardest-to-treat diseases and redefining how the industry approaches its most challenging targets.

Harnessing data and collaboration to transform drug discovery

The healthcare industry is undergoing a profound transformation, with data-driven approaches reshaping the way we discover and develop drugs. Traditional methods, which often rely on animal models or limited patient cohorts, struggle to fully capture the complexity of human biology. By properly curating data, and using high-quality data from human models, these startups are able to utilise the full potential of AI, offering a more precise and scalable way to develop new therapies.

Collaboration is a key driver in this revolution. Partnerships between innovative biotechs and established pharmaceutical companies are accelerating progress by combining expertise and resources. For example, Ochre Bio’s alliances with GSK and Boehringer Ingelheim, and Antiverse’s recent partnership with Nxera Pharma, demonstrate how startups can leverage pharma networks to scale their impact. Similarly, Qureight is also partnering with large pharma, as well as researchers and healthcare providers, to collect data for its platform.

As AI becomes more deeply integrated into drug discovery – and as biotech and pharma work together ever more closely – addressing security concerns, regulatory requirements, and compliance will also be critical to ensuring its safe and effective use.

An exciting time for Drug Discovery: role of AI startups

The healthcare landscape continues to evolve, and startups like Ochre Bio, Qureight and Antiverse will play an increasingly important role in driving progress and reimagining how we approach drug discovery and development. By integrating AI and data at every stage, from identifying targets to validating therapies and streamlining trials, they are helping to create a more efficient and precise system for developing new treatments – and setting new standards for what’s possible in drug discovery, clinical trials, and beyond.

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