Rethinking Drug Discovery with Transcription Factor Biology

For decades, drug discovery has largely been driven by a target-centric mindset. Researchers identify a protein believed to play a role in disease, design a molecule to modulate it and then assess whether altering that target produces a meaningful clinical effect. While this approach has delivered important medicines, its limitations are increasingly clear, particularly in complex, multifactorial diseases such as neurodegeneration. Despite enormous investment, many late-stage failures can be traced back to an incomplete understanding of disease biology and an over-reliance on familiar or well-studied targets. In parallel, advances in genomics and transcriptomics have transformed the ability to interrogate biological systems at scale. Rather than focusing on individual proteins in isolation, scientists can now measure how thousands of genes change their expression in disease and begin to reconstruct the regulatory networks that control those changes. At the centre of these networks are transcription factors. These are the cell’s primary method for regulation of gene expression, directly interacting with DNA and determining which genes are switched on or off in a cell. Changes in transcription factor activity therefore account for the gene expression shifts observed in disease. By calculating the transcription factor regulatory networks that control these aberrant gene expression signatures, the underlying biological networks of disease – including complex, multifactorial conditions – can be ‘mapped’. Recent advances in omics technologies, disease-relevant cellular models, high content imaging and artificial intelligence (AI) methods now make it possible to measure transcription factor activity directly, in single cells and at scale. Combined with clinical evidence that transcription factor pathways can be modulated indirectly through upstream targets, along with strong genetic evidence that they truly play a role in human disease, this has renewed interest in transcription factor-driven drug discovery. Scripta Therapeutics was founded in 2025 to apply this approach to neurodegenerative disease, with an initial focus on Alzheimer’s disease. From pharma to platform thinking Founder and CEO Peter Hamley’s interest in transcription factors is rooted in more than two decades of experience across large pharmaceutical organisations and biotech. He began his career at AstraZeneca in the UK before moving to Sanofi, where he led global chemistry groups supporting multiple drug discovery programmes. Later, he transitioned into business development, overseeing external technology partnerships and early-stage partnerships with companies including Schrödinger, PeptiDream, X-Chem and Exscientia, and later served as CSO at Samsara Therapeutics, a neurodegeneration start-up. His experience gained through involvement in many drug discovery programmes throughout his career led Hamley to a growing appreciation that many programmes ultimately fail in expensive proof of concept clinical trials not because chemistry or execution is weak, but because the underlying biological hypothesis is flawed. “In my view, most drug discovery starts with a target identified through a biased process, largely shaped by what appears in the scientific literature.” Scientific literature, Hamley notes, reflects funding priorities, historical focus and research trends as much as true biological importance. This bias can lead to repeated pursuit of the same targets while other, potentially more relevant drivers of disease remain unexplored. A more holistic approach, reflecting true human biology in an unbiased manner, should be more likely to be clinically effective. Why transcription factors matter Transcription factors occupy a unique position in biology. Around 1,600 are encoded in the human genome, each controlling specific gene expression programmes that govern cell fate, adaptation and function. In disease, these programmes become dysregulated, resulting in characteristic transcriptional signatures that reflect underlying pathology. Modern multiomic techniques make it possible to measure these signatures in patient tissue and disease models. Computational methods can then be used to infer which transcription factors are responsible for driving the observed changes. “Each transcription factor controls a specific programme of gene activity, which we can analyse using modern transcriptomics.” Advances in computational biology and transcriptomics have improved the ability to reconstruct gene regulatory networks from large data sets. These methods help distinguish upstream regulators from downstream effects, supporting a more mechanistic interpretation of disease biology. This is especially relevant in neurodegenerative disorders, where pathology arises from interactions across multiple pathways and cell types rather than a single dominant target. At Scripta, discovery begins with disease-associated transcriptional signatures rather than predefined molecular targets. Transcription factor activity is analysed in cellular context to identify upstream drivers of pathology, with proprietary networks of biology then used to guide the selection of druggable regulatory nodes. “To improve this situation, we aim to take a genuinely unbiased view of what’s causing disease.” The platform uses multiplexed live-cell imaging to measure transcription factor activity directly in cellular systems. Computer vision and AI-based analysis are applied to these data, enabling parallel assessment of multiple transcription factors and early characterisation of selectivity profiles. Another key component is the integration of patient-derived data. Scripta combines information from post-mortem tissue with data from patient-derived induced pluripotent stem cell (iPSC) models. In the context of Alzheimer’s disease, these cells can be differentiated into various disease-relevant cell types, such as cortical neurons, astrocytes and microglia, either individually or in combination, to capture specific aspects of pathology. By layering these data sources, the company builds detailed maps of how transcription factor networks evolve across disease stages, genetic backgrounds, and cell types. This provides a framework, not only for target identification, but also for understanding mechanism of action once potential therapeutics are identified. Making the undruggable druggable Transcription factors are challenging drug targets, particularly outside of oncology. Many lack obvious binding pockets for small molecules, likely because they act through protein–protein and protein–DNA interactions that are difficult to disrupt directly. Scripta’s strategy does not solely depend on binding transcription factors themselves. They can also modulate their activity indirectly by targeting upstream proteins that regulate their stability, localisation or activation state. “Our platform allows us to identify not only inhibitors but also activators of transcription factors. To do this, we’re focusing on finding ways to modulate transcription factor activity indirectly through upstream protein targets, though we don’t rule out the possibility of identifying direct binders.” There is growing clinical precedent for this approach. Omaveloxolone, marketed as Skyclarys, activates the transcription factor Nrf2 by inhibiting KEAP1, a regulatory protein that controls Nrf2 degradation. The drug does not bind Nrf2 directly yet successfully alters transcriptional programmes relevant to neurodegeneration. This example provides validation that transcription factor-driven biology can be translated into effective therapies when approached through the right regulatory nodes. Why start with Alzheimer’s disease Scripta’s initial focus on Alzheimer’s disease reflects both scientific opportunity and unmet medical need. Despite decades of research, the disease remains poorly understood at a systems level and effective disease-modifying treatments have been elusive. Hamley sees Alzheimer’s as an area where a more holistic, unbiased approach could yield new insights. Early work in patient-derived models has already identified transcription factors known to be involved in the disease, alongside others that have received far less attention but appear to play important roles. “These represent avenues into genuinely novel biology.” Importantly, Scripta uses the same patient-derived systems both to discover and to validate its molecules, rapidly learning and iterating through a ‘lab in the loop’ approach. This tight coupling between biology, screening and validation is designed to reduce the risk of disconnects between early discovery and later development. Building towards the clinic In early 2025, Scripta secured a $12 million seed round led by Oxford Science Enterprises and Apollo Health Ventures. Over the next 18 to 24 months, the company plans to scale its platform, run large high content screens and further develop its AI, bioinformatics and in silico systems, with the goal of taking new therapeutics into the clinic for Alzheimer’s disease and other neurodegenerative disorders. The Scripta team believes that their transcription factor-centric approach stands to uncover mechanistic insights into complex diseases and yield novel opportunities for disease-modifying therapeutics. While neurological disease is the initial focus, Hamley points out that the platform could understand and address other disease areas known to be driven by transcriptional dysregulation, including immunology and cardiovascular disease, as well as in addressing causes of ageing.