Oligonucleotide drugs—short strings of genetic material that can silence or repair faulty genes—are piling up in development pipelines, but the tools to check their purity during manufacturing are still stuck in the small-molecule era. Intellegens is building a machine-learning tool that predicts impurities in these large, complex molecules, using a database of known structures and intelligent look-up logic to create profiles for each target drug. Current impurity-prediction software, designed for conventional small-molecule drugs, cannot handle the size and complexity of oligonucleotides. That gap forces manufacturers into costly trial-and-error purification, slowing scale-up and raising development costs. If the tool works, it could cut those costs and speed the path from lab to clinic for a class of medicines already targeting oncology, central nervous system disorders, and genetic diseases. The project is applied, not fundamental: it aims to deliver a commercial digital interface that pharmaceutical companies can use directly in manufacturing. Success would mean faster, cheaper production of oligonucleotide therapies, potentially expanding access to treatments tailored to a patient’s own genome.
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Intellegens Ltd is seeking to develop a novel ML-powered digital tool to provide organisations with a user interface for oligonucleotide characterisation and impurity prediction. Intellegens will collaborate with the Centre for Process Innovation (CPI) to build an extensive database of associated structures and intelligent look-up logic defined and coded into the software to create specific profiles for target molecules. Nucleic Acid Therapies (NATs) is a major emerging new class of medicines, offering enormous potential to treat a range of common and rare diseases with typically reduced timescales for development that can be quicker than other classes of drugs. In addition, NATs provide opportunities to tailor treatments to individual patients based on their genome sequence. However, the broader clinical application of NATs can be limited by current methods of manufacture and delivery. Oligonucleotides are segmented into several classes, including antisense, ribozymes, aptamers, miRNA, CPG/Immunostimulatory and RNAi. Many therapeutic areas and indications are currently targeted by oligo therapies from oncology (29%), Central Nervous System (CNS) disorders (12%) and genetic disorders (9%) to cardiovascular, respiratory, ophthalmology, gastrointestinal and infectious diseases. The global oligonucleotide development pipeline currently has 660 in preclinical, 70 phase-1, 94 phase-2, 19 phase-3 and 13 marketed, with a larger proportion targeting patient populations \>500k. 40% of approvals have occurred within 5-years (e.g. Inclisiran), providing a positive signal/confidence that oligonucleotides are a valid therapeutic area \[NICE,2021\]. This is encouraging more investment at the discovery end. Impurity prediction tools designed for small molecules are not sophisticated enough to predict impurities for oligonucleotides. With improved mechanistic understanding and screening approaches, more potent oligo candidates with better safety profiles can be identified for treatment of an increasing range of diseases and patient populations. The recent surge in approved oligonucleotide therapeutics indicates imminent potential as oligos are of intermediate size with much-improved selectivity towards the target and fewer off-target effects than small molecules \[Thakur,2022\]. Intellegens addresses the unmet market need for a digital tool capable of impurity prediction and characterisation of the large and complex nature of oligonucleotides. Subsequently, reducing development costs and facilitating manufacturing scale-up.
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