The conversations surrounding artificial intelligence (AI) and its scope to transform the pharma industry have been underway for a while now. In fact, reports suggest that the global health-related AI market is set to be worth $284bn by 2030.
Pharmaceutical development company Algorae (ASX: 1AI) is one of the companies at the forefront of this development. With its AI platform, AlgoraeOS, the Company is gearing up to advance drug development.
AlgoraeOS is a proprietary AI biopharmaceutical prediction platform, under development by the Company in partnership with AI specialists from the University of New South Wales (UNSW). Its goal is to forecast synergistic combination drug targets using machine learning, deep learning, and neural network algorithms, leveraging the extensive AlgoraeOS Database, which houses medical and scientific data curated specifically for AI-driven drug discovery within the platform.
Expected to become operational in the third quarter of CY24, AlgoraeOS will generate fixed-dose combination drug targets, enhancing Algorae’s therapeutic pipeline or potentially being licensed to third parties.
Fixed-dose combination drugs contain two or more active pharmaceutical ingredients in a single dosage form. Developers can use existing data from individual drugs to create improved treatments. These drugs offer several advantages, including enhanced efficacy through synergistic effects, reduced side effects due to lower doses, a broader spectrum of activity, and better drug delivery.
The AlgoraeOS Database will continually receive data modules, while the AI platform will undergo refinement across subsequent versions for at least three years to enhance its predictive abilities.
Currently, data acquisition and customisation efforts are underway across four main areas: drug data, cellular data, chemistry, and biological data. The initial data being formatted and integrated into the database span various scientific and medical domains, including chemical structures, clinical drug details, gene expression, and drug perturbation data. Uptil now, the information received includes specific databases from some of the largest pharmaceutical companies in the world, originating most significantly from Merck and Co., Inc (Merck) and Novartis AG.
AlgoraeOS also has access to the Southern Hemisphere’s most powerful supercomputer, ‘Gadi’, managed by National Computational Infrastructure (NCI Australia). Previously used for climate modeling and disaster prediction, Gadi boasts over 250,000 CPU cores, 930 Terabytes of memory, and 640 Nvidia GPUs. It has a peak operational capacity surpassing 10 petaflops, or 10 quadrillion floating-point operations per second. Gadi, meaning ‘to search for’ in the Ngunnawal language, will greatly enhance computational power for AlgoraeOS. This will facilitate advanced AI analysis of the extensive scientific and medical data housed in the AlgoraeOS Database upon completion.
In H1 FY24, Algorae, which also has three drug candidates in its pipeline, reported a revenue of $50.5k against a net loss of $1.4m, with $405k on research and development. Overall, its net cash outflow from operating activities decreased from $1.1m in H1 FY23 to $1m, due to cost reductions. The Company ended the half with $622.4k cash in hand, down from H2 FY23’s $2m.
Since partnering with UNSW in October 2023 and appointing Associate Professor Fatemeh Vafaee as project leader, Algorae has hired three full-time development staff. Two of these staff members have received support from the CSIRO Next Generation AI Graduate Program, with CSIRO funding approximately two-thirds of their salaries over a three-year period, while Algorae covers the remaining one-third. A fourth full-time member, eligible for CSIRO grant funding, is anticipated to join the team soon, as several candidates with advanced pharmacology expertise are currently under consideration for the position.
Algorae maintains full ownership of all project intellectual property, including synergistic combination drug targets. AlgoraeOS will also specialise in predicting the therapeutic potential of cannabinoid combination drug targets, setting it apart from similar platforms developed by international peers.
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