Keerie, A. | Search bioRxiv

bioRxiv2025

Artificial intelligence-augmented drug discovery identifies gefitinib as a potential treatment for ALS

Amyotrophic lateral sclerosis (ALS) is characterised by motor neuron (MN) death; however, astrocytes play a key role in disease pathogenesis. Developments in the field of artificial intelligence (AI) have the potential to impact drug discovery in multiple ways, including the rapid identification of drug repurposing candidates. A combination of natural language processing and deep learning algorithms was used to generate a knowledge graph based on scientific literature, omics and chemical databases, and other public sources with the aim to identify drug repurposing candidates for ALS. The aim of the study was to determine the effect of a cancer compound identified by AI, gefitinib, on MN survival, and to decipher its mode of action inin vitroandin vivomodels of ALS. We used co-cultures of healthy motor neurons with ALS patient-derived astrocytes (iAstrocytes), obtained through a semi-direct conversion protocol, to assess the neuroprotective properties of gefitinib. Compound treatment led to a significant rescue of MNs cultured with ALS iAstrocytes and a significant reduction in the levels of cleaved TDP-43 fragments in ALS iAstrocytes. Our data suggest that gefitinib-mediated activation of autophagy decreased the 35 kDa fragments of TDP-43. In a proof-of-conceptin vivostudy in SOD1G93Amice, gefitinib treatment significantly delayed the onset of neurological symptoms, thus showing the potential of AI-augmented drug discovery for neurodegenerative disorders.Significance StatementThis study presents an AI-augmented method of identifying potential repurposing candidates for disease with an unprecedented speed. The AI’s results were validatedin vitrousing iAstrocytes differentiated from induced neuronal progenitor cells (iNPCs), which are pathophysiologically relevant models suitable for studying neurodegeneration. iNPCs recapitulate many pathological hallmarks of the disease and they retain the ageing phenotype of the patient that they are obtained from. TDP-43 proteinopathy is one of the disease hallmarks observed in patients and is present in 97% of ALS patients. Here, we show gefitinib, a repurposing candidate identified by AI, improves survival of MNs in a co-culture with patient-derived astrocytes and can modulate TDP-43 proteinopathy.

neuroscience↗

bioRxiv2024

Maximising the translational potential of neurophysiology in amyotrophic lateral sclerosis: a study on compound muscle action potentials

Transgenic mouse models of amyotrophic lateral sclerosis, such as the widely used SOD1G93A mouse, enable investigation of disease mechanisms and testing of novel therapeutic interventions. However, treatments that have been considered successful in mice have often failed to translate into human benefit in clinical trials, particularly when relying on the so-called survival read-out. Compound muscle action potentials (CMAPs), are a simple neurophysiological test that measures the summation of muscle fibre depolarisation in response to maximal stimulation of the innervating nerve. CMAPs can be measured in both mice and humans and decline with motor axon loss in ALS, making them a potential translational read-out of disease progression which could help bridge the preclinical and clinical divide. Herein we assess the translational potential of CMAPs and ascertain at what time points human and mouse data aligned most closely. We extracted data from 18 human studies and compared with results generated from SOD1G93A and control mice at different ages across different muscles. We found that the relative CMAP amplitude difference between SOD1G93A and control mice in tibialis anterior and gastrocnemius muscles at 70 days of age was most similar to the relative difference between baseline ALS patient CMAP measurements and healthy controls in the abductor pollicis brevis (APB) muscle. We also found that the relative decline in SOD1G93A tibialis anterior CMAP amplitude between 70-140 days was similar to that observed in 12 month human longitudinal studies in APB. Our findings suggest CMAP amplitudes can provide a translational window, from which to make comparisons between the SOD1G93A model and human ALS patients. CMAPs are easy to perform and can help determine the most clinically relevant starting/end points for preclinical studies and provide a basis for predicting potential clinical effect sizes.

neuroscience↗