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Aiding Drug Repurposing Investigations with AI

Drug repurposing offers a cost-effective and efficient pathway to discovery new therapeutic uses for existing treatments. AI can advance this process by rapidly analyzing large-scale biomedical data and scientific texts to identify drug-disease relationships, opening up avenues for treatments in unexplored indications.

Anna Tzani

February 23, 2024

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Comparison of Safety Biomarkers for Chemotherapeutics

The identification and utilization of safety biomarkers plays a key role in mitigating toxicity risks and reducing costs in drug development, thereby accelerating the delivery of safe and effective drugs to patients. AI can streamline the identification of relevant biomarkers from the ever-growing biomedical literature, offering insights into drug resistance and toxicity.

Anna Tzani

February 9, 2024

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AI-Powered Drug Discovery: Identifying Safety Red Flags

Unmanageable toxicity accounts for 30% of clinical drug development failures and can cause severe side effects and potential harm to patients. Download our report to see how AI-powered drug discovery can help mitigate late-stage clinical failures and market withdrawals.  

Anna Tzani

January 30, 2024

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Neurology

Anna Tzani • February 23, 2024

Aiding Drug Repurposing Investigations with AI

Drug repurposing offers a cost-effective and efficient pathway to discovery new therapeutic uses for existing treatments. AI can advance this process by rapidly analyzing large-scale biomedical data and scientific texts to identify drug-disease relationships, opening up avenues for treatments in unexplored indications.

Anna Tzani • November 1, 2023

Exploring the Cerebral Palsy Treatment Landscape

Cerebral palsy is an incurable neurological condition with profound motor function impact.  This blog explores the treatment challenges of cerebral palsy, focusing on central nervous system and musculoskeletal drugs, two mainstay medications to manage neurological symptoms, muscle plasticity and the related neuromuscular challenges.

Dana Mavreli • September 19, 2020

Preclinical safety analysis using Artificial Intelligence on the example of Alzheimer’s Disease.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that currently produces dementia in 5.8 million U.S citizens. This number is projected to reach 13.5 million by 2050 highlighting the urgent need for means to prevent, delay the onset, slow the progression and improve the symptoms of AD (1).