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How AI will reshape pharma by 2025

Drug Target Review

Artificial intelligence (AI) has revolutionised many industries, yet its adoption in pharmaceutical drug development has been notably slower. For years, AI and machine learning (ML) were often dismissed as little more than advanced statistics with little practical value in drug development.

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Nobel Prize celebrates AI’s role in protein structure innovation

Drug Target Review

Despite its recent development, AlphaFold2 has already been applied in numerous studies across biology and medicine. Its applications include studying disease pathology to develop targeted therapeutics, visualising enzymes that can decompose plastics, and engineering solutions to antibiotic resistance, among many others.

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Q&A: How to jump-start new psychiatric and neurological drug development

Broad Institute

Brain disorders are difficult to study and many drug candidates have failed in clinical trials, causing pharmaceutical companies to reduce their investments or even exit the field entirely.

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The Data-Driven Future of Drug Development

DrugBank

Data science has emerged as an innovative tool in the biopharmaceutical industry, leveraging the power of machine learning and artificial intelligence to drive innovation and efficiency across the entire drug development lifecycle. These complex molecules require precise engineering to ensure optimal efficacy and safety.

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Feature Engineering with Databricks and Unity Catalog

Perficient: Drug Development

Feature Engineering is the preprocessing step used to make raw data usable as input to an ML model through transformation, aggregation, enrichment, joining, normalization and other processes. Sometimes feature engineering is used against the output of another model rather than the raw data (transfer learning).

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New rapid viral plaque detection system, aided by deep learning and holographic imaging, can help accelerate vaccine and drug development

SCIENMAG: Medicine & Health

Findings Credit: Ozcan Lab Findings In a new paper published in Nature Biomedical Engineering, a team of scientists led by Professor Aydogan Ozcan from the Electrical and Computer Engineering Department at UCLA and an associate director of the California NanoSystems Institute, developed a rapid, stain-free, and automated viral plaque detection system (..)

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Macrophage cell therapy: a new hope for chronic liver disease patients

Drug Target Review

Delivered as an autologous cell therapy, these macrophages have been engineered to increase their anti-inflammatory and anti-fibrotic properties, with the aim of delivering more potent and durable clinical effect to patients with end-stage liver disease. He is named on 15 patents relating to drug development in liver disease.

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