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Chemistry-aware AI offers new routes in small molecule design
AI has advanced molecule design, yet synthetic feasibility remains a bottleneck. Chemistry-first approaches offer a practical way forward.
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Medicinal Chemistry
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Inside Zasocitinib: a new model for TYK2 inhibition in immune-mediated diseases
Zasocitinib is a highly selective, investigational TYK2 inhibitor developed to target immune-mediated diseases with fewer off-target effects than traditional JAK inhibitors. This article explores its mechanism, selectivity data and clinical progress.
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From injections to pills: oral peptides set to transform drug development
Oral peptide-based drugs are set to revolutionise the pharmaceutical industry, overcoming the long-standing challenge of poor bioavailability. Santosh Kulkarni reveals how new breakthroughs in drug discovery and delivery offer the potential for more convenient, effective treatments for a range of conditions – without the need for injections.
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How AI is quietly changing drug manufacturability
AI is moving beyond drug design to answer a critical question: can a promising compound actually be manufactured at scale? By predicting synthetic feasibility early, machine learning tools are helping drug developers avoid costly failures, streamline R&D and design molecules that are both effective and practical to produce.
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New class of chiral molecules offers strong stability for drug development
Scientists have created a new class of ultra-stable chiral molecules – a discovery that could lead to more precise drug design by preventing potentially harmful molecular “flipping” over time
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Fixing drug discovery’s most persistent problem with AI
AI will not replace drug discovery, but it might finally fix one of its most frustrating bottlenecks. Read how a targeted approach to ADMET is cutting through the noise.
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How one carbon atom is changing drug development
Researchers at the University of Oklahoma have found a way to improve drugs by adding just one carbon atom. This simple change could speed up drug discovery and lower costs.
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Shifting the ADC focus from antibody to payload
While ADCs continue to attract attention in oncology, many developers remain focused on antibodies – overlooking the critical role of payload design. At Sygnature Discovery, Dr Joshua Greally is leading a shift in perspective, advocating for a payload-first approach through the company’s new platform, NewPath ADC. In this interview, he…
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Breakthrough trial offers new hope for cystic fibrosis patients
A promising new inhaled therapy is progressing in Phase 2 trials, presenting new opportunities for improving cystic fibrosis treatment.
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Developing the next generation of antibody drug conjugates
In this Q&A, Léo Marx, Medicinal Chemistry Project Manager at Debiopharm, details how the therapeutic window of ADCs can be impacted, how we can overcome the challenges associated with achieving site-specific bioconjugation, and other essential considerations for optimising ADC performance.
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Mushroom growth method could help develop antivirals and cancer drugs
Although Cordyceps mushrooms are challenging to cultivate, researchers have shown that they can be grown on edible insects to exploit their strong therapeutic potential.
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Cell painting approach used to identify drug compounds with unwanted side effects
Novel research has shown that morphological fingerprinting could help identify side effects of new bioactive compounds in drug discovery.
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Possible new class of compounds to treat diabetes identified
A recent pre-clinical study from Washington University School of Medicine showed that a new class of compounds can potentially improve multiple aspects of metabolic syndrome, including diabetes.
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Virtual method enables screening of billions of chemical compounds
A new platform, named Virtual Synthon Hierarchical Enumeration Screening, has been developed by researchers to efficiently discover drugs.
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Transformational machine learning approach could accelerate drug design
In this Q&A, Professor Ross King from the University of Cambridge, UK, discusses how a new machine learning approach could aid drug discovery and development. The method learns from multiple problems and improves performance while it learns.
