Better Predictive Modelling for Better Drug Development
Discover how predictive modelling, QSP, AI, and systems biology creates better drug development by connecting biological evidence with better predictions.
“The pharma industry is beginning to look at biological age as a surrogate endpoint to improve clinical trials."
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Discover how predictive modelling, QSP, AI, and systems biology creates better drug development by connecting biological evidence with better predictions.
BMS and NVIDIA are building a powerful pharma AI factory using advanced supercomputing, AI models, and scientific data to accelerate drug discovery.
Find out how q-CAR drug discovery moves beyond static protein structures by linking protein dynamics, ligand activity, and AI to precision drug design.
Read about how Throne Science is advancing passive health monitoring with AI-powered sensing that automatically captures daily toilet habit data.
Ocular drug delivery faces major biological barriers. Nanocarriers could improve bioavailability, tissue targeting, controlled release, and treatment for difficult eye diseases.
AI-designed bacteriophages show how genome models could create new antibacterial therapies while forcing pharma to rethink biological AI governance and biosecurity.
WHOOP and Natural Cycles show how wearable health data is moving into regulated digital health, creating new opportunities for women’s health and pharma.
Collaboration in drug discovery can shape pharma R&D success. Explore the evidence on pharma partnerships, knowledge sharing, governance, and innovation.
RNA biosensors for diabetes could allow earlier diagnosis and better personalised care. Explore the power of AI monitoring and next-generation molecular diagnostics.
Find out how psychedelic drug discovery is evolving through receptor pharmacology, behavioural science, and neuroplasticity to develop safer CNS therapeutics.
Google SensorFM was pretrained on over one trillion minutes of wearable data. Discover what this AI foundation model could mean for digital health and pharma.
Read about machine learning for lipid nanoparticle design used to improve cell, gene, and RNA drug delivery and help optimise next-generation therapeutics.