Hi NVIDIA community,
I wanted to share a real-world application of NVIDIA GPUs in a fast-growing sector: AI-powered drug discovery.
We’ve been working with Ardigen, a platform that uses deep learning and bioinformatics to help identify novel drug candidates, especially in areas like oncology and immunotherapy.
⚙️ Where NVIDIA tech fits in:
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CUDA-powered training of deep learning models for compound screening and target identification
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Using NVIDIA A100 and RTX-series GPUs for rapid model iteration and testing
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Leveraging TensorRT and cuDNN for inference optimization across in-house pipelines
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Integration with Windows + WSL2 + Docker environments for hybrid prototyping and production workflows
This has helped Ardigen dramatically reduce training times and scale experimentation, which is crucial when working with high-dimensional multi-omics data.