Foundation models (FMs) represent a big leap in artificial intelligence, designed to work on diverse and complex tasks in life sciences and beyond. These versatile models are pre-trained on vast datasets such as biological sequences, protein structures, single-cell transcriptomics, biomedical images, and text. This extensive pretraining allows FMs to achieve general learning goals, enabling them to be fine-tuned for specific applications like disease detection, drug design, and the discovery of novel therapies without reinitializing their parameters. This adaptability has positioned FMs as state-of-the-art tools across various AI-driven domains.
Building effective foundation models requires sophisticated architectures like transformers, convolutional neural networks (CNNs), graph neural networks (GNNs), and more importantly, high-quality training datasets. These datasets must be diverse, well-curated, and annotated to capture the complexity of biological systems. The models’ ability to generalize across multiple downstream tasks depends heavily on the quality and scale of these datasets. For instance, FMs trained on noisy or incomplete data may struggle to provide reliable insights or require extensive customization to function effectively. (1)
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Website: https://www.elucidata.io/ Website: https://www.elucidata.io/ Elucidata leverages its platform, Polly to augment the quality of data in pre-clinical drug discovery. It curates multi-omics and assay data to make them ML-ready or analysis-ready. Our exceptional multi-disciplinary team of experts use Polly’s powerful curation engine to harmonize a diverse array of data-types, curate metadata and process data consistently at affordable costs while maintaining information-richness. We are one of the only companies to offer a tech-enabled approach to multi-modal data curation that serves the life science industry. Polly’s technology and experts have helped R&D teams arrive at multiple validated drug targets across immunology, oncology, and metabolomic disorders. Currently, 25+ research organizations, including 4 of the largest 10 pharma companies are using Polly and its allied solutions to accelerate their discovery programs. Many other data-driven healthcare companies also use Polly to process, harmonize and store public or in-house biomedical data. Address: 114 Sansome Street, Suite 250 San Francisco, CA 94104 Phone No: 9716140329 Contact Email: info@elucidata.io
