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    Accelerating Drug Discovery with BioLLMs

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    Sold by: Loka 
    Engage in our BioLLM Acceleration program and transform the traditionally costly and protracted drug discovery process. Within 10-12 weeks, our experts build model architectures using BioLLMs such as Protein and DNA language models customized to your proprietary and expanded public datasets. By leveraging generative AI, we are able to exceed the limits of physical screening for bigger sampling and better candidate selection. Our work concludes with a comprehensive Proof of Concept (POC), model performance comparison, resulting model, intermediate datasets and more – paving the way for broader training initiatives and productization.
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    Accelerating Drug Discovery with BioLLMs

     Info
    Sold by: Loka 

    Overview

    How it Works:

    Phase 1 - Discovery & Data Preparation (1-2 weeks): We collaborate with stakeholders to define specific drug discovery objectives and prepare the integrated proprietary and public datasets for model training. This phase sets the foundation for building architectures tailored to key tasks using BioLLMs.

    Phase 2 - Model Development & Preliminary Testing (6-7 weeks): During this technically intense phase, we train BioLLMs using advanced ML techniques on the prepared datasets, followed by initial testing to evaluate performance and scalability for predictive and/or generative workflows for drug discovery.

    Phase 3 - Optimization, Validation & POC (1-2 weeks): The final phase involves refining the BioLLMs for optimal performance and validating their predictions against known benchmarks. A comprehensive POC is developed to demonstrate the models' effectiveness in streamlining the drug discovery process.

    Who is this for?

    • Biotech companies
    • AgTech ventures
    • Big Pharma arms focusing on R&D rather than commercial or clinical stage

    What you get: Since 2023, over 60 life science and healthcare companies have accelerated generative AI adoption with the Loka.

    1. Proof of Concept (POC): Validate the effectiveness of BioLLMs in achieving goals such as advancing drug discovery.
    2. BioLLM Architecture: Develop a custom modeling architecture that leverages leading models such as ESM and MoLFormer that is customized your specific use case.
    3. Performance Evaluation: Setup a robust validation strategy and adequate evaluation metrics that best approximate performance in production.
    4. Model Training and Validation: Integrate optimized training jobs and experiment tracking within AWS, paving the way for broader training efforts and model productization.

    Highlights

    • Enhance Predictive Power: Embeddings from large open models like ESM can be readily calculated and paired with simple predictive architectures to boost predictive power on internal data. Expand Screening Capacity: Open generative models seamlessly generate novel molecules, enhancing success rates when combined with a robust predictive model. Tailor Models to In-House Data: Large open models can be fine-tuned with public and proprietary data to significantly improve performance.

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    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Vendor support

    To schedule your free Consultation contact Loka at AWS-team@loka.com , or your AWS representative.