Model Gateway: Model Management Platform for Model-Driven Drug Discovery

TL;DR

The paper introduces the Model Gateway, a comprehensive platform for managing machine learning models in drug discovery, supporting advanced AI tools and achieving high scalability to accelerate pharmaceutical research.

Contribution

It presents a novel management platform integrating LLM Agents and Generative AI for scalable, efficient model handling in drug discovery pipelines.

Findings

Achieved 0% failure rate beyond 10k clients

Supports dynamic consensus models and asynchronous execution

Enhances MLOps infrastructure for drug discovery

Abstract

This paper presents the Model Gateway, a management platform for managing machine learning (ML) and scientific computational models in the drug discovery pipeline. The platform supports Large Language Model (LLM) Agents and Generative AI-based tools to perform ML model management tasks in our Machine Learning operations (MLOps) pipelines, such as the dynamic consensus model, a model that aggregates several scientific computational models, registration and management, retrieving model information, asynchronous submission/execution of models, and receiving results once the model complete executions. The platform includes a Model Owner Control Panel, Platform Admin Tools, and Model Gateway API service for interacting with the platform and tracking model execution. The platform achieves a 0% failure rate when testing scaling beyond 10k simultaneous application clients consume models. The Model Gateway is a fundamental part of our model-driven drug discovery pipeline. It has the potential to significantly accelerate the development of new drugs with the maturity of our MLOps infrastructure and the integration of LLM Agents and Generative AI tools.