Pharmaceuticals: Drug Discovery and Development Workflow

PredictModel offers an advanced AWS-driven solution for drug discovery and development, enabling pharmaceutical companies to streamline the process of identifying and developing new medications. Our comprehensive data engineering and machine learning platform accelerates research, ensures regulatory compliance, and optimizes resource management.

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Workflow Step Explanation

1. Data Storage: Amazon S3 serves as the primary data lake for storing raw biomedical and chemical data from various laboratory instruments and research studies.
2. Data Processing: Amazon EC2 provides the computational power required for intensive data analysis and simulations during the drug discovery phase, facilitating faster experiments and analysis.
3. Data Management: Amazon Aurora acts as a highly available and scalable relational database to store structured research data and transactional records related to drug development.
4. Machine Learning: Amazon SageMaker is used to build, train, and deploy machine learning models that can predict compound effectiveness and potential side effects based on historical and real-time data.
5. Monitoring and Optimization: Amazon CloudWatch monitors the performance of the entire workflow, logging metrics, and setting alarms to ensure optimal operation and compliance with industry regulations.