Can you routinely identify potential off-target effects?
- Combine sophisticated machine learning-driven predictions with mass spectrometry and gene expression data to screen potential drug candidates for likely off-target effects.
- Quickly evaluate potential candidates for likely side effects or toxicity.
- Informed pipeline decision making at an early stage saves time, money and attrition, and improves the likelihood that your drugs will make it to market.
Can you adequately scale-up your analysis?
- The Aigenpulse Platform’s high-performance back end allows you to run advanced machine learning algorithms, including the Risk Profiling module, without slowing platform speed or functionality.
- Running as a scalable microservice that crunches the data in the background while you continue your work, the platform notifies you when the analysis has been completed and is ready for review.
- Run and re-run 100,000s of analyses with no loss of performance with the assurance of all parameters and results saved and accessible.
Interactive focus on key data
- Potential drug targets can be evaluated in the context of large amounts of expression data and visualised as interactive plots.
- Intuitive visualisation can help you to hone in on key data points, and inform on whether a candidate target should be progressed.
Built around in-house data, augmented with external sources
- The Aigenpulse Platform is designed to help you to build a powerful and tailored analysis pipeline by combining multiple, disparate datasets from internal and external sources.
- The Aigenpulse Platform takes care of standardising and integrating these datasets using our Gene Matching technology.
- This allows you to leverage advanced machine learning algorithms that maximize the benefit you can derive from valuable data and resources.