PREPAiRE is leveraging advanced machine learning techniques to innovate in the field of drug discovery and personalized medicine. Here’s a simplified summary of what they are doing:
Advanced Algorithm Use: The company is using Convolutional Deep Neural Networks (CNN) and Generative Adversarial Networks (GANs), both of which are complex machine learning models. CNNs are primarily used in pattern recognition within images, while GANs can generate new data that resembles the input data.
Chemical and Biological Modeling: With these algorithms, PREPAiRE is creating models that can identify the interactions between proteins and other substances (ligands), generate molecular structures with desired properties, and prepare synthetic data for drug discovery and personalized treatment. These models could potentially streamline the process of finding viable drug candidates.
Precision Medicine: The company is also working on integrating whole-genome sequencing with deep phenotyping to create a comprehensive view of a patient’s disease profile. This could enable more precise and effective treatment plans.
CRISPR and IPS Technologies: The utilization of advanced technologies such as CRISPR (a gene-editing tool) and IPS (induced pluripotent stem cells, which are a type of cell that can be guided to become any type of cell in the body) can establish new approaches for disease treatment and prevention.
Platform Integration: PREPAiRE’s platform aims to combine prediction done in silico (performed on computer or via computer simulation) with high-throughput wet-lab validation, which means testing these predictions in a lab environment. This iterative cycle of prediction and validation allows for continuous improvements and increases in efficiency, accuracy, and reliability.
In essence, PREPAiRE is pushing the boundaries of personalized medicine by combining advanced technologies and machine learning techniques to predict and validate effective treatments at an individual level. This could potentially revolutionize the drug discovery process and the way we approach disease treatment and prevention.
What does the collaboration look like?
The first part of the collaboration combines an Avalon representation of Prepaire to visualize on different services and procedures down to a genetic level. The information from population scale data, cell based disease models and predicitve insights will be a first part in the usage of the Aimedis NFT data marketplace to start mainstreaming on that type of information.
Prepaire will also enable Avalon users to get genetic information by sending in a blood sample that is being used to extract specific genetic information that then can be combined with the digital twin inside the Aimedis platform. In combination of health data, socio economic data, IoT and pharmaceutical data and the genetic information, AI is being used to further predict the likelyhood of future disease to help prolong life and health for decades to come.
