Computational Drug Discovery (CDD)

Solution Overview

Computational drug discovery is an AI-based solution that predicts the success of new molecules and helps revolutionize drug development. It analyzes molecular, biochemical, and pharmacological properties that offer insights for ameliorating essential decision-making processes. It uses advanced algorithms to shorten drug discovery timelines, cut costs, and double its success rate.More

Computational drug discovery is an AI-based solution that predicts the success of new molecules and helps revolutionize drug development. It analyzes molecular, biochemical, and pharmacological properties that offer insights for ameliorating essential decision-making processes. It uses advanced algorithms to shorten drug discovery timelines, cut costs, and double its success rate. By doing this, pharmaceutical companies get innovative treatments to market faster and become more cost-effective while also tackling many pain points in the industry and addressing an ever-increasing need for effective therapies in a competitive landscape.

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Industry Challenge

Developing new drugs and drug repositioning is an expensive, time-consuming, and uncertain process. Producing a single drug alone can cost more than USD 2.8 billion. Over the recent years, even as expenses to develop medicines continue to rise, there has been a sharp decline in manufacturing newly approved drugs. The pharmaceutical industry faces significant challenges, including higher costs and a lengthy development timeline. So, it is crucial to innovate and improve efficiencies in the drug discovery process to meet the growing demand for effective therapies in a competitive market.

Solution Highlights

AI-Powered Predictions

Utilizes AI to predict a molecule’s success by analyzing its molecular, biochemical, and pharmacological properties.

Deep Learning Insights

Leverages deep learning on drug datasets to uncover hidden relationships among parameters that influence drug development.

Enhanced Correlation Analysis

Provides a better understanding of correlations between molecular selection and biochemical entities to improve decision-making in the drug properties discovery process.

Advanced Algorithms

Shortens the drug development timeline using advanced algorithms to identify potential candidates faster.

Solution Benefits

  • Improves drug properties approval rates by 30%
  • Lowers drug development costs by up to 25%
  • 2x faster time to market the drug
  • Boosts research efficiency by 40%

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