SoftServe Gen AI Drug Discovery Solution

Speed up your drug discovery with SoftServe’s solution, accelerated by Generative AI and NVIDIA BioNeMo Blueprints for small molecule generation and protein prediction. We streamline drug development by integrating advanced AI tools like MolMIM, DiffDock, and our proprietary molecular generator. This allows you to quickly identify and refine promising drug candidates, bringing life-changing treatments to the market faster and potentially more affordable.

The early stages of drug discovery can be costly, lengthy, and have low success rates due to the inefficiencies of current manual methods for identifying successful drug candidates. 

SoftServe's solution incorporates NVIDIA drug discovery technologies, such as DiffDock for molecular docking, MoIMIM for small molecule generation, and our own tool for additional molecular generation. It allows researchers to analyze a wide array of drug molecules in a digital environment, prioritizing candidates to test in the wet lab. This approach reduces the need for extensive wet lab testing and enhances the overall success rates of drug development. 

Developing medicine is costly and time-consuming. Speed up this process with AI.
Solutions by SoftServe, Built on NVIDIA's AI Models

Reduce Cost In Early-stage Drug Discovery

Automated generative virtual screening accelerates drug discovery and reduces early-stage costs. Explore SoftServe’s solution to see the impact firsthand.

Computer-Aided Drug Discovery Solution Explained

SoftServe Drug Discovery solution helps researchers, application developers, TechBio companies, and AI pharma discovery teams generate novel drug candidates. The integration of NVIDIA's tools provides state-of-the-art AI models and also significantly speeds up this process, seamlessly connecting every step of molecular screening. 

That reduces research and development costs, boosts efficiency in early-stage drug production, and creates new revenue opportunities. Ultimately, our solution improves the chances of bringing successful drug candidates to patients and improves their outcomes.

  • Improve accuracy in candidate selection
  • Speed up time-to-market for new drugs
  • Cut costs with AI-driven automation

How It Works

Generate Novel Compounds

Each molecule has a unique numerical representation, allowing us to explore new ones by navigating this space. By finding representations similar to existing molecules, we can generate new candidate compounds for further exploration.

Predict Target Properties

We train machine learning drug discovery models to predict key properties and evaluate the quality of generated candidates based on their structure. The workflow's modular nature allows for adding new models and adjusting target criteria.

Rank Candidates

Predicted properties, along with deterministic drug-likeness metrics and synthesis difficulty, help prioritize the most promising candidates for lab experimentation. This focused selection process enhances the chances of selecting a successful drug candidate.

Solution Architecture

NVIDIA AI Enterprise enables the fast, scalable deployment of cutting-edge AI workflows through NVIDIA NIM microservices. This level of scalability is crucial for delivering real-time insights in healthcare and life sciences, ensuring seamless performance even in data-intensive environments.

NVIDIA AI Enterprise Software Used

  • NVIDIA NIM™
  • NVIDIA BioNeMo™
  • NVIDIA® TensorRT™
  • NVIDIA NeMo™
Explore NVIDIA's BioNemo Models

Use Cases

Generation of Novel Molecular Compounds

Generation of Novel Molecular Compounds

Rapidly create novel molecular compounds tailored for specific therapeutic targets. By using artificial intelligence in drug discovery, this tool employs advanced algorithms, enabling researchers to explore vast chemical spaces and optimize molecular properties to enhance efficacy and safety. 
BeautyHealthcare and Life Sciences

Protein Structure Prediction

Generation of Novel Molecular Compounds

Rapidly create novel molecular compounds tailored for specific therapeutic targets. By using artificial intelligence in drug discovery, this tool employs advanced algorithms, enabling researchers to explore vast chemical spaces and optimize molecular properties to enhance efficacy and safety. 
BeautyHealthcare and Life Sciences

Molecular Docking and ADME-Tox Predictions

Generation of Novel Molecular Compounds

Rapidly create novel molecular compounds tailored for specific therapeutic targets. By using artificial intelligence in drug discovery, this tool employs advanced algorithms, enabling researchers to explore vast chemical spaces and optimize molecular properties to enhance efficacy and safety. 
BeautyHealthcare and Life Sciences

Generation of Novel Molecular Compounds

Rapidly create novel molecular compounds tailored for specific therapeutic targets. By using artificial intelligence in drug discovery, this tool employs advanced algorithms, enabling researchers to explore vast chemical spaces and optimize molecular properties to enhance efficacy and safety. 
BeautyHealthcare and Life Sciences

Our Implementation Cycle

01Assessment & Design

  • Assess current workflows and identify inefficiencies
  • Set performance benchmarks
  • Develop AI-driven processes
  • Outline a high-level design and timeline

02Pilot Phase

  • Implement and fine-tune AI pipeline
  • Build a scalable infrastructure
  • Integrate with molecular data
  • Run pilot tests on candidate molecules

03Rollout & Improvements

  • Train research teams to use the AI pipeline
  • Analyze lab feedback and success rates 
  • Refine AI algorithms and workflows based on lab results 
  • Roll out the solution, fully integrating AI into the drug discovery process 
  • Assess current workflows and identify inefficiencies
  • Set performance benchmarks
  • Develop AI-driven processes
  • Outline a high-level design and timeline

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