Healthcare & Drug Discovery

Healthcare & Drug Discovery

AI-powered breakthroughs in drug discovery, precision medicine & diagnostics.

AI-powered breakthroughs in drug discovery, precision medicine & diagnostics.

We accelerate healthcare innovation through state-of-the-art AI technologies. From drug discovery to disease diagnostics, our machine learning models analyze molecular, genetic, and clinical data to deliver more accurate, faster, and cost-effective biomedical solutions.

Challenges

Drug discovery is slow, costly, and failure-prone

Diagnostic models often lack generalizability and interpretability

Scarcity of high-quality biomedical datasets

Long development cycles and expensive wet-lab validation

Virtual screening with Denvis

Challenge: Drug discovery is bottlenecked by the slow and expensive process of screening compounds against target proteins.


Solution: AI-powered virtual screening with GNNs which rapidly evaluates small molecules for potential drug candidates. Also an AI-Guided Drug Repurposing solution.


Results: Accelerates early-stage drug discovery, reduces costs, and improves hit identification by predicting binding affinity with high precision. Reduces reliance on costly and time-consuming wet-lab experiments.


Facts: In a global collaborative effort aimed at identifying binders for COVID-19 proteins, DeepLab was one of seven teams, out of over a hundred (130), to successfully identify true binders Speeds up early-stage drug discovery: DENVIS is 1,000 ~ 10,000 times faster than its competitors

Generative AI for De Novo Drug Design

Challenge: Traditional drug design is slow and expensive, with many failures due to poor drug properties. AI can generate molecules that are both potent and drug-like.


Solution: AI-driven molecule generation designs novel compounds tailored for specific targets and optimizes both potency and drug properties simultaneously


Results: Increases the likelihood of clinical success, shortens development cycles and automates and accelerates the design-make-test cycle.

ML Solutions on precision medicine with Deep-ID

Challenge: Deep learning models in healthcare are often criticized as “black boxes,” making it difficult to understand their decision-making process.


Solution: Multi-modal AI models integrate diverse biomedical data while maintaining interpretability, allowing clinicians to identify key biomarkers and disease patterns.


Results: Enhances diagnostic accuracy, enables early disease detection, and provides transparent, explainable AI-driven insights for precision medicine.


Facts: Top pharma company as a client

Solutions

Solutions

DeNViS – AI-powered virtual screening

Rapid screening of over 1B molecules using GNNs, reducing time & cost

AI-driven de novo drug design

Generate & optimize molecules with improved ADMET properties

Deep-ID – Precision medicine

Multimodal AI models for disease diagnosis, prognosis & biomarker discovery

AI-guided treatment personalization

Leverage genomics, imaging, and clinical data to suggest optimal treatments

Results

Faster product discovery

Higher conversion and engagement rates

Frictionless customer experience

Accelerate discovery and diagnosis with AI

Let’s discuss your project or explore a partnership