BioMedAI
From Target to Candidate — in One Platform

WeDaita is building BioMedAI, an agentic AI Operating System for drug discovery that accelerates biomedical research workflows, with an initial focus on target discovery and prioritization.

Live Now
Target Discovery Intelligence Agents (TDIA)
Coming Next
Drug Design
Coming Next
Clinical Trial
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Solving Drug Discovery at Scale

Drug discovery has long been defined by decade-long timelines, billion-dollar costs, and high failure rates. WeDaita is changing that — with AI agents built to compress timelines, cut costs, and improve decision quality at every stage of the pipeline.

90%
Failure Rate
9 in 10 drug candidates fail — most due to poor target validation and inadequate early-stage evidence. WeDaita's TDIA agents surface higher-confidence targets from the start.
10–15
Years per Drug
A decade-plus of research, design, and trials before patients see results. WeDaita compresses the early discovery pipeline from years to weeks.
$2–3B
Per Drug Candidate
Billions spent per approved drug — driven by inefficiency and late-stage failures. WeDaita reduces the cost burden by cutting wasted research cycles early.
Integrated Platform

Prediction-Driven Drug Discovery.

From target selection to patient advancement — guided by clinical progression intelligence at every stage.

Three specialized agent systems, each designed to reduce attrition at its stage and feed higher-confidence decisions into the next.

Stage 1 — Target Discovery
TDIA
Target Discovery Intelligence Agents
6 Agents Live
Target selection and prioritization, helping researchers identify and evaluate high-potential drug targets by integrating evidence from both public and proprietary data sources and generating predictions using our virtual AI models.
  • Deep Research Assistant
  • Disease Hypothesis Generation
  • Drug Target Prioritization
  • Drug Repurposing
  • Competitive Landscape
  • Biomarker Discovery
Focus
Target Discovery
Stage 2 — Drug Design
DDIA
Drug Design Intelligence Agents
1 Agent Live
Bridges the translation gap by automating protein, antibody, and small molecule design — with clinical progression guardrails baked into the generative process to reduce preclinical failure rates.
  • Protein / antibody drug design
  • Peptide/MacrocycleIn Dev
  • Small molecule design & optimisationIn Dev
Focus
AI Drug Design
Stage 3 — Clinical Trials
CTIA
Clinical Trial Intelligence Agents
1 Agent Live
Forecasts drug progression and addresses late-stage attrition through digital simulations, predictive recruitment, and biomarker-driven patient stratification — moving candidates from the lab ultimately to patients.
  • Pharmacovigilance
  • Predictive patient recruitmentRoadmap
  • AI-assisted protocol designRoadmap
  • Portfolio optimizationRoadmap
  • Digital twin trial simulationRoadmap
Focus
Clinical Prediction

See BioMedAI in Action

See how BioMedAI DBRA agents deliver trusted biomedical insights through intelligent AI agents

  • Plug-and-play biomedical AI via WeDaita MCP services
  • High-confidence insights from verified medical and clinical databases
  • Rapid literature review and clinical trial intelligence
  • Seamless agent-tool integration with zero local installation

Grounded in Primary Scientific Sources

Every insight traces back to 41 primary databases (PubMed, UniProt, ChEMBL, PDB, and more) and 173 scientific tools — not black-box outputs.

Built by Drug Discovery Scientists

Our team has decades of combined experience in computational biology, medicinal chemistry, and AI research.

Researcher in the Loop, Always

BioMedAI accelerates your thinking — your scientific judgement drives every key decision.

The Team Behind BioMedAI

Scientists, engineers, and domain experts united by one mission — making drug discovery faster and smarter.

Wenliang Zhang
Wenliang Zhang, PhD, MMed
Founder, CEO/CTO
  • Director of Data Science: Pfizer, Exo Therapeutics
  • Principal Data Engineer: AbbVie
  • Principal Software Engineer: PerkinElmer, Akoya Bio
  • Computational Biologist: Bluebird Bio, Tesaro
Chao Yang
Chao Yang, PhD
AI/ML Computational Chemistry Advisor
  • PhD in Chemistry, New York University
  • Postdoc Research, The Rockefeller University
  • Computational Chemistry: Axle Informatics, Exo Therapeutics
  • AI-guided Virtual Screening and Drug Design
Elena Chernokalskaya
Elena Chernokalskaya, Ph.D
Mentor and Growth Advisor
  • Founder, Boston Business Mentor
  • Certified Counselor, SCORE Mentors
  • Scientific Advisory Board, 908 Devices
  • Executive, Cytiva & GE Helathcare
  • Proteomics Group Leader, Vertex Pharmaceuticals
All Members  
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Ready to Accelerate Your Drug Discovery?

BioMedAI is live — start with target identification and protein drug design today, with more modules launching soon.

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