RADGenT logo RADGenT
🔬 AI-powered Drug Discovery Platform

Rajpal Agrawal Drug Generation Tool

RADGenT helps design and evaluate new chemical entities (NCEs) — from target identification through virtual hits, lead optimisation, and clinical evidence.

Explore Tools Drug Development Steps
⚙️ AutoDock Vina + cavity-aware scoring
🧪 hERG, CYPs, solubility, permeability
📦 SDF, MOL2, PDBQT, SMILES
🔁 Reproducible pipelines
📊 Statistical analysis with STMS
🧠 Pharmacology quiz — radgentQ
Platform
RADGenT tools

Modular apps that assist at every stage of drug discovery — from statistical analysis to ADMET prediction, docking, and beyond.

Available now

📊 STMS — Statistical Tool for Medical Students

Classical biostatistics for medical and pharmacological research: t-tests, ANOVA, Chi-square, regression, survival analysis and more.

  • Analyse preclinical and clinical data (efficacy, toxicity, PK).
  • Generate publication-ready DOCX & PDF reports.
  • ML exploration, sample size & power analysis built-in.
🚀 Launch STMS
Where STMS fits
  • Design & analysis of in-vivo / in-vitro experiments.
  • Data from toxicology & efficacy studies.
  • Summaries for clinical trial reports.
Available now

🧪 RADPT — Drug Prediction Tool

Predict drug-likeness and ADMET descriptors from Name + SMILES input.

  • MW, LogP, HBD, HBA, TPSA, RB descriptors.
  • Lipinski & Veber rule-based filters.
  • Similarity scoring to reference drugs.
🧪 Open RADPT
Where RADPT fits
  • Filter virtual hits before synthesis.
  • Support lead optimisation decisions.
  • Combine with docking and ML scores.
Planned

⚓ RADock — Molecular Docking

Structure-based virtual screening with Vina and cavity-aware scoring.

  • Upload PDB protein and ligand files.
  • Define binding site and constraints.
  • Export ranked docking poses and scores.
Planned role
RADock scores will feed into RADPT, RAlib and ML models — closing the loop between docking and data-driven filters.
Concept stage

📚 RAlib — Library of Drug Candidates

A central library of virtual and experimental candidates with docking, ADMET and ML scores in one place.

  • Organise molecules by project or scaffold.
  • Search by structure, similarity or properties.
  • Export shortlists for synthesis or testing.
Planned benefits
A single view of your NCE landscape — decide which series to advance and where to explore next.
Concept stage

🤖 ML Models — QSAR & property prediction

QSAR and deep learning (GNN) models to predict potency, selectivity and ADMET from structure.

  • Train on your project datasets.
  • Score RAlib batches automatically.
  • Combine with docking and RADPT for smarter ranking.
Vision
Integrate physics-based and data-driven approaches to propose NCEs with the best balance of affinity, safety and developability.
Future

🌱 RAEco — Environmental Toxicity

Estimate environmental risk of drugs and metabolites: persistence, bioaccumulation, ecotoxicity.

  • Flag molecules with high ecological hazard.
  • Support greener by design strategies.
  • Complement human safety with environmental safety.
Why it matters
New drugs should be safe for patients and for the environment. RAEco brings ecotoxicity into early decision-making.
Available now

🧠 radgentQ — Pharmacology Quiz

MCQ practice tool covering pharmacokinetics, adverse drug reactions, and clinical trial phases.

  • 33+ curated questions across multiple subsections.
  • Instant feedback with full explanations and formulas.
  • Practice modes: All, Random 5, or Random 10.
  • Add your own questions — bank saves in your browser.
🧠 Open radgentQ
Why radgentQ?
  • Reinforce PK formula fluency.
  • Prepare for NEET PG / AIIMS / clinical exams.
  • Understand drug regulation and ADR classification.
Workflow
Drug development: target to approval

RADGenT tools support each stage of the journey.

1

Target identification & validation

Select disease pathways and biological targets. Validate using in-vitro and in-vivo experiments.

2

Hit discovery & NCE design

Use RADock, RAlib and ML models to generate new chemical entities that interact with the target.

3

Lead optimisation & preclinical

Optimise potency and ADMET with RADPT and ML. Analyse preclinical data statistically using STMS.

4

Clinical trials & approval

Design and analyse clinical trials, compile evidence for regulators, and move NCEs toward market approval.

Tool
RADPT — Drug-likeness & ADMET helper

Enter candidate molecules (Name + SMILES) to evaluate key drug-likeness and ADMET-related properties.

🤝 Join RADGenT

Collaborate on AI-powered drug discovery.
Researchers, clinicians, chemists and developers are welcome.

📧 drugdesign@radgent.com
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