Loading BioAtlas...
Loading BioAtlas...
将生物大模型、对接计算引擎与组学管线并排横向对比。按获取方式、硬件开销及细分领域灵活筛选，在一分钟内得出客观可辩护的技术选型方案。
| 技术参数指标 | ＋ 添加工具 | |||
|---|---|---|---|---|
| Category | Drug Discovery & Chemistry | AI Drug Discovery | AI Drug Discovery | — |
| Subcategory | End-to-End AI Drug Discovery Platform | Research AI Methods | Molecular Property Prediction | — |
| Company | Insilico Medicine | Research / method authors | Luo Lab | — |
| Access mode | Commercial Subscription & Co-Development | Confirm distribution and exact release | Research code or publication | — |
| Licence conditions | Proprietary commercial software | NOT_INDEPENDENTLY_AUDITED | Check code and model weights separately | — |
| Compute requirements | Cloud SaaS with enterprise security compliance | Version and data dependent | Check selected checkpoint and runtime; no GPU catalog recommendation | — |
| Biological application | Fibrosis, oncology, immunology, and age-related disease drug discovery | 未明确记录 | 未明确记录 | — |
| Research workflow | Disease multi-omics data -> novel target selection -> generative chemistry -> candidate synthesis | 未明确记录 | 未明确记录 | — |
| Evidence level | Clinical-stage pipeline with published experimental and clinical validation (Nature Biotech 2024) | PEER_REVIEWED_METHOD_OR_CONFERENCE | Peer-reviewed primary method | — |
| Commercial eligibility | Commercial enterprise licensing and drug discovery partnerships | NOT_INDEPENDENTLY_AUDITED | Unknown, requires audit | — |
| Price | Enterprise partnership — contact vendor | Verify access and licence | Check selected model licence | — |
| Availability ⓘ | Globally available for biopharma partners | Method paper or official documentation | Public research method/code | — |
| Features | PandaOmics for multi-omics target identification and biological aging biomarker analysis, Chemistry42 generative chemistry platform with 42 distinct generative algorithms, Demonstrated progression of novel targets and molecules into Phase II clinical trials (e.g. ISM001-055 for IPF), High-throughput synthetic accessibility and automated ADMET filtering | ADMET-AI scientific method, Molecular SMILES with well-defined compound stereochemistry and relevant assay domain, Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Chemical foundation model for learned molecular representations, property prediction and conditional molecule generation., Molecular features, predicted properties or generated SMILES | — |
| Entry type | Commercial Platform | Source-scoped research method | Research AI model / method | — |
| AI role | End-to-End Generative Chemistry | ENSEMBLE_ML | Published biomedical AI method | — |
| Input data | 未明确记录 | Molecular SMILES with well-defined compound stereochemistry and relevant assay domain | Valid SMILES; trained downstream endpoint or conditioned molecule task | — |
| Output data | 未明确记录 | Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Molecular features; predicted properties or generated SMILES | — |
| Validation | 未明确记录 | Published method scope; no independent BioAtlas execution or benchmark | Requires independent dataset-specific evaluation | — |
| Type | End-to-end generative AI drug platform | 未明确记录 | 未明确记录 | — |
| Intended use | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Compatibility | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Manufacturer | Insilico Medicine | 未明确记录 | 未明确记录 | — |
| Integration evidence | https://insilico.com/platform | 未明确记录 | 未明确记录 | — |
| Laboratory handoff | Compounds synthesized in automated robotic labs for biochemical IC50 testing | 未明确记录 | 未明确记录 | — |