Release notes
Platform updates, feature documentation and verification records.
2026-09-10 · Admin preview
VHH sequence evidence, strengthenedNew patent insights, corrected VHH checks and clearer annotation confidence · Design tools remain in admin preview
Semi-de-novo Triage — display-first discovery funnel
A new discovery mode for wet-lab phage-display NGS pools. Instead of generating diversity, the platform triages an enriched pool (~10⁶ VHH sequences) down to a ranked shortlist: cheap streaming sequence filters (10⁶ → budget) → structure + affinity scoring on the survivors → an epitope×specificity matrix against an antigen panel (domain constructs, orthologs, and paralog counter-screens) → a composite rank validated on known-positive clones → an optional high-precision docking pass on the shortlist only. New /semi-de-novo page, /docs/semi-de-novo-workflow, CLI (python -m pipeline.semi_de_novo), and API (/api/v1/semi-de-novo). Diversity comes from the lab; the AI ranks and resolves epitope / specificity — it does not invent sequences.
Features
Single-file .amino pool ingest
Streams a real phage-display NGS export (Count/Ratio/Length/AA_Seq, no manifest) into the database, deduping by sequence and keeping abundance. Chain-format-agnostic (VHH now; scFv / paired VH+VL reserved). Antigen-panel and known-positive (binding-Excel) loaders land the specificity design alongside.
10⁶-scale cheap sequence funnel
Stage 1 streams the whole pool with O(N) gates (length, structural Cys) + CDR3-bucket clustering, doing ~99% of the reduction before anything structural runs. Abundance is a weak tiebreak, never a gate — rare unique-CDR3 clones survive.
Epitope × specificity matrix
Scores each candidate against every antigen-panel construct, assigns an epitope bin, and enforces specificity via the counter-screen (e.g. DLL1 / DLL4). Reproduces the shape of the wet-lab binding table. Specificity the cheap scorers can't resolve is flagged, not silently passed.
Anchor-validated ranking
Composite rank (affinity / interface / on-target epitope / specificity / developability / weak abundance) with a tunable-threshold shortlist. Known positives validate the ranking (recall into top decile + specificity reproduction) — never train it, since there are no negatives yet.
Two-tier docking depth
Bulk triage uses cheap scoring; true docking poses run only on the final shortlist, gated behind an explicit toggle and hard-capped. Never fabricates a pose when no backend is configured.
Changelog (4 changes)
- New backend package pipeline/semi_de_novo (runner + 5 stages + config + chain-format + validation).
- Schema: antibodies.chain_format + antigen_panel / anchor_clones / semi_denovo_runs / panel_matrix_scores tables.
- API router /api/v1/semi-de-novo (run + jobs + artifact downloads) and /semi-de-novo web page.
- Ranking is a sequence PROXY until a real affinity backend + Stage-5 poses are wired — surfaced in the UI and CLI, not hidden.
Praxis branding, sidebar Workflow restructure, bilingual tooltips, Whitepaper
Second half of the 2026-05-21 sprint. The platform now ships as Praxis (parent IASO Bio). The sidebar is reorganized around the canonical 6-step de novo binder design workflow (Workflow / Specialized / Utilities), with Agent / Guides / Settings as the three single-entry destinations at the bottom. New Guides hub at /guides; long-form platform whitepaper at /guides/whitepaper (bilingual EN/中文, sticky TOC). Bilingual hover hints across the sidebar; in-page InfoTip and TutorialLink components; the score tooltips are rewritten to be bilingual + include execution-logic calc + link directly to Scoring Audit. Provider names are removed from every user-facing surface.
Features
Praxis platform branding
Platform is Praxis (Greek for 'putting knowledge into action'), owned by IASO Bio. Whitepaper, sidebar, tooltips, and tutorials reflect the new name; internal codename remains GenPrime in repo metadata.
Sidebar reorganized around the canonical 6-step workflow
Three sections: Workflow (Import → Epitope Picker → Pipeline → Run History → Interface → Mutation Resistance → Candidates → Compare → CAR Design), Specialized (VHH Design, Two-VHH CAR, Mini-Binder, Programmable Design), Utilities (Structure Viewer, Scoring Dashboard, Models). Agent / Guides / Settings collapsed into three single-entry destinations below the main groups.
Praxis platform whitepaper
Long-form (~6500 EN words + ZH translation) master documentation at /guides/whitepaper covering therapeutic mission, industry context, design philosophy, platform capabilities by 6-step workflow, differentiation, future roadmap, and an honest open-questions list. Sticky TOC, EN/中文 toggle, single-source markdown editable via PR.
Guides hub at /guides
Single-entry sidebar destination consolidating every reading surface: Whitepaper, Tutorials, Scoring Audit, Readout Guide, Knowledge Map, Use Cases, References. Replaces the previous expandable Learning group.
Bilingual hover hints across the sidebar
Every sidebar nav item and section label has a tooltip showing EN above and ZH below with a hairline separator. ~33-term in-product glossary via the new <InfoTip term="…" /> component; <TutorialLink slug="…" /> for module-page top-right tutorial CTAs.
Bilingual score tooltips with execution logic
Every score (44 entries — ipTM, pTM, pLDDT, PAE, iPAE, BSA, AbLang, TAP, ThermoMPNN, AggreScan, CDR geometry, HCDR3, glyco, MW/pI/FcRn, cross-species, selectivity, tonic risk, CAR composite, Pareto rank, composite score, etc.) now exposes bilingual range / meaning / calc / caveat, plus links to its Readout Guide entry and the Scoring Audit page.
Vendor-name scrub
Removed provider references from every user-facing surface (Overview Models card, /pipeline backend selector, /interface job-status copy, /mini-binder banner, /settings labels, /releases entries, and docs walkthroughs). Replaced them with capability labels (API / GPU / Local); backend config identifiers remain internal.
Mutation Resistance + Readout Guide + Wet-Lab Loop + Wave-1 Report
/mutation-resistance (escape-mutation panel re-scoring), /docs/readout-guide (per-score operating manual), /docs/wet-lab-loop (Waves 2–4 architecture), /docs/wave-1-report (Boltz-2 swap sanity check on 30 BCMA candidates) — all added in the same sprint.
Changelog (8 changes)
- Added /guides, /guides/whitepaper, /mutation-resistance, /docs/readout-guide, /docs/wet-lab-loop, /docs/wave-1-report.
- Added web/src/lib/glossary.ts (~33 platform + biology terms; bilingual).
- Added web/src/components/info-tip.tsx, tutorial-link.tsx; rewrote score-tooltip.tsx for bilingual + calc + audit link.
- Rewrote web/src/lib/score-tooltips.ts — every one of 44 entries bilingual + has `calc` field.
- Reorganized web/src/components/sidebar.tsx into Workflow / Specialized / Utilities + Destinations.
- Scrubbed provider branding from walkthroughs and from Overview / Pipeline / Interface / Mini-Binder / Settings / Releases copy.
- Deleted docs/yongke-product-doc-draft.md (person-named filename + extensive person-name body references + a leaked basic-auth credential).
- Memory rules added: no-person-names-in-platform, no-vendor-names-in-ui, praxis-branding, terse-no-justification.
Tutorials deep pages + platform voice cleanup
Per-feature deep walkthroughs for all 17 sidebar features (TL;DR, inputs, outputs, step-by-step, backend, worked example, pitfalls, see-also — bilingual EN/中文). Platform-wide narrative cleanup to a standard SaaS voice. Sidebar decluttered — Architecture, Release Notes, and Research moved into Settings.
Features
Deep tutorial sub-pages
/docs/tutorials/[slug] dynamic route renders an 8-section walkthrough per feature with prev/next nav. All 17 slugs covered: pipeline, epitope-picker, programmable-design, mini-binder, vhh-design, two-vhh, candidates, scoring, compare, viewer, interface, import, car-design, rare-diseases, runs, models, agent.
Single source for tutorials
Index card + deep page both render from web/src/app/docs/tutorials/_data.ts — adding or revising a tutorial is one edit.
Standard SaaS narrative voice
Stripped all internal-team attributions from user-facing UI/docs/code. References to specific individuals replaced with platform-logic framing. Team subsection removed from architecture walkthrough.
Sidebar declutter
Roadmap entry removed from Learning. Architecture, Release Notes, and Research moved into Settings as sub-pages — reduces top-level nav weight.
Changelog (6 changes)
- Added web/src/app/docs/tutorials/[slug]/page.tsx (dynamic deep route).
- Added web/src/app/docs/tutorials/_data.ts (single content source, 17 features × 8 sections × bilingual).
- Updated web/src/app/docs/tutorials/page.tsx — cards now link to deep pages.
- Renamed public/references/yongke-blackboard-2026-05-17.jpg → blackboard-format-universe-2026-05-17.jpg.
- Redacted a demo credential previously visible in docs/v2 walkthrough.
- Removed Roadmap, Architecture, Release Notes, Research from sidebar; Architecture / Release Notes / Research now reachable from Settings tabs.
2026-05 sprint — scoring depth, epitope picker, agent DAG planning
Six-week consolidated release covering the May 2026 sprint: epitope picker UI with curated presets, six new scoring dimensions (BSA, CDR geometry, AggreScan3D, tonic-clustering proxy), cross-reactivity counter-screen stage, partial-diffusion HCDR3 redesign mode, agent DAG-planning, and the v4 English-first architecture walkthrough.
Features
Epitope Picker (v0)
Interactive 3D Mol* viewer with curated presets for BCMA / CD20 / HER2 / GPRC5D. Produces canonical chain:residue token strings for every downstream design surface.
Partial-diffusion HCDR3 redesign
Backbone mode that redesigns only HCDR3 against a parent VHH framework. The supported path for warm-start affinity-maturation workflows.
Cross-reactivity counter-screen stage
Pipeline stage that scores designed binders against a configurable panel of off-target antigens; flags candidates with elevated cross-reactivity risk.
Scoring depth — BSA, CDR geometry, AggreScan3D, tonic-clustering
Buried surface area on every complex; ANARCI/IMGT CDR-length validation; AggreScan3D aggregation propensity; tonic-clustering risk proxy (composite of surface hydrophobicity + net charge + Fv-Fv docking). All visible in /candidates and the Scoring Audit doc.
Agent — DAG-planning + 11-tool surface
Agent (Claude Opus 4.6 via Anthropic API) plans workflows as DAGs and renders them inline; 11 platform tools (run_design, query_candidates, score_candidate, chroma_generate, export_candidates, propose_dag, …) invocable from natural-language prompts.
Architecture walkthrough (v4) + bilingual toggle
English-first comprehensive walkthrough covering current state, 6-stage pipeline, MCP architecture, frontend inventory, and ~4-week roadmap. CN version maintained as translation.
Changelog (7 changes)
- Added pipeline/tools/cdr_geometry.py + ANARCI/IMGT CDR length validator wired into scoring stage.
- Added pipeline/tools/scoring_extras.py — BSA / AggreScan3D / tonic risk.
- Added pipeline stages: cross-reactivity counter-screen, partial-diffusion HCDR3 redesign.
- Added /epitope-picker page + curated EPITOPE_LIBRARY presets.
- Added pipeline/api/agent_routes.py with 11 tool surface; SSE streaming.
- Added /docs walkthrough v4 + v4-zh, plus /docs/knowledge-map, /docs/recipes, /docs/scoring-audit, /docs/references.
- Refreshed agent system prompt to surface new capabilities.
Two-VHH CAR Architect — Dual-VHH CAR Construct Design & Assembly
Complete Two-VHH CAR Architect module supporting three CAR architectures (in vivo LNP delivery, bispecific tandem, hybrid). Includes Expert Review system for capturing scientific decisions, construct component library (20 domains), target preset libraries (14 targets), construct assembly engine, sequence/mRNA/LNP/functional validation, and comparison-ready output.
Features
Three CAR Architectures
In vivo LNP delivery (VHH-targeted LNP + single-VHH CAR), bispecific tandem (dual-VHH in one construct with linker), and hybrid (LNP targeting + bispecific CAR). Each architecture has distinct molecular topology and validation requirements.
Expert Review System
9 structured scientific questions covering LNP display methods, component options, target libraries, and design strategy. Answers dynamically configure the pipeline.
Construct Component Library
20 curated CAR domain components: signal peptides (3), hinges (4), transmembrane (2), costimulatory (4), signaling (2), linkers (5). All with real amino acid sequences from UniProt.
Construct Assembly & Validation
Combinatorial assembly engine producing all construct variants (orientations × VHH combinations). Four-level validation: sequence (MW, pI, glyco), mRNA optimization (CAI, GC%), LNP compatibility scoring, and functional heuristics (signaling, persistence, AICD risk, fratricide).
Target Preset Libraries
6 T-cell markers (CD3ε, CD4, CD5, CD7, CD8α, NKG2D) and 8 disease targets (CD19, CD20, CD22, BCMA, GPC3, HER2, EGFR, Mesothelin) with PDB references, epitope suggestions, and clinical notes.
Structure Validation (Level 2)
Full construct structure prediction via AlphaFold-Multimer for top-K constructs. VHH domain independence, CDR accessibility, and inter-domain interaction analysis.
Changelog (6 changes)
- Added pipeline/car/ module — expert_review.py, components.py, targets.py, assembly.py, api.py, validation.py, mrna.py, lnp.py, functional.py
- Added pipeline/api/routers/car.py — FastAPI endpoints for CAR design
- Added pipeline/api/routers/expert_review.py — Expert Review CRUD endpoints
- Updated /two-vhh page — complete CAR Architect UI replacing placeholder
- Sidebar: Two-VHH CAR no longer marked as Coming Soon
- Added .spec-initialization/changes/build-two-vhh-car-architect/ — full specification
VHH-Design Engine — Professional VHH Nanobody Design Module
Complete VHH nanobody design engine with four design modes (de novo, germline-guided, template-based, humanization), VHH Hallmark Validation Gate with configurable stringency, germline database integration, and VHH-specific scoring presets. Built as the foundation for the Two-VHH CAR Architect module.
Features
Four VHH Design Modes
De novo design from target structure, germline-guided with camelid IGHV3 frameworks, template-based CDR optimization, and humanization with FR2 hallmark preservation. Each mode has distinct scientific logic and tool recommendations.
VHH Hallmark Validation Gate
Four-pillar VHH identity verification: FR2 hallmark residues (IMGT 42/49/50/52), CDR3 integrity, canonical disulfide (C23-C104), and ANARCI annotation. Three stringency levels: strict, relaxed, off.
Germline Database Integration
5 camelid IGHV3 + 5 human IGHV3 germline references with germline assignment, framework extraction, and closest human germline finder for humanization.
VHH-Specific Scoring Presets
Four weight presets (VHH Default, Humanization, CAR Compatible, Custom) with stability and aggregation upweighted for single-domain biology. Mode-specific auto-selection.
Internal API for Two-VHH CAR
VHHDesignRequest/Response schemas and VHHDesignEngine orchestrator with well-defined interface for the Two-VHH CAR Architect module to call programmatically.
Changelog (6 changes)
- Added pipeline/vhh/ module — hallmark.py, germline.py, scoring_presets.py, api.py
- Added pipeline/api/routers/vhh.py — FastAPI endpoints for VHH design
- Extended antibody_db schema with VHH-specific fields and vhh_presets table
- Added .spec-initialization/changes/build-vhh-design-engine/ — full specification
- Updated /vhh-design page — complete design UI replacing placeholder
- Sidebar: VHH-Design no longer marked as Coming Soon
Agent Mode — Claude Opus 4.6 Research Assistant
Added an AI-powered conversational Agent to the platform, powered by Claude Opus 4.6 with streaming SSE and tool use. The Agent handles both scientific workflows (design, score, query, Chroma generation) and platform guidance (page usage, metric explanations, workflow recommendations). Persistent conversation threads, multi-step planning, and 18 suggested starter questions across Science, Platform, and Strategy categories.
Features
Streaming Chat with Claude Opus 4.6
Real-time token-by-token streaming via Server-Sent Events. Markdown rendering with tables, code blocks, and formatted lists. Persistent conversation threads stored in SQLite.
11 Platform Tools
Agent can: run_design (launch workflows), query_candidates (filter/sort), chroma_generate (call Chroma directly), query_database (flexible SQL), score_candidate, export_candidates, explain_platform (platform docs), create_plan/update_plan_step (multi-step planning).
Platform Guidance
Agent serves as interactive documentation — answers questions about pages (Pipeline, Programmable Design, Candidates, Scoring), metrics (ipTM, pLDDT, Pareto ranking), tool selection, and workflows. Knowledge priority: local data > platform features > domain knowledge.
Multi-Step Planning
For complex research tasks (3+ steps), the Agent creates structured plans with goal and steps, executes each step with tool calls, and summarizes findings. Plans are persisted in the database.
Chat UI with Thread Management
Thread sidebar (create/delete/rename), auto-scrolling messages, file attachment support (.pdb, .fasta, .csv), tool call badges, loading animation. 18 suggested questions for new users.
Changelog (7 changes)
- Added pipeline/api/agent_routes.py — streaming SSE, 11 tools, system prompt, thread CRUD
- Added web/src/app/agent/page.tsx — chat UI with markdown rendering and tool badges
- Added agent_threads + agent_plans tables to antibody_db schema
- Added ANTHROPIC_API_KEY to known secrets
- Registered agent router in main.py
- Updated sidebar — Agent as first item in Design section
- Created .spec-initialization/changes/add-agent-mode/ — proposal, design, tasks
Chroma Integration — Programmable Generative Protein Design
Integrated GenerateBio's Chroma (Nature 2023) as a new design tool. Chroma enables constraint-guided protein generation via a pluggable conditioner system — substructure constraints, symmetry, shape, natural language descriptions, and more. This is the first tool on the platform that supports programmable structural constraints during generation.
Features
Chroma Modal GPU Deployment
Chroma deployed on Modal A100-40GB with 4 pretrained models (GraphBackbone, GraphDesign, GraphClassifier, ProteinCaption). Persistent volume for weight caching. Cold start ~22s, generation ~25-27s for 100-residue proteins.
Chroma MCP Server (6 tools)
MCP server exposing: chroma_sample, chroma_sample_conditioned, chroma_design, chroma_pack, chroma_score, chroma_redesign. Supports all 6 conditioner types + composed conditioners.
Programmable Design Page
Dedicated workflow page (/programmable-design) for Chroma's conditioner system. Radio card UI for constraint type selection, dynamic parameter forms, generation progress tracking. Designed for Dr. Zhang's demo.
Pipeline Integration
Chroma added to Pipeline page tool dropdown. When selected, shows conditioner-specific configuration UI. Chroma added to scout_tools in pipeline_config.yaml.
Candidate Detail — Chroma Metrics
Candidate detail page now shows source tool badge, conditioner type badge, and constraint satisfaction metrics (constraint_rmsd, symmetry_quality) for Chroma-generated candidates.
Release Notes Page
This page — platform documentation with feature descriptions, smoke test reports, and verification records for each release.
Smoke test report
Verify GPU availability, model loading, endpoint responsiveness
NVIDIA A100-SXM4-40GB detected. Backbone + Design models loaded. Endpoint returns JSON.
Generate a 100-residue monomer from scratch (200 diffusion steps)
100aa sequence returned. 796-line PDB with valid ATOM records. Backbone + sequence generated in single call.
Generate a C3-symmetric trimer (3x80 residues) with SymmetryConditioner
240 total residues (3 chains x 80aa). Conditioner correctly enforced C3 rotational symmetry. 2002-line PDB.
Design sequence for an 80-residue backbone using Potts model (design_t=0.5)
80aa sequence designed via Potts MCMC. design_t=0.5 for robustness. Backbone generated fresh, then design endpoint called independently.
Changelog (11 changes)
- Added modal-gpu-backend/chroma_serve.py — Modal serverless function with ChromaService class
- Added mcp-servers/chroma-mcp/server.py — 6 MCP tools for Chroma
- Added scripts/setup_chroma_weights.sh — one-time weight download script
- Added web/src/app/programmable-design/page.tsx — dedicated Programmable Design page
- Added web/src/app/releases/page.tsx — Release Notes page
- Updated web/src/app/pipeline/page.tsx — Chroma + conditioner UI in tool selection
- Updated web/src/app/candidates/[id]/page.tsx — Chroma tool/conditioner badges
- Updated web/src/lib/api.ts — source_tool, generation_params, constraint_rmsd fields
- Updated web/src/components/sidebar.tsx — Programmable Design + Release Notes navigation
- Updated pipeline/pipeline_config.yaml — Chroma as Stage 2 option with conditioner params
- Created .spec-initialization/changes/integrate-chroma-generative-design/ — proposal, design, tasks
Agentic MCP Architecture + mBER VHH Design
Major architecture shift from rigid DAG pipeline to Claude Code + MCP agent orchestration. Deployed mBER as the first self-hosted design tool on hosted GPU. Hosted inference API integrated for scoring and validation.
Features
MCP Architecture
Adopted ProteinMCP-style orchestration. Each design tool is an MCP server. Agent picks tools dynamically based on task context.
mBER VHH Design
mBER deployed on Modal A100-80GB. AF-Multimer hallucination + ESM2/AbLang2 sequence priors. 45% target-level success rate. VHH-only.
Hosted Inference API
10+ tools via REST: TAP, ImmuneBuilder, AlphaFold-Multimer, ThermoMPNN, BioPhi, Scoring system, Antibody Evolution.
Changelog (4 changes)
- Scaffolded 12 MCP servers for design tools
- Built FastAPI backend + Next.js frontend
- Implemented SQLite database with 6-table schema
- Created workflow skills: ab-pipeline, vhh-car-design, mini-binder-car-design
Platform Foundation
Initial scaffolding: DAG orchestrator, 6 skeleton pipeline stages, FastAPI backend, Next.js 15 frontend, SQLite database, Modal GPU stubs.
Features
Pipeline Harness
6-stage DAG orchestrator: Epitope → Backbone → Sequence → Validation → Scoring → Optimization.
Web Platform
Next.js 15 + React 19 frontend with Pipeline builder, Candidates explorer, Scoring dashboard, Mol* 3D viewer.
Changelog (4 changes)
- Initial project scaffold
- 6 pipeline stages (skeleton)
- FastAPI backend with auth
- SQLite schema: targets, antibodies, complexes, scores, sources, inference_jobs