Drugprogramsfailwhenriskisdiscoveredtoolate

Candidatequalityisnotdeterminedbybindingalone.Pipelinefailurecanarisefrominsufficienttargetefficacy,off-targettoxicity,immunogenicity,ADArisk,poorPK,shorthalf-life,insufficientexposure,aggregation,expressionproblems,lowstability,CMCrisk,andmanufacturabilityconstraints.SaintNovelisbuilttosuppresstheserisksearlierindiscovery.

Select a risk factor to explore

Visual comparison showing natural B-cell evolution as an integrated multi-stage selection funnel and current AI antibody design as isolated subtasks.

IMMUNE-EVOLVED INTELLIGENCE

Decoding Drug Discovery with Nature's Integrated Selection Logic.

Saint Novel takes inspiration from natural B-cell evolution to prioritize candidates across immune plausibility, structure, developability, cross-reactivity, and downstream progression risk.

OnePlatform.MultipleIntelligenceLayers

SaintNovelintegratesimmune-evolvedsequenceintelligence,high-throughputstructuralmodelling,multiparameterdevelopabilityscreening,diseaseandtargetcontext,conjugateintelligence,andexperimentalfeedbackintoasingleplatform

Iterate.Learn.Improve.

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Turn your phone landscape to view the full platform workflow.

Startwithabottleneck

Generate antibody or nanobody hits
Select stronger leads from existing hits
Improve an existing antibody or VHH
Identify targetable epitopes and avoid off-targets
Design bispecific or multispecific constructs
Design conjugates or linker-payload systems
Design macrocyclic peptide panels
Design stapled PPI candidates
Rank or validate therapeutic targets
Generate make-ready chemistry decisions
Package scientific evidence for review
Run secure local workflows

Beittarget,epitope,hitpanel,leadseries,developabilityrescue,conjugatedesign,peptidetopology,chemistrymodifications,documentation,orenterprisedeployment.Endwithapracticalsolution.

Validatedindustrialproofpoints

SaintNovel’splatformhasbeenvalidatedacrossdevelopabilityscreening,structuralthroughput,cross-reactivityde-risking,andcandidateoptimizationworkflows.

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antibody nativeness score for NovelDesign outputs

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experimental validation accuracy for AI-derived developability metrics

0x0x

throughput acceleration with NovelFold

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off-target candidates ruled out in 10 days in an early-discovery workflow

USD 00M

R&D cost saved per target by avoiding high-risk candidates

Exploremodality-specificplatformcapabilities

Exploredevelopment-awaredesign,screening,andoptimizationworkflowstailoredtoantibody,nanobody,andpeptidetherapeutics.

Scientific visualization representing canonical monoclonal antibody engineering

Canonical mAbs

Scientific visualization representing nanobody and single-domain antibody design

Nanobodies / sdAbs

Scientific visualization representing bispecific and multispecific antibody formats

Bispecifics & Multispecifics

Scientific visualization representing antibody-drug conjugates and linker-payload systems

ADCs & Conjugates

Scientific visualization representing antibody-fusion protein engineering

Antibody-Fusion Proteins

Scientific visualization representing antibody developability screening metrics

Antibody Developability Metrics

Scientific visualization representing cyclic and macrocyclic peptide design

Cyclic & Macrocyclic Peptides

Scientific visualization representing stapled and constrained peptide therapeutics

Stapled / Constrained Peptides

Scientific visualization representing cell-penetrating peptide delivery

Cell-Penetrating Peptides

Scientific visualization representing peptide lead optimization workflows

Peptide Lead Optimisation

Scientific visualization representing peptide-drug conjugate and PRRT linker workflows

PDC / PRRT & Conjugate Linker Workflows

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Securedeploymentforconfidentialworkflows

SaintNovelsupportsfullyofflinedeployment,AES-256encryptedstorage,userpermissionisolation,browser-basedmulti-useraccess,high-performancelocalinference,andintegratedreportingwithPDB,PDF,CSV,FASTA,andotherworkflowoutputs.

Fully offlinedeployment
AES-256encryption
Permissionisolation
Multi-useraccess
Localinference
Integratedreporting