From the first target hypothesis to the IND nonclinical package — BioMate handles the computational work that used to take weeks and cost hundreds of thousands of dollars in CRO fees.
BioMate covers the full small-molecule drug development arc. Start with a target, work through hit discovery, ADMET, lead optimization, and preclinical development, and finish with an IND-ready nonclinical summary — all in one platform.
Rank therapeutic targets by genetic support, tissue expression, known safety liabilities, and pocket druggability. Prioritize with confidence before committing to a scaffold.
Ranked target list · Druggability report · Evidence summary
Screen large compound libraries against your target structure. Prioritize hits by binding pose, pharmacophore match, and synthetic accessibility. Filter for ADMET liability before wet-lab synthesis.
Top-scored hits · Binding pose clusters · Affinity table · 3D structure overlays
Run a full ADMET panel in minutes. QC-gated results flag hERG, DILI, Ames, and Lipinski violations with Gold/Silver/Bronze evidence grades. REINVENT4 generative design proposes optimized scaffolds that pass your gates.
ADMET report · QC grade per metric · Cited thresholds · Redesigned scaffold suggestions
Simulate PK across species with PBPK modelling. Scale animal doses to human via allometric methods. Predict toxicity. Assemble CRO submission packages with a draft Methods section ready for regulatory review.
PK profiles · Species scaling tables · CRO submission package · Draft Methods section
Model population PK, simulate dose-escalation, assess pharmacogenomics interactions, and quantify drug-drug interaction risk — producing outputs that map directly to FDA guidance for first-in-human trials.
PK/PD projections · MTD estimate · DDI risk report · Clinical pharmacology summary
Detect post-market safety signals from FAERS and published adverse event databases. Disproportionality scoring (ROR, PRR) surfaces emerging risks early with full audit trail.
Signal detection report · ROR / PRR tables · Narrative summary
BioMate generates the computational sections of your IND Module 2.6 (§2.6.1–2.6.7) as a CTD-formatted DOCX: introduction, pharmacology summary, PK written summary, toxicology summary, and tabulated data. Wet-lab sections are clearly marked as placeholders for your RA team to complete. Every narrative cites the underlying run data and QC grade.
From whole-genome variant calling to single-cell transcriptomics to multi-omics integration — BioMate runs validated, nf-core-based pipelines on GPU-backed cloud compute and returns QC-graded, publication-ready results.
Germline and somatic variant calling from WGS and WES data. GATK Best Practices and DeepVariant pipelines with ACMG/AMP variant classification and comprehensive QC.
Annotated VCF · ACMG-classified variants · CNV calls · QC report (coverage, TS/TV)
Bulk RNA-seq differential expression with DESeq2 and edgeR. Single-cell RNA-seq (10x Genomics) with clustering, marker identification, trajectory analysis, and cell-type annotation.
DEG tables · Volcano / MA plots · GSEA enrichment · UMAP with cell-type labels
Chromatin accessibility (ATAC-seq), transcription factor binding (ChIP-seq / CUT&RUN), and DNA methylation profiling. All pipelines follow ENCODE4 standards with motif enrichment analysis.
Peak calls (BED/BigWig) · Differential accessibility · Motif enrichment · DMR maps
Data-independent acquisition (DIA-NN), label-free quantification, and TMT multiplexing. Differential protein abundance with volcano plots, pathway enrichment, and post-translational modification analysis.
Protein quant tables · Differential abundance · PTM maps · Pathway enrichment
Untargeted and targeted metabolomics from LC-MS and GC-MS data. Feature detection, alignment, annotation, and pathway enrichment to link metabolic changes to biological mechanisms.
Feature tables · Metabolite IDs · Enriched pathways · Heatmaps
Shotgun metagenomics taxonomic and functional profiling alongside 16S rRNA amplicon analysis. Alpha/beta diversity, differential abundance, and metabolic pathway reconstruction.
Taxonomic composition · Alpha/beta diversity · Functional profiles · Phylogenetic trees
Integrate genomics, transcriptomics, proteomics, and metabolomics into a unified view. Identify cross-layer biomarkers, regulatory relationships, and mechanistic hypotheses across modalities.
Multi-omics factor loadings · Cross-layer network · Integrated pathway report
BioMate supports the translational and clinical phases of research: trial design, population PK, pharmacogenomics, clinical genomics, and real-world evidence analysis. Every output is audit-ready and traceable to validated methods.
Design dose-escalation studies with the BOIN (Bayesian Optimal Interval) model. Simulate population PK curves, estimate MTD/RP2D, and generate a draft protocol section with decision rules and safety stopping criteria.
BOIN decision table · dose-escalation chart · PK simulation report · protocol draft
Identify genetic variants that predict drug response or toxicity. Stratify patient cohorts by CYP genotype, HLA allele, or polygenic risk score. Integrate with variant calling outputs to move from genomic data to clinical insight.
PGx report · stratification matrix · clinical decision support annotations
Variant calling on patient-derived samples with GATK4 and DeepVariant, annotated against ClinVar, OMIM, and population frequency databases. Structured VCF output with clinical interpretation — suitable for tumour board review and precision oncology programmes.
Annotated VCF · ACMG-classified variants · tumour board summary · audit-ready report
Analyse retrospective cohort data, EHR-derived datasets, and biobank samples. Identify prognostic biomarkers, validate surrogate endpoints, and model time-to-event outcomes. Outputs include structured statistical summaries ready for regulatory submission.
Kaplan-Meier plots · hazard ratio table · forest plot · biomarker significance report
Cryo-EM single particle analysis, protein structure prediction, molecular dynamics, and docking — fully automated pipelines with GPU-accelerated cloud execution and QC at every step.
Full CryoSPARC SPA pipeline from raw micrographs to near-atomic resolution map: import, motion correction, CTF estimation, particle picking (TOPAZ/blob), 2D/3D classification, homogeneous refinement, and map validation.
Refined density map · FSC / B-factor curves · EMDB-ready package · Resolution report
Predict 3D structures for monomers and multimers with AlphaFold3 and ESMFold. Validate with MolProbity, assess binding interfaces, and cross-reference against experimental structures in the PDB.
PDB structure file · pLDDT / PAE plots · Ramachandran report · Interface contacts
Run GPU-accelerated MD simulations with GROMACS and AmberTools. Study protein conformational dynamics, ligand binding stability, and binding free energy (FEP). Parameterization with ACPYPE for small molecules.
Trajectory files · RMSD / RMSF plots · Binding free energy (ΔG) · Contact maps
Rigid and flexible docking of small molecules into target structures. Blind docking with DiffDock for cases without a defined binding site. Binding pose clustering and interaction fingerprint analysis for structure-activity guidance.
Top-ranked poses · Binding affinity scores · Interaction fingerprint · SAR guidance
Gold (FDA/ICH consensus), Silver (community standard), Bronze (benchmark literature) — every threshold is cited to a primary source, not guessed.
CTD-formatted DOCX covering all in silico sections of Modules 2.6.1–2.6.7, automatically generated from your run data. Ready for your RA team to complete with wet-lab data.
Every run records tool versions, container hashes, parameters, and QC decisions. Re-run any analysis identically — the result resolves to the same methods and sources.
Timestamped, exportable audit trail covering every parameter decision, QC outcome, and output file. Designed to support regulatory submissions and internal review.
Workflows run on AWS Batch with GPU instances where needed. No infrastructure to manage — submit a job, get results in minutes, not days.
Describe your objective in plain English. BioMate selects the right workflow, pre-fills parameters from context, and confirms before running. No code, no queue management.