Biotech software development company

Building configurable LIMS that automate sample intake, chain‑of‑custody, plate maps, inventory, and QC. AI assists with anomaly detection (e.g., out‑of‑range results), instrument health, and workload forecasting; barcode/RFID and role‑based permissions ensure end‑to‑end traceability.

Implementing pipelines for assay setup, curve fitting, normalization, and result review with guardrails and review/approve workflows. ML models flag outliers, predict assay drift, and recommend repeats, compressing turnaround time while lifting confidence in reported values.

Developing CTMS with site/startup tracking, visit schedules, issue management, and KPIs. Predictive analytics support enrollment planning and risk‑based monitoring; integrations with EDC, eTMF, and safety systems remove manual reconciliation and improve inspection readiness.

Delivering ELNs with structured templates, embedded data capture, reagent lookup, and compliant e‑signatures. NLP auto‑tags entries, suggests related experiments, and surfaces prior art so teams reuse knowledge instead of reinventing it.

Building scalable pipelines for sequencing, alignment, variant calling, expression profiling, and proteomic quantification. AI/ML highlights significant variants, pathways, and biomarker candidates; cohort analytics and permissions keep PHI secure while enabling collaboration.

Building virtual screening, molecular modeling, de novo design, and QSAR/ADMET prediction workflows on HPC/GPU backends. Generative models propose candidates within synthetic constraints; docking/scoring and MD simulations help prioritize hits and reduce wet‑lab iteration.

Creating analysis suites for targeted panels and WES/WGS with automated QC, variant interpretation, and report generation. Knowledge‑base linking (ClinVar, gnomAD, COSMIC) and AI‑assisted classification speed up variant review and reduce VUS churn.

Engineering clinician‑ and patient‑facing apps for test ordering, device connectivity, and longitudinal monitoring. Models support earlier detection and triage, while audit trails and consent management satisfy regulatory expectations.

Delivering pipelines for microscopy/HCS, MRI/CT, and histopathology with robust segmentation, registration, and quantification. AI models accelerate cell counting, phenotype clustering, and anomaly detection; viewers are optimized for large tiled images and collaborative review.

Implementing end‑to‑end specimen tracking across collection, storage conditions, thaw/refreeze cycles, and disposal. Forecasting models predict depletion and storage demand; alerts assist with stability windows and environmental deviations to protect sample integrity.