Strateos Cloud Lab

Background Strateos Cloud Lab reimagines the laboratory as a cloud‑connected smart data center: a suite of remote access smart labs, modular workcells, and lab control software that together enable scientists to run end‑to‑end experiments from design through data analysis without being physically onsite. Built for life‑science R&D, the platform supports small‑molecule screening, synthetic biology, antibody discovery, cell and gene therapy workflows and integrates automation, analytics and instrument telemetry to create clean, reproducible, machine‑readable data. Core capabilities At its core the platform combines a browser‑based orchestration console, programmatic APIs, and robotics workcells to schedule and execute protocols at scale. Users can submit and manage experiment requests, view run queues and calendars, attach sample metadata (volume, mass, storage and custom properties) and retrieve near‑real‑time instrument data. The platform supports high‑throughput formats (384‑ and 1536‑well), automated compound and plate handling, and rapid data ingestion from imaging, mass spec, plate readers and other analytical instruments. The Strateos Lab Automation Software is offered both as the control plane for Strateos’ hosted cloud labs (Menlo Park and San Diego) and as deployable private lab control software for on‑premise facilities. Automation workflows and sample processing Strateos provides prebuilt and customizable workflows for common molecular biology and drug discovery tasks. For synthetic biology and protein work, services include high‑throughput Golden Gate or NEBuilder assembly, cell‑free IVTT expression to avoid toxicity/solubility issues, and automated plate‑based purification (e.g., Thermo KingFisher Flex) for downstream characterization. For antibody discovery and characterization the platform executes assembly, expression, multi‑array MSD and ELISA‑based binding and potency assays, and phenotypic or biochemical readouts. For small‑molecule programs the platform supports HTS campaigns (the site highlights prior screens of >1M compounds), automated medicinal chemistry cycles, and miniaturization to 384/1536 formats to maximize throughput and reduce costs. Integration, programmatic access and data Strateos emphasizes machine‑actionable data and FAIR principles. The platform exposes secure APIs and supports programmatic integration into client data engineering pipelines, enabling automated ingestion, analysis and closed‑loop optimization with AI or design tools. Developers can interact with the system via libraries such as the Transcriptic (TxPy) Python client—providing CLI and Jupyter notebook interfaces, objects for Runs, Projects and Datasets, and analysis helpers to work with returned datasets. Documentation, CLI autocompletion scripts and Jupyter support make it straightforward to script experiments, retrieve result datasets and slot them into downstream ML/analytics workflows. Note: some low‑level features (e.g., direct Autoprotocol submission) may require sales contact or additional access. Use cases and organizational fit Strateos Cloud Lab suits teams that need to scale experimental throughput, increase reproducibility, or run experiments remotely: academic labs running iterative synthetic biology builds, biotech teams outsourcing HTS and medicinal chemistry cycles, and pharma labs integrating automated discovery experiments with AI‑driven candidate generation. It also supports hybrid deployments where organizations use their own instruments under Strateos lab control software or switch between private and Strateos’ hosted workcells. Typical outcomes include faster design–make–test–analyze loops, reduced hands‑on time, higher instrument utilization, and traceable experiment‑to‑sample provenance that accelerates go/no‑go decisions. Operational services and support Beyond on‑demand access to hosted automation, Strateos offers lab design and build services to deliver modular smart labs or workcells tailored to a client’s needs. Their teams assist with protocol implementation, instrument integration, run‑submission workflows, and data pipelines so organizations can deploy scalable automation either in the cloud or on their premises. For teams looking to close the loop with AI, Strateos positions the platform to generate the clean, structured datasets required for model training and iterative optimization, providing the programmatic hooks needed to integrate with third‑party ML and informatics stacks.