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April 13, 2026
Async optimization, study validation reports, cell data filtering

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Asynchronous optimization evaluation

Optimizers now support asynchronous evaluation for both local and distributed workloads. A new ProcessPoolAsyncEvaluator runs evaluations in persistent multiprocessing workers locally, while the existing ActorPoolEvaluator gains a submit/wait-next API for distributed evaluation via Ray. Steady-state async mode keeps all workers saturated without waiting for generation boundaries, and new convergence criteria — including a patience counter and population diversity guards — prevent premature stopping.

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Study validation reports

Studies now include a validation workflow for comparing simulation results against experimental measurements. A new Report tab displays overlay plots of simulated vs. measured data along with quantitative error metrics (RMSE, MAE), and a Data tab lets you manage which measurements are paired with which simulations.Find out more →

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Cell data filtering and ordering

All cell list endpoints (specifications, instances, and measurements) now accept filter and ordering parameters — including name, creator email, date ranges, and sort direction. The Python SDK exposes matching keyword arguments on each list() method, and the frontend measurement table uses server-side filtering.
Improvements
  • Pipeline and cell measurement tables now support server-side sorting.
  • Added an error screen with auto-retry when the initial user info request fails.
  • Removed SNES optimizer option from the frontend.
Fixes
  • Removed XSS sinks in the notifications drawer and job progress display that rendered untrusted strings via dangerouslySetInnerHTML.
  • Normalized Redux thunk error handling to use extractApiError consistently.
  • Eliminated slow bucket.list() calls from file-measurement endpoints by caching filenames in the database, reducing response times from ~10 s to under 100 ms.
Improvements
  • Renamed the Pints optimizer to AskTellOptimizer across all code, tests, and documentation.
  • Added dedicated algorithm test suites for CMA-ES, XNES, and Nelder-Mead.
  • Added distribution mean evaluation for CMA-ES and XNES, preferring the evaluated mean when it outperforms the best sample.
Fixes
  • Fixed a flaky deterministic design optimization test.
Improvements
  • Added filter and ordering keyword arguments to CellSpecificationClient.list(), CellInstanceClient.list(), and CellMeasurementClient.list().
  • download_files(filenames=) now skips the listing round-trip; new get_file() method for single-file fetch.
Improvements
  • Added temperature column recognition for Biologic files.