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Comparison · Analytics

cloudml vs DoseFinding

A side-by-side editorial comparison of cloudml and DoseFinding — release velocity, themes, recent moves, and the top alternatives to consider.

cloudml vs DoseFinding: at a glance

FeaturecloudmlDoseFinding
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmachine-learning, google-cloud, tensorflow, model-trainingdose-response, mcp-mod, clinical-trials, model-averaging
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is cloudml?

Six years since the last functional change, and Google renamed the service it wraps in the release before that

cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.

Read the full cloudml trajectory →

What is DoseFinding?

New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing

DoseFinding implements MCP-Mod and related dose-response methodology for clinical trial design and analysis. In 2024 it changed hands — Marius Thomas took over as maintainer, Novartis was recorded as copyright holder and funder, and the package moved to the openpharma GitHub organisation with roxygen documentation and a proper NEWS file. The two releases since have added substantive methodology: model averaging for dose-response fitting in 1.3-1, and conditional and predictive power for interim analyses in 1.4-1.

Read the full DoseFinding trajectory →

cloudml vs DoseFinding: editorial side-by-side

C
cloudml
ANALYTICS
0.0

Six years since the last functional change, and Google renamed the service it wraps in the release before that

◆ Current state

cloudml lets R users train keras, tfestimators and tensorflow models on Google's managed machine learning service, tune hyperparameters there, and deploy the results. Its last release with functional content was 0.6.1 in September 2019, which adapted to Google renaming the service from ml-engine to ai-platform. The only entry since is a 2025 documentation update made to satisfy CRAN.

◆ Where it's heading

The visible arc is short and stops abruptly. Releases through 2018 tracked the TensorFlow runtime version and patched packaging problems; 0.6.1 added a customCommands hook so users could run OS-level setup before package installation, and adjusted to the service's new name. Then nothing for six years. A 2025 release containing only documentation changes is the standard signal of a package being kept on CRAN rather than being developed.

◆ Prediction

There is nothing in this feed to support a prediction of functional work. The most likely next event is another CRAN-driven documentation patch, or archival.

D
DoseFinding
ANALYTICS
0.0

New stewardship at openpharma, then two releases adding the methods MCP-Mod was missing

◆ Current state

DoseFinding implements MCP-Mod and related dose-response methodology for clinical trial design and analysis. In 2024 it changed hands — Marius Thomas took over as maintainer, Novartis was recorded as copyright holder and funder, and the package moved to the openpharma GitHub organisation with roxygen documentation and a proper NEWS file. The two releases since have added substantive methodology: model averaging for dose-response fitting in 1.3-1, and conditional and predictive power for interim analyses in 1.4-1.

◆ Where it's heading

The pattern before the handover was maintenance — R-devel compliance, a bug fix, a link. After it, each release carries a named methodological addition with an acknowledged contributor, plus documentation to match: a longitudinal analysis vignette shipped alongside the interim power work. Housekeeping continues underneath, mostly clearing deprecated ggplot2 interfaces, aes_string in one release and qplot in the next.

◆ Prediction

Given the last two releases each added one method with a supporting vignette, expect the next to follow the same shape. Both additions so far extend the package beyond fixed dose-response fitting, so adaptive and interim methodology is the more likely direction.

Alternatives to cloudml and DoseFinding

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either cloudml or DoseFinding.

See all cloudml alternatives → · See all DoseFinding alternatives →

Recent activity from cloudml and DoseFinding

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 0y agocloudmlDocumentation updated for CRAN
  2. 1y agoDoseFindingConditional and predictive power for interim analyses
  3. 1y agoDoseFindingModel averaging arrives for dose-response fitting
  4. 1y agoDoseFindingPackage moves to openpharma under new maintainership
  5. 2y agoDoseFindingCompliance update for R-devel
  6. 3y agoDoseFindingpowMCTBinCount bug fix
  7. 6y agocloudmlai-platform command adopted; custom pre-install commands added
  8. 7y agocloudmlDefault runtime moves to TensorFlow 1.9
  9. 8y agocloudmlPatch for CRAN results and a packrat error
  10. 8y agocloudmlCloud training, GPU jobs, tuning and deployment from R

Frequently asked questions

What is the difference between cloudml and DoseFinding?

They serve adjacent needs but don't currently overlap on shipped themes. cloudml and DoseFinding are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is cloudml better than DoseFinding?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cloudml and DoseFinding are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to cloudml?

Top cloudml alternatives in Analytics are ranked by recent ship velocity. Browse the "cloudml alternatives" section above for the current picks, or visit /alternatives/cloudml for the full list with editorial commentary on each.

What are the best alternatives to DoseFinding?

Top DoseFinding alternatives in Analytics are ranked by recent ship velocity. Browse the "DoseFinding alternatives" section above for the current picks, or visit /alternatives/dosefinding for the full list with editorial commentary on each.